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Liangjun Su

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

  1. Yiren Wang & Peter C B Phillips & Liangjun Su, 2023. "Panel Data Models with Time-Varying Latent Group Structures," Papers 2307.15863, arXiv.org.

    Cited by:

    1. Langevin, R.;, 2024. "Consistent Estimation of Finite Mixtures: An Application to Latent Group Panel Structures," Health, Econometrics and Data Group (HEDG) Working Papers 24/16, HEDG, c/o Department of Economics, University of York.

  2. Yiren Wang & Liangjun Su & Yichong Zhang, 2022. "Low-rank Panel Quantile Regression: Estimation and Inference," Papers 2210.11062, arXiv.org.

    Cited by:

    1. Yiren Wang & Peter C. B. Phillips & Liangjun Su, 2023. "Panel Data Models with Time-Varying Latent Group Structures," Cowles Foundation Discussion Papers 2364, Cowles Foundation for Research in Economics, Yale University.

  3. Bin Peng & Liangjun Su & Joakim Westerlund & Yanrong Yang, 2021. "Interactive Effects Panel Data Models with General Factors and Regressors," Papers 2111.11506, arXiv.org.

    Cited by:

    1. Hou, Li & Jin, Baisuo & Wu, Yuehua, 2024. "Estimation and variable selection for high-dimensional spatial dynamic panel data models," Journal of Econometrics, Elsevier, vol. 238(2).
    2. Georg Keilbar & Juan M. Rodriguez-Poo & Alexandra Soberon & Weining Wang, 2022. "A semiparametric approach for interactive fixed effects panel data models," Papers 2201.11482, arXiv.org, revised Mar 2023.

  4. Ke Miao & Peter C.B. Phillips & Liangjun Su, 2020. "High-Dimensional VARs with Common Factors," Cowles Foundation Discussion Papers 2252, Cowles Foundation for Research in Economics, Yale University.

    Cited by:

    1. Yiren Wang & Peter C. B. Phillips & Liangjun Su, 2023. "Panel Data Models with Time-Varying Latent Group Structures," Cowles Foundation Discussion Papers 2364, Cowles Foundation for Research in Economics, Yale University.
    2. Lyu, Chenyan & Do, Hung Xuan & Nepal, Rabindra & Jamasb, Tooraj, 2024. "Volatility spillovers and carbon price in the Nordic wholesale electricity markets," Energy Economics, Elsevier, vol. 134(C).
    3. Christian Brownlees & Gu{dh}mundur Stef'an Gu{dh}mundsson, 2021. "Performance of Empirical Risk Minimization for Linear Regression with Dependent Data," Papers 2104.12127, arXiv.org, revised May 2023.
    4. Alain Hecq & Luca Margaritella & Stephan Smeekes, 2023. "Inference in Non-stationary High-Dimensional VARs," Papers 2302.01434, arXiv.org, revised Sep 2023.
    5. Eugene Dettaa & Endong Wang, 2024. "Inference in High-Dimensional Linear Projections: Multi-Horizon Granger Causality and Network Connectedness," Papers 2410.04330, arXiv.org.
    6. Lin, Ling & Jiang, Yong & Zhou, Zhongbao, 2024. "Asymmetric spillover and network connectedness of policy uncertainty, fossil fuel energy, and global ESG investment," Applied Energy, Elsevier, vol. 368(C).
    7. Naeem, Muhammad Abubakr & Senthilkumar, Arunachalam & Arfaoui, Nadia & Mohnot, Rajesh, 2024. "Mapping fear in financial markets: Insights from dynamic networks and centrality measures," Pacific-Basin Finance Journal, Elsevier, vol. 85(C).
    8. Christis Katsouris, 2023. "Structural Analysis of Vector Autoregressive Models," Papers 2312.06402, arXiv.org, revised Feb 2024.
    9. Siphat Lim & Edman Flores & Casey Barnett, 2024. "Analyzing the Effectiveness of a System of Equation Model in Comparison to Single Equation Models for Predicting General Price Level in Cambodia," International Journal of Economics and Financial Issues, Econjournals, vol. 14(5), pages 156-166, September.
    10. Wang, Di & Zheng, Yao & Li, Guodong, 2024. "High-dimensional low-rank tensor autoregressive time series modeling," Journal of Econometrics, Elsevier, vol. 238(1).

  5. Huang, Wenxin & Jin, Sainan & Phillips, Peter C.B. & Su, Liangjun, 2020. "Nonstationary Panel Models with Latent Group Structures and Cross-Section Dependence," Economics and Statistics Working Papers 7-2020, Singapore Management University, School of Economics.

    Cited by:

    1. Liu, Yanbo & Phillips, Peter C. B. & Yu, Jun, 2022. "A Panel Clustering Approach to Analyzing Bubble Behavior," Economics and Statistics Working Papers 1-2022, Singapore Management University, School of Economics.
    2. Saptorshee Kanto Chakraborty & Massimiliano Mazzanti, 2021. "Revisiting the literature on the dynamic Environmental Kuznets Curves using a latent structure approach," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 38(3), pages 923-941, October.
    3. Bin Peng & Liangjun Su & Joakim Westerlund & Yanrong Yang, 2021. "Interactive Effects Panel Data Models with General Factors and Regressors," Monash Econometrics and Business Statistics Working Papers 23/21, Monash University, Department of Econometrics and Business Statistics.
    4. Jiti Gao & Fei Liu & Bin peng, 2020. "Binary Response Models for Heterogeneous Panel Data with Interactive Fixed Effects," Monash Econometrics and Business Statistics Working Papers 44/20, Monash University, Department of Econometrics and Business Statistics.
    5. Saptorshee Kanto Chakraborty & Antoine Mandel, 2024. "Understanding EU regional macroeconomic tipping points using panel threshold technique," Economic Change and Restructuring, Springer, vol. 57(3), pages 1-30, June.
    6. Jiti Gao & Bin Peng & Yayi Yan, 2022. "Nonparametric Estimation and Testing for Time-Varying VAR Models," Monash Econometrics and Business Statistics Working Papers 3/22, Monash University, Department of Econometrics and Business Statistics.
    7. Dong, Yingjie & Huang, Wenxin & Tse, Yiu-Kuen, 2023. "Price comovement and market segmentation of Chinese A- and H-shares: Evidence from a panel latent-factor model," Journal of International Money and Finance, Elsevier, vol. 131(C).
    8. Gao, J. & Linton, O. & Peng, B., 2022. "A Nonparametric Panel Model for Climate Data with Seasonal and Spatial Variation," Cambridge Working Papers in Economics 2239, Faculty of Economics, University of Cambridge.
    9. Jiti Gao & Fei Liu & Bin Peng & Yayi Yan, 2020. "Binary Response Models for Heterogeneous Panel Data with Interactive Fixed Effects," Papers 2012.03182, arXiv.org, revised Nov 2021.
    10. Guohua Feng & Jiti Gao & Bin Peng, 2022. "Multi-Level Panel Data Models: Estimation and Empirical Analysis," Monash Econometrics and Business Statistics Working Papers 4/22, Monash University, Department of Econometrics and Business Statistics.

  6. Zhentao Shi & Liangjun Su & Tian Xie, 2020. "L2-Relaxation: With Applications to Forecast Combination and Portfolio Analysis," Papers 2010.09477, arXiv.org, revised Aug 2022.

    Cited by:

    1. Nabil Bouamara & S'ebastien Laurent & Shuping Shi, 2023. "Sequential Cauchy Combination Test for Multiple Testing Problems with Financial Applications," Papers 2303.13406, arXiv.org, revised Jun 2023.

  7. Shujie Ma & Liangjun Su & Yichong Zhang, 2020. "Detecting Latent Communities in Network Formation Models," Papers 2005.03226, arXiv.org, revised Mar 2021.

    Cited by:

    1. Yiren Wang & Peter C. B. Phillips & Liangjun Su, 2023. "Panel Data Models with Time-Varying Latent Group Structures," Cowles Foundation Discussion Papers 2364, Cowles Foundation for Research in Economics, Yale University.
    2. Miao, Ke & Phillips, Peter C.B. & Su, Liangjun, 2023. "High-dimensional VARs with common factors," Journal of Econometrics, Elsevier, vol. 233(1), pages 155-183.
    3. Churchill, Brandyn F., 2021. "How important is the structure of school vaccine requirement opt-out provisions? Evidence from Washington, DC's HPV vaccine requirement," Journal of Health Economics, Elsevier, vol. 78(C).
    4. Lu, Xun & Su, Liangjun, 2023. "Uniform inference in linear panel data models with two-dimensional heterogeneity," Journal of Econometrics, Elsevier, vol. 235(2), pages 694-719.
    5. Wyrwich, Michael & Steinberg, Philip J. & Noseleit, Florian & de Faria, Pedro, 2022. "Is open innovation imprinted on new ventures? The cooperation-inhibiting legacy of authoritarian regimes," Research Policy, Elsevier, vol. 51(1).
    6. Yiren Wang & Liangjun Su & Yichong Zhang, 2022. "Low-rank Panel Quantile Regression: Estimation and Inference," Papers 2210.11062, arXiv.org.
    7. Candelaria, Luis E. & Ura, Takuya, 2023. "Identification and inference of network formation games with misclassified links," Journal of Econometrics, Elsevier, vol. 235(2), pages 862-891.

  8. Su, Liangjun & Miao, Ke & Jin, Sainan, 2019. "On Factor Models with Random Missing: EM Estimation, Inference, and Cross Validation," Economics and Statistics Working Papers 4-2019, Singapore Management University, School of Economics.

    Cited by:

    1. Zhou, Ruichao & Wu, Jianhong, 2023. "Determining the number of change-points in high-dimensional factor models by cross-validation with matrix completion," Economics Letters, Elsevier, vol. 232(C).
    2. Camacho, Maximo & Lopez-Buenache, German, 2023. "Factor models for large and incomplete data sets with unknown group structure," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1205-1220.
    3. Liu, Wei & Luo, Lan & Zhou, Ling, 2023. "Online missing value imputation for high-dimensional mixed-type data via generalized factor models," Computational Statistics & Data Analysis, Elsevier, vol. 187(C).
    4. Chaohua Dong & Jiti Gao & Oliver Linton & Bin peng, 2020. "On Time Trend of COVID-19: A Panel Data Study," Monash Econometrics and Business Statistics Working Papers 22/20, Monash University, Department of Econometrics and Business Statistics.
    5. Ercument Cahan & Jushan Bai & Serena Ng, 2021. "Factor-Based Imputation of Missing Values and Covariances in Panel Data of Large Dimensions," Papers 2103.03045, arXiv.org, revised Feb 2022.
    6. Wei, Jie & Chen, Hui, 2020. "Determining the number of factors in approximate factor models by twice K-fold cross validation," Economics Letters, Elsevier, vol. 191(C).
    7. Artūras Juodis & Simas Kučinskas, 2023. "Quantifying noise in survey expectations," Quantitative Economics, Econometric Society, vol. 14(2), pages 609-650, May.
    8. Victor Chernozhukov & Christian Hansen & Yuan Liao & Yinchu Zhu, 2021. "Inference for Low-Rank Models," Papers 2107.02602, arXiv.org, revised Jan 2023.
    9. Liddle, Brantley & Hasanov, Fakhri J. & Parker, Steven, 2022. "Your mileage may vary: Have road-fuel demand elasticities changed over time in middle-income countries?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 165(C), pages 38-53.
    10. Gao, J. & Linton, O. & Peng, B., 2022. "A Nonparametric Panel Model for Climate Data with Seasonal and Spatial Variation," Cambridge Working Papers in Economics 2239, Faculty of Economics, University of Cambridge.
    11. Ke, Shuyao & Phillips, Peter C.B. & Su, Liangjun, 2024. "Robust inference of panel data models with interactive fixed effects under long memory: A frequency domain approach," Journal of Econometrics, Elsevier, vol. 241(2).
    12. Jushan Bai & Serena Ng, 2021. "Matrix Completion, Counterfactuals, and Factor Analysis of Missing Data," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 116(536), pages 1746-1763, October.
    13. Choi, Jungjun & Kwon, Hyukjun & Liao, Yuan, 2024. "Inference for low-rank completion without sample splitting with application to treatment effect estimation," Journal of Econometrics, Elsevier, vol. 240(1).
    14. Junting Duan & Markus Pelger & Ruoxuan Xiong, 2023. "Target PCA: Transfer Learning Large Dimensional Panel Data," Papers 2308.15627, arXiv.org.
    15. Jungjun Choi & Ming Yuan, 2023. "Matrix Completion When Missing Is Not at Random and Its Applications in Causal Panel Data Models," Papers 2308.02364, arXiv.org.
    16. Ruoxuan Xiong & Markus Pelger, 2019. "Large Dimensional Latent Factor Modeling with Missing Observations and Applications to Causal Inference," Papers 1910.08273, arXiv.org, revised Jan 2022.
    17. Yinchu Zhu, 2019. "How well can we learn large factor models without assuming strong factors?," Papers 1910.10382, arXiv.org, revised Nov 2019.
    18. Jungjun Choi & Hyukjun Kwon & Yuan Liao, 2023. "Inference for Low-rank Completion without Sample Splitting with Application to Treatment Effect Estimation," Papers 2307.16370, arXiv.org.
    19. Jianqing Fan & Kunpeng Li & Yuan Liao, 2020. "Recent Developments on Factor Models and its Applications in Econometric Learning," Papers 2009.10103, arXiv.org.
    20. Serena Ng & Susannah Scanlan, 2023. "Constructing High Frequency Economic Indicators by Imputation," Papers 2303.01863, arXiv.org, revised Oct 2023.

  9. Hong, Shengjie & Su, Liangjun & Wang, Yaqi, 2019. "Inference in partially identified panel data models with interactive fixed effects," Economics and Statistics Working Papers 14-2019, Singapore Management University, School of Economics.

    Cited by:

    1. Juodis, Arturas & Sarafidis, Vasilis, 2020. "An Incidental Parameters Free Inference Approach for Panels with Common Shocks," MPRA Paper 104906, University Library of Munich, Germany.

  10. Ke, Miao & Su, Liangjun & Wang, Wendun, 2019. "Panel threshold regressions with latent group structures," Economics and Statistics Working Papers 13-2019, Singapore Management University, School of Economics.

    Cited by:

    1. Huang, Danyang & Hu, Wei & Jing, Bingyi & Zhang, Bo, 2023. "Grouped spatial autoregressive model," Computational Statistics & Data Analysis, Elsevier, vol. 178(C).
    2. Huang, Wenxin & Jin, Sainan & Phillips, Peter C.B. & Su, Liangjun, 2020. "Nonstationary Panel Models with Latent Group Structures and Cross-Section Dependence," Economics and Statistics Working Papers 7-2020, Singapore Management University, School of Economics.
    3. Leng, Xuan & Chen, Heng & Wang, Wendun, 2023. "Multi-dimensional latent group structures with heterogeneous distributions," Journal of Econometrics, Elsevier, vol. 233(1), pages 1-21.
    4. Saptorshee Kanto Chakraborty & Antoine Mandel, 2024. "Understanding EU regional macroeconomic tipping points using panel threshold technique," Economic Change and Restructuring, Springer, vol. 57(3), pages 1-30, June.
    5. Lawal, Adedoyin Isola & Ozturk, Ilhan & Olanipekun, Ifedolapo O. & Asaleye, Abiola John, 2020. "Examining the linkages between electricity consumption and economic growth in African economies," Energy, Elsevier, vol. 208(C).
    6. Lumsdaine, Robin L. & Okui, Ryo & Wang, Wendun, 2023. "Estimation of panel group structure models with structural breaks in group memberships and coefficients," Journal of Econometrics, Elsevier, vol. 233(1), pages 45-65.
    7. Su, Liangjun & Wang, Wuyi & Xu, Xingbai, 2023. "Identifying latent group structures in spatial dynamic panels," Journal of Econometrics, Elsevier, vol. 235(2), pages 1955-1980.
    8. Woosik Gong & Myung Hwan Seo, 2022. "Bootstraps for Dynamic Panel Threshold Models," Papers 2211.04027, arXiv.org, revised Sep 2024.
    9. Yu, Lu & Gu, Jiaying & Volgushev, Stanislav, 2024. "Spectral clustering with variance information for group structure estimation in panel data," Journal of Econometrics, Elsevier, vol. 241(1).

  11. Lu, Xun & Miao, Ke & Su, Liangjun, 2018. "Determination of Different Types of Fixed Effects in Three-Dimensional Panels," Economics and Statistics Working Papers 10-2018, Singapore Management University, School of Economics.

    Cited by:

    1. Chiang, Harold D. & Rodrigue, Joel & Sasaki, Yuya, 2023. "Post-Selection Inference In Three-Dimensional Panel Data," Econometric Theory, Cambridge University Press, vol. 39(3), pages 623-658, June.

  12. Huang, Wenxin & Jin, Sainan & Su, Liangjun, 2018. "Identifying Latent Grouped Patterns in Cointegrated Panels," Economics and Statistics Working Papers 3-2019, Singapore Management University, School of Economics.

    Cited by:

    1. Yiren Wang & Peter C. B. Phillips & Liangjun Su, 2023. "Panel Data Models with Time-Varying Latent Group Structures," Cowles Foundation Discussion Papers 2364, Cowles Foundation for Research in Economics, Yale University.
    2. Huang, Wenxin & Jin, Sainan & Phillips, Peter C.B. & Su, Liangjun, 2020. "Nonstationary Panel Models with Latent Group Structures and Cross-Section Dependence," Economics and Statistics Working Papers 7-2020, Singapore Management University, School of Economics.
    3. Saptorshee Kanto Chakraborty & Massimiliano Mazzanti, 2021. "Revisiting the literature on the dynamic Environmental Kuznets Curves using a latent structure approach," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 38(3), pages 923-941, October.
    4. Gobillon, Laurent & Magnac, Thierry & Roux, Sébastien, 2022. "Lifecycle Wages and Human Capital Investments: Selection and Missing Data," CEPR Discussion Papers 16999, C.E.P.R. Discussion Papers.
    5. Dong, Yingjie & Huang, Wenxin & Tse, Yiu-Kuen, 2023. "Price comovement and market segmentation of Chinese A- and H-shares: Evidence from a panel latent-factor model," Journal of International Money and Finance, Elsevier, vol. 131(C).
    6. Christis Katsouris, 2023. "Optimal Estimation Methodologies for Panel Data Regression Models," Papers 2311.03471, arXiv.org, revised Nov 2023.
    7. Su, Liangjun & Wang, Wuyi & Xu, Xingbai, 2023. "Identifying latent group structures in spatial dynamic panels," Journal of Econometrics, Elsevier, vol. 235(2), pages 1955-1980.

  13. Ma, Shujie & Lan, Wei & Su, Liangjun & Tsai, Chih-Ling, 2018. "Testing Alphas in Conditional Time-Varying Factor Models with High Dimensional Assets," Economics and Statistics Working Papers 9-2018, Singapore Management University, School of Economics.

    Cited by:

    1. Miao, Ke & Phillips, Peter C.B. & Su, Liangjun, 2023. "High-dimensional VARs with common factors," Journal of Econometrics, Elsevier, vol. 233(1), pages 155-183.
    2. M. Hashem Pesaran & Takashi Yamagata, 2017. "Testing for Alpha in Linear Factor Pricing Models with a Large Number of Securities," Discussion Papers 17/04, Department of Economics, University of York.
    3. Cui, Junfeng & Wang, Guanghui & Zou, Changliang & Wang, Zhaojun, 2023. "Change-point testing for parallel data sets with FDR control," Computational Statistics & Data Analysis, Elsevier, vol. 182(C).
    4. Feng, Long & Lan, Wei & Liu, Binghui & Ma, Yanyuan, 2022. "High-dimensional test for alpha in linear factor pricing models with sparse alternatives," Journal of Econometrics, Elsevier, vol. 229(1), pages 152-175.
    5. Cheng, Tingting & Yan, Cheng & Yan, Yayi, 2021. "Improved inference for fund alphas using high-dimensional cross-sectional tests," Journal of Empirical Finance, Elsevier, vol. 61(C), pages 57-81.
    6. Jianqing Fan & Kunpeng Li & Yuan Liao, 2020. "Recent Developments on Factor Models and its Applications in Econometric Learning," Papers 2009.10103, arXiv.org.

  14. Wang, Wuyi & Phillips, Peter C.B. & Su, Liangjun, 2018. "The Heterogeneous Effects of the Minimum Wage on Employment Across States," Economics and Statistics Working Papers 11-2018, Singapore Management University, School of Economics.

    Cited by:

    1. Yiren Wang & Peter C. B. Phillips & Liangjun Su, 2023. "Panel Data Models with Time-Varying Latent Group Structures," Cowles Foundation Discussion Papers 2364, Cowles Foundation for Research in Economics, Yale University.
    2. Umedjon Ibragimov & Stephanie Beane & Samuel R Friedman & Kelli Komro & Adaora A Adimora & Jessie K Edwards & Leslie D Williams & Barbara Tempalski & Melvin D Livingston & Ronald D Stall & Gina M Wing, 2019. "States with higher minimum wages have lower STI rates among women: Results of an ecological study of 66 US metropolitan areas, 2003-2015," PLOS ONE, Public Library of Science, vol. 14(10), pages 1-18, October.
    3. Alessandrini, Diana & Milla, Joniada, 2021. "Minimum Wage Effects on Human Capital Accumulation: Evidence from Canadian Data," IZA Discussion Papers 14178, Institute of Labor Economics (IZA).
    4. Loukas Karabarbounis & Jeremy Lise & Anusha Nath, 2022. "Minimum Wages and Labor Markets in the Twin Cities," Working Papers 793, Federal Reserve Bank of Minneapolis.
    5. Cristian Valeriu Paun & Radu Nechita & Alexandru Patruti & Mihai Vladimir Topan, 2021. "The Impact of the Minimum Wage on Employment: An EU Panel Data Analysis," Sustainability, MDPI, vol. 13(16), pages 1-17, August.
    6. Wang, Wuyi & Su, Liangjun, 2017. "Identifying Latent Group Structures in Nonlinear Panels," Economics and Statistics Working Papers 19-2017, Singapore Management University, School of Economics.
    7. Luis E. Arango & Sergio A. Rivera, 2020. "“Disemployment” effects of the minimum wage in the Colombian manufacturing sector," Borradores de Economia 1107, Banco de la Republica de Colombia.
    8. Subir K. Chakrabarti & Srikant Devaraj & Pankaj C. Patel, 2021. "Minimum wage and restaurant hygiene violations: Evidence from Seattle," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 42(1), pages 85-99, January.
    9. David Neumark & Peter Shirley, 2022. "Myth or measurement: What does the new minimum wage research say about minimum wages and job loss in the United States?," Industrial Relations: A Journal of Economy and Society, Wiley Blackwell, vol. 61(4), pages 384-417, October.
    10. Francesco Fallucchi & Andrea Mercatanti & Jan Niederreiter, 2021. "Identifying types in contest experiments," International Journal of Game Theory, Springer;Game Theory Society, vol. 50(1), pages 39-61, March.
    11. Arango, Luis E. & Rivera, Sergio A., 2022. "Moderate wage increases and flexible labour contracts to protect employment in Colombian manufacturing," Journal of Policy Modeling, Elsevier, vol. 44(3), pages 578-598.
    12. McGuinness, Seamus & Redmond, Paul & Delaney, Judith, 2019. "The prevalence and effect on hours worked of the minimum wage in Ireland: A sectoral and regional analysis," Research Series, Economic and Social Research Institute (ESRI), number RS93.
    13. Devereux, Kevin & Studnicka, Zuzanna, 2024. "Non-monotonic employment effects by market structure and minimum wage level," CLEF Working Paper Series 66, Canadian Labour Economics Forum (CLEF), University of Waterloo.
    14. Sophie-Charlotte Klose, 2020. "Identifying Latent Structures in Maternal Employment: Evidence on the German Parental Benefit Reform," Papers 2011.03541, arXiv.org.
    15. Aleksandra Majchrowska & Paweł Strawiński, 2021. "Minimum wage and local employment: A spatial panel approach," Regional Science Policy & Practice, Wiley Blackwell, vol. 13(5), pages 1581-1602, October.
    16. Aleksandra Majchrowska & Paweł Strawiński, 2022. "Heterogeneous employment effects of minimum wage policies," Working Papers 2022-18, Faculty of Economic Sciences, University of Warsaw.
    17. Yiren Wang & Liangjun Su & Yichong Zhang, 2022. "Low-rank Panel Quantile Regression: Estimation and Inference," Papers 2210.11062, arXiv.org.
    18. Baek, Jisun & Lee, Changkeun & Park, WooRam, 2021. "The impact of the minimum wage on the characteristics of new establishments: Evidence from South Korea," Labour Economics, Elsevier, vol. 72(C).
    19. Jan Niederreiter, 2023. "Broadening Economics in the Era of Artificial Intelligence and Experimental Evidence," Italian Economic Journal: A Continuation of Rivista Italiana degli Economisti and Giornale degli Economisti, Springer;Società Italiana degli Economisti (Italian Economic Association), vol. 9(1), pages 265-294, March.
    20. Gmeiner, Michael & Gmeiner, Robert, 2023. "Estimating the employment effect of the minimum wage through variation in compliance: evidence from five US states," LSE Research Online Documents on Economics 121277, London School of Economics and Political Science, LSE Library.

  15. Daniel J. Henderson & Christopher F. Parmeter & Liangjun Su, 2017. "M-Estimation of a Nonparametric Threshold Regression Model," Working Papers 2017-15, University of Miami, Department of Economics.

    Cited by:

    1. Yoonseok Lee & Yulong Wang, 2019. "Threshold Regression with Nonparametric Sample Splitting," Papers 1905.13140, arXiv.org, revised Jan 2021.

  16. Su, Liangjun & Ura, Takuya & Zhang, Yichong, 2017. "Non-separable Models with High-dimensional Data," Economics and Statistics Working Papers 15-2017, Singapore Management University, School of Economics.

    Cited by:

    1. Sasaki, Yuya & Ura, Takuya, 2023. "Estimation and inference for policy relevant treatment effects," Journal of Econometrics, Elsevier, vol. 234(2), pages 394-450.
    2. Ying-Ying Lee & Chu-An Liu, 2024. "Lee Bounds with a Continuous Treatment in Sample Selection," Papers 2411.04312, arXiv.org, revised Jan 2025.
    3. Sylvia Klosin, 2021. "Automatic Double Machine Learning for Continuous Treatment Effects," Papers 2104.10334, arXiv.org.
    4. Qingliang Fan & Zijian Guo & Ziwei Mei & Cun-Hui Zhang, 2023. "Inference for Nonlinear Endogenous Treatment Effects Accounting for High-Dimensional Covariate Complexity," Papers 2310.08063, arXiv.org, revised Jun 2024.
    5. Chunrong Ai & Yue Fang & Haitian Xie, 2024. "Data-driven Policy Learning for Continuous Treatments," Papers 2402.02535, arXiv.org, revised Nov 2024.
    6. Yuya Sasaki & Takuya Ura & Yichong Zhang, 2020. "Unconditional Quantile Regression with High Dimensional Data," Papers 2007.13659, arXiv.org, revised Feb 2022.
    7. Stefan Tübbicke, 2020. "Entropy Balancing for Continuous Treatments," CEPA Discussion Papers 21, Center for Economic Policy Analysis.
    8. Ta-Wei Huang & Eva Ascarza, 2024. "Doing More with Less: Overcoming Ineffective Long-Term Targeting Using Short-Term Signals," Marketing Science, INFORMS, vol. 43(4), pages 863-884, July.
    9. Rahul Singh & Liyuan Xu & Arthur Gretton, 2020. "Kernel Methods for Causal Functions: Dose, Heterogeneous, and Incremental Response Curves," Papers 2010.04855, arXiv.org, revised Oct 2022.
    10. Alexander Krei{ss} & Christoph Rothe, 2021. "Inference in Regression Discontinuity Designs with High-Dimensional Covariates," Papers 2110.13725, arXiv.org, revised May 2022.
    11. Qingliang Fan & Yu-Chin Hsu & Robert P. Lieli & Yichong Zhang, 2022. "Estimation of Conditional Average Treatment Effects With High-Dimensional Data," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(1), pages 313-327, January.
    12. Ganesh Karapakula, 2023. "Stable Probability Weighting: Large-Sample and Finite-Sample Estimation and Inference Methods for Heterogeneous Causal Effects of Multivalued Treatments Under Limited Overlap," Papers 2301.05703, arXiv.org, revised Jan 2023.
    13. Yizhen Xu & Numair Sani & AmirEmad Ghassami & Ilya Shpitser, 2021. "Multiply Robust Causal Mediation Analysis with Continuous Treatments," Papers 2105.09254, arXiv.org, revised Oct 2024.
    14. Lucas Zhang, 2024. "Continuous difference-in-differences with double/debiased machine learning," Papers 2408.10509, arXiv.org.
    15. Alexander Kreiss & Christoph Rothe, 2023. "Inference in regression discontinuity designs with high-dimensional covariates," The Econometrics Journal, Royal Economic Society, vol. 26(2), pages 105-123.
    16. Xie, Haitian, 2024. "Nonlinear and nonseparable structural functions in regression discontinuity designs with a continuous treatment," Journal of Econometrics, Elsevier, vol. 242(1).

  17. Wang, Wuyi & Su, Liangjun, 2017. "Identifying Latent Group Structures in Nonlinear Panels," Economics and Statistics Working Papers 19-2017, Singapore Management University, School of Economics.

    Cited by:

    1. Yiren Wang & Peter C. B. Phillips & Liangjun Su, 2023. "Panel Data Models with Time-Varying Latent Group Structures," Cowles Foundation Discussion Papers 2364, Cowles Foundation for Research in Economics, Yale University.
    2. Xiaorong Yang & Jia Chen & Degui Li & Runze Li, 2023. "Functional-Coefficient Quantile Regression for Panel Data with Latent Group Structure," Papers 2303.13218, arXiv.org.
    3. Bofei Xiao & Bo Lei & Wei Lan & Bin Guo, 2022. "A blockwise network autoregressive model with application for fraud detection," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 74(6), pages 1043-1065, December.
    4. Boyuan Zhang, 2022. "Incorporating Prior Knowledge of Latent Group Structure in Panel Data Models," Papers 2211.16714, arXiv.org, revised Oct 2023.
    5. Leng, Xuan & Chen, Heng & Wang, Wendun, 2023. "Multi-dimensional latent group structures with heterogeneous distributions," Journal of Econometrics, Elsevier, vol. 233(1), pages 1-21.
    6. Ando, Tomohiro & Bai, Jushan, 2021. "Large-scale generalized linear longitudinal data models with grouped patterns of unobserved heterogeneity," MPRA Paper 111431, University Library of Munich, Germany.
    7. Mehrabani, Ali, 2023. "Estimation and identification of latent group structures in panel data," Journal of Econometrics, Elsevier, vol. 235(2), pages 1464-1482.
    8. Li, Donglin & Wang, Wenyue & Ren, Yanyan, 2024. "Quantile estimation of heterogenous panel quantile model with group structure," Economics Letters, Elsevier, vol. 241(C).
    9. Su, Liangjun & Wang, Wuyi & Xu, Xingbai, 2023. "Identifying latent group structures in spatial dynamic panels," Journal of Econometrics, Elsevier, vol. 235(2), pages 1955-1980.
    10. Yiren Wang & Liangjun Su & Yichong Zhang, 2022. "Low-rank Panel Quantile Regression: Estimation and Inference," Papers 2210.11062, arXiv.org.
    11. Chen, Elynn Y. & Fan, Jianqing & Zhu, Xuening, 2023. "Community network auto-regression for high-dimensional time series," Journal of Econometrics, Elsevier, vol. 235(2), pages 1239-1256.
    12. Yu, Lu & Gu, Jiaying & Volgushev, Stanislav, 2024. "Spectral clustering with variance information for group structure estimation in panel data," Journal of Econometrics, Elsevier, vol. 241(1).
    13. Langevin, R.;, 2024. "Consistent Estimation of Finite Mixtures: An Application to Latent Group Panel Structures," Health, Econometrics and Data Group (HEDG) Working Papers 24/16, HEDG, c/o Department of Economics, University of York.

  18. Wuyi Wang & Peter C.B. Phillips & Liangjun Su, 2016. "Homogeneity Pursuit in Panel Data Models: Theory and Applications," Cowles Foundation Discussion Papers 2063, Cowles Foundation for Research in Economics, Yale University.

    Cited by:

    1. Andreas Dzemski & Ryo Okui, 2020. "Convergence rate of estimators of clustered panel models with misclassification," Papers 2008.04708, arXiv.org.
    2. Yiren Wang & Peter C. B. Phillips & Liangjun Su, 2023. "Panel Data Models with Time-Varying Latent Group Structures," Cowles Foundation Discussion Papers 2364, Cowles Foundation for Research in Economics, Yale University.
    3. Andreas Dzemski & Ryo Okui, 2024. "Confidence set for group membership," Quantitative Economics, Econometric Society, vol. 15(2), pages 245-277, May.
    4. Sun, Yan & Wan, Chuang & Zhang, Wenyang & Zhong, Wei, 2024. "A Multi-Kink quantile regression model with common structure for panel data analysis," Journal of Econometrics, Elsevier, vol. 239(2).
    5. Boyuan Zhang, 2022. "Incorporating Prior Knowledge of Latent Group Structure in Panel Data Models," Papers 2211.16714, arXiv.org, revised Oct 2023.
    6. Tadao Hoshino, 2020. "A Pairwise Strategic Network Formation Model with Group Heterogeneity: With an Application to International Travel," Papers 2012.14886, arXiv.org, revised Feb 2021.
    7. Michael Vogt & Oliver Linton, 2018. "Multiscale clustering of nonparametric regression curves," CeMMAP working papers CWP08/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    8. Leng, Xuan & Chen, Heng & Wang, Wendun, 2023. "Multi-dimensional latent group structures with heterogeneous distributions," Journal of Econometrics, Elsevier, vol. 233(1), pages 1-21.
    9. Miao, Ke & Su, Liangjun & Wang, Wendun, 2020. "Panel threshold regressions with latent group structures," Journal of Econometrics, Elsevier, vol. 214(2), pages 451-481.
    10. Saptorshee Kanto Chakraborty & Massimiliano Mazzanti, 2021. "Revisiting the literature on the dynamic Environmental Kuznets Curves using a latent structure approach," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 38(3), pages 923-941, October.
    11. Dante Amengual & Jesús Bueren & Julio A. Crego, 2021. "Endogenous health groups and heterogeneous dynamics of the elderly," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(7), pages 878-897, November.
    12. Wang, Wuyi & Su, Liangjun, 2017. "Identifying Latent Group Structures in Nonlinear Panels," Economics and Statistics Working Papers 19-2017, Singapore Management University, School of Economics.
    13. Denis Chetverikov & Elena Manresa, 2022. "Spectral and post-spectral estimators for grouped panel data models," Papers 2212.13324, arXiv.org, revised Dec 2022.
    14. Ando, Tomohiro & Bai, Jushan, 2021. "Large-scale generalized linear longitudinal data models with grouped patterns of unobserved heterogeneity," MPRA Paper 111431, University Library of Munich, Germany.
    15. Nibbering, D. & Paap, R., 2019. "Panel Forecasting with Asymmetric Grouping," Econometric Institute Research Papers EI-2019-30, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    16. Mehrabani, Ali, 2023. "Estimation and identification of latent group structures in panel data," Journal of Econometrics, Elsevier, vol. 235(2), pages 1464-1482.
    17. Su, Liangjun & Ju, Gaosheng, 2018. "Identifying latent grouped patterns in panel data models with interactive fixed effects," Journal of Econometrics, Elsevier, vol. 206(2), pages 554-573.
    18. Okui, Ryo & Wang, Wendun, 2021. "Heterogeneous structural breaks in panel data models," Journal of Econometrics, Elsevier, vol. 220(2), pages 447-473.
    19. Max Cytrynbaum, 2020. "Blocked Clusterwise Regression," Papers 2001.11130, arXiv.org.
    20. Dzemski, Andreas & Okui, Ryo, 2018. "Confidence Set for Group Membership," Working Papers in Economics 727, University of Gothenburg, Department of Economics.
    21. Didier Nibbering & Richard Paap, 2024. "Forecasting carbon emissions using asymmetric grouping," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(6), pages 2228-2256, September.
    22. Lumsdaine, Robin L. & Okui, Ryo & Wang, Wendun, 2023. "Estimation of panel group structure models with structural breaks in group memberships and coefficients," Journal of Econometrics, Elsevier, vol. 233(1), pages 45-65.
    23. Su, Liangjun & Wang, Wuyi & Xu, Xingbai, 2023. "Identifying latent group structures in spatial dynamic panels," Journal of Econometrics, Elsevier, vol. 235(2), pages 1955-1980.
    24. Yiren Wang & Liangjun Su & Yichong Zhang, 2022. "Low-rank Panel Quantile Regression: Estimation and Inference," Papers 2210.11062, arXiv.org.
    25. Yu, Lu & Gu, Jiaying & Volgushev, Stanislav, 2024. "Spectral clustering with variance information for group structure estimation in panel data," Journal of Econometrics, Elsevier, vol. 241(1).
    26. Langevin, R.;, 2024. "Consistent Estimation of Finite Mixtures: An Application to Latent Group Panel Structures," Health, Econometrics and Data Group (HEDG) Working Papers 24/16, HEDG, c/o Department of Economics, University of York.
    27. Marie-Hélène Felt, 2020. "Losing Contact: The Impact of Contactless Payments on Cash Usage," Staff Working Papers 20-56, Bank of Canada.

  19. Stefan Hoderlein & Liangjun Su & Halbert White & Thomas Tao Yang, 2016. "Testing for Monotonicity in Unobservables under Unconfoundedness," Working Papers 03-2016, Singapore Management University, School of Economics.

    Cited by:

    1. Babii, Andrii & Florens, Jean-Pierre, 2017. "Are unobservables separable?," TSE Working Papers 17-802, Toulouse School of Economics (TSE).
    2. Christoph Breunig, 2019. "Specification Testing in Nonparametric Instrumental Quantile Regression," Papers 1909.10129, arXiv.org.
    3. Su, Liangjun & Ura, Takuya & Zhang, Yichong, 2017. "Non-separable Models with High-dimensional Data," Economics and Statistics Working Papers 15-2017, Singapore Management University, School of Economics.
    4. Tatiana Komarova & Javier Hidalgo, 2019. "Testing nonparametric shape restrictions," Papers 1909.01675, arXiv.org, revised Jun 2020.
    5. Nir Billfeld & Moshe Kim, 2024. "Context-dependent Causality (the Non-Nonotonic Case)," Papers 2404.05021, arXiv.org.

  20. Xun Lu & Liangjun Su & Halbert White, 2016. "Granger Causality and Structural Causality in Cross-Section and Panel Data," Working Papers 04-2016, Singapore Management University, School of Economics.

    Cited by:

    1. Issam Khelfaoui & Yuantao Xie & Muhammad Hafeez & Danish Ahmed & Houssem Eddine Degha & Hicham Meskher, 2022. "Information Communication Technology and Infant Mortality in Low-Income Countries: Empirical Study Using Panel Data Models," IJERPH, MDPI, vol. 19(12), pages 1-24, June.

  21. Shujie Ma & Liangjun Su, 2016. "Estimation of Large Dimensional Factor Models with an Unknown Number of Breaks," Working Papers 05-2016, Singapore Management University, School of Economics.

    Cited by:

    1. Barigozzi, Matteo & Cho, Haeran & Fryzlewicz, Piotr, 2018. "Simultaneous multiple change-point and factor analysis for high-dimensional time series," Journal of Econometrics, Elsevier, vol. 206(1), pages 187-225.

  22. Xun Lu & Su Liangjun, 2015. "Shrinkage Estimation of Dynamic Panel Data Models with Interactive Fixed Effects," Working Papers 02-2015, Singapore Management University, School of Economics.

    Cited by:

    1. Ma, Shujie & Su, Liangjun, 2018. "Estimation of large dimensional factor models with an unknown number of breaks," Journal of Econometrics, Elsevier, vol. 207(1), pages 1-29.
    2. Yiren Wang & Peter C. B. Phillips & Liangjun Su, 2023. "Panel Data Models with Time-Varying Latent Group Structures," Cowles Foundation Discussion Papers 2364, Cowles Foundation for Research in Economics, Yale University.
    3. Badi Baltagi & Qu Feng & Chihwa Kao, 2019. "Structural Changes in Heterogeneous Panels with Endogenous Regressors," Center for Policy Research Working Papers 214, Center for Policy Research, Maxwell School, Syracuse University.
    4. Otilia Boldea & Bettina Drepper & Zhuojiong Gan, 2018. "Change Point Estimation in Panel Data with Time-Varying Individual Effects," Papers 1808.03109, arXiv.org.
    5. Chiang, Harold D. & Rodrigue, Joel & Sasaki, Yuya, 2023. "Post-Selection Inference In Three-Dimensional Panel Data," Econometric Theory, Cambridge University Press, vol. 39(3), pages 623-658, June.
    6. Miao, Ke & Li, Kunpeng & Su, Liangjun, 2020. "Panel threshold models with interactive fixed effects," Journal of Econometrics, Elsevier, vol. 219(1), pages 137-170.
    7. Jan Ditzen & Yiannis Karavias & Joakim Westerlund, 2023. "Multiple structural breaks in interactive effects panel data and the impace of quantitative easing on bank lending," Discussion Papers 23-02, Department of Economics, University of Birmingham.
    8. Babii, Andrii & Ball, Ryan T. & Ghysels, Eric & Striaukas, Jonas, 2023. "Machine learning panel data regressions with heavy-tailed dependent data: Theory and application," Journal of Econometrics, Elsevier, vol. 237(2).
    9. Yiannis Karavias & Paresh Narayan & Joakim Westerlund, 2021. "Structural Breaks in Interactive Effects Panels and the Stock Market Reaction to COVID-19," Papers 2111.03035, arXiv.org.
    10. Tingting Cheng & Chaohua Dong & Jiti Gao & Oliver Linton, 2022. "GMM Estimation for High-Dimensional Panel Data Models," Monash Econometrics and Business Statistics Working Papers 11/22, Monash University, Department of Econometrics and Business Statistics.
    11. Hsiao, Cheng, 2018. "Panel models with interactive effects," Journal of Econometrics, Elsevier, vol. 206(2), pages 645-673.
    12. Tadao Hoshino, 2018. "Semiparametric Spatial Autoregressive Models With Endogenous Regressors: With an Application to Crime Data," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 36(1), pages 160-172, January.
    13. Freeman, Hugo & Weidner, Martin, 2023. "Linear panel regressions with two-way unobserved heterogeneity," Journal of Econometrics, Elsevier, vol. 237(1).
    14. Ruiqi Liu & Ben Boukai & Zuofeng Shang, 2019. "Statistical Inference on Partially Linear Panel Model under Unobserved Linearity," Papers 1911.08830, arXiv.org.
    15. Su, Liangjun & Wang, Xia, 2017. "On time-varying factor models: Estimation and testing," Journal of Econometrics, Elsevier, vol. 198(1), pages 84-101.
    16. Huang, Wenxin & Jin, Sainan & Phillips, Peter C.B. & Su, Liangjun, 2020. "Nonstationary Panel Models with Latent Group Structures and Cross-Section Dependence," Economics and Statistics Working Papers 7-2020, Singapore Management University, School of Economics.
    17. Karsten Schweikert, 2022. "Detecting Multiple Structural Breaks in Systems of Linear Regression Equations with Integrated and Stationary Regressors," Papers 2201.05430, arXiv.org, revised Sep 2024.
    18. Vira Semenova & Matt Goldman & Victor Chernozhukov & Matt Taddy, 2023. "Inference on heterogeneous treatment effects in high‐dimensional dynamic panels under weak dependence," Quantitative Economics, Econometric Society, vol. 14(2), pages 471-510, May.
    19. Alessandro Casini & Pierre Perron, 2018. "Structural Breaks in Time Series," Boston University - Department of Economics - Working Papers Series WP2019-02, Boston University - Department of Economics.
    20. Jafari-Sadeghi, Vahid & Garcia-Perez, Alexeis & Candelo, Elena & Couturier, Jerome, 2021. "Exploring the impact of digital transformation on technology entrepreneurship and technological market expansion: The role of technology readiness, exploration and exploitation," Journal of Business Research, Elsevier, vol. 124(C), pages 100-111.
    21. Miao, Ke & Phillips, Peter C.B. & Su, Liangjun, 2023. "High-dimensional VARs with common factors," Journal of Econometrics, Elsevier, vol. 233(1), pages 155-183.
    22. Juodis, Arturas & Sarafidis, Vasilis, 2020. "An Incidental Parameters Free Inference Approach for Panels with Common Shocks," MPRA Paper 104906, University Library of Munich, Germany.
    23. Ye, Xiaoqing & Xu, Juan & Wu, Xiangjun, 2018. "Estimation of an unbalanced panel data Tobit model with interactive effects," Journal of choice modelling, Elsevier, vol. 28(C), pages 108-123.
    24. T. Thomson & S. Hossain, 2018. "Efficient Shrinkage for Generalized Linear Mixed Models Under Linear Restrictions," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 80(2), pages 385-410, August.
    25. Jiang, Peiyun & Kurozumi, Eiji, 2021. "A new test for common breaks in heterogeneous panel data models," Discussion paper series HIAS-E-107, Hitotsubashi Institute for Advanced Study, Hitotsubashi University.
    26. Ayden Higgins & Federico Martellosio, 2019. "Shrinkage Estimation of Network Spillovers with Factor Structured Errors," Papers 1909.02823, arXiv.org, revised Nov 2021.
    27. Jaeho Kim & Le Wang, 2019. "Hidden group patterns in democracy developments: Bayesian inference for grouped heterogeneity," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(6), pages 1016-1028, September.
    28. Hyungsik Roger Moon & Martin Weidner, 2019. "Nuclear norm regularized estimation of panel regression models," CeMMAP working papers CWP14/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    29. Miranda, Karen & Martínez Ibáñez, Oscar & Manjón Antolín, Miguel C., 2018. "A correlated random effects spatial Durbin model," Working Papers 2072/313840, Universitat Rovira i Virgili, Department of Economics.
    30. F. Marta L. Di Lascio & Selene Perazzini, 2024. "A three-way dynamic panel threshold regression model for change point detection in bioimpedance data," BEMPS - Bozen Economics & Management Paper Series BEMPS104, Faculty of Economics and Management at the Free University of Bozen.
    31. Yang, Kai & Lee, Lung-fei, 2021. "Estimation of dynamic panel spatial vector autoregression: Stability and spatial multivariate cointegration," Journal of Econometrics, Elsevier, vol. 221(2), pages 337-367.
    32. Bai, Jushan & Li, Kunpeng, 2021. "Dynamic spatial panel data models with common shocks," Journal of Econometrics, Elsevier, vol. 224(1), pages 134-160.
    33. Minyoung Jo & Sangyeol Lee, 2021. "On CUSUM test for dynamic panel models," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(2), pages 515-542, June.
    34. Siem Jan Koopman & Julia Schaumburg & Quint Wiersma, 2021. "Joint Modelling and Estimation of Global and Local Cross-Sectional Dependence in Large Panels," Tinbergen Institute Discussion Papers 21-008/III, Tinbergen Institute.
    35. Vogt, M. & Walsh, C. & Linton, O., 2022. "CCE Estimation of High-Dimensional Panel Data Models with Interactive Fixed Effects," Janeway Institute Working Papers 2218, Faculty of Economics, University of Cambridge.
    36. Su, Liangjun & Ju, Gaosheng, 2018. "Identifying latent grouped patterns in panel data models with interactive fixed effects," Journal of Econometrics, Elsevier, vol. 206(2), pages 554-573.
    37. Feng, Guohua & Gao, Jiti & Peng, Bin, 2022. "An integrated panel data approach to modelling economic growth," Journal of Econometrics, Elsevier, vol. 228(2), pages 379-397.
    38. Ke, Shuyao & Phillips, Peter C.B. & Su, Liangjun, 2024. "Robust inference of panel data models with interactive fixed effects under long memory: A frequency domain approach," Journal of Econometrics, Elsevier, vol. 241(2).
    39. Cheng, Tingting & Gao, Jiti & Yan, Yayi, 2019. "Regime switching panel data models with interactive fixed effects," Economics Letters, Elsevier, vol. 177(C), pages 47-51.
    40. Francesco Giordano & Marcella Niglio & Maria Lucia Parrella, 2024. "Testing Spatial Dynamic Panel Data Models with Heterogeneous Spatial and Regression Coefficients," Journal of Time Series Analysis, Wiley Blackwell, vol. 45(5), pages 771-799, September.
    41. Okui, Ryo & Wang, Wendun, 2021. "Heterogeneous structural breaks in panel data models," Journal of Econometrics, Elsevier, vol. 220(2), pages 447-473.
    42. Su, Liangjun & Ura, Takuya & Zhang, Yichong, 2017. "Non-separable Models with High-dimensional Data," Economics and Statistics Working Papers 15-2017, Singapore Management University, School of Economics.
    43. Hugo Freeman & Martin Weidner, 2021. "Linear Panel Regressions with Two-Way Unobserved Heterogeneity," Papers 2109.11911, arXiv.org, revised Aug 2022.
    44. Shi, Wei & Lee, Lung-fei, 2017. "Spatial dynamic panel data models with interactive fixed effects," Journal of Econometrics, Elsevier, vol. 197(2), pages 323-347.
    45. Jin, Sainan & Miao, Ke & Su, Liangjun, 2021. "On factor models with random missing: EM estimation, inference, and cross validation," Journal of Econometrics, Elsevier, vol. 222(1), pages 745-777.
    46. Feng, Guohua & Peng, Bin & Su, Liangjun & Yang, Thomas Tao, 2019. "Semi-parametric single-index panel data models with interactive fixed effects: Theory and practice," Journal of Econometrics, Elsevier, vol. 212(2), pages 607-622.
    47. Anil K. Bera & Osman Doğan & Süleyman Taşpınar & Monalisa Sen, 2020. "Specification tests for spatial panel data models," Journal of Spatial Econometrics, Springer, vol. 1(1), pages 1-39, December.
    48. Yufeng Mao & Bin Peng & Mervyn J Silvapulle & Param Silvapulle & Yanrong Yang, 2021. "Decomposition of Bilateral Trade Flows Using a Three-Dimensional Panel Data Model," Monash Econometrics and Business Statistics Working Papers 7/21, Monash University, Department of Econometrics and Business Statistics.
    49. Hong, Shengjie & Su, Liangjun & Jiang, Tao, 2023. "Profile GMM estimation of panel data models with interactive fixed effects," Journal of Econometrics, Elsevier, vol. 235(2), pages 927-948.
    50. Chen, Likai & Wang, Weining & Wu, Wei Biao, 2019. "Inference of Break-Points in High-Dimensional Time Series," IRTG 1792 Discussion Papers 2019-013, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    51. Linton, O. B. & Rücker, M. & Vogt, M. & Walsh, C., 2024. "Estimation and Inference in High-Dimensional Panel Data Models with Interactive Fixed Effects," Cambridge Working Papers in Economics 2467, Faculty of Economics, University of Cambridge.
    52. Wolter, James Lewis, 2016. "Kernel estimation of hazard functions when observations have dependent and common covariates," Journal of Econometrics, Elsevier, vol. 193(1), pages 1-16.
    53. Yufeng Mao & Bin Peng & Mervyn Silvapulle & Param Silvapulle & Yanrong Yang, 2021. "Decomposition of Bilateral Trade Flows Using a Three-Dimensional Panel Data Model," Papers 2101.06805, arXiv.org.
    54. Feng, Qu, 2020. "Common factors and common breaks in panels: An empirical investigation," Economics Letters, Elsevier, vol. 187(C).
    55. Georg Keilbar & Juan M. Rodriguez-Poo & Alexandra Soberon & Weining Wang, 2022. "A semiparametric approach for interactive fixed effects panel data models," Papers 2201.11482, arXiv.org, revised Mar 2023.
    56. Shi, Wei & Lee, Lung-fei, 2018. "A spatial panel data model with time varying endogenous weights matrices and common factors," Regional Science and Urban Economics, Elsevier, vol. 72(C), pages 6-34.
    57. Agiwal Varun & Kumar Jitendra & Shangodoyin Dahud Kehinde, 2018. "A Bayesian Inference Of Multiple Structural Breaks In Mean And Error Variance In Panelar (1) Model," Statistics in Transition New Series, Statistics Poland, vol. 19(1), pages 7-23, March.
    58. Degui Li & Junhui Qian & Liangjun Su, 2016. "Panel Data Models With Interactive Fixed Effects and Multiple Structural Breaks," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(516), pages 1804-1819, October.
    59. Qian, Junhui & Su, Liangjun, 2016. "Shrinkage estimation of common breaks in panel data models via adaptive group fused Lasso," Journal of Econometrics, Elsevier, vol. 191(1), pages 86-109.
    60. Chen, Sanpan & Cui, Guowei & Zhang, Jianhua, 2017. "On testing for structural break of coefficients in factor-augmented regression models," Economics Letters, Elsevier, vol. 161(C), pages 141-145.
    61. Christis Katsouris, 2023. "Optimal Estimation Methodologies for Panel Data Regression Models," Papers 2311.03471, arXiv.org, revised Nov 2023.
    62. Cheng Hsiao & Yimeng Xie & Qiankun Zhou, 2021. "Factor dimension determination for panel interactive effects models: an orthogonal projection approach," Computational Statistics, Springer, vol. 36(2), pages 1481-1497, June.
    63. Yuki Takara & Shingo Takagi, 2023. "An empirical approach to measure unobserved cultural relations using music trade data," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 47(2), pages 205-245, June.
    64. Lumsdaine, Robin L. & Okui, Ryo & Wang, Wendun, 2023. "Estimation of panel group structure models with structural breaks in group memberships and coefficients," Journal of Econometrics, Elsevier, vol. 233(1), pages 45-65.
    65. Bai, Jushan & Han, Xu & Shi, Yutang, 2020. "Estimation and inference of change points in high-dimensional factor models," Journal of Econometrics, Elsevier, vol. 219(1), pages 66-100.
    66. Hou, Lei & Li, Kunpeng & Li, Qi & Ouyang, Min, 2021. "Revisiting the location of FDI in China: A panel data approach with heterogeneous shocks," Journal of Econometrics, Elsevier, vol. 221(2), pages 483-509.
    67. Hugo Freeman & Martin Weidner, 2021. "Linear panel regressions with two-way unobserved heterogeneity," CeMMAP working papers CWP39/21, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    68. Higgins, Ayden & Martellosio, Federico, 2023. "Shrinkage estimation of network spillovers with factor structured errors," Journal of Econometrics, Elsevier, vol. 233(1), pages 66-87.
    69. Qu, Xi & Lee, Lung-fei & Yu, Jihai, 2017. "QML estimation of spatial dynamic panel data models with endogenous time varying spatial weights matrices," Journal of Econometrics, Elsevier, vol. 197(2), pages 173-201.
    70. Sun, Yanqing & Zhang, Yuanqing & Huang, Jianhua Z., 2019. "Estimation of a semiparametric varying-coefficient mixed regressive spatial autoregressive model," Econometrics and Statistics, Elsevier, vol. 9(C), pages 140-155.
    71. Costantini, Mauro & Paradiso, Antonio, 2018. "What do panel data say on inequality and GDP? New evidence at US state-level," Economics Letters, Elsevier, vol. 168(C), pages 115-117.
    72. Ando, Tomohiro & Li, Kunpeng & Lu, Lina, 2023. "A spatial panel quantile model with unobserved heterogeneity," Journal of Econometrics, Elsevier, vol. 232(1), pages 191-213.
    73. James Wolter, 2015. "Kernel Estimation Of Hazard Functions When Observations Have Dependent and Common Covariates," Economics Series Working Papers 761, University of Oxford, Department of Economics.
    74. Horváth, Lajos & Rice, Gregory, 2019. "Asymptotics for empirical eigenvalue processes in high-dimensional linear factor models," Journal of Multivariate Analysis, Elsevier, vol. 169(C), pages 138-165.
    75. Ma, Chenchen & Tu, Yundong, 2023. "Group fused Lasso for large factor models with multiple structural breaks," Journal of Econometrics, Elsevier, vol. 233(1), pages 132-154.
    76. Bera, Anil K. & Doğan, Osman & Taşpınar, Süleyman, 2018. "Simple tests for endogeneity of spatial weights matrices," Regional Science and Urban Economics, Elsevier, vol. 69(C), pages 130-142.
    77. Yuichi Goto & Kotone Suzuki & Xiaofei Xu & Masanobu Taniguchi, 2023. "Tests for the existence of group effects and interactions for two-way models with dependent errors," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 75(3), pages 511-532, June.
    78. Shobande, Olatunji A., 2023. "Rethinking social change: Does the permanent and transitory effects of electricity and solid fuel use predict health outcome in Africa?," Technological Forecasting and Social Change, Elsevier, vol. 186(PB).
    79. Feng, Xingdong & Li, Wenyu & Zhu, Qianqian, 2024. "Estimation and bootstrapping under spatiotemporal models with unobserved heterogeneity," Journal of Econometrics, Elsevier, vol. 238(1).
    80. Badi H. Baltagi & Georges Bresson & Anoop Chaturvedi & Guy Lacroix, 2023. "Robust dynamic space–time panel data models using $$\varepsilon $$ ε -contamination: an application to crop yields and climate change," Empirical Economics, Springer, vol. 64(6), pages 2475-2509, June.

  23. Su Liangjun & Tadao Hoshino, 2015. "Sieve Instrumental Variable Quantile Regression Estimation of Functional Coefficient Models," Working Papers 01-2015, Singapore Management University, School of Economics.

    Cited by:

    1. Wüthrich, Kaspar, 2020. "A Comparison of Two Quantile Models With Endogeneity," University of California at San Diego, Economics Working Paper Series qt0q43931f, Department of Economics, UC San Diego.
    2. Antonio F. Galvao & Jiaying Gu & Stanislav Volgushev, 2018. "On the Unbiased Asymptotic Normality of Quantile Regression with Fixed Effects," Papers 1807.11863, arXiv.org, revised Feb 2020.
    3. Xiaorong Yang & Jia Chen & Degui Li & Runze Li, 2023. "Functional-Coefficient Quantile Regression for Panel Data with Latent Group Structure," Papers 2303.13218, arXiv.org.
    4. Xu, Xiu & Wang, Weining & Shin, Yongcheol, 2020. "Dynamic Spatial Network Quantile Autoregression," IRTG 1792 Discussion Papers 2020-024, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    5. Zhou, Ying & Shen, Long & Ballester, Laura, 2023. "A two-stage credit scoring model based on random forest: Evidence from Chinese small firms," International Review of Financial Analysis, Elsevier, vol. 89(C).
    6. Miao, Ke & Li, Kunpeng & Su, Liangjun, 2020. "Panel threshold models with interactive fixed effects," Journal of Econometrics, Elsevier, vol. 219(1), pages 137-170.
    7. Tadao Hoshino, 2018. "Semiparametric Spatial Autoregressive Models With Endogenous Regressors: With an Application to Crime Data," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 36(1), pages 160-172, January.
    8. Tadao Hoshino, 2014. "Quantile regression estimation of partially linear additive models," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 26(3), pages 509-536, September.
    9. Liang Chen, 2019. "Nonparametric Quantile Regressions for Panel Data Models with Large T," Papers 1911.01824, arXiv.org, revised Sep 2020.
    10. Su, Liangjun & Ura, Takuya & Zhang, Yichong, 2017. "Non-separable Models with High-dimensional Data," Economics and Statistics Working Papers 15-2017, Singapore Management University, School of Economics.
    11. Christis Katsouris, 2023. "High Dimensional Time Series Regression Models: Applications to Statistical Learning Methods," Papers 2308.16192, arXiv.org.
    12. Koo, Chao, 2018. "Essays on functional coefficient models," Other publications TiSEM ba87b8a5-3c55-40ec-967d-9, Tilburg University, School of Economics and Management.

  24. Su Liangjun & Zhang Yonghui, 2015. "Semiparametric Estimation of Partially Linear Dynamic Panel Data Models with Fixed Effects," Working Papers 06-2015, Singapore Management University, School of Economics.

    Cited by:

    1. Yashar Tarverdi, 2018. "Aspects of Governance and $$\hbox {CO}_2$$ CO 2 Emissions: A Non-linear Panel Data Analysis," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 69(1), pages 167-194, January.
    2. Qian, Junhui & Su, Liangjun, 2016. "Shrinkage estimation of common breaks in panel data models via adaptive group fused Lasso," Journal of Econometrics, Elsevier, vol. 191(1), pages 86-109.
    3. Sun, Yanqing & Zhang, Yuanqing & Huang, Jianhua Z., 2019. "Estimation of a semiparametric varying-coefficient mixed regressive spatial autoregressive model," Econometrics and Statistics, Elsevier, vol. 9(C), pages 140-155.

  25. Su Liangjun & Junhui Qian, 2015. "Shrinkage Estimation of Common Breaks in Panel Data Models via Adaptive Group Fused Lasso," Working Papers 07-2015, Singapore Management University, School of Economics.

    Cited by:

    1. Badi H. Baltagi & Qu Feng & Chihwa Kao, 2015. "Estimation of Heterogeneous Panels with Structural Breaks," Center for Policy Research Working Papers 179, Center for Policy Research, Maxwell School, Syracuse University.
    2. Huanjun Zhu & Vasilis Sarafidis & Mervyn Silvapulle & Jiti Gao, 2015. "Testing for a Structural Break in Dynamic Panel Data Models with Common Factors," Monash Econometrics and Business Statistics Working Papers 20/15, Monash University, Department of Econometrics and Business Statistics.

  26. Stefan Hoderlein & Liangjun Su & Halbert White & Thomas Tao Yang, 2015. "Testing for Monotonicity in Unobservables under Unconfoundedness," Boston College Working Papers in Economics 899, Boston College Department of Economics.

    Cited by:

    1. Babii, Andrii & Florens, Jean-Pierre, 2017. "Are unobservables separable?," TSE Working Papers 17-802, Toulouse School of Economics (TSE).
    2. Christoph Breunig, 2019. "Specification Testing in Nonparametric Instrumental Quantile Regression," Papers 1909.10129, arXiv.org.
    3. Su, Liangjun & Ura, Takuya & Zhang, Yichong, 2017. "Non-separable Models with High-dimensional Data," Economics and Statistics Working Papers 15-2017, Singapore Management University, School of Economics.
    4. Tatiana Komarova & Javier Hidalgo, 2019. "Testing nonparametric shape restrictions," Papers 1909.01675, arXiv.org, revised Jun 2020.

  27. Su Liangjun & Xia Wang, 2015. "On Time-Varying Factor Models: Estimation and Testing," Working Papers 08-2015, Singapore Management University, School of Economics.

    Cited by:

    1. Qian, Junhui & Su, Liangjun, 2016. "Shrinkage estimation of common breaks in panel data models via adaptive group fused Lasso," Journal of Econometrics, Elsevier, vol. 191(1), pages 86-109.

  28. Degui Li & Junhui Qian & Su Liangjun, 2015. "Panel Data Models with Interactive Fixed Effects and Multiple Structural Breaks," Working Papers 12-2015, Singapore Management University, School of Economics.

    Cited by:

    1. Saptorshee Kanto Chakraborty & Massimiliano Mazzanti, 2021. "Revisiting the literature on the dynamic Environmental Kuznets Curves using a latent structure approach," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 38(3), pages 923-941, October.
    2. Jafari-Sadeghi, Vahid & Garcia-Perez, Alexeis & Candelo, Elena & Couturier, Jerome, 2021. "Exploring the impact of digital transformation on technology entrepreneurship and technological market expansion: The role of technology readiness, exploration and exploitation," Journal of Business Research, Elsevier, vol. 124(C), pages 100-111.
    3. Bin Peng & Liangjun Su & Joakim Westerlund & Yanrong Yang, 2021. "Interactive Effects Panel Data Models with General Factors and Regressors," Monash Econometrics and Business Statistics Working Papers 23/21, Monash University, Department of Econometrics and Business Statistics.
    4. F. Marta L. Di Lascio & Selene Perazzini, 2024. "A three-way dynamic panel threshold regression model for change point detection in bioimpedance data," BEMPS - Bozen Economics & Management Paper Series BEMPS104, Faculty of Economics and Management at the Free University of Bozen.
    5. Kock, Anders Bredahl, 2016. "Oracle inequalities, variable selection and uniform inference in high-dimensional correlated random effects panel data models," Journal of Econometrics, Elsevier, vol. 195(1), pages 71-85.
    6. Su, Liangjun & Ura, Takuya & Zhang, Yichong, 2017. "Non-separable Models with High-dimensional Data," Economics and Statistics Working Papers 15-2017, Singapore Management University, School of Economics.
    7. Yufeng Mao & Bin Peng & Mervyn Silvapulle & Param Silvapulle & Yanrong Yang, 2021. "Decomposition of Bilateral Trade Flows Using a Three-Dimensional Panel Data Model," Papers 2101.06805, arXiv.org.
    8. Badi H. Baltagi & Qu Feng & Chihwa Kao, 2015. "Estimation of Heterogeneous Panels with Structural Breaks," Center for Policy Research Working Papers 179, Center for Policy Research, Maxwell School, Syracuse University.
    9. Christis Katsouris, 2023. "Optimal Estimation Methodologies for Panel Data Regression Models," Papers 2311.03471, arXiv.org, revised Nov 2023.

  29. Ozabaci, Deniz & Henderson, Daniel J. & Su, Liangjun, 2014. "Additive Nonparametric Regression in the Presence of Endogenous Regressors," IZA Discussion Papers 8144, Institute of Labor Economics (IZA).

    Cited by:

    1. Xin Geng & Carlos Martins-Filho & Feng Yao, 2018. "Estimation of a Partially Linear Regression in Triangular Systems," Working Papers 18-05, Department of Economics, West Virginia University.
    2. Hao Dong & Taisuke Otsu & Luke Taylor, 2022. "Nonparametric estimation of additive models with errors-in-variables," Econometric Reviews, Taylor & Francis Journals, vol. 41(10), pages 1164-1204, November.
    3. Teresa D. Harrison & Daniel J. Henderson & Deniz Ozabaci & Christopher A. Laincz, 2023. "Does one size fit all in the non‐profit donation production function?," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 85(2), pages 373-402, April.
    4. Centorrino Samuele & Feve Frederique & Florens Jean-Pierre, 2017. "Additive Nonparametric Instrumental Regressions: A Guide to Implementation," Journal of Econometric Methods, De Gruyter, vol. 6(1), pages 1-25, January.
    5. Regmi, Krishna & J. Henderson, Daniel, 2019. "Labor demand shocks at birth and cognitive achievement during childhood," Economics of Education Review, Elsevier, vol. 73(C).
    6. Daniel J. Henderson & Anne-Charlotte Souto, 2018. "An Introduction to Nonparametric Regression for Labor Economists," Journal of Labor Research, Springer, vol. 39(4), pages 355-382, December.
    7. Qingliang Fan & Zijian Guo & Ziwei Mei & Cun-Hui Zhang, 2023. "Inference for Nonlinear Endogenous Treatment Effects Accounting for High-Dimensional Covariate Complexity," Papers 2310.08063, arXiv.org, revised Jun 2024.
    8. Chi‐Yang Chu & Mingming Jiang, 2021. "Financial depth, income inequality, and economic transition," Southern Economic Journal, John Wiley & Sons, vol. 88(1), pages 199-244, July.
    9. Andros Kourtellos & Thanasis Stengos & Yiguo Sun, 2017. "Endogeneity in Semiparametric Threshold Regression," Working Paper series 17-13, Rimini Centre for Economic Analysis.
    10. Taining Wang & Feng Yao & Subal C. Kumbhakar, 2024. "A flexible stochastic production frontier model with panel data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(4), pages 564-588, June.
    11. Regmi, Krishna & Henderson, Daniel J., 2019. "Labor Demand Shocks at Birth and Cognitive Achievement during Childhood," IZA Discussion Papers 12521, Institute of Labor Economics (IZA).
    12. Mustafa Koroglu, 2019. "Growth and Debt: An Endogenous Smooth Coefficient Approach," JRFM, MDPI, vol. 12(1), pages 1-22, February.
    13. Kumbhakar, Subal C. & Li, Mingyang & Lien, Gudbrand, 2023. "Do subsidies matter in productivity and profitability changes?," Economic Modelling, Elsevier, vol. 123(C).

  30. Liangjun Su & Zhentao Shi & Peter C.B. Phillips, 2014. "Identifying Latent Structures in Panel Data," Cowles Foundation Discussion Papers 1965, Cowles Foundation for Research in Economics, Yale University.

    Cited by:

    1. Srinivasan, Shweta & Kholod, Nazar & Chaturvedi, Vaibhav & Ghosh, Probal Pratap & Mathur, Ritu & Clarke, Leon & Evans, Meredydd & Hejazi, Mohamad & Kanudia, Amit & Koti, Poonam Nagar & Liu, Bo & Parik, 2018. "Water for electricity in India: A multi-model study of future challenges and linkages to climate change mitigation," Applied Energy, Elsevier, vol. 210(C), pages 673-684.
    2. Andreas Dzemski & Ryo Okui, 2020. "Convergence rate of estimators of clustered panel models with misclassification," Papers 2008.04708, arXiv.org.
    3. Zhan Gao & M. Hashem Pesaran, 2023. "Identification and estimation of categorical random coefficient models," Empirical Economics, Springer, vol. 64(6), pages 2543-2588, June.
    4. Boyuan Zhang, 2020. "Forecasting with Bayesian Grouped Random Effects in Panel Data," Papers 2007.02435, arXiv.org, revised Oct 2020.
    5. Arturas Juodis & Simon Reese, 2018. "The Incidental Parameters Problem in Testing for Remaining Cross-section Correlation," Papers 1810.03715, arXiv.org, revised Feb 2021.
    6. Yiren Wang & Peter C. B. Phillips & Liangjun Su, 2023. "Panel Data Models with Time-Varying Latent Group Structures," Cowles Foundation Discussion Papers 2364, Cowles Foundation for Research in Economics, Yale University.
    7. Wagner, Martin & Grabarczyk, Peter & Hong, Seung Hyun, 2020. "Fully modified OLS estimation and inference for seemingly unrelated cointegrating polynomial regressions and the environmental Kuznets curve for carbon dioxide emissions," Journal of Econometrics, Elsevier, vol. 214(1), pages 216-255.
    8. Xiaorong Yang & Jia Chen & Degui Li & Runze Li, 2023. "Functional-Coefficient Quantile Regression for Panel Data with Latent Group Structure," Papers 2303.13218, arXiv.org.
    9. Fei Liu & Jiti Gao & Yanrong Yang, 2020. "Time-Varying Panel Data Models with an Additive Factor Structure," Monash Econometrics and Business Statistics Working Papers 42/20, Monash University, Department of Econometrics and Business Statistics.
    10. Levent Kutlu & Robin C. Sickles & Mike G. Tsionas & Emmanuel Mamatzakis, 2022. "Heterogeneous decision-making and market power: an application to Eurozone banks," Empirical Economics, Springer, vol. 63(6), pages 3061-3092, December.
    11. Huang, Danyang & Hu, Wei & Jing, Bingyi & Zhang, Bo, 2023. "Grouped spatial autoregressive model," Computational Statistics & Data Analysis, Elsevier, vol. 178(C).
    12. Lamarche, Carlos & Parker, Thomas, 2023. "Wild bootstrap inference for penalized quantile regression for longitudinal data," Journal of Econometrics, Elsevier, vol. 235(2), pages 1799-1826.
    13. Jorge A. Rivero, 2023. "Unobserved Grouped Heteroskedasticity and Fixed Effects," Papers 2310.14068, arXiv.org, revised Oct 2023.
    14. Chiang, Harold D. & Rodrigue, Joel & Sasaki, Yuya, 2023. "Post-Selection Inference In Three-Dimensional Panel Data," Econometric Theory, Cambridge University Press, vol. 39(3), pages 623-658, June.
    15. Miao, Ke & Li, Kunpeng & Su, Liangjun, 2020. "Panel threshold models with interactive fixed effects," Journal of Econometrics, Elsevier, vol. 219(1), pages 137-170.
    16. Babii, Andrii & Ball, Ryan T. & Ghysels, Eric & Striaukas, Jonas, 2023. "Machine learning panel data regressions with heavy-tailed dependent data: Theory and application," Journal of Econometrics, Elsevier, vol. 237(2).
    17. Joao, Igor Custodio & Lucas, André & Schaumburg, Julia & Schwaab, Bernd, 2021. "Dynamic clustering of multivariate panel data," Working Paper Series 2577, European Central Bank.
    18. Nicolas Apfel & Helmut Farbmacher & Rebecca Groh & Martin Huber & Henrika Langen, 2022. "Detecting Grouped Local Average Treatment Effects and Selecting True Instruments," Papers 2207.04481, arXiv.org, revised Oct 2023.
    19. Yang, Shuquan & Ling, Nengxiang, 2023. "Robust projected principal component analysis for large-dimensional semiparametric factor modeling," Journal of Multivariate Analysis, Elsevier, vol. 195(C).
    20. Oh, Dong Hwan & Patton, Andrew J., 2023. "Dynamic factor copula models with estimated cluster assignments," Journal of Econometrics, Elsevier, vol. 237(2).
    21. Sun, Yan & Wan, Chuang & Zhang, Wenyang & Zhong, Wei, 2024. "A Multi-Kink quantile regression model with common structure for panel data analysis," Journal of Econometrics, Elsevier, vol. 239(2).
    22. Jiti Gao & Kai Xia, 2017. "Heterogeneous panel data models with cross-sectional dependence," Monash Econometrics and Business Statistics Working Papers 16/17, Monash University, Department of Econometrics and Business Statistics.
    23. Bhaumik, Sumon & Chowdhury, Subhasish M. & Dimova, Ralitza & Fromell, Hanna, 2023. "Identity, Communication, and Conflict: An Experiment," GLO Discussion Paper Series 1255, Global Labor Organization (GLO).
    24. Jin Seo Cho & Peter C. B. Phillips & Juwon Seo, 2019. "Parametric Inference on the Mean of Functional Data Applied to Lifetime Income Curves," Working papers 2019rwp-153, Yonsei University, Yonsei Economics Research Institute.
    25. Vasilis Sarafidis & Tom Wansbeek, 2020. "Celebrating 40 Years of Panel Data Analysis: Past, Present and Future," Monash Econometrics and Business Statistics Working Papers 6/20, Monash University, Department of Econometrics and Business Statistics.
    26. Alonso, Andrés M. & Galeano, Pedro & Peña, Daniel, 2020. "A robust procedure to build dynamic factor models with cluster structure," Journal of Econometrics, Elsevier, vol. 216(1), pages 35-52.
    27. Boyuan Zhang, 2022. "Incorporating Prior Knowledge of Latent Group Structure in Panel Data Models," Papers 2211.16714, arXiv.org, revised Oct 2023.
    28. Dong Hwan Oh & Andrew J. Patton, 2021. "Dynamic Factor Copula Models with Estimated Cluster Assignments," Finance and Economics Discussion Series 2021-029r1, Board of Governors of the Federal Reserve System (U.S.), revised 06 May 2022.
    29. Weijie Cui & Yong Li, 2023. "Bicluster Analysis of Heterogeneous Panel Data via M-Estimation," Mathematics, MDPI, vol. 11(10), pages 1-19, May.
    30. Liu, Ruiqi & Shang, Zuofeng & Zhang, Yonghui & Zhou, Qiankun, 2020. "Identification and estimation in panel models with overspecified number of groups," Journal of Econometrics, Elsevier, vol. 215(2), pages 574-590.
    31. Freeman, Hugo & Weidner, Martin, 2023. "Linear panel regressions with two-way unobserved heterogeneity," Journal of Econometrics, Elsevier, vol. 237(1).
    32. Feng, Guohua & Gao, Jiti & Peng, Bin & Zhang, Xiaohui, 2017. "A varying-coefficient panel data model with fixed effects: Theory and an application to US commercial banks," Journal of Econometrics, Elsevier, vol. 196(1), pages 68-82.
    33. Tadao Hoshino, 2020. "A Pairwise Strategic Network Formation Model with Group Heterogeneity: With an Application to International Travel," Papers 2012.14886, arXiv.org, revised Feb 2021.
    34. Pigini, Claudia & Pionati, Alessandro & Valentini, Francesco, 2023. "Specification testing with grouped fixed effects," MPRA Paper 117821, University Library of Munich, Germany.
    35. Michael Vogt & Oliver Linton, 2018. "Multiscale clustering of nonparametric regression curves," CeMMAP working papers CWP08/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    36. Liu, Yanbo & Phillips, Peter C. B. & Yu, Jun, 2022. "A Panel Clustering Approach to Analyzing Bubble Behavior," Economics and Statistics Working Papers 1-2022, Singapore Management University, School of Economics.
    37. Ruiqi Liu & Ben Boukai & Zuofeng Shang, 2019. "Statistical Inference on Partially Linear Panel Model under Unobserved Linearity," Papers 1911.08830, arXiv.org.
    38. Huang, Wenxin & Jin, Sainan & Phillips, Peter C.B. & Su, Liangjun, 2020. "Nonstationary Panel Models with Latent Group Structures and Cross-Section Dependence," Economics and Statistics Working Papers 7-2020, Singapore Management University, School of Economics.
    39. Leng, Xuan & Chen, Heng & Wang, Wendun, 2023. "Multi-dimensional latent group structures with heterogeneous distributions," Journal of Econometrics, Elsevier, vol. 233(1), pages 1-21.
    40. Wang, Wuyi & Phillips, Peter C.B. & Su, Liangjun, 2018. "The Heterogeneous Effects of the Minimum Wage on Employment Across States," Economics and Statistics Working Papers 11-2018, Singapore Management University, School of Economics.
    41. Miao, Ke & Su, Liangjun & Wang, Wendun, 2020. "Panel threshold regressions with latent group structures," Journal of Econometrics, Elsevier, vol. 214(2), pages 451-481.
    42. Shujie Ma & Liangjun Su & Yichong Zhang, 2020. "Detecting Latent Communities in Network Formation Models," Papers 2005.03226, arXiv.org, revised Mar 2021.
    43. Falco J. Bargagli-Stoffi & Jan Niederreiter & Massimo Riccaboni, 2020. "Supervised learning for the prediction of firm dynamics," Papers 2009.06413, arXiv.org.
    44. Mei, Ziwei & Shi, Zhentao, 2024. "On LASSO for high dimensional predictive regression," Journal of Econometrics, Elsevier, vol. 242(2).
    45. Vira Semenova & Matt Goldman & Victor Chernozhukov & Matt Taddy, 2023. "Inference on heterogeneous treatment effects in high‐dimensional dynamic panels under weak dependence," Quantitative Economics, Econometric Society, vol. 14(2), pages 471-510, May.
    46. Michael Vogt & Oliver Linton, 2015. "Classification of nonparametric regression functions in heterogeneous panels," CeMMAP working papers 06/15, Institute for Fiscal Studies.
    47. Lee, Ji Hyung & Shi, Zhentao & Gao, Zhan, 2022. "On LASSO for predictive regression," Journal of Econometrics, Elsevier, vol. 229(2), pages 322-349.
    48. Saptorshee Kanto Chakraborty & Massimiliano Mazzanti, 2021. "Revisiting the literature on the dynamic Environmental Kuznets Curves using a latent structure approach," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 38(3), pages 923-941, October.
    49. In Choi & Rui Lin & Yongcheol Shin, 2020. "Canonical Correlation-based Model Selection for the Multilevel Factors," Working Papers 2008, Nam Duck-Woo Economic Research Institute, Sogang University (Former Research Institute for Market Economy).
    50. Jia Chen, 2019. "Estimating latent group structure in time-varying coefficient panel data models," The Econometrics Journal, Royal Economic Society, vol. 22(3), pages 223-240.
    51. Wang, Wuyi & Su, Liangjun, 2017. "Identifying Latent Group Structures in Nonlinear Panels," Economics and Statistics Working Papers 19-2017, Singapore Management University, School of Economics.
    52. Simon Freyaldenhoven & Christian Hansen & Jorge Perez Perez & Jesse Shapiro, 2021. "Visualization, Identification, and stimation in the Linear Panel Event-Study Design," Working Papers 21-44, Federal Reserve Bank of Philadelphia.
    53. Jianning Kong & Peter C.B. Phillips & Donggyu Sul, 2017. "Weak s- Convergence: Theory and Applications," Cowles Foundation Discussion Papers 2072, Cowles Foundation for Research in Economics, Yale University.
    54. Degui Li & Bin Peng & Songqiao Tang & Weibiao Wu, 2023. "Inference of Grouped Time-Varying Network Vector Autoregression Models," Monash Econometrics and Business Statistics Working Papers 5/23, Monash University, Department of Econometrics and Business Statistics.
    55. Yannick V. Markhof, 2020. "Divide to Conquer? Latent Preference Types and Country-level Heterogeneity," CSAE Working Paper Series 2020-05, Centre for the Study of African Economies, University of Oxford.
    56. Andrea Orame, 2020. "The role of bank supply in the Italian credit market: evidence from a new regional survey," Temi di discussione (Economic working papers) 1279, Bank of Italy, Economic Research and International Relations Area.
    57. Yoonseok Lee & Donggyu Sul, 2022. "Trimmed Mean Group Estimation," Advances in Econometrics, in: Essays in Honor of M. Hashem Pesaran: Panel Modeling, Micro Applications, and Econometric Methodology, volume 43, pages 177-202, Emerald Group Publishing Limited.
    58. Jiaying Gu & Stanislav Volgushev, 2018. "Panel Data Quantile Regression with Grouped Fixed Effects," Papers 1801.05041, arXiv.org, revised Aug 2018.
    59. Denis Chetverikov & Elena Manresa, 2022. "Spectral and post-spectral estimators for grouped panel data models," Papers 2212.13324, arXiv.org, revised Dec 2022.
    60. Okui, Ryo & Yanagi, Takahide, 2019. "Panel data analysis with heterogeneous dynamics," Journal of Econometrics, Elsevier, vol. 212(2), pages 451-475.
    61. Chang Cai & Sandy Dall’Erba, 2021. "On the evaluation of heterogeneous climate change impacts on US agriculture: does group membership matter?," Climatic Change, Springer, vol. 167(1), pages 1-23, July.
    62. Juan Romero-Padilla, 2018. "A method for clustering panel data based on parameter homogeneity," Journal of Statistical and Econometric Methods, SCIENPRESS Ltd, vol. 7(3), pages 1-3.
    63. Ziwei Mei & Zhentao Shi & Peter C. B. Phillips, 2022. "The boosted HP filter is more general than you might think," Cowles Foundation Discussion Papers 2348, Cowles Foundation for Research in Economics, Yale University.
    64. Ayden Higgins & Federico Martellosio, 2019. "Shrinkage Estimation of Network Spillovers with Factor Structured Errors," Papers 1909.02823, arXiv.org, revised Nov 2021.
    65. Gao, Jiti & Xia, Kai & Zhu, Huanjun, 2020. "Heterogeneous panel data models with cross-sectional dependence," Journal of Econometrics, Elsevier, vol. 219(2), pages 329-353.
    66. Saptorshee Kanto Chakraborty & Antoine Mandel, 2024. "Understanding EU regional macroeconomic tipping points using panel threshold technique," Economic Change and Restructuring, Springer, vol. 57(3), pages 1-30, June.
    67. Fei Liu & Jiti Gao & Yanrong Yang, 2019. "Nonparametric Estimation in Panel Data Models with Heterogeneity and Time Varyingness," Monash Econometrics and Business Statistics Working Papers 24/19, Monash University, Department of Econometrics and Business Statistics.
    68. Francesco Fallucchi & Andrea Mercatanti & Jan Niederreiter, 2021. "Identifying types in contest experiments," International Journal of Game Theory, Springer;Game Theory Society, vol. 50(1), pages 39-61, March.
    69. Ando, Tomohiro & Bai, Jushan, 2021. "Large-scale generalized linear longitudinal data models with grouped patterns of unobserved heterogeneity," MPRA Paper 111431, University Library of Munich, Germany.
    70. Mammen, Enno & Wilke, Ralf A. & Zapp, Kristina Maria, 2022. "Estimation of group structures in panel models with individual fixed effects," ZEW Discussion Papers 22-023, ZEW - Leibniz Centre for European Economic Research.
    71. Zhao, Jiayang & Liu, Jie, 2023. "Homogeneous analysis on network effects in network autoregressive model," Finance Research Letters, Elsevier, vol. 58(PD).
    72. Zhan Gao & Zhentao Shi, 2018. "Implementing Convex Optimization in R: Two Econometric Examples," Papers 1806.10423, arXiv.org, revised Aug 2019.
    73. Dong, Yingjie & Huang, Wenxin & Tse, Yiu-Kuen, 2023. "Price comovement and market segmentation of Chinese A- and H-shares: Evidence from a panel latent-factor model," Journal of International Money and Finance, Elsevier, vol. 131(C).
    74. Yeonwoo Rho & Yun Liu & Hie Joo Ahn, 2020. "Revealing Cluster Structures Based on Mixed Sampling Frequencies," Papers 2004.09770, arXiv.org, revised Feb 2021.
    75. Ziwei Mei & Peter C. B. Phillips & Zhentao Shi, 2024. "The boosted Hodrick‐Prescott filter is more general than you might think," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(7), pages 1260-1281, November.
    76. Yu Hao & Hiroyuki Kasahara, 2022. "Testing the Number of Components in Finite Mixture Normal Regression Model with Panel Data," Papers 2210.02824, arXiv.org, revised Jun 2023.
    77. Nibbering, D. & Paap, R., 2019. "Panel Forecasting with Asymmetric Grouping," Econometric Institute Research Papers EI-2019-30, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    78. Daniel J. Lewis & Davide Melcangi & Laura Pilossoph & Aidan Toner-Rodgers, 2022. "Approximating Grouped Fixed Effects Estimation via Fuzzy Clustering Regression," Staff Reports 1033, Federal Reserve Bank of New York.
    79. Mehrabani, Ali, 2023. "Estimation and identification of latent group structures in panel data," Journal of Econometrics, Elsevier, vol. 235(2), pages 1464-1482.
    80. Su, Liangjun & Ju, Gaosheng, 2018. "Identifying latent grouped patterns in panel data models with interactive fixed effects," Journal of Econometrics, Elsevier, vol. 206(2), pages 554-573.
    81. Ziwei Mei & Zhentao Shi, 2022. "On LASSO for High Dimensional Predictive Regression," Papers 2212.07052, arXiv.org, revised Jan 2024.
    82. Hie Joo Ahn & Yun Liu & Yeonwoo Rho, 2020. "Revealing Cluster Structures Based on Mixed Sampling Frequencies," Finance and Economics Discussion Series 2020-082, Board of Governors of the Federal Reserve System (U.S.).
    83. Okui, Ryo & Wang, Wendun, 2021. "Heterogeneous structural breaks in panel data models," Journal of Econometrics, Elsevier, vol. 220(2), pages 447-473.
    84. Ryo Okui & Takahide Yanagi, 2018. "Kernel Estimation for Panel Data with Heterogeneous Dynamics," Papers 1802.08825, arXiv.org, revised May 2019.
    85. Lu, Xun & Su, Liangjun, 2023. "Uniform inference in linear panel data models with two-dimensional heterogeneity," Journal of Econometrics, Elsevier, vol. 235(2), pages 694-719.
    86. Hafner, Christian & Walders, Fabian, 2017. "Heterogeneous Liquidity Effects in Corporate Bond Spreads," LIDAM Reprints ISBA 2017037, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    87. Hong, Shengjie & Su, Liangjun & Jiang, Tao, 2023. "Profile GMM estimation of panel data models with interactive fixed effects," Journal of Econometrics, Elsevier, vol. 235(2), pages 927-948.
    88. Max Cytrynbaum, 2020. "Blocked Clusterwise Regression," Papers 2001.11130, arXiv.org.
    89. Sophie-Charlotte Klose, 2020. "Identifying Latent Structures in Maternal Employment: Evidence on the German Parental Benefit Reform," Papers 2011.03541, arXiv.org.
    90. Kathleen T. Li, 2024. "Frontiers: A Simple Forward Difference-in-Differences Method," Marketing Science, INFORMS, vol. 43(2), pages 267-279, March.
    91. Min Wang & Yunbei Ma, 2024. "Spatial Heterogeneity and Clustering of County-Level Carbon Emissions in China," Sustainability, MDPI, vol. 16(23), pages 1-17, November.
    92. Zhang, Yingying & Wang, Huixia Judy & Zhu, Zhongyi, 2019. "Quantile-regression-based clustering for panel data," Journal of Econometrics, Elsevier, vol. 213(1), pages 54-67.
    93. Li, Donglin & Wang, Wenyue & Ren, Yanyan, 2024. "Quantile estimation of heterogenous panel quantile model with group structure," Economics Letters, Elsevier, vol. 241(C).
    94. Wei Chen & Xilu Chen & Chang-Tai Hsieh & Zheng Song, 2019. "A Forensic Examination of China's National Accounts," NBER Working Papers 25754, National Bureau of Economic Research, Inc.
    95. Qian, Junhui & Su, Liangjun, 2016. "Shrinkage estimation of common breaks in panel data models via adaptive group fused Lasso," Journal of Econometrics, Elsevier, vol. 191(1), pages 86-109.
    96. Krasnokutskaya, Elena & Song, Kyungchul & Tang, Xun, 2022. "Estimating unobserved individual heterogeneity using pairwise comparisons," Journal of Econometrics, Elsevier, vol. 226(2), pages 477-497.
    97. Christis Katsouris, 2023. "Optimal Estimation Methodologies for Panel Data Regression Models," Papers 2311.03471, arXiv.org, revised Nov 2023.
    98. Wang, Wei & Xiao, Zhijie & Ren, Yanyan & Yan, Xiaodong, 2023. "A bi-integrative analysis of two-dimensional heterogeneous panel data models," Economics Letters, Elsevier, vol. 230(C).
    99. Jiangtao Duan & Wei Gao & Hao Qu & Hon Keung Tony, 2019. "Subspace Clustering for Panel Data with Interactive Effects," Papers 1909.09928, arXiv.org, revised Feb 2021.
    100. Fernández-Val, Iván & Gao, Wayne Yuan & Liao, Yuan & Vella, Francis, 2022. "Dynamic Heterogeneous Distribution Regression Panel Models, with an Application to Labor Income Processes," IZA Discussion Papers 15236, Institute of Labor Economics (IZA).
    101. Didier Nibbering & Richard Paap, 2024. "Forecasting carbon emissions using asymmetric grouping," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(6), pages 2228-2256, September.
    102. Lumsdaine, Robin L. & Okui, Ryo & Wang, Wendun, 2023. "Estimation of panel group structure models with structural breaks in group memberships and coefficients," Journal of Econometrics, Elsevier, vol. 233(1), pages 45-65.
    103. Bruhin, Adrian & Janizzi, Kelly & Thöni, Christian, 2020. "Uncovering the heterogeneity behind cross-cultural variation in antisocial punishment," Journal of Economic Behavior & Organization, Elsevier, vol. 180(C), pages 291-308.
    104. Liebl, Dominik & Walders, Fabian, 2019. "Parameter regimes in partial functional panel regression," Econometrics and Statistics, Elsevier, vol. 11(C), pages 105-115.
    105. Sophie Therese Schneider & Konstantin M. Wacker, 2022. "Explaining the global landscape of foreign direct investment: Knowledge capital, gravity, and the role of culture and institutions," The World Economy, Wiley Blackwell, vol. 45(10), pages 3080-3108, October.
    106. Su, Liangjun & Wang, Wuyi & Xu, Xingbai, 2023. "Identifying latent group structures in spatial dynamic panels," Journal of Econometrics, Elsevier, vol. 235(2), pages 1955-1980.
    107. Yiren Wang & Liangjun Su & Yichong Zhang, 2022. "Low-rank Panel Quantile Regression: Estimation and Inference," Papers 2210.11062, arXiv.org.
    108. Myungkou Shin, 2022. "Finitely Heterogeneous Treatment Effect in Event-study," Papers 2204.02346, arXiv.org, revised Oct 2024.
    109. Degui Li & Bin Peng & Songqiao Tang & Weibiao Wu, 2023. "Estimation of Grouped Time-Varying Network Vector Autoregression Models," Papers 2303.10117, arXiv.org, revised Mar 2024.
    110. Lu, Xun & Su, Liangjun, 2020. "Determining individual or time effects in panel data models," Journal of Econometrics, Elsevier, vol. 215(1), pages 60-83.
    111. Likai Chen & Georg Keilbar & Liangjun Su & Weining Wang, 2023. "Inference on many jumps in nonparametric panel regression models," Papers 2312.01162, arXiv.org, revised Jan 2025.
    112. Friedel Bolle & Jonathan H. W. Tan, 2021. "Behavioral types of the dark side: identifying heterogeneous conflict strategies," Journal of the Economic Science Association, Springer;Economic Science Association, vol. 7(1), pages 49-63, September.
    113. Bennedsen, Mikkel & Hillebrand, Eric & Jensen, Sebastian, 2023. "A neural network approach to the environmental Kuznets curve," Energy Economics, Elsevier, vol. 126(C).
    114. Katerina Chrysikou & George Kapetanios, 2024. "Heterogeneous Grouping Structures in Panel Data," Papers 2407.19509, arXiv.org.
    115. Archer Gong Zhang & Jiahua Chen, 2023. "Optimal Estimation under a Semiparametric Density Ratio Model," Papers 2309.09103, arXiv.org.
    116. Gu, Jiaying & Volgushev, Stanislav, 2019. "Panel data quantile regression with grouped fixed effects," Journal of Econometrics, Elsevier, vol. 213(1), pages 68-91.
    117. Guðmundsson, Guðmundur Stefán & Brownlees, Christian, 2021. "Detecting groups in large vector autoregressions," Journal of Econometrics, Elsevier, vol. 225(1), pages 2-26.
    118. Geert Dhaene & Martin Weidner, 2023. "Approximate Functional Differencing," Papers 2301.13736, arXiv.org, revised May 2023.
    119. Yu, Lu & Gu, Jiaying & Volgushev, Stanislav, 2024. "Spectral clustering with variance information for group structure estimation in panel data," Journal of Econometrics, Elsevier, vol. 241(1).
    120. Langevin, R.;, 2024. "Consistent Estimation of Finite Mixtures: An Application to Latent Group Panel Structures," Health, Econometrics and Data Group (HEDG) Working Papers 24/16, HEDG, c/o Department of Economics, University of York.
    121. Zhentao Shi & Liangjun Su & Tian Xie, 2020. "L2-Relaxation: With Applications to Forecast Combination and Portfolio Analysis," Papers 2010.09477, arXiv.org, revised Aug 2022.
    122. Michael Vogt & Oliver Linton, 2017. "Classification of non-parametric regression functions in longitudinal data models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 79(1), pages 5-27, January.
    123. Arturas Juodis & Yiannis Karavias, 2019. "Partially heterogeneous tests for Granger non-causality in panel data," Bank of Lithuania Working Paper Series 59, Bank of Lithuania.
    124. Levent Kutlu & Kien C. Tran & Mike G. Tsionas, 2020. "Unknown latent structure and inefficiency in panel stochastic frontier models," Journal of Productivity Analysis, Springer, vol. 54(1), pages 75-86, August.
    125. Jan Niederreiter, 2023. "Broadening Economics in the Era of Artificial Intelligence and Experimental Evidence," Italian Economic Journal: A Continuation of Rivista Italiana degli Economisti and Giornale degli Economisti, Springer;Società Italiana degli Economisti (Italian Economic Association), vol. 9(1), pages 265-294, March.
    126. Li, Kunpeng & Cui, Guowei & Lu, Lina, 2020. "Efficient estimation of heterogeneous coefficients in panel data models with common shocks," Journal of Econometrics, Elsevier, vol. 216(2), pages 327-353.
    127. Thomas Wiemann, 2023. "Optimal Categorical Instrumental Variables," Papers 2311.17021, arXiv.org, revised May 2024.

  31. Liangjun Su & Sainan Jin & Yonghui Zhang, 2014. "Specification Test for Panel Data Models with Interactive Fixed Effects," Working Papers 08-2014, Singapore Management University, School of Economics.

    Cited by:

    1. Xun Lu & Su Liangjun, 2015. "Shrinkage Estimation of Dynamic Panel Data Models with Interactive Fixed Effects," Working Papers 02-2015, Singapore Management University, School of Economics.
    2. Bai, Jushan, 2013. "Likelihood approach to dynamic panel models with interactive effects," MPRA Paper 50267, University Library of Munich, Germany.
    3. Gao, Jiti & Linton, Oliver & Peng, Bin, 2020. "Inference On A Semiparametric Model With Global Power Law And Local Nonparametric Trends," Econometric Theory, Cambridge University Press, vol. 36(2), pages 223-249, April.
    4. Jiti Gao & Bin Peng & Yayi Yan, 2023. "Higher-order Expansions and Inference for Panel Data Models," Monash Econometrics and Business Statistics Working Papers 15/23, Monash University, Department of Econometrics and Business Statistics.
    5. Sainan Jin & Liangjun Su & Yonghui Zhang, 2014. "Nonparametric Testing for Anomaly Effects in Empirical Asset Pricing Models," Working Papers 09-2014, Singapore Management University, School of Economics.
    6. Jafari-Sadeghi, Vahid & Sukumar, Arun & Pagán-Castaño, Esther & Dana, Léo-Paul, 2021. "What drives women towards domestic vs international business venturing? An empirical analysis in emerging markets," Journal of Business Research, Elsevier, vol. 134(C), pages 647-660.
    7. Cesa-Bianchi, Ambrogio, 2016. "Finance and synchronization," LSE Research Online Documents on Economics 86226, London School of Economics and Political Science, LSE Library.
    8. Bing Jiang & Yanrong Yang & Jiti Gao & Cheng Hsiao, 2017. "Recursive estimation in large panel data models: Theory and practice," Monash Econometrics and Business Statistics Working Papers 5/17, Monash University, Department of Econometrics and Business Statistics.
    9. Wang, Hongfei & Liu, Binghui & Feng, Long & Ma, Yanyuan, 2024. "Rank-based max-sum tests for mutual independence of high-dimensional random vectors," Journal of Econometrics, Elsevier, vol. 238(1).
    10. Su, Liangjun & Wang, Xia, 2017. "On time-varying factor models: Estimation and testing," Journal of Econometrics, Elsevier, vol. 198(1), pages 84-101.
    11. Jafari-Sadeghi, Vahid & Garcia-Perez, Alexeis & Candelo, Elena & Couturier, Jerome, 2021. "Exploring the impact of digital transformation on technology entrepreneurship and technological market expansion: The role of technology readiness, exploration and exploitation," Journal of Business Research, Elsevier, vol. 124(C), pages 100-111.
    12. Juodis, Arturas & Sarafidis, Vasilis, 2020. "An Incidental Parameters Free Inference Approach for Panels with Common Shocks," MPRA Paper 104906, University Library of Munich, Germany.
    13. F. Marta L. Di Lascio & Selene Perazzini, 2024. "A three-way dynamic panel threshold regression model for change point detection in bioimpedance data," BEMPS - Bozen Economics & Management Paper Series BEMPS104, Faculty of Economics and Management at the Free University of Bozen.
    14. Bai, Jushan & Li, Kunpeng, 2021. "Dynamic spatial panel data models with common shocks," Journal of Econometrics, Elsevier, vol. 224(1), pages 134-160.
    15. Jiti Gao & Bin Peng & Yayi Yan, 2022. "A Simple Bootstrap Method for Panel Data Inferences," Monash Econometrics and Business Statistics Working Papers 7/22, Monash University, Department of Econometrics and Business Statistics.
    16. Su, Liangjun & Ju, Gaosheng, 2018. "Identifying latent grouped patterns in panel data models with interactive fixed effects," Journal of Econometrics, Elsevier, vol. 206(2), pages 554-573.
    17. Feng, Guohua & Gao, Jiti & Peng, Bin, 2022. "An integrated panel data approach to modelling economic growth," Journal of Econometrics, Elsevier, vol. 228(2), pages 379-397.
    18. Su, Liangjun & Ura, Takuya & Zhang, Yichong, 2017. "Non-separable Models with High-dimensional Data," Economics and Statistics Working Papers 15-2017, Singapore Management University, School of Economics.
    19. Isabel Casas & Jiti Gao & Bin Peng & Shangyu Xie, 2019. "Time-Varying Income Elasticities of Healthcare Expenditure for the OECD and Eurozone," Monash Econometrics and Business Statistics Working Papers 28/19, Monash University, Department of Econometrics and Business Statistics.
    20. Su, Liangjun & Zhang, Yonghui & Wei, Jie, 2016. "A practical test for strict exogeneity in linear panel data models with fixed effects," Economics Letters, Elsevier, vol. 147(C), pages 27-31.
    21. Jin, Sainan & Miao, Ke & Su, Liangjun, 2021. "On factor models with random missing: EM estimation, inference, and cross validation," Journal of Econometrics, Elsevier, vol. 222(1), pages 745-777.
    22. Feng, Guohua & Peng, Bin & Su, Liangjun & Yang, Thomas Tao, 2019. "Semi-parametric single-index panel data models with interactive fixed effects: Theory and practice," Journal of Econometrics, Elsevier, vol. 212(2), pages 607-622.
    23. Badi H. Baltagi & Qu Feng & Chihwa Kao, 2015. "Estimation of Heterogeneous Panels with Structural Breaks," Center for Policy Research Working Papers 179, Center for Policy Research, Maxwell School, Syracuse University.
    24. Li, Jiaman & Liu, Guixian & Dong, Jiajia, 2024. "Coordinated reduction effect of pollutant discharge fees on enterprises' pollutant and carbon emissions in China," Energy Economics, Elsevier, vol. 136(C).
    25. Christis Katsouris, 2023. "Optimal Estimation Methodologies for Panel Data Regression Models," Papers 2311.03471, arXiv.org, revised Nov 2023.
    26. Jafari-Sadeghi, Vahid, 2020. "The motivational factors of business venturing: Opportunity versus necessity? A gendered perspective on European countries," Journal of Business Research, Elsevier, vol. 113(C), pages 279-289.
    27. Bai, Jushan & Liao, Yuan, 2017. "Inferences in panel data with interactive effects using large covariance matrices," Journal of Econometrics, Elsevier, vol. 200(1), pages 59-78.
    28. Victor Chernozhukov & Christian Hansen & Yuan Liao & Yinchu Zhu, 2019. "Inference for heterogeneous effects using low-rank estimations," CeMMAP working papers CWP31/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    29. Li, Hongjun & Li, Qi & Liu, Ruixuan, 2016. "Consistent model specification tests based on k-nearest-neighbor estimation method," Journal of Econometrics, Elsevier, vol. 194(1), pages 187-202.
    30. Su, Liangjun & Zheng, Xin, 2017. "A martingale-difference-divergence-based test for specification," Economics Letters, Elsevier, vol. 156(C), pages 162-167.

  32. Sainan Jin & Liangjun Su & Yonghui Zhang, 2014. "Nonparametric Testing for Anomaly Effects in Empirical Asset Pricing Models," Working Papers 09-2014, Singapore Management University, School of Economics.

    Cited by:

    1. Rubo Zhao & Yixiang Tian & Ao Lei & Francis Boadu & Ze Ren, 2019. "The Effect of Local Government Debt on Regional Economic Growth in China: A Nonlinear Relationship Approach," Sustainability, MDPI, vol. 11(11), pages 1-22, May.

  33. Yan Li & Liangjun Su & Yuewu Xu, 2014. "A Combined Approach to the Inference of Conditional Factor Models," Working Papers 10-2014, Singapore Management University, School of Economics.

    Cited by:

    1. Sainan Jin & Liangjun Su & Yonghui Zhang, 2014. "Nonparametric Testing for Anomaly Effects in Empirical Asset Pricing Models," Working Papers 09-2014, Singapore Management University, School of Economics.
    2. Mikihito Nishi, 2024. "Estimating Time-Varying Parameters of Various Smoothness in Linear Models via Kernel Regression," Papers 2406.14046, arXiv.org, revised Jan 2025.
    3. Wolter, James Lewis, 2016. "Kernel estimation of hazard functions when observations have dependent and common covariates," Journal of Econometrics, Elsevier, vol. 193(1), pages 1-16.
    4. James Wolter, 2015. "Kernel Estimation Of Hazard Functions When Observations Have Dependent and Common Covariates," Economics Series Working Papers 761, University of Oxford, Department of Economics.

  34. Junhui Qian & Liangjun Su, 2014. "Shrinkage Estimation of Regression Models with Multiple Structural Changes," Working Papers 06-2014, Singapore Management University, School of Economics.

    Cited by:

    1. Behrendt, Simon & Schweikert, Karsten, 2021. "A Note on Adaptive Group Lasso for Structural Break Time Series," Econometrics and Statistics, Elsevier, vol. 17(C), pages 156-172.
    2. Ma, Shujie & Su, Liangjun, 2018. "Estimation of large dimensional factor models with an unknown number of breaks," Journal of Econometrics, Elsevier, vol. 207(1), pages 1-29.
    3. Yoshiyuki Kurachi & Kazuhiro Hiraki & Shinichi Nishioka, 2016. "Does a Higher Frequency of Micro-level Price Changes Matter for Macro Price Stickiness?: Assessing the Impact of Temporary Price Changes," Bank of Japan Working Paper Series 16-E-9, Bank of Japan.
    4. Guanyu Su & Junhui Qian, 2021. "Structural Changes in the Renminbi Exchange Rate Mechanism," China & World Economy, Institute of World Economics and Politics, Chinese Academy of Social Sciences, vol. 29(2), pages 1-23, March.
    5. Artem Prokhorov & Peter Radchenko & Alexander Semenov & Anton Skrobotov, 2024. "Change-Point Detection in Time Series Using Mixed Integer Programming," Papers 2408.05665, arXiv.org.
    6. Weijie Cui & Yong Li, 2023. "Bicluster Analysis of Heterogeneous Panel Data via M-Estimation," Mathematics, MDPI, vol. 11(10), pages 1-19, May.
    7. Karsten Schweikert, 2022. "Detecting Multiple Structural Breaks in Systems of Linear Regression Equations with Integrated and Stationary Regressors," Papers 2201.05430, arXiv.org, revised Sep 2024.
    8. Wang, Wuyi & Su, Liangjun, 2017. "Identifying Latent Group Structures in Nonlinear Panels," Economics and Statistics Working Papers 19-2017, Singapore Management University, School of Economics.
    9. Miao, Ke & Phillips, Peter C.B. & Su, Liangjun, 2023. "High-dimensional VARs with common factors," Journal of Econometrics, Elsevier, vol. 233(1), pages 155-183.
    10. Lee Jaeeun & Chen Jie, 2019. "A penalized regression approach for DNA copy number study using the sequencing data," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 18(4), pages 1-14, August.
    11. Xu Cheng & Zhipeng Liao & Frank Schorfheide, 2016. "Shrinkage Estimation of High-Dimensional Factor Models with Structural Instabilities," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 83(4), pages 1511-1543.
    12. Gabriela Ciuperca & Matúš Maciak, 2020. "Change‐point detection in a linear model by adaptive fused quantile method," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 47(2), pages 425-463, June.
    13. Okui, Ryo & Wang, Wendun, 2021. "Heterogeneous structural breaks in panel data models," Journal of Econometrics, Elsevier, vol. 220(2), pages 447-473.
    14. Christis Katsouris, 2023. "High Dimensional Time Series Regression Models: Applications to Statistical Learning Methods," Papers 2308.16192, arXiv.org.
    15. Tae-Hwy Lee & Shahnaz Parsaeian & Aman Ullah, 2021. "Efficient Combined Estimation under Structural Breaks," Working Papers 202101, University of California at Riverside, Department of Economics.
    16. Berndt Jesenko & Christian Schlögl, 2021. "The effect of web of science subject categories on clustering: the case of data-driven methods in business and economic sciences," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(8), pages 6785-6801, August.
    17. Tu, Yundong & Xie, Xinling, 2023. "Penetrating sporadic return predictability," Journal of Econometrics, Elsevier, vol. 237(1).
    18. Skrobotov Anton, 2023. "Testing for explosive bubbles: a review," Dependence Modeling, De Gruyter, vol. 11(1), pages 1-26, January.
    19. Qian, Junhui & Su, Liangjun, 2014. "Structural change estimation in time series regressions with endogenous variables," Economics Letters, Elsevier, vol. 125(3), pages 415-421.
    20. Ma, Chenchen & Tu, Yundong, 2023. "Shrinkage estimation of multiple threshold factor models," Journal of Econometrics, Elsevier, vol. 235(2), pages 1876-1892.
    21. Qian, Junhui & Su, Liangjun, 2016. "Shrinkage estimation of common breaks in panel data models via adaptive group fused Lasso," Journal of Econometrics, Elsevier, vol. 191(1), pages 86-109.
    22. Muhammad Jaffri Mohd Nasir & Ramzan Nazim Khan & Gopalan Nair & Darfiana Nur, 2024. "Active-set based block coordinate descent algorithm in group LASSO for self-exciting threshold autoregressive model," Statistical Papers, Springer, vol. 65(5), pages 2973-3006, July.
    23. Gabriela Ciuperca, 2018. "Test by adaptive LASSO quantile method for real-time detection of a change-point," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 81(6), pages 689-720, August.
    24. Karsten Schweikert, 2020. "Oracle Efficient Estimation of Structural Breaks in Cointegrating Regressions," Papers 2001.07949, arXiv.org, revised Apr 2021.
    25. Karsten Schweikert, 2022. "Oracle Efficient Estimation of Structural Breaks in Cointegrating Regressions," Journal of Time Series Analysis, Wiley Blackwell, vol. 43(1), pages 83-104, January.
    26. Ma, Chenchen & Tu, Yundong, 2023. "Group fused Lasso for large factor models with multiple structural breaks," Journal of Econometrics, Elsevier, vol. 233(1), pages 132-154.

  35. Xun Lu & Liangjun Su, 2014. "Jackknife Model Averaging for Quantile Regressions," Working Papers 11-2014, Singapore Management University, School of Economics.

    Cited by:

    1. Lu Zhang & Xiaomeng Zhang & Xinyu Zhang, 2024. "Asymptotic Properties of the Distributional Synthetic Controls," Papers 2405.00953, arXiv.org, revised Aug 2024.
    2. Xun Lu & Su Liangjun, 2015. "Shrinkage Estimation of Dynamic Panel Data Models with Interactive Fixed Effects," Working Papers 02-2015, Singapore Management University, School of Economics.
    3. Zhang, Xiaomeng & Zhang, Xinyu, 2023. "Optimal model averaging based on forward-validation," Journal of Econometrics, Elsevier, vol. 237(2).
    4. Yang Feng & Qingfeng Liu, 2020. "Nested Model Averaging on Solution Path for High-dimensional Linear Regression," Papers 2005.08057, arXiv.org.
    5. Shangwei Zhao & Jun Liao & Dalei Yu, 2020. "Model averaging estimator in ridge regression and its large sample properties," Statistical Papers, Springer, vol. 61(4), pages 1719-1739, August.
    6. Aman Ullah & Alan T.K. Wan & Huansha Wang & Xinyu Zhang & Guohua Zou, 2014. "A Semiparametric Generalized Ridge Estimator and Link with Model Averaging," Working Papers 201412, University of California at Riverside, Department of Economics.
    7. Guozhi Hu & Weihu Cheng & Jie Zeng, 2023. "Optimal Model Averaging for Semiparametric Partially Linear Models with Censored Data," Mathematics, MDPI, vol. 11(3), pages 1-21, February.
    8. Anthoulla Phella, 2020. "Forecasting With Factor-Augmented Quantile Autoregressions: A Model Averaging Approach," Papers 2010.12263, arXiv.org.
    9. Chen, Qitong & Hong, Yongmiao & Li, Haiqi, 2024. "Time-varying forecast combination for factor-augmented regressions with smooth structural changes," Journal of Econometrics, Elsevier, vol. 240(1).
    10. Jonathan Berrisch & Florian Ziel, 2021. "CRPS Learning," Papers 2102.00968, arXiv.org, revised Nov 2021.
    11. Xiaochao Xia, 2021. "Model averaging prediction for nonparametric varying-coefficient models with B-spline smoothing," Statistical Papers, Springer, vol. 62(6), pages 2885-2905, December.
    12. Tu, Yundong & Wang, Siwei, 2020. "Jackknife model averaging for expectile regressions in increasing dimension," Economics Letters, Elsevier, vol. 197(C).
    13. Qingfeng Liu & Qingsong Yao & Guoqing Zhao, 2020. "Model averaging estimation for conditional volatility models with an application to stock market volatility forecast," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(5), pages 841-863, August.
    14. Aman Ullah & Xinyu Zhang, 2015. "Grouped Model Averaging for Finite Sample Size," Working Papers 201501, University of California at Riverside, Department of Economics.
    15. Jingwen Tu & Hu Yang & Chaohui Guo & Jing Lv, 2021. "Model averaging marginal regression for high dimensional conditional quantile prediction," Statistical Papers, Springer, vol. 62(6), pages 2661-2689, December.
    16. Zhang, Xinyu & Liu, Chu-An, 2023. "Model averaging prediction by K-fold cross-validation," Journal of Econometrics, Elsevier, vol. 235(1), pages 280-301.
    17. Shi, Pengfei & Zhang, Xinyu & Zhong, Wei, 2024. "Estimating conditional average treatment effects with heteroscedasticity by model averaging and matching," Economics Letters, Elsevier, vol. 238(C).
    18. Jiawen Luo & Shengjie Fu & Oguzhan Cepni & Rangan Gupta, 2024. "Climate Risks and Forecastability of US Inflation: Evidence from Dynamic Quantile Model Averaging," Working Papers 202420, University of Pretoria, Department of Economics.
    19. Miaomiao Wang & Xinyu Zhang & Alan T. K. Wan & Kang You & Guohua Zou, 2023. "Jackknife model averaging for high‐dimensional quantile regression," Biometrics, The International Biometric Society, vol. 79(1), pages 178-189, March.
    20. Fan, Rui & Lee, Ji Hyung & Shin, Youngki, 2023. "Predictive quantile regression with mixed roots and increasing dimensions: The ALQR approach," Journal of Econometrics, Elsevier, vol. 237(2).
    21. Ruoyao Shi, 2021. "An Averaging Estimator for Two Step M Estimation in Semiparametric Models," Working Papers 202105, University of California at Riverside, Department of Economics.
    22. Berrisch, Jonathan & Ziel, Florian, 2023. "CRPS learning," Journal of Econometrics, Elsevier, vol. 237(2).
    23. Giuseppe De Luca & Jan R. Magnus & Franco Peracchi, 2017. "Weighted-average least squares estimation of generalized linear models," EIEF Working Papers Series 1711, Einaudi Institute for Economics and Finance (EIEF), revised Aug 2017.
    24. Zishu Zhan & Yang Li & Yuhong Yang & Cunjie Lin, 2023. "Model averaging for semiparametric varying coefficient quantile regression models," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 75(4), pages 649-681, August.
    25. Cheng, Tingting & Jiang, Shan & Zhao, Albert Bo & Jia, Zhimin, 2023. "Complete subset averaging methods in corporate bond return prediction," Finance Research Letters, Elsevier, vol. 54(C).
    26. Su, Liangjun & Hoshino, Tadao, 2016. "Sieve instrumental variable quantile regression estimation of functional coefficient models," Journal of Econometrics, Elsevier, vol. 191(1), pages 231-254.
    27. Ji Hyung Lee & Youngki Shin, 2020. "Complete Subset Averaging for Quantile Regressions," Papers 2003.03299, arXiv.org, revised Jul 2021.
    28. Yundong Tu & Siwei Wang, 2023. "Variable Screening and Model Averaging for Expectile Regressions," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 85(3), pages 574-598, June.
    29. Ziwen Gao & Jiahui Zou & Xinyu Zhang & Yanyuan Ma, 2023. "Frequentist model averaging for envelope models," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 50(3), pages 1325-1364, September.
    30. Qian, Junhui & Su, Liangjun, 2016. "Shrinkage estimation of common breaks in panel data models via adaptive group fused Lasso," Journal of Econometrics, Elsevier, vol. 191(1), pages 86-109.
    31. Yuan, Chaoxia & Fang, Fang & Ni, Lyu, 2022. "Mallows model averaging with effective model size in fragmentary data prediction," Computational Statistics & Data Analysis, Elsevier, vol. 173(C).
    32. Yongmiao Hong & Tae-Hwy Lee & Yuying Sun & Shouyang Wang & Xinyu Zhang, 2017. "Time-varying Model Averaging," Working Papers 202001, University of California at Riverside, Department of Economics.
    33. Shou-Yung Yin & Chu-An Liu & Chang-Ching Lin, 2016. "Focused Information Criterion and Model Averaging for Large Panels with a Multifactor Error Structure," IEAS Working Paper : academic research 16-A016, Institute of Economics, Academia Sinica, Taipei, Taiwan.
    34. Peng, Jingfu & Yang, Yuhong, 2022. "On improvability of model selection by model averaging," Journal of Econometrics, Elsevier, vol. 229(2), pages 246-262.
    35. Xianwen Sun & Lixin Zhang, 2024. "Jackknife model averaging for mixed-data kernel-weighted spline quantile regressions," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 87(7), pages 805-842, October.
    36. Ruoyao Shi & Zhipeng Liao, 2018. "An Averaging GMM Estimator Robust to Misspecification," Working Papers 201803, University of California at Riverside, Department of Economics.
    37. Iania, Leonardo & Algieri, Bernardina & Leccadito, Arturo, 2022. "Forecasting total energy’s CO2 emissions," LIDAM Discussion Papers LFIN 2022003, Université catholique de Louvain, Louvain Finance (LFIN).
    38. Jie Zeng & Weihu Cheng & Guozhi Hu, 2023. "Optimal Model Averaging Estimation for the Varying-Coefficient Partially Linear Models with Missing Responses," Mathematics, MDPI, vol. 11(8), pages 1-21, April.
    39. Wenchao Xu & Xinyu Zhang, 2024. "On Asymptotic Optimality of Least Squares Model Averaging When True Model Is Included," Papers 2411.09258, arXiv.org.
    40. Lu, Xun & Su, Liangjun, 2020. "Determining individual or time effects in panel data models," Journal of Econometrics, Elsevier, vol. 215(1), pages 60-83.
    41. Zhang, Xinyu & Ullah, Aman & Zhao, Shangwei, 2016. "On the dominance of Mallows model averaging estimator over ordinary least squares estimator," Economics Letters, Elsevier, vol. 142(C), pages 69-73.
    42. Xiaomeng Zhang & Wendun Wang & Xinyu Zhang, 2022. "Asymptotic Properties of the Synthetic Control Method," Papers 2211.12095, arXiv.org.
    43. Chu-An Liu & Biing-Shen Kuo & Wen-Jen Tsay, 2017. "Autoregressive Spectral Averaging Estimator," IEAS Working Paper : academic research 17-A013, Institute of Economics, Academia Sinica, Taipei, Taiwan.
    44. Haowen Bao & Zongwu Cai & Yuying Sun & Shouyang Wang, 2023. "Penalized Model Averaging for High Dimensional Quantile Regressions," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202302, University of Kansas, Department of Economics, revised Jan 2023.

  36. Arthur Lewbel & Xun Lu & Liangjun Su, 2012. "Specification Testing for Transformation Models with an Application to Generalized Accelerated Failure-time Models," Boston College Working Papers in Economics 817, Boston College Department of Economics, revised 01 May 2013.

    Cited by:

    1. Babii, Andrii & Florens, Jean-Pierre, 2017. "Are unobservables separable?," TSE Working Papers 17-802, Toulouse School of Economics (TSE).
    2. Chiappori, Pierre-André & Komunjer, Ivana & Kristensen, Dennis, 2015. "Nonparametric identification and estimation of transformation models," Journal of Econometrics, Elsevier, vol. 188(1), pages 22-39.
    3. Breunig, Christoph & Hoderlein, Stefan, 2016. "Specification testing in random coefficient models," SFB 649 Discussion Papers 2015-053, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    4. Khalil, Umair & Yıldız, Neşe, 2022. "A test of the selection on observables assumption using a discontinuously distributed covariate," Journal of Econometrics, Elsevier, vol. 226(2), pages 423-450.
    5. Effraimidis, Georgios, 2016. "Nonparametric Identification of a Time-Varying Frailty Model," DaCHE discussion papers 2016:6, University of Southern Denmark, Dache - Danish Centre for Health Economics.
    6. Hoderlein, Stefan & Su, Liangjun & White, Halbert & Yang, Thomas Tao, 2016. "Testing for monotonicity in unobservables under unconfoundedness," Journal of Econometrics, Elsevier, vol. 193(1), pages 183-202.
    7. Lin, Yingqian & Tu, Yundong & Yao, Qiwei, 2020. "Estimation for double-nonlinear cointegration," LSE Research Online Documents on Economics 103830, London School of Economics and Political Science, LSE Library.
    8. Nick Kloodt & Natalie Neumeyer & Ingrid Keilegom, 2021. "Specification testing in semi-parametric transformation models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 30(4), pages 980-1003, December.
    9. Christoph Breunig, 2019. "Specification Testing in Nonparametric Instrumental Quantile Regression," Papers 1909.10129, arXiv.org.
    10. Su, Liangjun & Ura, Takuya & Zhang, Yichong, 2017. "Non-separable Models with High-dimensional Data," Economics and Statistics Working Papers 15-2017, Singapore Management University, School of Economics.
    11. Huang, Liquan & Khalil, Umair & Yıldız, Neşe, 2019. "Identification and estimation of a triangular model with multiple endogenous variables and insufficiently many instrumental variables," Journal of Econometrics, Elsevier, vol. 208(2), pages 346-366.
    12. Christoph Breunig & Stefan Hoderlein, 2016. "Nonparametric Specification Testing in Random Parameter Models," Boston College Working Papers in Economics 897, Boston College Department of Economics.
    13. Lin, Yingqian & Tu, Yundong & Yao, Qiwei, 2020. "Estimation for double-nonlinear cointegration," Journal of Econometrics, Elsevier, vol. 216(1), pages 175-191.
    14. Breunig, Christoph, 2016. "Specification testing in nonparametric instrumental quantile regression," SFB 649 Discussion Papers 2016-032, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    15. Li, Hongjun & Li, Qi & Liu, Ruixuan, 2016. "Consistent model specification tests based on k-nearest-neighbor estimation method," Journal of Econometrics, Elsevier, vol. 194(1), pages 187-202.

  37. Yonghui Zhang & Liangjun Su & Peter C.B. Phillips, 2011. "Testing for Common Trends in Semiparametric Panel Data Models with Fixed Effects," Cowles Foundation Discussion Papers 1832, Cowles Foundation for Research in Economics, Yale University.

    Cited by:

    1. Uddin, Md. Main & Mishra, Vinod & Smyth, Russell, 2020. "Income inequality and CO2 emissions in the G7, 1870–2014: Evidence from non-parametric modelling," Energy Economics, Elsevier, vol. 88(C).
    2. Xu, Ke-Li, 2016. "Multivariate trend function testing with mixed stationary and integrated disturbances," Journal of Multivariate Analysis, Elsevier, vol. 147(C), pages 38-57.
    3. Awaworyi Churchill, Sefa & Inekwe, John & Smyth, Russell & Zhang, Xibin, 2019. "R&D intensity and carbon emissions in the G7: 1870–2014," Energy Economics, Elsevier, vol. 80(C), pages 30-37.
    4. Hidalgo, Javier & Schafgans, Marcia, 2017. "Inference and testing breaks in large dynamic panels with strong cross sectional dependence," Journal of Econometrics, Elsevier, vol. 196(2), pages 259-274.
    5. Jiti Gao & Kai Xia, 2017. "Heterogeneous panel data models with cross-sectional dependence," Monash Econometrics and Business Statistics Working Papers 16/17, Monash University, Department of Econometrics and Business Statistics.
    6. Ivanovski, Kris & Hailemariam, Abebe, 2022. "Time-varying geopolitical risk and oil prices," International Review of Economics & Finance, Elsevier, vol. 77(C), pages 206-221.
    7. Awaworyi Churchill, Sefa & Inekwe, John & Ivanovski, Kris & Smyth, Russell, 2020. "The Environmental Kuznets Curve across Australian states and territories," Energy Economics, Elsevier, vol. 90(C).
    8. Jia Chen, 2019. "Estimating latent group structure in time-varying coefficient panel data models," The Econometrics Journal, Royal Economic Society, vol. 22(3), pages 223-240.
    9. Javier Hidalgo & Jungyoon Lee, 2014. "A Cusum Test of Common Trends in Large Heterogeneous Panels," STICERD - Econometrics Paper Series 576, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    10. Silvapulle, Param & Smyth, Russell & Zhang, Xibin & Fenech, Jean-Pierre, 2017. "Nonparametric panel data model for crude oil and stock market prices in net oil importing countries," Energy Economics, Elsevier, vol. 67(C), pages 255-267.
    11. Gao, Jiti & Xia, Kai & Zhu, Huanjun, 2020. "Heterogeneous panel data models with cross-sectional dependence," Journal of Econometrics, Elsevier, vol. 219(2), pages 329-353.
    12. Bhattacharya, Mita & Inekwe, John & Yan, Eric, 2021. "Dynamics of energy poverty: Evidence from nonparametric estimates across the ASEAN+6 region," Energy Economics, Elsevier, vol. 103(C).
    13. Ghazouani, Tarek, 2022. "Dynamic impact of globalization on renewable energy consumption: Non-parametric modelling evidence," Technological Forecasting and Social Change, Elsevier, vol. 185(C).
    14. Yao, Yao & Ivanovski, Kris & Inekwe, John & Smyth, Russell, 2020. "Human capital and CO2 emissions in the long run," Energy Economics, Elsevier, vol. 91(C).
    15. Chen, Zhihong & Xia, Huizhu, 2020. "Trend instrumental variable regression with an application to the US New Keynesian Phillips Curve," Economic Modelling, Elsevier, vol. 93(C), pages 595-604.
    16. Dogan, Ergun & Zhang, Xibin, 2023. "A nonparametric panel data model for examining the contribution of tourism to economic growth," Economic Modelling, Elsevier, vol. 128(C).
    17. Liddle, Brantley & Smyth, Russell & Zhang, Xibin, 2020. "Time-varying income and price elasticities for energy demand: Evidence from a middle-income panel," Energy Economics, Elsevier, vol. 86(C).
    18. Khismatullina, Marina & Vogt, Michael, 2023. "Nonparametric comparison of epidemic time trends: The case of COVID-19," Journal of Econometrics, Elsevier, vol. 232(1), pages 87-108.
    19. Maghyereh, Aktham & Abdoh, Hussein, 2021. "The effect of structural oil shocks on bank systemic risk in the GCC countries," Energy Economics, Elsevier, vol. 103(C).
    20. Awaworyi Churchill, Sefa & Inekwe, John & Ivanovski, Kris, 2021. "R&D expenditure and energy consumption in OECD nations," Energy Economics, Elsevier, vol. 100(C).
    21. Moghaddam, Mohsen Bakhshi & Lloyd-Ellis, Huw, 2022. "Heterogeneous effects of oil price fluctuations: Evidence from a nonparametric panel data model in Canada," Energy Economics, Elsevier, vol. 110(C).
    22. Chen, Bin & Huang, Liquan, 2018. "Nonparametric testing for smooth structural changes in panel data models," Journal of Econometrics, Elsevier, vol. 202(2), pages 245-267.
    23. Marina Khismatullina & Michael Vogt, 2022. "Multiscale Comparison of Nonparametric Trend Curves," Papers 2209.10841, arXiv.org.

  38. Ye Chen & Liangjun Su & Aman Ullah, 2009. "Functional Coefficient Estimation with Both Categorical and Continuous Data," Working Papers 200909, University of California at Riverside, Department of Economics, revised Jun 2009.

    Cited by:

    1. Tae-Hwy Lee & Shahnaz Parsaeian & Aman Ullah, 2022. "Forecasting under Structural Breaks Using Improved Weighted Estimation," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202212, University of Kansas, Department of Economics.
    2. Yan Li & Liangjun Su & Yuewu Xu, 2014. "A Combined Approach to the Inference of Conditional Factor Models," Working Papers 10-2014, Singapore Management University, School of Economics.

  39. Xiangdong Long & Liangjun Su & Aman Ullah, 2009. "Estimation and Forecasting of Dynamic Conditional Covariance: A Semiparametric Multivariate Model Variables with Econometric Applications," Working Papers 200908, University of California at Riverside, Department of Economics, revised Jul 2009.

    Cited by:

    1. Matteo Barigozzi & Christian T. Brownlees & Giampiero M. Gallo & David Veredas, 2010. "Disentangling Systematic and Idiosyncratic Risk for Large Panels of Assets," Econometrics Working Papers Archive wp2010_06, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    2. Serra, Teresa, 2011. "Volatility spillovers between food and energy markets: A semiparametric approach," Energy Economics, Elsevier, vol. 33(6), pages 1155-1164.

  40. Peter C.B. Phillips & Liangjun Su, 2009. "Nonparametric Structural Estimation via Continuous Location Shifts in an Endogenous Regressor," Cowles Foundation Discussion Papers 1702, Cowles Foundation for Research in Economics, Yale University.

    Cited by:

    1. Peter C.B. Phillips & Liangjun Su, 2009. "A Paradox of Inconsistent Parametric and Consistent Nonparametric Regression," Cowles Foundation Discussion Papers 1704, Cowles Foundation for Research in Economics, Yale University.

  41. Liangjun Su & Zhenlin Yang, 2008. "Asymptotics and Bootstrap for Transformed Panel Data Regressions," Development Economics Working Papers 22477, East Asian Bureau of Economic Research.

    Cited by:

    1. Jin, Fei & Lee, Lung-fei, 2015. "On the bootstrap for Moran’s I test for spatial dependence," Journal of Econometrics, Elsevier, vol. 184(2), pages 295-314.
    2. Ou Bianling & Long Zhihe & Li Wenqian, 2019. "Bootstrap LM Tests for Spatial Dependence in Panel Data Models with Fixed Effects," Journal of Systems Science and Information, De Gruyter, vol. 7(4), pages 330-343, August.

  42. Liangjun Su & Zhenlin Yang, 2007. "Instrumental Variable Quantile Estimation of Spatial Autoregressive Models," Development Economics Working Papers 22476, East Asian Bureau of Economic Research.

    Cited by:

    1. Su, Liangjun, 2012. "Semiparametric GMM estimation of spatial autoregressive models," Journal of Econometrics, Elsevier, vol. 167(2), pages 543-560.
    2. Coro Chasco & Julie Le Gallo, 2015. "Heterogeneity in Perceptions of Noise and Air Pollution: A Spatial Quantile Approach on the City of Madrid," Spatial Economic Analysis, Taylor & Francis Journals, vol. 10(3), pages 317-343, September.
    3. Luciano de Castro & Antonio F. Galvao & David M. Kaplan & Xin Liu, 2017. "Smoothed GMM for quantile models," Papers 1707.03436, arXiv.org, revised Feb 2018.
    4. Jiawei Hou & Yunquan Song, 2022. "Interquantile shrinkage in spatial additive autoregressive models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 31(4), pages 1030-1057, December.
    5. Alfredo Cartone & Paolo Postiglione, 2016. "Modelli spaziali di regressione quantilica per l?analisi della convergenza economica regionale," RIVISTA DI ECONOMIA E STATISTICA DEL TERRITORIO, FrancoAngeli Editore, vol. 2016(3), pages 28-48.
    6. Weiguang Wang & Yangyang Wang, 2023. "Regional Differences, Dynamic Evolution and Driving Factors Analysis of PM 2.5 in the Yangtze River Economic Belt," Sustainability, MDPI, vol. 15(4), pages 1-24, February.
    7. Danqing Chen & Jianbao Chen & Shuangshuang Li, 2021. "Instrumental Variable Quantile Regression of Spatial Dynamic Durbin Panel Data Model with Fixed Effects," Mathematics, MDPI, vol. 9(24), pages 1-24, December.
    8. Liao, Wen-Chi & Wang, Xizhu, 2012. "Hedonic house prices and spatial quantile regression," Journal of Housing Economics, Elsevier, vol. 21(1), pages 16-27.
    9. Philip Kostov, 2013. "Empirical likelihood estimation of the spatial quantile regression," Journal of Geographical Systems, Springer, vol. 15(1), pages 51-69, January.
    10. He Jiang, 2023. "Robust forecasting in spatial autoregressive model with total variation regularization," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(2), pages 195-211, March.
    11. Philip Kostov & Julie Le Gallo, 2015. "Convergence: A Story of Quantiles and Spillovers," Kyklos, Wiley Blackwell, vol. 68(4), pages 552-576, November.
    12. Luciano de Castro & Antonio F. Galvao & David M. Kaplan, 2017. "Smoothed instrumental variables quantile regression, with estimation of quantile Euler equations," Working Papers 1710, Department of Economics, University of Missouri, revised 28 Feb 2018.
    13. Marusca De Castris & Daniele Di Gennaro, 2018. "Does agricultural subsidies foster Italian southern farms? A Spatial Quantile Regression Approach," Papers 1803.05659, arXiv.org.
    14. Philip Kostov, 2009. "A Spatial Quantile Regression Hedonic Model of Agricultural Land Prices," Spatial Economic Analysis, Taylor & Francis Journals, vol. 4(1), pages 53-72.
    15. Stephen Matthews & Daniel M. Parker, 2013. "Progress in Spatial Demography," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 28(10), pages 271-312.
    16. Bernardo Furtado & Frank van Oort, 2011. "Neighborhood weight matrix in a spatial-quantile real estate modeling environment: Evidence from Brazil," ERSA conference papers ersa10p424, European Regional Science Association.

  43. Su, Liangjun & White, Halbert, 2003. "A Consistent Characteristic-Function-Based Test for Conditional Independence," University of California at San Diego, Economics Working Paper Series qt4dv0837f, Department of Economics, UC San Diego.

    Cited by:

    1. Yu-Chin Hsu & Ta-Cheng Huang & Haiqing Xu, 2018. "Testing for Unobserved Heterogeneous Treatment Effects with Observational Data," Papers 1803.07514, arXiv.org, revised Aug 2021.
    2. Chen, Bin & Hong, Yongmiao, 2012. "Testing For The Markov Property In Time Series," Econometric Theory, Cambridge University Press, vol. 28(1), pages 130-178, February.
    3. Su, Liangjun & White, Halbert, 2014. "Testing conditional independence via empirical likelihood," Journal of Econometrics, Elsevier, vol. 182(1), pages 27-44.
    4. Chuang, Chia-Chang & Kuan, Chung-Ming & Lin, Hsin-Yi, 2009. "Causality in quantiles and dynamic stock return-volume relations," Journal of Banking & Finance, Elsevier, vol. 33(7), pages 1351-1360, July.
    5. Xu, Kai & Cheng, Qing, 2024. "Test of conditional independence in factor models via Hilbert–Schmidt independence criterion," Journal of Multivariate Analysis, Elsevier, vol. 199(C).
    6. Taoufik Bouezmarni & Mohamed Doukali & Abderrahim Taamouti, 2023. "Testing Granger Non-Causality in Expectiles," University of East Anglia School of Economics Working Paper Series 2023-02, School of Economics, University of East Anglia, Norwich, UK..
    7. Xiaojun Song & Haoyu Wei, 2021. "Nonparametric Tests of Conditional Independence for Time Series," Papers 2110.04847, arXiv.org.
    8. Nadarajah, Saralees & Chan, Stephen & Afuecheta, Emmanuel, 2013. "On the characteristic function for asymmetric Student t distributions," Economics Letters, Elsevier, vol. 121(2), pages 271-274.
    9. Wang, Hongfei & Liu, Binghui & Feng, Long & Ma, Yanyuan, 2024. "Rank-based max-sum tests for mutual independence of high-dimensional random vectors," Journal of Econometrics, Elsevier, vol. 238(1).
    10. Chen, Bin & Hong, Yongmiao, 2011. "Generalized spectral testing for multivariate continuous-time models," Journal of Econometrics, Elsevier, vol. 164(2), pages 268-293, October.
    11. Long, Xiangdong & Su, Liangjun & Ullah, Aman, 2011. "Estimation and Forecasting of Dynamic Conditional Covariance: A Semiparametric Multivariate Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 29(1), pages 109-125.
    12. Xueqin Wang & Wenliang Pan & Wenhao Hu & Yuan Tian & Heping Zhang, 2015. "Conditional Distance Correlation," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(512), pages 1726-1734, December.
    13. Shi, Chengchun & Xu, Tianlin & Bergsma, Wicher & Li, Lexin, 2021. "Double generative adversarial networks for conditional independence testing," LSE Research Online Documents on Economics 112550, London School of Economics and Political Science, LSE Library.
    14. Lee, Sangyeol & Meintanis, Simos G. & Pretorius, Charl, 2022. "Monitoring procedures for strict stationarity based on the multivariate characteristic function," Journal of Multivariate Analysis, Elsevier, vol. 189(C).
    15. Bertrand Candelon & Sessi Tokpavi, 2016. "A Nonparametric Test for Granger Causality in Distribution With Application to Financial Contagion," Post-Print hal-03528203, HAL.
    16. Huang, Meng & Sun, Yixiao & White, Hal, 2013. "A Flexible Nonparametric Test for Conditional Independence," University of California at San Diego, Economics Working Paper Series qt3pt89204, Department of Economics, UC San Diego.
    17. Simos G. Meintanis & Joseph Ngatchou-Wandji & James Allison, 2018. "Testing for serial independence in vector autoregressive models," Statistical Papers, Springer, vol. 59(4), pages 1379-1410, December.
    18. Cheng, Yu-Hsiang & Huang, Tzee-Ming, 2012. "A conditional independence test for dependent data based on maximal conditional correlation," Journal of Multivariate Analysis, Elsevier, vol. 107(C), pages 210-226.
    19. Zhou, Yeqing & Liu, Jingyuan & Zhu, Liping, 2020. "Test for conditional independence with application to conditional screening," Journal of Multivariate Analysis, Elsevier, vol. 175(C).
    20. de Luna Xavier & Johansson Per, 2014. "Testing for the Unconfoundedness Assumption Using an Instrumental Assumption," Journal of Causal Inference, De Gruyter, vol. 2(2), pages 187-199, September.
    21. Taoufik Bouezmarni & Jeroen V.K. Rombouts & Abderrahim Taamouti, 2011. "Nonparametric Copula-Based Test for Conditional Independence with Applications to Granger Causality," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(2), pages 275-287, October.
    22. Bianchi, Pascal & Elgui, Kevin & Portier, François, 2023. "Conditional independence testing via weighted partial copulas," Journal of Multivariate Analysis, Elsevier, vol. 193(C).
    23. Zhang, Wei & Gao, Wei & Ng, Hon Keung Tony, 2023. "Multivariate tests of independence based on a new class of measures of independence in Reproducing Kernel Hilbert Space," Journal of Multivariate Analysis, Elsevier, vol. 195(C).
    24. Li, Haiqi & Zhong, Wanling & Park, Sung Y., 2016. "Generalized cross-spectral test for nonlinear Granger causality with applications to money–output and price–volume relations," Economic Modelling, Elsevier, vol. 52(PB), pages 661-671.
    25. Dante Amengual & Marine Carrasco & Enrique Sentana, 2017. "Testing Distributional Assumptions Using a Continuum of Moments," Working Papers wp2017_1709, CEMFI.
    26. Liu, Nianqing & Vuong, Quang & Xu, Haiqing, 2017. "Rationalization and identification of binary games with correlated types," Journal of Econometrics, Elsevier, vol. 201(2), pages 249-268.
    27. Matos, João Manuel Gonçalves Amaro de & Fernandes, Marcelo, 2001. "Testing the Markov property with ultra high frequency financial data," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 414, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
    28. Fu, Zhonghao & Hong, Yongmiao, 2019. "A model-free consistent test for structural change in regression possibly with endogeneity," Journal of Econometrics, Elsevier, vol. 211(1), pages 206-242.
    29. Bertrand Caudelon & Sessi Tokpavi, 2014. "A Nonparametric Test for Granger-causality in Distribution with Application to Financial Contagion," EconomiX Working Papers 2014-18, University of Paris Nanterre, EconomiX.
    30. Chen, Bin & Song, Zhaogang, 2013. "Testing whether the underlying continuous-time process follows a diffusion: An infinitesimal operator-based approach," Journal of Econometrics, Elsevier, vol. 173(1), pages 83-107.
    31. Xuehu Zhu & Jun Lu & Jun Zhang & Lixing Zhu, 2021. "Testing for conditional independence: A groupwise dimension reduction‐based adaptive‐to‐model approach," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 48(2), pages 549-576, June.
    32. Nianqing Liu & Quang Vuong & Haiqing Xu, 2012. "Rationalization and Identification of Discrete Games with Correlated Types," Department of Economics Working Papers 130915, The University of Texas at Austin, Department of Economics.
    33. Fan, Jianqing & Feng, Yang & Xia, Lucy, 2020. "A projection-based conditional dependence measure with applications to high-dimensional undirected graphical models," Journal of Econometrics, Elsevier, vol. 218(1), pages 119-139.
    34. Ai, Chunrong & Sun, Li-Hsien & Zhang, Zheng & Zhu, Liping, 2024. "Testing unconditional and conditional independence via mutual information," Journal of Econometrics, Elsevier, vol. 240(2).
    35. Chen, Feifei & Meintanis, Simos G. & Zhu, Lixing, 2019. "On some characterizations and multidimensional criteria for testing homogeneity, symmetry and independence," Journal of Multivariate Analysis, Elsevier, vol. 173(C), pages 125-144.
    36. Amaro de Matos, Joao & Fernandes, Marcelo, 2007. "Testing the Markov property with high frequency data," Journal of Econometrics, Elsevier, vol. 141(1), pages 44-64, November.
    37. Zhang, Yaowu & Zhou, Yeqing & Zhu, Liping, 2024. "A post-screening diagnostic study for ultrahigh dimensional data," Journal of Econometrics, Elsevier, vol. 239(2).
    38. Herman J. Bierens & Li Wang, 2017. "Weighted simulated integrated conditional moment tests for parametric conditional distributions of stationary time series processes," Econometric Reviews, Taylor & Francis Journals, vol. 36(1-3), pages 103-135, March.
    39. Xiangdong Long & Liangjun Su & Aman Ullah, 2009. "Estimation and Forecasting of Dynamic Conditional Covariance: A Semiparametric Multivariate Model Variables with Econometric Applications," Working Papers 200908, University of California at Riverside, Department of Economics, revised Jul 2009.
    40. Maomao Ding & Ruosha Li & Jin Qin & Jing Ning, 2023. "A double‐robust test for high‐dimensional gene coexpression networks conditioning on clinical information," Biometrics, The International Biometric Society, vol. 79(4), pages 3227-3238, December.
    41. Su, Liangjun & Zheng, Xin, 2017. "A martingale-difference-divergence-based test for specification," Economics Letters, Elsevier, vol. 156(C), pages 162-167.

  44. Su, Liangjun & White, Halbert, 2003. "Testing Conditional Independence Via Empirical Likelihood," University of California at San Diego, Economics Working Paper Series qt35v8g0fm, Department of Economics, UC San Diego.

    Cited by:

    1. Xu, Kai & Cheng, Qing, 2024. "Test of conditional independence in factor models via Hilbert–Schmidt independence criterion," Journal of Multivariate Analysis, Elsevier, vol. 199(C).
    2. Xiaojun Song & Haoyu Wei, 2021. "Nonparametric Tests of Conditional Independence for Time Series," Papers 2110.04847, arXiv.org.
    3. de Luna, Xavier & Waernbaum, Ingeborg, 2005. "Covariate selection for non-parametric estimation of treatment effects," Working Paper Series 2005:4, IFAU - Institute for Evaluation of Labour Market and Education Policy.
    4. Wang, Hongfei & Liu, Binghui & Feng, Long & Ma, Yanyuan, 2024. "Rank-based max-sum tests for mutual independence of high-dimensional random vectors," Journal of Econometrics, Elsevier, vol. 238(1).
    5. Yoon-Jae Whang, 2004. "Smoothed Empirical Likelihood Methods for Quantile Regression Models," Cowles Foundation Discussion Papers 1453, Cowles Foundation for Research in Economics, Yale University.
    6. Bertrand Candelon & Sessi Tokpavi, 2016. "A Nonparametric Test for Granger Causality in Distribution With Application to Financial Contagion," Post-Print hal-03528203, HAL.
    7. Huang, Meng & Sun, Yixiao & White, Hal, 2013. "A Flexible Nonparametric Test for Conditional Independence," University of California at San Diego, Economics Working Paper Series qt3pt89204, Department of Economics, UC San Diego.
    8. Hoderlein, Stefan & Su, Liangjun & White, Halbert & Yang, Thomas Tao, 2016. "Testing for monotonicity in unobservables under unconfoundedness," Journal of Econometrics, Elsevier, vol. 193(1), pages 183-202.
    9. Christophe Dutang, 2012. "The customer, the insurer and the market," Post-Print hal-01616152, HAL.
    10. Zhou, Yeqing & Liu, Jingyuan & Zhu, Liping, 2020. "Test for conditional independence with application to conditional screening," Journal of Multivariate Analysis, Elsevier, vol. 175(C).
    11. Taoufik Bouezmarni & Jeroen V.K. Rombouts & Abderrahim Taamouti, 2011. "Nonparametric Copula-Based Test for Conditional Independence with Applications to Granger Causality," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(2), pages 275-287, October.
    12. Taoufik Bouezmarni & Abderrahim Taamouti, 2014. "Nonparametric tests for conditional independence using conditional distributions," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 26(4), pages 697-719, December.
    13. Yahya Can DURA & Mustafa Kemal BESER & Hakan ACAROGLU, 2017. "Türkiye’nin Ihracata Dayali Buyumesinin Ekonometrik Analizi," Ege Academic Review, Ege University Faculty of Economics and Administrative Sciences, vol. 17(2), pages 295-310.
    14. Li, Haiqi & Zhong, Wanling & Park, Sung Y., 2016. "Generalized cross-spectral test for nonlinear Granger causality with applications to money–output and price–volume relations," Economic Modelling, Elsevier, vol. 52(PB), pages 661-671.
    15. Ersin Sünbül, 2023. "Linear and Nonlinear Relationship Between Real Exchange Rate, Real Interest Rate and Consumer Price Index: An Empirical Application for Countries with Different Levels of Development," Scientific Annals of Economics and Business (continues Analele Stiintifice), Alexandru Ioan Cuza University, Faculty of Economics and Business Administration, vol. 70(1), pages 57-70, March.
    16. Patrick Gagliardini & Diego Ronchetti, 2020. "Comparing Asset Pricing Models by the Conditional Hansen-Jagannathan Distance," Journal of Financial Econometrics, Oxford University Press, vol. 18(2), pages 333-394.
    17. Bertrand Caudelon & Sessi Tokpavi, 2014. "A Nonparametric Test for Granger-causality in Distribution with Application to Financial Contagion," EconomiX Working Papers 2014-18, University of Paris Nanterre, EconomiX.
    18. Xuehu Zhu & Jun Lu & Jun Zhang & Lixing Zhu, 2021. "Testing for conditional independence: A groupwise dimension reduction‐based adaptive‐to‐model approach," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 48(2), pages 549-576, June.
    19. Fan, Jianqing & Feng, Yang & Xia, Lucy, 2020. "A projection-based conditional dependence measure with applications to high-dimensional undirected graphical models," Journal of Econometrics, Elsevier, vol. 218(1), pages 119-139.
    20. Ai, Chunrong & Sun, Li-Hsien & Zhang, Zheng & Zhu, Liping, 2024. "Testing unconditional and conditional independence via mutual information," Journal of Econometrics, Elsevier, vol. 240(2).
    21. Kyungchul Song, 2007. "Testing Conditional Independence via Rosenblatt Transforms," PIER Working Paper Archive 07-026, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    22. Zhang, Yaowu & Zhou, Yeqing & Zhu, Liping, 2024. "A post-screening diagnostic study for ultrahigh dimensional data," Journal of Econometrics, Elsevier, vol. 239(2).
    23. Gospodinov, Nikolay & Otsu, Taisuke, 2012. "Local GMM estimation of time series models with conditional moment restrictions," Journal of Econometrics, Elsevier, vol. 170(2), pages 476-490.
    24. Su, Liangjun & Zheng, Xin, 2017. "A martingale-difference-divergence-based test for specification," Economics Letters, Elsevier, vol. 156(C), pages 162-167.

Articles

  1. Wang, Yiren & Phillips, Peter C.B. & Su, Liangjun, 2024. "Panel data models with time-varying latent group structures," Journal of Econometrics, Elsevier, vol. 240(1).
    See citations under working paper version above.
  2. Lu, Xun & Su, Liangjun, 2023. "Uniform inference in linear panel data models with two-dimensional heterogeneity," Journal of Econometrics, Elsevier, vol. 235(2), pages 694-719.

    Cited by:

    1. Yiren Wang & Peter C. B. Phillips & Liangjun Su, 2023. "Panel Data Models with Time-Varying Latent Group Structures," Cowles Foundation Discussion Papers 2364, Cowles Foundation for Research in Economics, Yale University.

  3. Miao, Ke & Phillips, Peter C.B. & Su, Liangjun, 2023. "High-dimensional VARs with common factors," Journal of Econometrics, Elsevier, vol. 233(1), pages 155-183.
    See citations under working paper version above.
  4. Hong, Shengjie & Su, Liangjun & Jiang, Tao, 2023. "Profile GMM estimation of panel data models with interactive fixed effects," Journal of Econometrics, Elsevier, vol. 235(2), pages 927-948.

    Cited by:

    1. Yiren Wang & Peter C. B. Phillips & Liangjun Su, 2023. "Panel Data Models with Time-Varying Latent Group Structures," Cowles Foundation Discussion Papers 2364, Cowles Foundation for Research in Economics, Yale University.
    2. Shittu, Ibrahim & Abdul Latiff, Abdul Rais Bin & Baharudin, Siti 'Aisyah, 2024. "Closing the clean cooking gap: Which policies and institutional qualities matter?," Energy Policy, Elsevier, vol. 185(C).
    3. Zhenhao Gong & Min Seong Kim, 2024. "Improved inference for interactive fixed effects model under cross-sectional dependence," Empirical Economics, Springer, vol. 67(2), pages 727-760, August.
    4. Ruiqin Tian & Miaojie Xia & Dengke Xu, 2024. "Profile quasi-maximum likelihood estimation for semiparametric varying-coefficient spatial autoregressive panel models with fixed effects," Statistical Papers, Springer, vol. 65(8), pages 5109-5143, October.
    5. Bataka, Hodabalo, 2024. "Global value chains participation and gender inequalities in Sub-Saharan Africa: Importance of women education," International Economics, Elsevier, vol. 178(C).
    6. Zhenhao Gong & Min Seong Kim, 2024. "Improved Inference for Interactive Fixed Effects Model under Cross-Sectional Dependence," Working papers 2024-02, University of Connecticut, Department of Economics.

  5. Su, Liangjun & Wang, Wuyi & Xu, Xingbai, 2023. "Identifying latent group structures in spatial dynamic panels," Journal of Econometrics, Elsevier, vol. 235(2), pages 1955-1980.

    Cited by:

    1. Yiren Wang & Peter C. B. Phillips & Liangjun Su, 2023. "Panel Data Models with Time-Varying Latent Group Structures," Cowles Foundation Discussion Papers 2364, Cowles Foundation for Research in Economics, Yale University.

  6. Wenxin Huang & Liangjun Su & Yuan Zhuang, 2023. "Detecting Unobserved Heterogeneity in Efficient Prices via Classifier-Lasso," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 41(2), pages 509-522, April.

    Cited by:

    1. Long, Yunshen & Yan, Jingzhou & Wu, Liang & Long, Xingchen, 2024. "Market price determination: Interpreting quote order imbalance under zero-profit equilibrium," Economic Modelling, Elsevier, vol. 134(C).

  7. Huang, Wenxin & Jin, Sainan & Phillips, Peter C.B. & Su, Liangjun, 2021. "Nonstationary panel models with latent group structures and cross-section dependence," Journal of Econometrics, Elsevier, vol. 221(1), pages 198-222.
    See citations under working paper version above.
  8. Wang, Wuyi & Su, Liangjun, 2021. "Identifying latent group structures in nonlinear panels," Journal of Econometrics, Elsevier, vol. 220(2), pages 272-295.
    See citations under working paper version above.
  9. Jin, Sainan & Miao, Ke & Su, Liangjun, 2021. "On factor models with random missing: EM estimation, inference, and cross validation," Journal of Econometrics, Elsevier, vol. 222(1), pages 745-777.
    See citations under working paper version above.
  10. Xun Lu & Ke Miao & Liangjun Su, 2021. "Determination of different types of fixed effects in three-dimensional panels," Econometric Reviews, Taylor & Francis Journals, vol. 40(9), pages 867-898, October.
    See citations under working paper version above.
  11. Shujie Ma & Wei Lan & Liangjun Su & Chih-Ling Tsai, 2020. "Testing Alphas in Conditional Time-Varying Factor Models With High-Dimensional Assets," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(1), pages 214-227, January.
    See citations under working paper version above.
  12. Lu, Xun & Su, Liangjun, 2020. "Determining individual or time effects in panel data models," Journal of Econometrics, Elsevier, vol. 215(1), pages 60-83.

    Cited by:

    1. Vira Semenova & Matt Goldman & Victor Chernozhukov & Matt Taddy, 2023. "Inference on heterogeneous treatment effects in high‐dimensional dynamic panels under weak dependence," Quantitative Economics, Econometric Society, vol. 14(2), pages 471-510, May.
    2. Stanislav Zabojník & Dusan Steinhauser & Viktoria Pestova, 2023. "EU Decarbonisation: Do EU Electricity Costs Harm Export Competitiveness?," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 25(63), pages 522-522, April.
    3. Steinhauser Dušan & Kittová Zuzana & Khúlová Lucia, 2024. "Relationship Between CO2 Emissions and Trade: The Case of the EU," Intereconomics: Review of European Economic Policy, Sciendo, vol. 59(1), pages 41-47, February.

  13. Huang, Wenxin & Jin, Sainan & Su, Liangjun, 2020. "Identifying Latent Grouped Patterns In Cointegrated Panels," Econometric Theory, Cambridge University Press, vol. 36(3), pages 410-456, June.
    See citations under working paper version above.
  14. Su, Liangjun & Wang, Xia, 2020. "Testing For Structural Changes In Factor Models Via A Nonparametric Regression," Econometric Theory, Cambridge University Press, vol. 36(6), pages 1127-1158, December.

    Cited by:

    1. Yiren Wang & Peter C. B. Phillips & Liangjun Su, 2023. "Panel Data Models with Time-Varying Latent Group Structures," Cowles Foundation Discussion Papers 2364, Cowles Foundation for Research in Economics, Yale University.
    2. Chen, Qitong & Hong, Yongmiao & Li, Haiqi, 2024. "Time-varying forecast combination for factor-augmented regressions with smooth structural changes," Journal of Econometrics, Elsevier, vol. 240(1).
    3. Bai, Jushan & Duan, Jiangtao & Han, Xu, 2024. "The likelihood ratio test for structural changes in factor models," Journal of Econometrics, Elsevier, vol. 238(2).
    4. Fu, Zhonghao & Hong, Yongmiao & Wang, Xia, 2023. "Testing for structural changes in large dimensional factor models via discrete Fourier transform," Journal of Econometrics, Elsevier, vol. 233(1), pages 302-331.
    5. Yang, Qing & Zhang, Yi, 2022. "Change-point detection for the link function in a single-index model," Statistics & Probability Letters, Elsevier, vol. 186(C).
    6. Wei, Jie & Zhang, Yonghui, 2020. "A time-varying diffusion index forecasting model," Economics Letters, Elsevier, vol. 193(C).

  15. Miao, Ke & Li, Kunpeng & Su, Liangjun, 2020. "Panel threshold models with interactive fixed effects," Journal of Econometrics, Elsevier, vol. 219(1), pages 137-170.

    Cited by:

    1. Piaopeng Song & Yuxiao Gu & Bin Su & Arifa Tanveer & Qiao Peng & Weijun Gao & Shaomin Wu & Shihong Zeng, 2023. "The Impact of Green Technology Research and Development (R&D) Investment on Performance: A Case Study of Listed Energy Companies in Beijing, China," Sustainability, MDPI, vol. 15(16), pages 1-24, August.
    2. Paravee Maneejuk & Woraphon Yamaka, 2021. "The Impact of Higher Education on Economic Growth in ASEAN-5 Countries," Sustainability, MDPI, vol. 13(2), pages 1-28, January.

  16. Miao, Ke & Su, Liangjun & Wang, Wendun, 2020. "Panel threshold regressions with latent group structures," Journal of Econometrics, Elsevier, vol. 214(2), pages 451-481.
    See citations under working paper version above.
  17. Liangjun Su & Xia Wang & Sainan Jin, 2019. "Sieve Estimation of Time-Varying Panel Data Models With Latent Structures," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 37(2), pages 334-349, April.

    Cited by:

    1. Fu, Zhonghao & Hong, Yongmiao & Su, Liangjun & Wang, Xia, 2023. "Specification tests for time-varying coefficient models," Journal of Econometrics, Elsevier, vol. 235(2), pages 720-744.
    2. Boyuan Zhang, 2020. "Forecasting with Bayesian Grouped Random Effects in Panel Data," Papers 2007.02435, arXiv.org, revised Oct 2020.
    3. Yiren Wang & Peter C. B. Phillips & Liangjun Su, 2023. "Panel Data Models with Time-Varying Latent Group Structures," Cowles Foundation Discussion Papers 2364, Cowles Foundation for Research in Economics, Yale University.
    4. Xiaorong Yang & Jia Chen & Degui Li & Runze Li, 2023. "Functional-Coefficient Quantile Regression for Panel Data with Latent Group Structure," Papers 2303.13218, arXiv.org.
    5. Huang, Danyang & Hu, Wei & Jing, Bingyi & Zhang, Bo, 2023. "Grouped spatial autoregressive model," Computational Statistics & Data Analysis, Elsevier, vol. 178(C).
    6. Oh, Dong Hwan & Patton, Andrew J., 2023. "Dynamic factor copula models with estimated cluster assignments," Journal of Econometrics, Elsevier, vol. 237(2).
    7. Sun, Yan & Wan, Chuang & Zhang, Wenyang & Zhong, Wei, 2024. "A Multi-Kink quantile regression model with common structure for panel data analysis," Journal of Econometrics, Elsevier, vol. 239(2).
    8. Vasilis Sarafidis & Tom Wansbeek, 2020. "Celebrating 40 Years of Panel Data Analysis: Past, Present and Future," Monash Econometrics and Business Statistics Working Papers 6/20, Monash University, Department of Econometrics and Business Statistics.
    9. Boyuan Zhang, 2022. "Incorporating Prior Knowledge of Latent Group Structure in Panel Data Models," Papers 2211.16714, arXiv.org, revised Oct 2023.
    10. Dong Hwan Oh & Andrew J. Patton, 2021. "Dynamic Factor Copula Models with Estimated Cluster Assignments," Finance and Economics Discussion Series 2021-029r1, Board of Governors of the Federal Reserve System (U.S.), revised 06 May 2022.
    11. Liu, Ruiqi & Shang, Zuofeng & Zhang, Yonghui & Zhou, Qiankun, 2020. "Identification and estimation in panel models with overspecified number of groups," Journal of Econometrics, Elsevier, vol. 215(2), pages 574-590.
    12. Freeman, Hugo & Weidner, Martin, 2023. "Linear panel regressions with two-way unobserved heterogeneity," Journal of Econometrics, Elsevier, vol. 237(1).
    13. Huang, Wenxin & Jin, Sainan & Phillips, Peter C.B. & Su, Liangjun, 2020. "Nonstationary Panel Models with Latent Group Structures and Cross-Section Dependence," Economics and Statistics Working Papers 7-2020, Singapore Management University, School of Economics.
    14. Miao, Ke & Su, Liangjun & Wang, Wendun, 2020. "Panel threshold regressions with latent group structures," Journal of Econometrics, Elsevier, vol. 214(2), pages 451-481.
    15. Wang, Wuyi & Su, Liangjun, 2017. "Identifying Latent Group Structures in Nonlinear Panels," Economics and Statistics Working Papers 19-2017, Singapore Management University, School of Economics.
    16. Degui Li & Bin Peng & Songqiao Tang & Weibiao Wu, 2023. "Inference of Grouped Time-Varying Network Vector Autoregression Models," Monash Econometrics and Business Statistics Working Papers 5/23, Monash University, Department of Econometrics and Business Statistics.
    17. Zhan Gao & Zhentao Shi, 2018. "Implementing Convex Optimization in R: Two Econometric Examples," Papers 1806.10423, arXiv.org, revised Aug 2019.
    18. Mehrabani, Ali, 2023. "Estimation and identification of latent group structures in panel data," Journal of Econometrics, Elsevier, vol. 235(2), pages 1464-1482.
    19. Okui, Ryo & Wang, Wendun, 2021. "Heterogeneous structural breaks in panel data models," Journal of Econometrics, Elsevier, vol. 220(2), pages 447-473.
    20. Lu, Xun & Su, Liangjun, 2023. "Uniform inference in linear panel data models with two-dimensional heterogeneity," Journal of Econometrics, Elsevier, vol. 235(2), pages 694-719.
    21. Hong, Shengjie & Su, Liangjun & Jiang, Tao, 2023. "Profile GMM estimation of panel data models with interactive fixed effects," Journal of Econometrics, Elsevier, vol. 235(2), pages 927-948.
    22. Daniel Czarnowske, 2022. "A Classifier-Lasso Approach for Estimating Production Functions with Latent Group Structures," Papers 2203.02220, arXiv.org.
    23. Su, Liangjun & Wang, Wuyi & Xu, Xingbai, 2023. "Identifying latent group structures in spatial dynamic panels," Journal of Econometrics, Elsevier, vol. 235(2), pages 1955-1980.
    24. Yiren Wang & Liangjun Su & Yichong Zhang, 2022. "Low-rank Panel Quantile Regression: Estimation and Inference," Papers 2210.11062, arXiv.org.
    25. Degui Li & Bin Peng & Songqiao Tang & Weibiao Wu, 2023. "Estimation of Grouped Time-Varying Network Vector Autoregression Models," Papers 2303.10117, arXiv.org, revised Mar 2024.
    26. Katerina Chrysikou & George Kapetanios, 2024. "Heterogeneous Grouping Structures in Panel Data," Papers 2407.19509, arXiv.org.
    27. Langevin, R.;, 2024. "Consistent Estimation of Finite Mixtures: An Application to Latent Group Panel Structures," Health, Econometrics and Data Group (HEDG) Working Papers 24/16, HEDG, c/o Department of Economics, University of York.
    28. Zhentao Shi & Liangjun Su & Tian Xie, 2020. "L2-Relaxation: With Applications to Forecast Combination and Portfolio Analysis," Papers 2010.09477, arXiv.org, revised Aug 2022.

  18. Feng, Guohua & Peng, Bin & Su, Liangjun & Yang, Thomas Tao, 2019. "Semi-parametric single-index panel data models with interactive fixed effects: Theory and practice," Journal of Econometrics, Elsevier, vol. 212(2), pages 607-622.

    Cited by:

    1. Juodis, Arturas & Sarafidis, Vasilis, 2020. "An Incidental Parameters Free Inference Approach for Panels with Common Shocks," MPRA Paper 104906, University Library of Munich, Germany.
    2. Fei Liu & Jiti Gao & Yanrong Yang, 2019. "Nonparametric Estimation in Panel Data Models with Heterogeneity and Time Varyingness," Monash Econometrics and Business Statistics Working Papers 24/19, Monash University, Department of Econometrics and Business Statistics.
    3. Jiti Gao & Fei Liu & Bin Peng & Yayi Yan, 2020. "Binary Response Models for Heterogeneous Panel Data with Interactive Fixed Effects," Papers 2012.03182, arXiv.org, revised Nov 2021.

  19. Liangjun Su & Pai Xu, 2019. "Common threshold in quantile regressions with an application to pricing for reputation," Econometric Reviews, Taylor & Francis Journals, vol. 38(4), pages 417-450, April.

    Cited by:

    1. Li, Zheng & Zeng, Jingjing & Hensher, David A., 2023. "An efficient approach to structural breaks and the case of automobile gasoline consumption in Australia," Transportation Research Part A: Policy and Practice, Elsevier, vol. 169(C).
    2. Junho Lee & Ying Sun & Huixia Judy Wang, 2021. "Spatial cluster detection with threshold quantile regression," Environmetrics, John Wiley & Sons, Ltd., vol. 32(8), December.
    3. Martins, Luis F., 2021. "The US debt–growth nexus along the business cycle," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    4. Hong, Yanran & Li, Pan & Wang, Lu & Zhang, Yaojie, 2023. "New evidence of extreme risk transmission between financial stress and international crude oil markets," Research in International Business and Finance, Elsevier, vol. 64(C).

  20. Su, Liangjun & Ura, Takuya & Zhang, Yichong, 2019. "Non-separable models with high-dimensional data," Journal of Econometrics, Elsevier, vol. 212(2), pages 646-677.
    See citations under working paper version above.
  21. Wang, Wuyi & Phillips, Peter C.B. & Su, Liangjun, 2019. "The heterogeneous effects of the minimum wage on employment across states," Economics Letters, Elsevier, vol. 174(C), pages 179-185.
    See citations under working paper version above.
  22. Ma, Shujie & Su, Liangjun, 2018. "Estimation of large dimensional factor models with an unknown number of breaks," Journal of Econometrics, Elsevier, vol. 207(1), pages 1-29.

    Cited by:

    1. Zhou, Ruichao & Wu, Jianhong, 2023. "Determining the number of change-points in high-dimensional factor models by cross-validation with matrix completion," Economics Letters, Elsevier, vol. 232(C).
    2. Badi Baltagi & Qu Feng & Chihwa Kao, 2019. "Structural Changes in Heterogeneous Panels with Endogenous Regressors," Center for Policy Research Working Papers 214, Center for Policy Research, Maxwell School, Syracuse University.
    3. Urga, Giovanni & Wang, Fa, 2022. "Estimation and Inference for High Dimensional Factor Model with Regime Switching," MPRA Paper 117012, University Library of Munich, Germany, revised 10 Apr 2023.
    4. Duan, Jiangtao & Bai, Jushan & Han, Xu, 2023. "Quasi-maximum likelihood estimation of break point in high-dimensional factor models," Journal of Econometrics, Elsevier, vol. 233(1), pages 209-236.
    5. Thomas Despois & Catherine Doz, 2021. "Identifying and interpreting the factors in factor models via sparsity: Different approaches," Working Papers halshs-02235543, HAL.
    6. Wang, Lu & Zhou, Ruichao & Wu, Jianhong, 2021. "Determining the number of breaks in large dimensional factor models with structural changes," Economics Letters, Elsevier, vol. 199(C).
    7. Li, Degui, 2024. "Estimation of Large Dynamic Covariance Matrices: A Selective Review," Econometrics and Statistics, Elsevier, vol. 29(C), pages 16-30.
    8. Wang, Lu & Wu, Jianhong, 2022. "Estimation of high-dimensional factor models with multiple structural changes," Economic Modelling, Elsevier, vol. 108(C).
    9. Urga, Giovanni & Wang, Fa, 2022. "Estimation and inference for high dimensional factor model with regime switching," MPRA Paper 113172, University Library of Munich, Germany.
    10. Wu, Jianhong, 2021. "Estimation of high dimensional factor model with multiple threshold-type regime shifts," Computational Statistics & Data Analysis, Elsevier, vol. 157(C).
    11. Catherine Doz & Peter Fuleky, 2019. "Dynamic Factor Models," PSE Working Papers halshs-02262202, HAL.
    12. Bai, Jushan & Duan, Jiangtao & Han, Xu, 2024. "The likelihood ratio test for structural changes in factor models," Journal of Econometrics, Elsevier, vol. 238(2).
    13. Xialu Liu & Elynn Y. Chen, 2022. "Identification and estimation of threshold matrix‐variate factor models," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 49(3), pages 1383-1417, September.
    14. Thomas Despois & Catherine Doz, 2021. "Identifying and interpreting the factors in factor models via sparsity: Different approaches," PSE Working Papers halshs-02235543, HAL.
    15. Bai, Jushan & Han, Xu & Shi, Yutang, 2020. "Estimation and inference of change points in high-dimensional factor models," Journal of Econometrics, Elsevier, vol. 219(1), pages 66-100.
    16. Wang, Hanchao & Peng, Bin & Li, Degui & Leng, Chenlei, 2021. "Nonparametric estimation of large covariance matrices with conditional sparsity," Journal of Econometrics, Elsevier, vol. 223(1), pages 53-72.
    17. Urga, Giovanni & Wang, Fa, 2024. "Estimation and inference for high dimensional factor model with regime switching," Journal of Econometrics, Elsevier, vol. 241(2).
    18. Yiren Wang & Liangjun Su & Yichong Zhang, 2022. "Low-rank Panel Quantile Regression: Estimation and Inference," Papers 2210.11062, arXiv.org.
    19. Baltagi, Badi H. & Kao, Chihwa & Wang, Fa, 2021. "Estimating and testing high dimensional factor models with multiple structural changes," Journal of Econometrics, Elsevier, vol. 220(2), pages 349-365.
    20. Xialu Liu & John Guerard & Rong Chen & Ruey Tsay, 2024. "Improving Estimation of Portfolio Risk Using New Statistical Factors," Papers 2409.17182, arXiv.org.
    21. Ma, Chenchen & Tu, Yundong, 2023. "Group fused Lasso for large factor models with multiple structural breaks," Journal of Econometrics, Elsevier, vol. 233(1), pages 132-154.

  23. Su, Liangjun & Ju, Gaosheng, 2018. "Identifying latent grouped patterns in panel data models with interactive fixed effects," Journal of Econometrics, Elsevier, vol. 206(2), pages 554-573.

    Cited by:

    1. Yiren Wang & Peter C. B. Phillips & Liangjun Su, 2023. "Panel Data Models with Time-Varying Latent Group Structures," Cowles Foundation Discussion Papers 2364, Cowles Foundation for Research in Economics, Yale University.
    2. Lamarche, Carlos & Parker, Thomas, 2023. "Wild bootstrap inference for penalized quantile regression for longitudinal data," Journal of Econometrics, Elsevier, vol. 235(2), pages 1799-1826.
    3. Jorge A. Rivero, 2023. "Unobserved Grouped Heteroskedasticity and Fixed Effects," Papers 2310.14068, arXiv.org, revised Oct 2023.
    4. Chiang, Harold D. & Rodrigue, Joel & Sasaki, Yuya, 2023. "Post-Selection Inference In Three-Dimensional Panel Data," Econometric Theory, Cambridge University Press, vol. 39(3), pages 623-658, June.
    5. Miao, Ke & Li, Kunpeng & Su, Liangjun, 2020. "Panel threshold models with interactive fixed effects," Journal of Econometrics, Elsevier, vol. 219(1), pages 137-170.
    6. Boyuan Zhang, 2022. "Incorporating Prior Knowledge of Latent Group Structure in Panel Data Models," Papers 2211.16714, arXiv.org, revised Oct 2023.
    7. Liu, Ruiqi & Shang, Zuofeng & Zhang, Yonghui & Zhou, Qiankun, 2020. "Identification and estimation in panel models with overspecified number of groups," Journal of Econometrics, Elsevier, vol. 215(2), pages 574-590.
    8. Michael Vogt & Oliver Linton, 2018. "Multiscale clustering of nonparametric regression curves," CeMMAP working papers CWP08/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    9. Huang, Wenxin & Jin, Sainan & Phillips, Peter C.B. & Su, Liangjun, 2020. "Nonstationary Panel Models with Latent Group Structures and Cross-Section Dependence," Economics and Statistics Working Papers 7-2020, Singapore Management University, School of Economics.
    10. Wang, Wuyi & Phillips, Peter C.B. & Su, Liangjun, 2018. "The Heterogeneous Effects of the Minimum Wage on Employment Across States," Economics and Statistics Working Papers 11-2018, Singapore Management University, School of Economics.
    11. Miao, Ke & Su, Liangjun & Wang, Wendun, 2020. "Panel threshold regressions with latent group structures," Journal of Econometrics, Elsevier, vol. 214(2), pages 451-481.
    12. Gobillon, Laurent & Magnac, Thierry & Roux, Sébastien, 2022. "Lifecycle Wages and Human Capital Investments: Selection and Missing Data," CEPR Discussion Papers 16999, C.E.P.R. Discussion Papers.
    13. Wang, Wuyi & Su, Liangjun, 2017. "Identifying Latent Group Structures in Nonlinear Panels," Economics and Statistics Working Papers 19-2017, Singapore Management University, School of Economics.
    14. Denis Chetverikov & Elena Manresa, 2022. "Spectral and post-spectral estimators for grouped panel data models," Papers 2212.13324, arXiv.org, revised Dec 2022.
    15. Zhan Gao & Zhentao Shi, 2018. "Implementing Convex Optimization in R: Two Econometric Examples," Papers 1806.10423, arXiv.org, revised Aug 2019.
    16. Daniel J. Lewis & Davide Melcangi & Laura Pilossoph & Aidan Toner-Rodgers, 2022. "Approximating Grouped Fixed Effects Estimation via Fuzzy Clustering Regression," Staff Reports 1033, Federal Reserve Bank of New York.
    17. Mehrabani, Ali, 2023. "Estimation and identification of latent group structures in panel data," Journal of Econometrics, Elsevier, vol. 235(2), pages 1464-1482.
    18. Hong, Shengjie & Su, Liangjun & Jiang, Tao, 2023. "Profile GMM estimation of panel data models with interactive fixed effects," Journal of Econometrics, Elsevier, vol. 235(2), pages 927-948.
    19. Su, Liangjun & Wang, Wuyi & Xu, Xingbai, 2023. "Identifying latent group structures in spatial dynamic panels," Journal of Econometrics, Elsevier, vol. 235(2), pages 1955-1980.
    20. Yiren Wang & Liangjun Su & Yichong Zhang, 2022. "Low-rank Panel Quantile Regression: Estimation and Inference," Papers 2210.11062, arXiv.org.
    21. Likai Chen & Georg Keilbar & Liangjun Su & Weining Wang, 2023. "Inference on many jumps in nonparametric panel regression models," Papers 2312.01162, arXiv.org, revised Jan 2025.
    22. Katerina Chrysikou & George Kapetanios, 2024. "Heterogeneous Grouping Structures in Panel Data," Papers 2407.19509, arXiv.org.
    23. Zhentao Shi & Liangjun Su & Tian Xie, 2020. "L2-Relaxation: With Applications to Forecast Combination and Portfolio Analysis," Papers 2010.09477, arXiv.org, revised Aug 2022.
    24. Li, Kunpeng & Cui, Guowei & Lu, Lina, 2020. "Efficient estimation of heterogeneous coefficients in panel data models with common shocks," Journal of Econometrics, Elsevier, vol. 216(2), pages 327-353.

  24. Wuyi Wang & Peter C. B. Phillips & Liangjun Su, 2018. "Homogeneity pursuit in panel data models: Theory and application," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(6), pages 797-815, September.
    See citations under working paper version above.
  25. Liangjun Su & Xi Qu, 2017. "Specification Test for Spatial Autoregressive Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(4), pages 572-584, October.

    Cited by:

    1. Sun, Yiguo & Malikov, Emir, 2018. "Estimation and inference in functional-coefficient spatial autoregressive panel data models with fixed effects," Journal of Econometrics, Elsevier, vol. 203(2), pages 359-378.
    2. Liu, Li & Bu, Ruijun & Pan, Zhiyuan & Xu, Yuhua, 2019. "Are financial returns really predictable out-of-sample?: Evidence from a new bootstrap test," Economic Modelling, Elsevier, vol. 81(C), pages 124-135.
    3. Gao, Min & Yang, Wenzhi & Wu, Shipeng & Yu, Wei, 2022. "Asymptotic normality of residual density estimator in stationary and explosive autoregressive models," Computational Statistics & Data Analysis, Elsevier, vol. 175(C).
    4. Francesco Giordano & Marcella Niglio & Maria Lucia Parrella, 2024. "Testing Spatial Dynamic Panel Data Models with Heterogeneous Spatial and Regression Coefficients," Journal of Time Series Analysis, Wiley Blackwell, vol. 45(5), pages 771-799, September.
    5. Abhimanyu Gupta & Jungyoon Lee & Francesca Rossi, 2024. "Testing linearity of spatial interaction functions \`a la Ramsey," Papers 2412.14778, arXiv.org.
    6. Jungyoon Lee & Peter C.B. Phillips & Francesca Rossi, 2020. "Consistent Misspecification Testing in Spatial Autoregressive Models," Cowles Foundation Discussion Papers 2256, Cowles Foundation for Research in Economics, Yale University.
    7. Lu, Xun & Su, Liangjun, 2020. "Determining individual or time effects in panel data models," Journal of Econometrics, Elsevier, vol. 215(1), pages 60-83.
    8. Abhimanyu Gupta & Xi Qu, 2021. "Consistent specification testing under spatial dependence," Papers 2101.10255, arXiv.org, revised Aug 2022.

  26. Su, Liangjun & Zheng, Xin, 2017. "A martingale-difference-divergence-based test for specification," Economics Letters, Elsevier, vol. 156(C), pages 162-167.

    Cited by:

    1. Ghazinoory, Sepehr & Aghaei, Parvaneh, 2021. "Differences between policy assessment & policy evaluation; a case study on supportive policies for knowledge-based firms," Technological Forecasting and Social Change, Elsevier, vol. 169(C).
    2. Emmanuel Selorm Tsyawo, 2021. "Feasible IV Regression without Excluded Instruments," Papers 2103.09621, arXiv.org, revised Nov 2022.
    3. Lai, Tingyu & Zhang, Zhongzhan & Wang, Yafei, 2021. "A kernel-based measure for conditional mean dependence," Computational Statistics & Data Analysis, Elsevier, vol. 160(C).
    4. Emmanuel Selorm Tsyawo & Abdul-Nasah Soale, 2021. "A Distance Covariance-based Estimator," Papers 2102.07008, arXiv.org, revised Sep 2024.

  27. Xun Lu & Liangjun Su, 2017. "Determining the number of groups in latent panel structures with an application to income and democracy," Quantitative Economics, Econometric Society, vol. 8(3), pages 729-760, November.

    Cited by:

    1. Yiren Wang & Peter C. B. Phillips & Liangjun Su, 2023. "Panel Data Models with Time-Varying Latent Group Structures," Cowles Foundation Discussion Papers 2364, Cowles Foundation for Research in Economics, Yale University.
    2. Jorge A. Rivero, 2023. "Unobserved Grouped Heteroskedasticity and Fixed Effects," Papers 2310.14068, arXiv.org, revised Oct 2023.
    3. Joao, Igor Custodio & Lucas, André & Schaumburg, Julia & Schwaab, Bernd, 2021. "Dynamic clustering of multivariate panel data," Working Paper Series 2577, European Central Bank.
    4. Andreas Dzemski & Ryo Okui, 2024. "Confidence set for group membership," Quantitative Economics, Econometric Society, vol. 15(2), pages 245-277, May.
    5. Bruce E. Hansen & Seojeong Jay Lee, 2018. "Inference for Iterated GMM Under Misspecification and Clustering," Discussion Papers 2018-07, School of Economics, The University of New South Wales.
    6. Liu, Ruiqi & Shang, Zuofeng & Zhang, Yonghui & Zhou, Qiankun, 2020. "Identification and estimation in panel models with overspecified number of groups," Journal of Econometrics, Elsevier, vol. 215(2), pages 574-590.
    7. Liu, Yanbo & Phillips, Peter C. B. & Yu, Jun, 2022. "A Panel Clustering Approach to Analyzing Bubble Behavior," Economics and Statistics Working Papers 1-2022, Singapore Management University, School of Economics.
    8. Huang, Wenxin & Jin, Sainan & Phillips, Peter C.B. & Su, Liangjun, 2020. "Nonstationary Panel Models with Latent Group Structures and Cross-Section Dependence," Economics and Statistics Working Papers 7-2020, Singapore Management University, School of Economics.
    9. Wang, Wuyi & Phillips, Peter C.B. & Su, Liangjun, 2018. "The Heterogeneous Effects of the Minimum Wage on Employment Across States," Economics and Statistics Working Papers 11-2018, Singapore Management University, School of Economics.
    10. Miao, Ke & Su, Liangjun & Wang, Wendun, 2020. "Panel threshold regressions with latent group structures," Journal of Econometrics, Elsevier, vol. 214(2), pages 451-481.
    11. Yao Luo & Hidenori Takahashi, 2022. "Bidding for Contracts under Uncertain Demand: Skewed Bidding and Risk Sharing," Working Papers tecipa-732, University of Toronto, Department of Economics.
    12. Saptorshee Kanto Chakraborty & Massimiliano Mazzanti, 2021. "Revisiting the literature on the dynamic Environmental Kuznets Curves using a latent structure approach," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 38(3), pages 923-941, October.
    13. Wang, Wuyi & Su, Liangjun, 2017. "Identifying Latent Group Structures in Nonlinear Panels," Economics and Statistics Working Papers 19-2017, Singapore Management University, School of Economics.
    14. Bruce E. Hansen & Seojeong Lee, 2021. "Inference for Iterated GMM Under Misspecification," Econometrica, Econometric Society, vol. 89(3), pages 1419-1447, May.
    15. Francesco Fallucchi & Andrea Mercatanti & Jan Niederreiter, 2021. "Identifying types in contest experiments," International Journal of Game Theory, Springer;Game Theory Society, vol. 50(1), pages 39-61, March.
    16. Zhan Gao & Zhentao Shi, 2018. "Implementing Convex Optimization in R: Two Econometric Examples," Papers 1806.10423, arXiv.org, revised Aug 2019.
    17. Yu Hao & Hiroyuki Kasahara, 2022. "Testing the Number of Components in Finite Mixture Normal Regression Model with Panel Data," Papers 2210.02824, arXiv.org, revised Jun 2023.
    18. Mehrabani, Ali, 2023. "Estimation and identification of latent group structures in panel data," Journal of Econometrics, Elsevier, vol. 235(2), pages 1464-1482.
    19. Okui, Ryo & Wang, Wendun, 2021. "Heterogeneous structural breaks in panel data models," Journal of Econometrics, Elsevier, vol. 220(2), pages 447-473.
    20. Dzemski, Andreas & Okui, Ryo, 2018. "Confidence Set for Group Membership," Working Papers in Economics 727, University of Gothenburg, Department of Economics.
    21. Su, Liangjun & Wang, Wuyi & Xu, Xingbai, 2023. "Identifying latent group structures in spatial dynamic panels," Journal of Econometrics, Elsevier, vol. 235(2), pages 1955-1980.
    22. Jan Niederreiter, 2023. "Broadening Economics in the Era of Artificial Intelligence and Experimental Evidence," Italian Economic Journal: A Continuation of Rivista Italiana degli Economisti and Giornale degli Economisti, Springer;Società Italiana degli Economisti (Italian Economic Association), vol. 9(1), pages 265-294, March.

  28. Su, Liangjun & Wang, Xia, 2017. "On time-varying factor models: Estimation and testing," Journal of Econometrics, Elsevier, vol. 198(1), pages 84-101.

    Cited by:

    1. Fu, Zhonghao & Hong, Yongmiao & Su, Liangjun & Wang, Xia, 2023. "Specification tests for time-varying coefficient models," Journal of Econometrics, Elsevier, vol. 235(2), pages 720-744.
    2. Ma, Shujie & Su, Liangjun, 2018. "Estimation of large dimensional factor models with an unknown number of breaks," Journal of Econometrics, Elsevier, vol. 207(1), pages 1-29.
    3. Fei Liu & Jiti Gao & Yanrong Yang, 2020. "Time-Varying Panel Data Models with an Additive Factor Structure," Monash Econometrics and Business Statistics Working Papers 42/20, Monash University, Department of Econometrics and Business Statistics.
    4. Chen, J. & Li, D. & Li, Y. & Linton, O. B., 2022. "Estimating Time-Varying Networks for High-Dimensional Time Series," Cambridge Working Papers in Economics 2273, Faculty of Economics, University of Cambridge.
    5. Shikha Gupta & Nand Kumar, 2023. "Time varying dynamics of globalization effect in India," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 22(1), pages 81-97, January.
    6. Chen, Qitong & Hong, Yongmiao & Li, Haiqi, 2024. "Time-varying forecast combination for factor-augmented regressions with smooth structural changes," Journal of Econometrics, Elsevier, vol. 240(1).
    7. Pedro Isaac Chavez-Lopez & Tae-Hwy Lee, 2025. "Quantile-Covariance Three-Pass Regression Filter," Working Papers 202501, University of California at Riverside, Department of Economics.
    8. Fan, Qingliang & Wu, Ruike & Yang, Yanrong & Zhong, Wei, 2024. "Time-varying minimum variance portfolio," Journal of Econometrics, Elsevier, vol. 239(2).
    9. Cheng, Mingmian & Liao, Yuan & Yang, Xiye, 2023. "Uniform predictive inference for factor models with instrumental and idiosyncratic betas," Journal of Econometrics, Elsevier, vol. 237(2).
    10. Barigozzi, Matteo & Hallin, Marc & Soccorsi, Stefano & von Sachs, Rainer, 2021. "Time-varying general dynamic factor models and the measurement of financial connectedness," Journal of Econometrics, Elsevier, vol. 222(1), pages 324-343.
    11. Freeman, Hugo & Weidner, Martin, 2023. "Linear panel regressions with two-way unobserved heterogeneity," Journal of Econometrics, Elsevier, vol. 237(1).
    12. Rudrani Bhattacharya & Parma Chakravartti & Sudipto Mundle, 2019. "Forecasting India’s economic growth: a time-varying parameter regression approach," Macroeconomics and Finance in Emerging Market Economies, Taylor & Francis Journals, vol. 12(3), pages 205-228, September.
    13. Li, Degui, 2024. "Estimation of Large Dynamic Covariance Matrices: A Selective Review," Econometrics and Statistics, Elsevier, vol. 29(C), pages 16-30.
    14. Alessandro Casini & Pierre Perron, 2018. "Structural Breaks in Time Series," Boston University - Department of Economics - Working Papers Series WP2019-02, Boston University - Department of Economics.
    15. Miao, Ke & Phillips, Peter C.B. & Su, Liangjun, 2023. "High-dimensional VARs with common factors," Journal of Econometrics, Elsevier, vol. 233(1), pages 155-183.
    16. Kong, Xin-Bing & Liu, Cheng, 2018. "Testing against constant factor loading matrix with large panel high-frequency data," Journal of Econometrics, Elsevier, vol. 204(2), pages 301-319.
    17. Urga, Giovanni & Wang, Fa, 2022. "Estimation and inference for high dimensional factor model with regime switching," MPRA Paper 113172, University Library of Munich, Germany.
    18. Markus Pelger & Ruoxuan Xiong, 2018. "State-Varying Factor Models of Large Dimensions," Papers 1807.02248, arXiv.org, revised Oct 2020.
    19. Sun, Yuying & Hong, Yongmiao & Wang, Shouyang & Zhang, Xinyu, 2023. "Penalized time-varying model averaging," Journal of Econometrics, Elsevier, vol. 235(2), pages 1355-1377.
    20. Aslanidis, Nektarios & Hartigan, Luke, 2021. "Is the assumption of constant factor loadings too strong in practice?," Economic Modelling, Elsevier, vol. 98(C), pages 100-108.
    21. Yousuf, Kashif & Ng, Serena, 2021. "Boosting high dimensional predictive regressions with time varying parameters," Journal of Econometrics, Elsevier, vol. 224(1), pages 60-87.
    22. Sun, Yucheng & Xu, Wen & Zhang, Chuanhai, 2023. "Identifying latent factors based on high-frequency data," Journal of Econometrics, Elsevier, vol. 233(1), pages 251-270.
    23. Catherine Doz & Peter Fuleky, 2019. "Dynamic Factor Models," PSE Working Papers halshs-02262202, HAL.
    24. Jie Wei & Yonghui Zhang, 2023. "Does Principal Component Analysis Preserve the Sparsity in Sparse Weak Factor Models?," Papers 2305.05934, arXiv.org, revised Nov 2024.
    25. Fu, Zhonghao & Hong, Yongmiao & Wang, Xia, 2023. "Testing for structural changes in large dimensional factor models via discrete Fourier transform," Journal of Econometrics, Elsevier, vol. 233(1), pages 302-331.
    26. Su, Liangjun & Ju, Gaosheng, 2018. "Identifying latent grouped patterns in panel data models with interactive fixed effects," Journal of Econometrics, Elsevier, vol. 206(2), pages 554-573.
    27. Hugo Freeman & Martin Weidner, 2021. "Linear Panel Regressions with Two-Way Unobserved Heterogeneity," Papers 2109.11911, arXiv.org, revised Aug 2022.
    28. Liang Chen & Juan Jose Dolado & Jesus Gonzalo, 2019. "Quantile Factor Models," Papers 1911.02173, arXiv.org, revised Sep 2020.
    29. Jin, Sainan & Miao, Ke & Su, Liangjun, 2021. "On factor models with random missing: EM estimation, inference, and cross validation," Journal of Econometrics, Elsevier, vol. 222(1), pages 745-777.
    30. Raffaella Giacomini & Katja Smetanina & Jason Lu, 2024. "Perceived shocks and impulse responses," IFS Working Papers WCWP21/24, Institute for Fiscal Studies.
    31. Eric Hillebrand & Jakob Mikkelsen & Lars Spreng & Giovanni Urga, 2020. "Exchange Rates and Macroeconomic Fundamentals: Evidence of Instabilities from Time-Varying Factor Loadings," CREATES Research Papers 2020-19, Department of Economics and Business Economics, Aarhus University.
    32. Hong, Shengjie & Su, Liangjun & Jiang, Tao, 2023. "Profile GMM estimation of panel data models with interactive fixed effects," Journal of Econometrics, Elsevier, vol. 235(2), pages 927-948.
    33. Esther Ruiz & Pilar Poncela, 2022. "Factor Extraction in Dynamic Factor Models: Kalman Filter Versus Principal Components," Foundations and Trends(R) in Econometrics, now publishers, vol. 12(2), pages 121-231, November.
    34. Zhe Sun & Yundong Tu, 2024. "Factors in Fashion: Factor Analysis towards the Mode," Papers 2409.19287, arXiv.org.
    35. Qingliang Fan & Ruike Wu & Yanrong Yang, 2024. "Shocks-adaptive Robust Minimum Variance Portfolio for a Large Universe of Assets," Papers 2410.01826, arXiv.org.
    36. Duván Humberto Cataño & Carlos Vladimir Rodríguez-Caballero & Daniel Peña, 2019. "Wavelet Estimation for Dynamic Factor Models with Time-Varying Loadings," CREATES Research Papers 2019-23, Department of Economics and Business Economics, Aarhus University.
    37. Reiß, Markus & Winkelmann, Lars, 2021. "Inference on the maximal rank of time-varying covariance matrices using high-frequency data," Discussion Papers 2021/14, Free University Berlin, School of Business & Economics.
    38. Christian Brownlees & Gu{dh}mundur Stef'an Gu{dh}mundsson & Yaping Wang, 2024. "Performance of Empirical Risk Minimization For Principal Component Regression," Papers 2409.03606, arXiv.org, revised Sep 2024.
    39. Ma, Chenchen & Tu, Yundong, 2023. "Shrinkage estimation of multiple threshold factor models," Journal of Econometrics, Elsevier, vol. 235(2), pages 1876-1892.
    40. Wang, Hanchao & Peng, Bin & Li, Degui & Leng, Chenlei, 2021. "Nonparametric estimation of large covariance matrices with conditional sparsity," Journal of Econometrics, Elsevier, vol. 223(1), pages 53-72.
    41. Hugo Freeman & Martin Weidner, 2021. "Linear panel regressions with two-way unobserved heterogeneity," CeMMAP working papers CWP39/21, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    42. Urga, Giovanni & Wang, Fa, 2024. "Estimation and inference for high dimensional factor model with regime switching," Journal of Econometrics, Elsevier, vol. 241(2).
    43. Raffaella Giacomini & Jason Lu & Katja Smetanina, 2024. "Perceived shocks and impulse responses," CeMMAP working papers 21/24, Institute for Fiscal Studies.
    44. Xialu Liu & John Guerard & Rong Chen & Ruey Tsay, 2024. "Improving Estimation of Portfolio Risk Using New Statistical Factors," Papers 2409.17182, arXiv.org.
    45. Jianqing Fan & Kunpeng Li & Yuan Liao, 2020. "Recent Developments on Factor Models and its Applications in Econometric Learning," Papers 2009.10103, arXiv.org.
    46. Jaeheon Jung, 2019. "Estimating a Large Covariance Matrix in Time-varying Factor Models," Papers 1910.11965, arXiv.org.
    47. Mehmet Balcilar & Riza Demirer & Festus V. Bekun, 2021. "Flexible Time-Varying Betas in a Novel Mixture Innovation Factor Model with Latent Threshold," Mathematics, MDPI, vol. 9(8), pages 1-20, April.
    48. Ma, Chenchen & Tu, Yundong, 2023. "Group fused Lasso for large factor models with multiple structural breaks," Journal of Econometrics, Elsevier, vol. 233(1), pages 132-154.
    49. He, Lingyu & Huang, Fei & Shi, Jianjie & Yang, Yanrong, 2021. "Mortality forecasting using factor models: Time-varying or time-invariant factor loadings?," Insurance: Mathematics and Economics, Elsevier, vol. 98(C), pages 14-34.
    50. Wei, Jie & Zhang, Yonghui, 2020. "A time-varying diffusion index forecasting model," Economics Letters, Elsevier, vol. 193(C).

  29. Hoderlein, Stefan & Su, Liangjun & White, Halbert & Yang, Thomas Tao, 2016. "Testing for monotonicity in unobservables under unconfoundedness," Journal of Econometrics, Elsevier, vol. 193(1), pages 183-202.
    See citations under working paper version above.
  30. Degui Li & Junhui Qian & Liangjun Su, 2016. "Panel Data Models With Interactive Fixed Effects and Multiple Structural Breaks," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(516), pages 1804-1819, October.

    Cited by:

    1. Ma, Shujie & Su, Liangjun, 2018. "Estimation of large dimensional factor models with an unknown number of breaks," Journal of Econometrics, Elsevier, vol. 207(1), pages 1-29.
    2. Yiren Wang & Peter C. B. Phillips & Liangjun Su, 2023. "Panel Data Models with Time-Varying Latent Group Structures," Cowles Foundation Discussion Papers 2364, Cowles Foundation for Research in Economics, Yale University.
    3. Badi Baltagi & Qu Feng & Chihwa Kao, 2019. "Structural Changes in Heterogeneous Panels with Endogenous Regressors," Center for Policy Research Working Papers 214, Center for Policy Research, Maxwell School, Syracuse University.
    4. Otilia Boldea & Bettina Drepper & Zhuojiong Gan, 2018. "Change Point Estimation in Panel Data with Time-Varying Individual Effects," Papers 1808.03109, arXiv.org.
    5. Chiang, Harold D. & Rodrigue, Joel & Sasaki, Yuya, 2023. "Post-Selection Inference In Three-Dimensional Panel Data," Econometric Theory, Cambridge University Press, vol. 39(3), pages 623-658, June.
    6. Miao, Ke & Li, Kunpeng & Su, Liangjun, 2020. "Panel threshold models with interactive fixed effects," Journal of Econometrics, Elsevier, vol. 219(1), pages 137-170.
    7. Jan Ditzen & Yiannis Karavias & Joakim Westerlund, 2023. "Multiple structural breaks in interactive effects panel data and the impace of quantitative easing on bank lending," Discussion Papers 23-02, Department of Economics, University of Birmingham.
    8. Yiannis Karavias & Paresh Narayan & Joakim Westerlund, 2021. "Structural Breaks in Interactive Effects Panels and the Stock Market Reaction to COVID-19," Papers 2111.03035, arXiv.org.
    9. Ruiqi Liu & Ben Boukai & Zuofeng Shang, 2019. "Statistical Inference on Partially Linear Panel Model under Unobserved Linearity," Papers 1911.08830, arXiv.org.
    10. Huang, Wenxin & Jin, Sainan & Phillips, Peter C.B. & Su, Liangjun, 2020. "Nonstationary Panel Models with Latent Group Structures and Cross-Section Dependence," Economics and Statistics Working Papers 7-2020, Singapore Management University, School of Economics.
    11. Li, Degui, 2024. "Estimation of Large Dynamic Covariance Matrices: A Selective Review," Econometrics and Statistics, Elsevier, vol. 29(C), pages 16-30.
    12. Saptorshee Kanto Chakraborty & Massimiliano Mazzanti, 2021. "Revisiting the literature on the dynamic Environmental Kuznets Curves using a latent structure approach," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 38(3), pages 923-941, October.
    13. Alessandro Casini & Pierre Perron, 2018. "Structural Breaks in Time Series," Boston University - Department of Economics - Working Papers Series WP2019-02, Boston University - Department of Economics.
    14. Bin Peng & Liangjun Su & Joakim Westerlund & Yanrong Yang, 2021. "Interactive Effects Panel Data Models with General Factors and Regressors," Monash Econometrics and Business Statistics Working Papers 23/21, Monash University, Department of Econometrics and Business Statistics.
    15. Wang,Dieter, 2021. "Natural Capital and Sovereign Bonds," Policy Research Working Paper Series 9606, The World Bank.
    16. Jiang, Peiyun & Kurozumi, Eiji, 2021. "A new test for common breaks in heterogeneous panel data models," Discussion paper series HIAS-E-107, Hitotsubashi Institute for Advanced Study, Hitotsubashi University.
    17. Ayden Higgins & Federico Martellosio, 2019. "Shrinkage Estimation of Network Spillovers with Factor Structured Errors," Papers 1909.02823, arXiv.org, revised Nov 2021.
    18. Fei Liu & Jiti Gao & Yanrong Yang, 2019. "Nonparametric Estimation in Panel Data Models with Heterogeneity and Time Varyingness," Monash Econometrics and Business Statistics Working Papers 24/19, Monash University, Department of Econometrics and Business Statistics.
    19. Hyungsik Roger Moon & Martin Weidner, 2019. "Nuclear norm regularized estimation of panel regression models," CeMMAP working papers CWP14/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    20. Bai, Jushan & Li, Kunpeng, 2021. "Dynamic spatial panel data models with common shocks," Journal of Econometrics, Elsevier, vol. 224(1), pages 134-160.
    21. Minyoung Jo & Sangyeol Lee, 2021. "On CUSUM test for dynamic panel models," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(2), pages 515-542, June.
    22. Su, Liangjun & Ju, Gaosheng, 2018. "Identifying latent grouped patterns in panel data models with interactive fixed effects," Journal of Econometrics, Elsevier, vol. 206(2), pages 554-573.
    23. Shahnaz Parsaeian, 2024. "Stein-like Common Correlated Effects Estimation under Structural Breaks," Econometrics, MDPI, vol. 12(2), pages 1-23, April.
    24. Feng, Guohua & Gao, Jiti & Peng, Bin, 2022. "An integrated panel data approach to modelling economic growth," Journal of Econometrics, Elsevier, vol. 228(2), pages 379-397.
    25. Cheng, Tingting & Gao, Jiti & Yan, Yayi, 2019. "Regime switching panel data models with interactive fixed effects," Economics Letters, Elsevier, vol. 177(C), pages 47-51.
    26. Okui, Ryo & Wang, Wendun, 2021. "Heterogeneous structural breaks in panel data models," Journal of Econometrics, Elsevier, vol. 220(2), pages 447-473.
    27. Feng, Guohua & Peng, Bin & Su, Liangjun & Yang, Thomas Tao, 2019. "Semi-parametric single-index panel data models with interactive fixed effects: Theory and practice," Journal of Econometrics, Elsevier, vol. 212(2), pages 607-622.
    28. Yufeng Mao & Bin Peng & Mervyn J Silvapulle & Param Silvapulle & Yanrong Yang, 2021. "Decomposition of Bilateral Trade Flows Using a Three-Dimensional Panel Data Model," Monash Econometrics and Business Statistics Working Papers 7/21, Monash University, Department of Econometrics and Business Statistics.
    29. Hong, Shengjie & Su, Liangjun & Jiang, Tao, 2023. "Profile GMM estimation of panel data models with interactive fixed effects," Journal of Econometrics, Elsevier, vol. 235(2), pages 927-948.
    30. Chen, Likai & Wang, Weining & Wu, Wei Biao, 2019. "Inference of Break-Points in High-Dimensional Time Series," IRTG 1792 Discussion Papers 2019-013, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    31. Yufeng Mao & Bin Peng & Mervyn Silvapulle & Param Silvapulle & Yanrong Yang, 2021. "Decomposition of Bilateral Trade Flows Using a Three-Dimensional Panel Data Model," Papers 2101.06805, arXiv.org.
    32. Feng, Qu, 2020. "Common factors and common breaks in panels: An empirical investigation," Economics Letters, Elsevier, vol. 187(C).
    33. Georg Keilbar & Juan M. Rodriguez-Poo & Alexandra Soberon & Weining Wang, 2022. "A semiparametric approach for interactive fixed effects panel data models," Papers 2201.11482, arXiv.org, revised Mar 2023.
    34. Chaohua Dong & Jiti Gao & Bin Peng, 2018. "Varying-coefficient panel data models with partially observed factor structure," Monash Econometrics and Business Statistics Working Papers 1/18, Monash University, Department of Econometrics and Business Statistics.
    35. Agiwal Varun & Kumar Jitendra & Shangodoyin Dahud Kehinde, 2018. "A Bayesian Inference Of Multiple Structural Breaks In Mean And Error Variance In Panelar (1) Model," Statistics in Transition New Series, Statistics Poland, vol. 19(1), pages 7-23, March.
    36. Chen, Sanpan & Cui, Guowei & Zhang, Jianhua, 2017. "On testing for structural break of coefficients in factor-augmented regression models," Economics Letters, Elsevier, vol. 161(C), pages 141-145.
    37. Lumsdaine, Robin L. & Okui, Ryo & Wang, Wendun, 2023. "Estimation of panel group structure models with structural breaks in group memberships and coefficients," Journal of Econometrics, Elsevier, vol. 233(1), pages 45-65.
    38. Bai, Jushan & Han, Xu & Shi, Yutang, 2020. "Estimation and inference of change points in high-dimensional factor models," Journal of Econometrics, Elsevier, vol. 219(1), pages 66-100.
    39. Hou, Lei & Li, Kunpeng & Li, Qi & Ouyang, Min, 2021. "Revisiting the location of FDI in China: A panel data approach with heterogeneous shocks," Journal of Econometrics, Elsevier, vol. 221(2), pages 483-509.
    40. Xi Chen & Ye Luo & Martin Spindler, 2019. "Adaptive Discrete Smoothing for High-Dimensional and Nonlinear Panel Data," Papers 1912.12867, arXiv.org, revised Jan 2020.
    41. Costantini, Mauro & Paradiso, Antonio, 2018. "What do panel data say on inequality and GDP? New evidence at US state-level," Economics Letters, Elsevier, vol. 168(C), pages 115-117.
    42. Horváth, Lajos & Rice, Gregory, 2019. "Asymptotics for empirical eigenvalue processes in high-dimensional linear factor models," Journal of Multivariate Analysis, Elsevier, vol. 169(C), pages 138-165.
    43. Ma, Chenchen & Tu, Yundong, 2023. "Group fused Lasso for large factor models with multiple structural breaks," Journal of Econometrics, Elsevier, vol. 233(1), pages 132-154.
    44. Yuichi Goto & Kotone Suzuki & Xiaofei Xu & Masanobu Taniguchi, 2023. "Tests for the existence of group effects and interactions for two-way models with dependent errors," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 75(3), pages 511-532, June.
    45. Shobande, Olatunji A., 2023. "Rethinking social change: Does the permanent and transitory effects of electricity and solid fuel use predict health outcome in Africa?," Technological Forecasting and Social Change, Elsevier, vol. 186(PB).
    46. Li, Kunpeng & Cui, Guowei & Lu, Lina, 2020. "Efficient estimation of heterogeneous coefficients in panel data models with common shocks," Journal of Econometrics, Elsevier, vol. 216(2), pages 327-353.

  31. Su, Liangjun & Zhang, Yonghui & Wei, Jie, 2016. "A practical test for strict exogeneity in linear panel data models with fixed effects," Economics Letters, Elsevier, vol. 147(C), pages 27-31.

    Cited by:

    1. Alderighi, Stefano & Cleary, Siobhan & Varanasi, Padmasai, 2018. "The determinants of cross-border portfolio equity flows: new evidence from emerging markets," Economics Discussion Papers 23310, University of Essex, Department of Economics.
    2. Ardiyono, Sulistiyo K., 2022. "Covid-19 pandemic, firms’ responses, and unemployment in the ASEAN-5," Economic Analysis and Policy, Elsevier, vol. 76(C), pages 337-372.
    3. Alderighi, Stefano, 2018. "The determinants of retail trading activity in emerging markets: A cross-market analysis," Global Finance Journal, Elsevier, vol. 37(C), pages 152-167.
    4. Mayer, Alexander, 2022. "On the local power of some tests of strict exogeneity in linear fixed effects models," Econometrics and Statistics, Elsevier, vol. 24(C), pages 49-74.
    5. Zerbib, Olivier David, 2019. "The effect of pro-environmental preferences on bond prices: Evidence from green bonds," Journal of Banking & Finance, Elsevier, vol. 98(C), pages 39-60.
    6. Alderighi, Stefano & Cleary, Siobhan & Varanasi, Padmasai, 2019. "Do institutional factors influence cross-border portfolio equity flows? New evidence from emerging markets," Journal of International Money and Finance, Elsevier, vol. 99(C).
    7. Laura Spierdijk, 2023. "Assessing the consistency of the fixed-effects estimator: a regression-based Wald test," Empirical Economics, Springer, vol. 64(4), pages 1599-1630, April.
    8. Nguyen Thi Tuong Anh & Hung Quang Doan & Tuan Anh Bui & Nam Hoang Vu & Duong Thuy Thanh Le, 2022. "A Revisit of Motives for Chinese Outward Foreign Direct Investment: The Role of the Institution in Host Countries," SAGE Open, , vol. 12(4), pages 21582440221, December.
    9. Breitung, Jörg & Kripfganz, Sebastian & Hayakawa, Kazuhiko, 2022. "Bias-corrected method of moments estimators for dynamic panel data models," Econometrics and Statistics, Elsevier, vol. 24(C), pages 116-132.

  32. Qian, Junhui & Su, Liangjun, 2016. "Shrinkage Estimation Of Regression Models With Multiple Structural Changes," Econometric Theory, Cambridge University Press, vol. 32(6), pages 1376-1433, December.
    See citations under working paper version above.
  33. Lu, Xun & Su, Liangjun, 2016. "Shrinkage estimation of dynamic panel data models with interactive fixed effects," Journal of Econometrics, Elsevier, vol. 190(1), pages 148-175.
    See citations under working paper version above.
  34. Liangjun Su & Zhentao Shi & Peter C. B. Phillips, 2016. "Identifying Latent Structures in Panel Data," Econometrica, Econometric Society, vol. 84, pages 2215-2264, November.
    See citations under working paper version above.
  35. Su, Liangjun & Hoshino, Tadao, 2016. "Sieve instrumental variable quantile regression estimation of functional coefficient models," Journal of Econometrics, Elsevier, vol. 191(1), pages 231-254.
    See citations under working paper version above.
  36. Qian, Junhui & Su, Liangjun, 2016. "Shrinkage estimation of common breaks in panel data models via adaptive group fused Lasso," Journal of Econometrics, Elsevier, vol. 191(1), pages 86-109.

    Cited by:

    1. Ma, Shujie & Su, Liangjun, 2018. "Estimation of large dimensional factor models with an unknown number of breaks," Journal of Econometrics, Elsevier, vol. 207(1), pages 1-29.
    2. Yiren Wang & Peter C. B. Phillips & Liangjun Su, 2023. "Panel Data Models with Time-Varying Latent Group Structures," Cowles Foundation Discussion Papers 2364, Cowles Foundation for Research in Economics, Yale University.
    3. Otilia Boldea & Bettina Drepper & Zhuojiong Gan, 2018. "Change Point Estimation in Panel Data with Time-Varying Individual Effects," Papers 1808.03109, arXiv.org.
    4. Chiang, Harold D. & Rodrigue, Joel & Sasaki, Yuya, 2023. "Post-Selection Inference In Three-Dimensional Panel Data," Econometric Theory, Cambridge University Press, vol. 39(3), pages 623-658, June.
    5. Miao, Ke & Li, Kunpeng & Su, Liangjun, 2020. "Panel threshold models with interactive fixed effects," Journal of Econometrics, Elsevier, vol. 219(1), pages 137-170.
    6. Jan Ditzen & Yiannis Karavias & Joakim Westerlund, 2023. "Multiple structural breaks in interactive effects panel data and the impace of quantitative easing on bank lending," Discussion Papers 23-02, Department of Economics, University of Birmingham.
    7. Andrey G. Maksimov & Marina S. Telezhkina, 2024. "Similarity Of Structural Changes: The Case Of University Enrollment Rates," HSE Working papers WP BRP 271/EC/2024, National Research University Higher School of Economics.
    8. Hsiao, Cheng, 2018. "Panel models with interactive effects," Journal of Econometrics, Elsevier, vol. 206(2), pages 645-673.
    9. Vasilis Sarafidis & Tom Wansbeek, 2020. "Celebrating 40 Years of Panel Data Analysis: Past, Present and Future," Monash Econometrics and Business Statistics Working Papers 6/20, Monash University, Department of Econometrics and Business Statistics.
    10. Weijie Cui & Yong Li, 2023. "Bicluster Analysis of Heterogeneous Panel Data via M-Estimation," Mathematics, MDPI, vol. 11(10), pages 1-19, May.
    11. Tatsushi Oka & Pierre Perron, 2016. "Testing for Common Breaks in a Multiple Equations System," Papers 1606.00092, arXiv.org, revised Jan 2018.
    12. Ruiqi Liu & Ben Boukai & Zuofeng Shang, 2019. "Statistical Inference on Partially Linear Panel Model under Unobserved Linearity," Papers 1911.08830, arXiv.org.
    13. Huang, Wenxin & Jin, Sainan & Phillips, Peter C.B. & Su, Liangjun, 2020. "Nonstationary Panel Models with Latent Group Structures and Cross-Section Dependence," Economics and Statistics Working Papers 7-2020, Singapore Management University, School of Economics.
    14. Karsten Schweikert, 2022. "Detecting Multiple Structural Breaks in Systems of Linear Regression Equations with Integrated and Stationary Regressors," Papers 2201.05430, arXiv.org, revised Sep 2024.
    15. Alessandro Casini & Pierre Perron, 2018. "Structural Breaks in Time Series," Boston University - Department of Economics - Working Papers Series WP2019-02, Boston University - Department of Economics.
    16. Juodis, Arturas & Sarafidis, Vasilis, 2020. "An Incidental Parameters Free Inference Approach for Panels with Common Shocks," MPRA Paper 104906, University Library of Munich, Germany.
    17. Jiang, Peiyun & Kurozumi, Eiji, 2021. "A new test for common breaks in heterogeneous panel data models," Discussion paper series HIAS-E-107, Hitotsubashi Institute for Advanced Study, Hitotsubashi University.
    18. Martin C. Arnold & Thilo Reinschlussel, 2024. "Bootstrap Adaptive Lasso Solution Path Unit Root Tests," Papers 2409.07859, arXiv.org.
    19. Minyoung Jo & Sangyeol Lee, 2021. "On CUSUM test for dynamic panel models," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(2), pages 515-542, June.
    20. Mehrabani, Ali, 2023. "Estimation and identification of latent group structures in panel data," Journal of Econometrics, Elsevier, vol. 235(2), pages 1464-1482.
    21. Shahnaz Parsaeian, 2024. "Stein-like Common Correlated Effects Estimation under Structural Breaks," Econometrics, MDPI, vol. 12(2), pages 1-23, April.
    22. Okui, Ryo & Wang, Wendun, 2021. "Heterogeneous structural breaks in panel data models," Journal of Econometrics, Elsevier, vol. 220(2), pages 447-473.
    23. Kock, Anders Bredahl, 2016. "Oracle inequalities, variable selection and uniform inference in high-dimensional correlated random effects panel data models," Journal of Econometrics, Elsevier, vol. 195(1), pages 71-85.
    24. Lu, Xun & Su, Liangjun, 2023. "Uniform inference in linear panel data models with two-dimensional heterogeneity," Journal of Econometrics, Elsevier, vol. 235(2), pages 694-719.
    25. Linton, O. B. & Rücker, M. & Vogt, M. & Walsh, C., 2024. "Estimation and Inference in High-Dimensional Panel Data Models with Interactive Fixed Effects," Cambridge Working Papers in Economics 2467, Faculty of Economics, University of Cambridge.
    26. Oualid Bada & Alois Kneip & Dominik Liebl & Tim Mensinger & James Gualtieri & Robin C. Sickles, 2021. "A Wavelet Method for Panel Models with Jump Discontinuities in the Parameters," Papers 2109.10950, arXiv.org.
    27. Maciak, Matúš, 2021. "Quantile LASSO with changepoints in panel data models applied to option pricing," Econometrics and Statistics, Elsevier, vol. 20(C), pages 166-175.
    28. Georg Keilbar & Juan M. Rodriguez-Poo & Alexandra Soberon & Weining Wang, 2022. "A semiparametric approach for interactive fixed effects panel data models," Papers 2201.11482, arXiv.org, revised Mar 2023.
    29. Degui Li & Junhui Qian & Liangjun Su, 2016. "Panel Data Models With Interactive Fixed Effects and Multiple Structural Breaks," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(516), pages 1804-1819, October.
    30. Wang, Wei & Xiao, Zhijie & Ren, Yanyan & Yan, Xiaodong, 2023. "A bi-integrative analysis of two-dimensional heterogeneous panel data models," Economics Letters, Elsevier, vol. 230(C).
    31. Lumsdaine, Robin L. & Okui, Ryo & Wang, Wendun, 2023. "Estimation of panel group structure models with structural breaks in group memberships and coefficients," Journal of Econometrics, Elsevier, vol. 233(1), pages 45-65.
    32. Xi Chen & Ye Luo & Martin Spindler, 2019. "Adaptive Discrete Smoothing for High-Dimensional and Nonlinear Panel Data," Papers 1912.12867, arXiv.org, revised Jan 2020.
    33. Langevin, R.;, 2024. "Consistent Estimation of Finite Mixtures: An Application to Latent Group Panel Structures," Health, Econometrics and Data Group (HEDG) Working Papers 24/16, HEDG, c/o Department of Economics, University of York.
    34. Chen, Bin & Huang, Liquan, 2018. "Nonparametric testing for smooth structural changes in panel data models," Journal of Econometrics, Elsevier, vol. 202(2), pages 245-267.

  37. Jin, Sainan & Su, Liangjun & Xiao, Zhijie, 2015. "Adaptive Nonparametric Regression With Conditional Heteroskedasticity," Econometric Theory, Cambridge University Press, vol. 31(6), pages 1153-1191, December.

    Cited by:

    1. Linton, Oliver & Xiao, Zhijie, 2019. "Efficient estimation of nonparametric regression in the presence of dynamic heteroskedasticity," Journal of Econometrics, Elsevier, vol. 213(2), pages 608-631.
    2. Javier Alejo & Antonio F. Galvao & Julian Martinez-Iriarte & Gabriel Montes-Rojas, 2024. "Endogenous Heteroskedasticity in Linear Models," Papers 2412.02767, arXiv.org, revised Jan 2025.
    3. F. Comte & V. Genon-Catalot, 2020. "Regression function estimation on non compact support in an heteroscesdastic model," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 83(1), pages 93-128, January.

  38. Sainan Jin & Liangjun Su & Yonghui Zhang, 2015. "Nonparametric testing for anomaly effects in empirical asset pricing models," Empirical Economics, Springer, vol. 48(1), pages 9-36, February.
    See citations under working paper version above.
  39. Su, Liangjun & Jin, Sainan & Zhang, Yonghui, 2015. "Specification test for panel data models with interactive fixed effects," Journal of Econometrics, Elsevier, vol. 186(1), pages 222-244.
    See citations under working paper version above.
  40. Liangjun Su & Yundong Tu & Aman Ullah, 2015. "Testing Additive Separability of Error Term in Nonparametric Structural Models," Econometric Reviews, Taylor & Francis Journals, vol. 34(6-10), pages 1057-1088, December.

    Cited by:

    1. Yu-Chin Hsu & Ta-Cheng Huang & Haiqing Xu, 2018. "Testing for Unobserved Heterogeneous Treatment Effects with Observational Data," Papers 1803.07514, arXiv.org, revised Aug 2021.
    2. Babii, Andrii & Florens, Jean-Pierre, 2017. "Are unobservables separable?," TSE Working Papers 17-802, Toulouse School of Economics (TSE).
    3. Ghanem, Dalia, 2017. "Testing identifying assumptions in nonseparable panel data models," Journal of Econometrics, Elsevier, vol. 197(2), pages 202-217.
    4. Laura Schmitz, 2022. "Heterogeneous Effects of After-School Care on Child Development," Discussion Papers of DIW Berlin 2006, DIW Berlin, German Institute for Economic Research.
    5. Hoderlein, Stefan & Su, Liangjun & White, Halbert & Yang, Thomas Tao, 2016. "Testing for monotonicity in unobservables under unconfoundedness," Journal of Econometrics, Elsevier, vol. 193(1), pages 183-202.
    6. Li, Hongjun & Li, Qi & Liu, Ruixuan, 2016. "Consistent model specification tests based on k-nearest-neighbor estimation method," Journal of Econometrics, Elsevier, vol. 194(1), pages 187-202.

  41. Lewbel, Arthur & Lu, Xun & Su, Liangjun, 2015. "Specification testing for transformation models with an application to generalized accelerated failure-time models," Journal of Econometrics, Elsevier, vol. 184(1), pages 81-96.
    See citations under working paper version above.
  42. Yan Li & Liangjun Su & Yuewu Xu, 2015. "A Combined Approach to the Inference of Conditional Factor Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(2), pages 203-220, April.
    See citations under working paper version above.
  43. Su, Liangjun & Yang, Zhenlin, 2015. "QML estimation of dynamic panel data models with spatial errors," Journal of Econometrics, Elsevier, vol. 185(1), pages 230-258.

    Cited by:

    1. Olivier Parent & James P. Lesage, 2010. "A Spatial Dynamic Panel Model with Random Effects Applied to Commuting Times," University of Cincinnati, Economics Working Papers Series 2010-01, University of Cincinnati, Department of Economics.
    2. Corinne Autant-Bernard, 2011. "Spatial econometrics of innovation : Recent contributions and research perspectives," Working Papers 1120, Groupe d'Analyse et de Théorie Economique Lyon St-Étienne (GATE Lyon St-Étienne), Université de Lyon.
    3. Cizek, P. & Jacobs, J. & Ligthart, J.E. & Vrijburg, H., 2015. "GMM Estimation of Fixed Effects Dynamic Panel Data Models with Spatial Lag and Spatial Errors (Revised version of CentER DP 2011-134)," Discussion Paper 2015-003, Tilburg University, Center for Economic Research.
    4. Yang, Zhenlin & Yu, Jihai & Liu, Shew Fan, 2016. "Bias correction and refined inferences for fixed effects spatial panel data models," Regional Science and Urban Economics, Elsevier, vol. 61(C), pages 52-72.
    5. Kelejian, Harry H. & Prucha, Ingmar R., 2010. "Specification and estimation of spatial autoregressive models with autoregressive and heteroskedastic disturbances," Journal of Econometrics, Elsevier, vol. 157(1), pages 53-67, July.
    6. Liqian Cai & Arnab Bhattacharjee & Roger Calantone & Taps Maiti, 2019. "Variable Selection with Spatially Autoregressive Errors: A Generalized Moments LASSO Estimator," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 81(1), pages 146-200, September.
    7. Bera Anil K. & Doğan Osman & Taşpınar Süleyman, 2019. "Testing Spatial Dependence in Spatial Models with Endogenous Weights Matrices," Journal of Econometric Methods, De Gruyter, vol. 8(1), pages 1-33, January.
    8. Christopher L. Foote, 2007. "Space and time in macroeconomic panel data: young workers and state-level unemployment revisited," Working Papers 07-10, Federal Reserve Bank of Boston.
    9. Lee, Lung-fei & Yu, Jihai, 2015. "Estimation of fixed effects panel regression models with separable and nonseparable space–time filters," Journal of Econometrics, Elsevier, vol. 184(1), pages 174-192.
    10. Kuti Ayomide Oluwafunmisho & Aderogba Taiwo Adebusuyi & Ezenwa Ndubuisi Johnbosco & Quadri Rasheed Adegboyega, 2023. "Catalysts of Economic Welfare in Africa: A Cross-Sectional Autoregressive Distributed Lag Approach," Acta Universitatis Sapientiae, Economics and Business, Sciendo, vol. 11(1), pages 18-41, October.
    11. Tadao Hoshino, 2018. "Semiparametric Spatial Autoregressive Models With Endogenous Regressors: With an Application to Crime Data," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 36(1), pages 160-172, January.
    12. Huang, Naqun & Yang, Zhenlin, 2021. "Spatial dynamic models with short panels: Evaluating the impact of purchase restrictions on housing prices," Economic Modelling, Elsevier, vol. 103(C).
    13. Wei Shi & Lung-fei Lee, 2018. "The effects of gun control on crimes: a spatial interactive fixed effects approach," Empirical Economics, Springer, vol. 55(1), pages 233-263, August.
    14. Rabovic, Renata & Cizek, Pavel, 2016. "Estimation of Spatial Sample Selection Models : A Partial Maximum Likelihood Approach," Other publications TiSEM 8a4b2e5d-6787-4685-8b9e-1, Tilburg University, School of Economics and Management.
    15. LeSage, James P. & Chih, Yao-Yu & Vance, Colin, 2019. "Markov Chain Monte Carlo estimation of spatial dynamic panel models for large samples," Computational Statistics & Data Analysis, Elsevier, vol. 138(C), pages 107-125.
    16. Liang, Jinwen & Härdle, Wolfgang Karl & Tian, Maozai, 2023. "Imputed quantile tensor regression for near-sited spatial-temporal data," Computational Statistics & Data Analysis, Elsevier, vol. 182(C).
    17. Baltagi, Badi H. & Pirotte, Alain & Yang, Zhenlin, 2020. "Diagnostic Tests for Homoskedasticity in Spatial Cross-Sectional or Panel Models," IZA Discussion Papers 13803, Institute of Labor Economics (IZA).
    18. Jafari-Sadeghi, Vahid & Garcia-Perez, Alexeis & Candelo, Elena & Couturier, Jerome, 2021. "Exploring the impact of digital transformation on technology entrepreneurship and technological market expansion: The role of technology readiness, exploration and exploitation," Journal of Business Research, Elsevier, vol. 124(C), pages 100-111.
    19. Al Mamun, Md & Sohag, Kazi & Hassan, M. Kabir, 2017. "Governance, resources and growth," Economic Modelling, Elsevier, vol. 63(C), pages 238-261.
    20. Parent, Olivier & LeSage, James P., 2011. "A space-time filter for panel data models containing random effects," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 475-490, January.
    21. Cizek, P. & Jacobs, J.P.A.M. & Ligthart, J.E. & Vrijburg, H., 2011. "GMM Estimation of Fixed Effects Dynamic Panel Data Models with Spatial Lag and Spatial Errors (Replaced by CentER DP 2015-003)," Discussion Paper 2011-134, Tilburg University, Center for Economic Research.
    22. Miranda, Karen & Martínez Ibáñez, Oscar & Manjón Antolín, Miguel C., 2018. "A correlated random effects spatial Durbin model," Working Papers 2072/313840, Universitat Rovira i Virgili, Department of Economics.
    23. Danqing Chen & Jianbao Chen & Shuangshuang Li, 2021. "Instrumental Variable Quantile Regression of Spatial Dynamic Durbin Panel Data Model with Fixed Effects," Mathematics, MDPI, vol. 9(24), pages 1-24, December.
    24. Jin, Fei & Lee, Lung-fei & Yu, Jihai, 2020. "First difference estimation of spatial dynamic panel data models with fixed effects," Economics Letters, Elsevier, vol. 189(C).
    25. Ng, Choy Peng & Law, Teik Hua & Jakarni, Fauzan Mohd & Kulanthayan, S., 2018. "Relative improvements in road mobility as compared to improvements in road accessibility and urban growth: A panel data analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 117(C), pages 292-301.
    26. Kazuhiko Hayakawa & M. Hashem Pesaran & L. Vanessa Smith, 2014. "Transformed Maximum Likelihood Estimation of Short Dynamic Panel Data Models with Interactive Effects," CESifo Working Paper Series 4822, CESifo.
    27. Yang, Kai & Lee, Lung-fei, 2021. "Estimation of dynamic panel spatial vector autoregression: Stability and spatial multivariate cointegration," Journal of Econometrics, Elsevier, vol. 221(2), pages 337-367.
    28. Jihai Yu & Lung-Fei Lee, 2012. "Convergence: A Spatial Dynamic Panel Data Approach," Global Journal of Economics (GJE), World Scientific Publishing Co. Pte. Ltd., vol. 1(01), pages 1-36.
    29. Hans DEWACHTER & Romain HOUSSA & Priscilla TOFFANO, 2010. "Spatial propagation of macroeconomic shocks in Europe," Working Papers of Department of Economics, Leuven ces10.12, KU Leuven, Faculty of Economics and Business (FEB), Department of Economics, Leuven.
    30. Eduardo A. Souza-Rodrigues, 2016. "Nonparametric Regression with Common Shocks," Econometrics, MDPI, vol. 4(3), pages 1-17, September.
    31. Baltagi, Badi H. & Bresson, Georges & Chaturvedi, Anoop & Lacroix, Guy, 2022. "Robust Dynamic Space-Time Panel Data Models Using ?-Contamination: An Application to Crop Yields and Climate Change," IZA Discussion Papers 15815, Institute of Labor Economics (IZA).
    32. Francesco Giordano & Marcella Niglio & Maria Lucia Parrella, 2024. "Testing Spatial Dynamic Panel Data Models with Heterogeneous Spatial and Regression Coefficients," Journal of Time Series Analysis, Wiley Blackwell, vol. 45(5), pages 771-799, September.
    33. Parent, Olivier & LeSage, James P., 2012. "Spatial dynamic panel data models with random effects," Regional Science and Urban Economics, Elsevier, vol. 42(4), pages 727-738.
    34. Ana Angulo & F. Trívez, 2010. "The impact of spatial elements on the forecasting of Spanish labour series," Journal of Geographical Systems, Springer, vol. 12(2), pages 155-174, June.
    35. Su, Liangjun & Ura, Takuya & Zhang, Yichong, 2017. "Non-separable Models with High-dimensional Data," Economics and Statistics Working Papers 15-2017, Singapore Management University, School of Economics.
    36. Shi, Wei & Lee, Lung-fei, 2017. "Spatial dynamic panel data models with interactive fixed effects," Journal of Econometrics, Elsevier, vol. 197(2), pages 323-347.
    37. Anil K. Bera & Osman Doğan & Süleyman Taşpınar & Monalisa Sen, 2020. "Specification tests for spatial panel data models," Journal of Spatial Econometrics, Springer, vol. 1(1), pages 1-39, December.
    38. Giulio Cainelli & Sandro Montresor & Giuseppe Vittucci Marzetti, 2014. "Spatial agglomeration and firm exit: a spatial dynamic analysis for Italian provinces," Small Business Economics, Springer, vol. 43(1), pages 213-228, June.
    39. Li, Liyao & Yang, Zhenlin, 2021. "Spatial dynamic panel data models with correlated random effects," Journal of Econometrics, Elsevier, vol. 221(2), pages 424-454.
    40. Wolter, James Lewis, 2016. "Kernel estimation of hazard functions when observations have dependent and common covariates," Journal of Econometrics, Elsevier, vol. 193(1), pages 1-16.
    41. Qian, Junhui & Su, Liangjun, 2016. "Shrinkage estimation of common breaks in panel data models via adaptive group fused Lasso," Journal of Econometrics, Elsevier, vol. 191(1), pages 86-109.
    42. Christis Katsouris, 2023. "Optimal Estimation Methodologies for Panel Data Regression Models," Papers 2311.03471, arXiv.org, revised Nov 2023.
    43. Lung-fei Lee & Jihai Yu, 2012. "QML Estimation of Spatial Dynamic Panel Data Models with Time Varying Spatial Weights Matrices," Spatial Economic Analysis, Taylor & Francis Journals, vol. 7(1), pages 31-74, March.
    44. Nikodem Szumilo & Edyta Laszkiewicz & Franz Fuerst, 2017. "The spatial impact of employment centres on housing markets," Spatial Economic Analysis, Taylor & Francis Journals, vol. 12(4), pages 472-491, October.
    45. Su, Liangjun & Wang, Wuyi & Xu, Xingbai, 2023. "Identifying latent group structures in spatial dynamic panels," Journal of Econometrics, Elsevier, vol. 235(2), pages 1955-1980.
    46. Lee, Lung-fei & Yu, Jihai, 2014. "Efficient GMM estimation of spatial dynamic panel data models with fixed effects," Journal of Econometrics, Elsevier, vol. 180(2), pages 174-197.
    47. Qu, Xi & Lee, Lung-fei & Yu, Jihai, 2017. "QML estimation of spatial dynamic panel data models with endogenous time varying spatial weights matrices," Journal of Econometrics, Elsevier, vol. 197(2), pages 173-201.
    48. Taspinar, Suleyman & Dogan, Osman & Bera, Anil K., 2017. "GMM Gradient Tests for Spatial Dynamic Panel Data Models," MPRA Paper 82830, University Library of Munich, Germany.
    49. Liangjun Su & Xi Qu, 2017. "Specification Test for Spatial Autoregressive Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(4), pages 572-584, October.
    50. Li, Liyao & Yang, Zhenlin, 2020. "Estimation of fixed effects spatial dynamic panel data models with small T and unknown heteroskedasticity," Regional Science and Urban Economics, Elsevier, vol. 81(C).
    51. James Wolter, 2015. "Kernel Estimation Of Hazard Functions When Observations Have Dependent and Common Covariates," Economics Series Working Papers 761, University of Oxford, Department of Economics.
    52. Taşpınar, Süleyman & Doğan, Osman & Bera, Anil K., 2017. "GMM gradient tests for spatial dynamic panel data models," Regional Science and Urban Economics, Elsevier, vol. 65(C), pages 65-88.
    53. Kwok, Hon Ho, 2019. "Identification and estimation of linear social interaction models," Journal of Econometrics, Elsevier, vol. 210(2), pages 434-458.
    54. Bera, Anil K. & Doğan, Osman & Taşpınar, Süleyman, 2018. "Simple tests for endogeneity of spatial weights matrices," Regional Science and Urban Economics, Elsevier, vol. 69(C), pages 130-142.
    55. Olivier Parent, 2012. "A space-time analysis of knowledge production," Journal of Geographical Systems, Springer, vol. 14(1), pages 49-73, January.
    56. Feng, Xingdong & Li, Wenyu & Zhu, Qianqian, 2024. "Estimation and bootstrapping under spatiotemporal models with unobserved heterogeneity," Journal of Econometrics, Elsevier, vol. 238(1).
    57. Badi H. Baltagi & Georges Bresson & Anoop Chaturvedi & Guy Lacroix, 2023. "Robust dynamic space–time panel data models using $$\varepsilon $$ ε -contamination: an application to crop yields and climate change," Empirical Economics, Springer, vol. 64(6), pages 2475-2509, June.
    58. Lee, Lung-fei & Yu, Jihai, 2010. "Some recent developments in spatial panel data models," Regional Science and Urban Economics, Elsevier, vol. 40(5), pages 255-271, September.

  44. Lu, Xun & Su, Liangjun, 2015. "Jackknife model averaging for quantile regressions," Journal of Econometrics, Elsevier, vol. 188(1), pages 40-58.
    See citations under working paper version above.
  45. Qian, Junhui & Su, Liangjun, 2014. "Structural change estimation in time series regressions with endogenous variables," Economics Letters, Elsevier, vol. 125(3), pages 415-421.

    Cited by:

    1. Yoshiyuki Kurachi & Kazuhiro Hiraki & Shinichi Nishioka, 2016. "Does a Higher Frequency of Micro-level Price Changes Matter for Macro Price Stickiness?: Assessing the Impact of Temporary Price Changes," Bank of Japan Working Paper Series 16-E-9, Bank of Japan.
    2. Otilia Boldea & Bettina Drepper & Zhuojiong Gan, 2018. "Change Point Estimation in Panel Data with Time-Varying Individual Effects," Papers 1808.03109, arXiv.org.
    3. Laurent Callot & Johannes Tang Kristensen, 2014. "Vector Autoregressions with Parsimoniously Time Varying Parameters and an Application to Monetary Policy," CREATES Research Papers 2014-41, Department of Economics and Business Economics, Aarhus University.
    4. Otilia Boldea & Adriana Cornea-Madeira & Alastair R. Hall, 2018. "Bootstrapping Structural Change Tests," Papers 1811.04125, arXiv.org.
    5. Maciak, Matúš, 2021. "Quantile LASSO with changepoints in panel data models applied to option pricing," Econometrics and Statistics, Elsevier, vol. 20(C), pages 166-175.
    6. Ma, Chenchen & Tu, Yundong, 2023. "Shrinkage estimation of multiple threshold factor models," Journal of Econometrics, Elsevier, vol. 235(2), pages 1876-1892.
    7. Qian, Junhui & Su, Liangjun, 2016. "Shrinkage estimation of common breaks in panel data models via adaptive group fused Lasso," Journal of Econometrics, Elsevier, vol. 191(1), pages 86-109.

  46. Sainan Jin & Liangjun Su & Aman Ullah, 2014. "Robustify Financial Time Series Forecasting with Bagging," Econometric Reviews, Taylor & Francis Journals, vol. 33(5-6), pages 575-605, August.

    Cited by:

    1. Özen, Kadir & Yıldırım, Dilem, 2021. "Application of bagging in day-ahead electricity price forecasting and factor augmentation," Energy Economics, Elsevier, vol. 103(C).
    2. Manuel Lukas & Eric Hillebrand, 2014. "Bagging Weak Predictors," CREATES Research Papers 2014-01, Department of Economics and Business Economics, Aarhus University.
    3. Lenza, Michele & Moutachaker, Inès & Paredes, Joan, 2023. "Density forecasts of inflation: a quantile regression forest approach," CEPR Discussion Papers 18298, C.E.P.R. Discussion Papers.
    4. Tanja Markovic-Hribernik & Matej Tomec, 2015. "Bad Bank And Other Possible Banks’ Rescuing Models – The Case Of Slovenia," Annals - Economy Series, Constantin Brancusi University, Faculty of Economics, vol. 1, pages 128-141, January.
    5. Kadir Özen & Dilem Yıldırım, 2021. "Application of Bagging in Day-Ahead Electricity Price Forecasting and Factor Augmentation," ERC Working Papers 2101, ERC - Economic Research Center, Middle East Technical University, revised Apr 2021.
    6. Domenico Giannone & Michele Lenza & Giorgio E. Primiceri, 2021. "Economic Predictions With Big Data: The Illusion of Sparsity," Econometrica, Econometric Society, vol. 89(5), pages 2409-2437, September.
    7. Ribeiro, Pinho J., 2017. "Selecting exchange rate fundamentals by bootstrap," International Journal of Forecasting, Elsevier, vol. 33(4), pages 894-914.
    8. Lu, Xun & Su, Liangjun, 2015. "Jackknife model averaging for quantile regressions," Journal of Econometrics, Elsevier, vol. 188(1), pages 40-58.
    9. Hu, Huanling & Wang, Lin & Peng, Lu & Zeng, Yu-Rong, 2020. "Effective energy consumption forecasting using enhanced bagged echo state network," Energy, Elsevier, vol. 193(C).
    10. Dantas, Tiago Mendes & Cyrino Oliveira, Fernando Luiz, 2018. "Improving time series forecasting: An approach combining bootstrap aggregation, clusters and exponential smoothing," International Journal of Forecasting, Elsevier, vol. 34(4), pages 748-761.
    11. Yongmiao Hong & Tae-Hwy Lee & Yuying Sun & Shouyang Wang & Xinyu Zhang, 2017. "Time-varying Model Averaging," Working Papers 202001, University of California at Riverside, Department of Economics.
    12. Pedro Henrique Melo Albuquerque & Yaohao Peng & João Pedro Fontoura da Silva, 2022. "Making the whole greater than the sum of its parts: A literature review of ensemble methods for financial time series forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(8), pages 1701-1724, December.
    13. Luo, Qin & Bu, Jinfeng & Xu, Weiju & Huang, Dengshi, 2023. "Stock market volatility prediction: Evidence from a new bagging model," International Review of Economics & Finance, Elsevier, vol. 87(C), pages 445-456.
    14. Kitova, Olga & Savinova, Victoria, 2021. "Development of an Ensemble of Models for Predicting Socio-Economic Indicators of the Russian Federation using IRT-Theory and Bagging Methods," MPRA Paper 110824, University Library of Munich, Germany.
    15. Haowen Bao & Zongwu Cai & Yuying Sun & Shouyang Wang, 2023. "Penalized Model Averaging for High Dimensional Quantile Regressions," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202302, University of Kansas, Department of Economics, revised Jan 2023.

  47. Deniz Ozabaci & Daniel J. Henderson & Liangjun Su, 2014. "Additive Nonparametric Regression in the Presence of Endogenous Regressors," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 32(4), pages 555-575, October.
    See citations under working paper version above.
  48. Su, Liangjun & White, Halbert, 2014. "Testing conditional independence via empirical likelihood," Journal of Econometrics, Elsevier, vol. 182(1), pages 27-44.
    See citations under working paper version above.
  49. Su, Liangjun & Ullah, Aman, 2013. "A Nonparametric Goodness-Of-Fit-Based Test For Conditional Heteroskedasticity," Econometric Theory, Cambridge University Press, vol. 29(1), pages 187-212, February.

    Cited by:

    1. Fu, Zhonghao & Hong, Yongmiao & Su, Liangjun & Wang, Xia, 2023. "Specification tests for time-varying coefficient models," Journal of Econometrics, Elsevier, vol. 235(2), pages 720-744.
    2. Aman Ullah & Huansha Wang, 2013. "Parametric and Nonparametric Frequentist Model Selection and Model Averaging," Econometrics, MDPI, vol. 1(2), pages 1-23, September.
    3. Liangjun Su & Stefan Hoderlein & Halbert White, 2013. "Testing Monotonicity in Unobservables with Panel Data," Boston College Working Papers in Economics 892, Boston College Department of Economics, revised 01 Feb 2016.
    4. Liangjun Su & Sainan Jin & Yonghui Zhang, 2014. "Specification Test for Panel Data Models with Interactive Fixed Effects," Working Papers 08-2014, Singapore Management University, School of Economics.
    5. Yan Li & Liangjun Su & Yuewu Xu, 2014. "A Combined Approach to the Inference of Conditional Factor Models," Working Papers 10-2014, Singapore Management University, School of Economics.
    6. Hu, Yue & Li, Haiqi & Tan, Falong, 2024. "Testing the parametric form of the conditional variance in regressions based on distance covariance," Computational Statistics & Data Analysis, Elsevier, vol. 189(C).
    7. Lu, Xun & Su, Liangjun, 2015. "Jackknife model averaging for quantile regressions," Journal of Econometrics, Elsevier, vol. 188(1), pages 40-58.
    8. Li, Zhaoyuan & Yao, Jianfeng, 2019. "Testing for heteroscedasticity in high-dimensional regressions," Econometrics and Statistics, Elsevier, vol. 9(C), pages 122-139.
    9. Li, Hongjun & Li, Qi & Liu, Ruixuan, 2016. "Consistent model specification tests based on k-nearest-neighbor estimation method," Journal of Econometrics, Elsevier, vol. 194(1), pages 187-202.

  50. Su, Liangjun & Chen, Qihui, 2013. "Testing Homogeneity In Panel Data Models With Interactive Fixed Effects," Econometric Theory, Cambridge University Press, vol. 29(6), pages 1079-1135, December.

    Cited by:

    1. Xun Lu & Su Liangjun, 2015. "Shrinkage Estimation of Dynamic Panel Data Models with Interactive Fixed Effects," Working Papers 02-2015, Singapore Management University, School of Economics.
    2. Yiren Wang & Peter C. B. Phillips & Liangjun Su, 2023. "Panel Data Models with Time-Varying Latent Group Structures," Cowles Foundation Discussion Papers 2364, Cowles Foundation for Research in Economics, Yale University.
    3. Baglan, Deniz & Ege Yazgan, M. & Yilmazkuday, Hakan, 2016. "Relative price variability and inflation: New evidence," Journal of Macroeconomics, Elsevier, vol. 48(C), pages 263-282.
    4. Levent Kutlu & Robin C. Sickles & Mike G. Tsionas & Emmanuel Mamatzakis, 2022. "Heterogeneous decision-making and market power: an application to Eurozone banks," Empirical Economics, Springer, vol. 63(6), pages 3061-3092, December.
    5. Jean-Baptiste Hasse & Quentin Lajaunie, 2020. "Does the Yield Curve Signal Recessions? New Evidence from an International Panel Data Analysis," AMSE Working Papers 2013, Aix-Marseille School of Economics, France.
    6. Bai, Jushan, 2013. "Likelihood approach to dynamic panel models with interactive effects," MPRA Paper 50267, University Library of Munich, Germany.
    7. Kutlu, Levent & Sickles, Robin & Tsionas, Mike G., 2019. "Heterogeneous Decision-Making and Market Power," Working Papers 19-008, Rice University, Department of Economics.
    8. Miao, Ke & Li, Kunpeng & Su, Liangjun, 2020. "Panel threshold models with interactive fixed effects," Journal of Econometrics, Elsevier, vol. 219(1), pages 137-170.
    9. Hidalgo, Javier & Schafgans, Marcia, 2017. "Inference and testing breaks in large dynamic panels with strong cross sectional dependence," Journal of Econometrics, Elsevier, vol. 196(2), pages 259-274.
    10. Feng Xu & Zekai He, 2020. "Testing slope homogeneity in panel data models with a multifactor error structure," Statistical Papers, Springer, vol. 61(1), pages 201-224, February.
    11. Hansen, Christian & Liao, Yuan, 2016. "The Factor-Lasso and K-Step Bootstrap Approach for Inference in High-Dimensional Economic Applications," MPRA Paper 75313, University Library of Munich, Germany.
    12. Liangjun Su & Sainan Jin & Yonghui Zhang, 2014. "Specification Test for Panel Data Models with Interactive Fixed Effects," Working Papers 08-2014, Singapore Management University, School of Economics.
    13. Sainan Jin & Liangjun Su & Yonghui Zhang, 2014. "Nonparametric Testing for Anomaly Effects in Empirical Asset Pricing Models," Working Papers 09-2014, Singapore Management University, School of Economics.
    14. Liu, Ruiqi & Shang, Zuofeng & Zhang, Yonghui & Zhou, Qiankun, 2020. "Identification and estimation in panel models with overspecified number of groups," Journal of Econometrics, Elsevier, vol. 215(2), pages 574-590.
    15. Freeman, Hugo & Weidner, Martin, 2023. "Linear panel regressions with two-way unobserved heterogeneity," Journal of Econometrics, Elsevier, vol. 237(1).
    16. Andreea Halunga & Chris D. Orme & Takashi Yamagata, 2011. "A Heteroskedasticity Robust Breusch-Pagan Test for Contemporaneous Correlation in Dynamic Panel Data Models," Economics Discussion Paper Series 1118, Economics, The University of Manchester.
    17. Ruiqi Liu & Ben Boukai & Zuofeng Shang, 2019. "Statistical Inference on Partially Linear Panel Model under Unobserved Linearity," Papers 1911.08830, arXiv.org.
    18. Su, Liangjun & Wang, Xia, 2017. "On time-varying factor models: Estimation and testing," Journal of Econometrics, Elsevier, vol. 198(1), pages 84-101.
    19. Miao, Ke & Su, Liangjun & Wang, Wendun, 2020. "Panel threshold regressions with latent group structures," Journal of Econometrics, Elsevier, vol. 214(2), pages 451-481.
    20. Yunus Emre Ergemen & Carlos Velasco, 2019. "Persistence Heterogeneity Testing in Panels with Interactive Fixed Effects," Journal of Time Series Analysis, Wiley Blackwell, vol. 40(4), pages 573-589, July.
    21. Saptorshee Kanto Chakraborty & Massimiliano Mazzanti, 2021. "Revisiting the literature on the dynamic Environmental Kuznets Curves using a latent structure approach," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 38(3), pages 923-941, October.
    22. Wang, Wuyi & Su, Liangjun, 2017. "Identifying Latent Group Structures in Nonlinear Panels," Economics and Statistics Working Papers 19-2017, Singapore Management University, School of Economics.
    23. Juan Romero-Padilla, 2018. "A method for clustering panel data based on parameter homogeneity," Journal of Statistical and Econometric Methods, SCIENPRESS Ltd, vol. 7(3), pages 1-3.
    24. Liangjun Su & Zhentao Shi & Peter C. B. Phillips, 2016. "Identifying Latent Structures in Panel Data," Econometrica, Econometric Society, vol. 84, pages 2215-2264, November.
    25. Olatunji A. Shobande & Simplice A. Asongu, 2021. "Financial Development, Human Capital Development and Climate Change in East and Southern Africa," Research Africa Network Working Papers 21/042, Research Africa Network (RAN).
    26. Kudabayeva Lyazzat & Aktolkin Abubakirova & Omarova Aizhan Igilikovna & Taskinbaikyzy Zhanargul & Saubetova Bibigul Suleimenovna, 2023. "The Relationship between Energy Consumption, Carbon Emissions and Economic Growth in ASEAN-5 Countries," International Journal of Energy Economics and Policy, Econjournals, vol. 13(2), pages 265-271, March.
    27. Mehrabani, Ali, 2023. "Estimation and identification of latent group structures in panel data," Journal of Econometrics, Elsevier, vol. 235(2), pages 1464-1482.
    28. Su, Liangjun & Ju, Gaosheng, 2018. "Identifying latent grouped patterns in panel data models with interactive fixed effects," Journal of Econometrics, Elsevier, vol. 206(2), pages 554-573.
    29. Okui, Ryo & Wang, Wendun, 2021. "Heterogeneous structural breaks in panel data models," Journal of Econometrics, Elsevier, vol. 220(2), pages 447-473.
    30. Ali Mehrabani & Aman Ullah, 2020. "Improved Average Estimation in Seemingly Unrelated Regressions," Econometrics, MDPI, vol. 8(2), pages 1-22, April.
    31. Su, Liangjun & Ura, Takuya & Zhang, Yichong, 2017. "Non-separable Models with High-dimensional Data," Economics and Statistics Working Papers 15-2017, Singapore Management University, School of Economics.
    32. Daniel Borup & Bent Jesper Christensen & Yunus Emre Ergemen, 2019. "Assessing predictive accuracy in panel data models with long-range dependence," CREATES Research Papers 2019-04, Department of Economics and Business Economics, Aarhus University.
    33. Hugo Freeman & Martin Weidner, 2021. "Linear Panel Regressions with Two-Way Unobserved Heterogeneity," Papers 2109.11911, arXiv.org, revised Aug 2022.
    34. Jiti Gao & Fei Liu & Bin Peng & Yayi Yan, 2020. "Binary Response Models for Heterogeneous Panel Data with Interactive Fixed Effects," Papers 2012.03182, arXiv.org, revised Nov 2021.
    35. Lu, Xun & Su, Liangjun, 2023. "Uniform inference in linear panel data models with two-dimensional heterogeneity," Journal of Econometrics, Elsevier, vol. 235(2), pages 694-719.
    36. Su, Liangjun & Zhang, Yonghui & Wei, Jie, 2016. "A practical test for strict exogeneity in linear panel data models with fixed effects," Economics Letters, Elsevier, vol. 147(C), pages 27-31.
    37. Jin, Sainan & Miao, Ke & Su, Liangjun, 2021. "On factor models with random missing: EM estimation, inference, and cross validation," Journal of Econometrics, Elsevier, vol. 222(1), pages 745-777.
    38. Feng, Guohua & Peng, Bin & Su, Liangjun & Yang, Thomas Tao, 2019. "Semi-parametric single-index panel data models with interactive fixed effects: Theory and practice," Journal of Econometrics, Elsevier, vol. 212(2), pages 607-622.
    39. Hong, Shengjie & Su, Liangjun & Jiang, Tao, 2023. "Profile GMM estimation of panel data models with interactive fixed effects," Journal of Econometrics, Elsevier, vol. 235(2), pages 927-948.
    40. Ando, Tomohiro & Bai, Jushan, 2014. "A simple new test for slope homogeneity in panel data models with interactive effects," MPRA Paper 60795, University Library of Munich, Germany.
    41. Mohitosh Kejriwal & Xiaoxiao Li & Evan Totty, 2020. "Multidimensional skills and the returns to schooling: Evidence from an interactive fixed‐effects approach and a linked survey‐administrative data set," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(5), pages 548-566, August.
    42. Ivan Fernandez-Val & Martin Weidner, 2014. "Individual and time effects in nonlinear panel models with large N , T," CeMMAP working papers 32/14, Institute for Fiscal Studies.
    43. Mohitosh Kejriwal & Xiaoxiao Li & Evan Totty, 2019. "Multidemsional Skills and Returns to Schooling: Evidence from an Interactive Fixed Effects Aproach and a Linked Survey-Administrative Dataset," Purdue University Economics Working Papers 1316, Purdue University, Department of Economics.
    44. Qian, Junhui & Su, Liangjun, 2016. "Shrinkage estimation of common breaks in panel data models via adaptive group fused Lasso," Journal of Econometrics, Elsevier, vol. 191(1), pages 86-109.
    45. Yang, Qing & Zhang, Yi, 2022. "Change-point detection for the link function in a single-index model," Statistics & Probability Letters, Elsevier, vol. 186(C).
    46. Christis Katsouris, 2023. "Optimal Estimation Methodologies for Panel Data Regression Models," Papers 2311.03471, arXiv.org, revised Nov 2023.
    47. Bai, Jushan & Liao, Yuan, 2017. "Inferences in panel data with interactive effects using large covariance matrices," Journal of Econometrics, Elsevier, vol. 200(1), pages 59-78.
    48. Hugo Freeman & Martin Weidner, 2021. "Linear panel regressions with two-way unobserved heterogeneity," CeMMAP working papers CWP39/21, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    49. Su, Liangjun & Wang, Wuyi & Xu, Xingbai, 2023. "Identifying latent group structures in spatial dynamic panels," Journal of Econometrics, Elsevier, vol. 235(2), pages 1955-1980.
    50. Yiren Wang & Liangjun Su & Yichong Zhang, 2022. "Low-rank Panel Quantile Regression: Estimation and Inference," Papers 2210.11062, arXiv.org.
    51. Guowei Cui & Kazuhiko Hayakawa & Shuichi Nagata & Takashi Yamagata, 2018. "A robust approach to heteroskedasticity, error serial correlation and slope heterogeneity for large linear panel data models with interactive effects," ISER Discussion Paper 1037r, Institute of Social and Economic Research, Osaka University, revised Jun 2019.
    52. Likai Chen & Georg Keilbar & Liangjun Su & Weining Wang, 2023. "Inference on many jumps in nonparametric panel regression models," Papers 2312.01162, arXiv.org, revised Jan 2025.
    53. Hidalgo, Javier & Schafgans, Marcia, 2017. "Inference and testing breaks in large dynamic panels with strong cross sectional dependence," LSE Research Online Documents on Economics 68839, London School of Economics and Political Science, LSE Library.
    54. Chen, Bin & Huang, Liquan, 2018. "Nonparametric testing for smooth structural changes in panel data models," Journal of Econometrics, Elsevier, vol. 202(2), pages 245-267.

  51. Su, Liangjun & Lu, Xun, 2013. "Nonparametric dynamic panel data models: Kernel estimation and specification testing," Journal of Econometrics, Elsevier, vol. 176(2), pages 112-133.

    Cited by:

    1. Wei, Honglei & Zhang, Hongfan & Jiang, Hui & Huang, Lei, 2022. "On the semi-varying coefficient dynamic panel data model with autocorrelated errors," Computational Statistics & Data Analysis, Elsevier, vol. 173(C).
    2. Liangjun Su & Sainan Jin & Yonghui Zhang, 2014. "Specification Test for Panel Data Models with Interactive Fixed Effects," Working Papers 08-2014, Singapore Management University, School of Economics.
    3. Sainan Jin & Liangjun Su & Yonghui Zhang, 2014. "Nonparametric Testing for Anomaly Effects in Empirical Asset Pricing Models," Working Papers 09-2014, Singapore Management University, School of Economics.
    4. Hoshino, Tadao, 2022. "Sieve IV estimation of cross-sectional interaction models with nonparametric endogenous effect," Journal of Econometrics, Elsevier, vol. 229(2), pages 263-275.
    5. Rodriguez-Poo, Juan M. & Soberón, Alexandra, 2015. "Nonparametric estimation of fixed effects panel data varying coefficient models," Journal of Multivariate Analysis, Elsevier, vol. 133(C), pages 95-122.
    6. Yashar Tarverdi, 2018. "Aspects of Governance and $$\hbox {CO}_2$$ CO 2 Emissions: A Non-linear Panel Data Analysis," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 69(1), pages 167-194, January.
    7. Christopher F. Parmeter & Jeffrey S. Racine, 2018. "Nonparametric Estimation and Inference for Panel Data Models," Department of Economics Working Papers 2018-02, McMaster University.
    8. Li, Cong & Liang, Zhongwen, 2015. "Asymptotics for nonparametric and semiparametric fixed effects panel models," Journal of Econometrics, Elsevier, vol. 185(2), pages 420-434.
    9. Green, Carl & Long, Wei & Hsiao, Cheng, 2015. "Testing error serial correlation in fixed effects nonparametric panel data models," Journal of Econometrics, Elsevier, vol. 188(2), pages 466-473.
    10. Juan Rodriguez-Poo & Alexandra Soberón, 2015. "Differencing techniques in semi-parametric panel data varying coefficient models with fixed effects: a Monte Carlo study," Computational Statistics, Springer, vol. 30(3), pages 885-906, September.
    11. Li, Hongjun & Li, Qi & Liu, Ruixuan, 2016. "Consistent model specification tests based on k-nearest-neighbor estimation method," Journal of Econometrics, Elsevier, vol. 194(1), pages 187-202.
    12. Chu, Chi-Yang & Henderson, Daniel J. & Parmeter, Christopher F., 2017. "On discrete Epanechnikov kernel functions," Computational Statistics & Data Analysis, Elsevier, vol. 116(C), pages 79-105.

  52. Liangjun Su & Martin Spindler, 2013. "Nonparametric Testing for Asymmetric Information," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 31(2), pages 208-225, April.

    Cited by:

    1. Georges Dionne, 2012. "The Empirical Measure of Information Problems with Emphasis on Insurance Fraud and Dynamic Data," Cahiers de recherche 1233, CIRPEE.
    2. Polanski, Arnold & Stoja, Evarist & Chiu, Ching-Wai (Jeremy), 2019. "Tail risk interdependence," Bank of England working papers 815, Bank of England.
    3. Helmi Jedidi & Georges Dionne, 2024. "Nonparametric Testing for Information Asymmetry in the Mortgage Servicing Market," Risks, MDPI, vol. 12(12), pages 1-40, November.
    4. Choi Yun Jeong & Chen Joe & Sawada Yasuyuki, 2015. "Life Insurance and Suicide: Asymmetric Information Revisited," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 15(3), pages 1127-1149, July.
    5. Spindler, Martin & Winter, Joachim & Hagmayer, Steffen, 2012. "Asymmetric Information in the Market for Automobile Insurance: Evidence from Germany," MEA discussion paper series 201208, Munich Center for the Economics of Aging (MEA) at the Max Planck Institute for Social Law and Social Policy.
    6. Su, Liangjun & White, Halbert, 2014. "Testing conditional independence via empirical likelihood," Journal of Econometrics, Elsevier, vol. 182(1), pages 27-44.
    7. Dionne, Georges & Michaud, Pierre-Carl & Pinquet, Jean, 2012. "A review of recent theoretical and empirical analyses of asymmetric information in road safety and automobile insurance," Working Papers 12-1, HEC Montreal, Canada Research Chair in Risk Management.
    8. Hao Zheng & Yi Yao & Yinglu Deng & Feng Gao, 2022. "Information asymmetry, ex ante moral hazard, and uninsurable risk in liability coverage: Evidence from China's automobile insurance market," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 89(1), pages 131-160, March.
    9. Polanski, Arnold & Stoja, Evarist, 2015. "Extreme risk interdependence," Bank of England working papers 563, Bank of England.
    10. Xiaoqi Zhang & Yi Chen & Yi Yao, 2021. "Dynamic information asymmetry in micro health insurance: implications for sustainability," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 46(3), pages 468-507, July.
    11. Spindler, Martin, 2013. "“They do know what they are doing... at least most of them.†Asymmetric Information in the (private) Disability Insurance," MEA discussion paper series 201209, Munich Center for the Economics of Aging (MEA) at the Max Planck Institute for Social Law and Social Policy.
    12. David Rowell & Son Nghiem & Luke B Connelly, 2017. "Two Tests for Ex Ante Moral Hazard in a Market for Automobile Insurance," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 84(4), pages 1103-1126, December.
    13. Alois S. Mlambo, 2017. "From an Industrial Powerhouse to a Nation of Vendors: Over Two Decades of Economic Decline and Deindustrialization in Zimbabwe 1990–2015," Journal of Developing Societies, , vol. 33(1), pages 99-125, March.
    14. Polanski, Arnold & Stoja, Evarist, 2017. "Forecasting multidimensional tail risk at short and long horizons," International Journal of Forecasting, Elsevier, vol. 33(4), pages 958-969.
    15. Polanski, Arnold & Stoja, Evarist, 2016. "Extreme risk interdependence," ESRB Working Paper Series 12, European Systemic Risk Board.
    16. Spindler, M., 2014. "“They do know what they are doing ... at least most of them.†Asymmetric Information in the (private) Disability Insurance," Health, Econometrics and Data Group (HEDG) Working Papers 14/16, HEDG, c/o Department of Economics, University of York.
    17. Arnold Polanski & Evarist Stoja & Ching‐Wai (Jeremy) Chiu, 2021. "Tail risk interdependence," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(4), pages 5499-5511, October.
    18. Polanski, Arnold & Stoja, Evarist, 2017. "Forecasting multidimensional tail risk at short and long horizons," Bank of England working papers 660, Bank of England.
    19. Karl Ove Aarbu, 2017. "Asymmetric Information in the Home Insurance Market," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 84(1), pages 35-72, March.
    20. Feng Gao & Michael R. Powers & Jun Wang, 2017. "Decomposing Asymmetric Information in China's Automobile Insurance Market," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 84(4), pages 1269-1293, December.

  53. Liangjun Su & Aman Ullah & Yun Wang, 2013. "Nonparametric regression estimation with general parametric error covariance: a more efficient two-step estimator," Empirical Economics, Springer, vol. 45(2), pages 1009-1024, October.

    Cited by:

    1. Artem Prokhorov & Kien C. Tran & Mike G. Tsionas, 2021. "Estimation of semi- and nonparametric stochastic frontier models with endogenous regressors," Empirical Economics, Springer, vol. 60(6), pages 3043-3068, June.
    2. Sun, Yiguo & Malikov, Emir, 2018. "Estimation and inference in functional-coefficient spatial autoregressive panel data models with fixed effects," Journal of Econometrics, Elsevier, vol. 203(2), pages 359-378.
    3. Aman Ullah & Tao Wang & Weixin Yao, 2021. "Modal regression for fixed effects panel data," Empirical Economics, Springer, vol. 60(1), pages 261-308, January.
    4. Tae-Hwy Lee & Bai Huang & Aman Ullah, 2018. "Combined Estimation of Semiparametric Panel Data Models," Working Papers 201915, University of California at Riverside, Department of Economics.
    5. Shujie Ma & Jeffrey S. Racine & Aman Ullah, 2015. "Nonparametric Regression-Spline Random Effects Models," Department of Economics Working Papers 2015-10, McMaster University.
    6. Syed F. Mahmud & Murat Tiniç, 2018. "Herding in Chinese stock markets: a nonparametric approach," Empirical Economics, Springer, vol. 55(2), pages 679-711, September.

  54. Sainan Jin & Liangjun Su, 2013. "A Nonparametric Poolability Test for Panel Data Models with Cross Section Dependence," Econometric Reviews, Taylor & Francis Journals, vol. 32(4), pages 469-512, December.

    Cited by:

    1. Xun Lu & Su Liangjun, 2015. "Shrinkage Estimation of Dynamic Panel Data Models with Interactive Fixed Effects," Working Papers 02-2015, Singapore Management University, School of Economics.
    2. Liangjun Su & Sainan Jin & Yonghui Zhang, 2014. "Specification Test for Panel Data Models with Interactive Fixed Effects," Working Papers 08-2014, Singapore Management University, School of Economics.
    3. Christopher F. Parmeter & Jeffrey S. Racine, 2018. "Nonparametric Estimation and Inference for Panel Data Models," Department of Economics Working Papers 2018-02, McMaster University.
    4. Zongwu Cai & Ying Fang & Qiuhua Xu, 2020. "Testing Capital Asset Pricing Models using Functional-Coefficient Panel Data Models with Cross-Sectional Dependence," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202009, University of Kansas, Department of Economics, revised Jul 2020.
    5. Nibbering, D. & Paap, R., 2019. "Panel Forecasting with Asymmetric Grouping," Econometric Institute Research Papers EI-2019-30, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    6. Su, Liangjun & Ju, Gaosheng, 2018. "Identifying latent grouped patterns in panel data models with interactive fixed effects," Journal of Econometrics, Elsevier, vol. 206(2), pages 554-573.
    7. Wolter, James Lewis, 2016. "Kernel estimation of hazard functions when observations have dependent and common covariates," Journal of Econometrics, Elsevier, vol. 193(1), pages 1-16.
    8. Didier Nibbering & Richard Paap, 2024. "Forecasting carbon emissions using asymmetric grouping," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(6), pages 2228-2256, September.
    9. Cai, Zongwu & Fang, Ying & Xu, Qiuhua, 2022. "Testing capital asset pricing models using functional-coefficient panel data models with cross-sectional dependence," Journal of Econometrics, Elsevier, vol. 227(1), pages 114-133.
    10. James Wolter, 2015. "Kernel Estimation Of Hazard Functions When Observations Have Dependent and Common Covariates," Economics Series Working Papers 761, University of Oxford, Department of Economics.
    11. Chen, Bin & Huang, Liquan, 2018. "Nonparametric testing for smooth structural changes in panel data models," Journal of Econometrics, Elsevier, vol. 202(2), pages 245-267.

  55. Liangjun Su & Irina Murtazashvili & Aman Ullah, 2013. "Local Linear GMM Estimation of Functional Coefficient IV Models With an Application to Estimating the Rate of Return to Schooling," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 31(2), pages 184-207, April.

    Cited by:

    1. Zhang, Hong-Fan, 2021. "Iterative GMM for partially linear single-index models with partly endogenous regressors," Computational Statistics & Data Analysis, Elsevier, vol. 156(C).
    2. S. Centorrino & J. S. Racine, 2016. "Semiparametric Varying Coefficient Models with Endogenous Covariates," Department of Economics Working Papers 2016-02, McMaster University.
    3. Tae-Hwy Lee & Shahnaz Parsaeian & Aman Ullah, 2022. "Forecasting under Structural Breaks Using Improved Weighted Estimation," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202212, University of Kansas, Department of Economics.
    4. Tadao Hoshino, 2018. "Semiparametric Spatial Autoregressive Models With Endogenous Regressors: With an Application to Crime Data," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 36(1), pages 160-172, January.
    5. Cai, Zongwu & Fang, Ying & Lin, Ming & Su, Jia, 2018. "Inferences for a Partially Varying Coefficient Model With Endogenous Regressors," IRTG 1792 Discussion Papers 2018-047, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    6. Feng Yao & Junsen Zhang, 2015. "Efficient kernel-based semiparametric IV estimation with an application to resolving a puzzle on the estimates of the return to schooling," Empirical Economics, Springer, vol. 48(1), pages 253-281, February.
    7. Yan Li & Liangjun Su & Yuewu Xu, 2014. "A Combined Approach to the Inference of Conditional Factor Models," Working Papers 10-2014, Singapore Management University, School of Economics.
    8. Su, Liangjun & Hoshino, Tadao, 2016. "Sieve instrumental variable quantile regression estimation of functional coefficient models," Journal of Econometrics, Elsevier, vol. 191(1), pages 231-254.
    9. Tae-Hwy Lee & Bai Huang & Aman Ullah, 2018. "Combined Estimation of Semiparametric Panel Data Models," Working Papers 201915, University of California at Riverside, Department of Economics.
    10. Pan Zhao & Yifan Cui, 2023. "A Semiparametric Instrumented Difference-in-Differences Approach to Policy Learning," Papers 2310.09545, arXiv.org.
    11. Shengjie Hong & Yu-Chin Hsu & Yuanyuan Wan, 2023. "Subvector inference for Varying Coefficient Models with Partial Identification," Working Papers tecipa-756, University of Toronto, Department of Economics.
    12. Koo, Chao, 2018. "Essays on functional coefficient models," Other publications TiSEM ba87b8a5-3c55-40ec-967d-9, Tilburg University, School of Economics and Management.
    13. Lu, Xun & Su, Liangjun, 2015. "Jackknife model averaging for quantile regressions," Journal of Econometrics, Elsevier, vol. 188(1), pages 40-58.
    14. Irina Murtazashvili & Di Liu & Artem Prokhorov, 2015. "Two‐sample nonparametric estimation of intergenerational income mobility in the United States and Sweden," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 48(5), pages 1733-1761, December.
    15. Aman Ullah & Tao Wang & Weixin Yao, 2022. "Semiparametric Partially Linear Varying Coefficient Modal Regression," Working Papers 202215, University of California at Riverside, Department of Economics, revised Jun 2022.
    16. Athey, Susan & Tibshirani, Julie & Wager, Stefan, 2017. "Generalized Random Forests," Research Papers 3575, Stanford University, Graduate School of Business.
    17. Stefan Sperlich, 2014. "On the choice of regularization parameters in specification testing: a critical discussion," Empirical Economics, Springer, vol. 47(2), pages 427-450, September.

  56. Yonghui Zhang & Liangjun Su & Peter C. B. Phillips, 2012. "Testing for common trends in semi‐parametric panel data models with fixed effects," Econometrics Journal, Royal Economic Society, vol. 15(1), pages 56-100, February.
    See citations under working paper version above.
  57. Su, Liangjun, 2012. "Semiparametric GMM estimation of spatial autoregressive models," Journal of Econometrics, Elsevier, vol. 167(2), pages 543-560.

    Cited by:

    1. Jianbao Chen & Suli Cheng, 2021. "GMM Estimation of a Partially Linear Additive Spatial Error Model," Mathematics, MDPI, vol. 9(6), pages 1-28, March.
    2. Tizheng Li & Xiaojuan Kang, 2022. "Variable selection of higher-order partially linear spatial autoregressive model with a diverging number of parameters," Statistical Papers, Springer, vol. 63(1), pages 243-285, February.
    3. Qiong Pang & Xijian Hu, 2024. "INLA Estimation of Semi-Variable Coefficient Spatial Lag Model—Analysis of PM2.5 Influencing Factors in the Context of Urbanization in China," Mathematics, MDPI, vol. 12(7), pages 1-24, March.
    4. Alberto Gude & Inmaculada Álvarez & Luis Orea, 2018. "Heterogeneous spillovers among Spanish provinces: a generalized spatial stochastic frontier model," Journal of Productivity Analysis, Springer, vol. 50(3), pages 155-173, December.
    5. Yang, Zhenlin, 2015. "A general method for third-order bias and variance corrections on a nonlinear estimator," Journal of Econometrics, Elsevier, vol. 186(1), pages 178-200.
    6. Xuan Liang & Jiti Gao & Xiaodong Gong, 2019. "Time-Varying Coefficient Spatial Autoregressive Panel Data Model with Fixed Effects," Monash Econometrics and Business Statistics Working Papers 26/19, Monash University, Department of Econometrics and Business Statistics.
    7. Tadao Hoshino, 2018. "Semiparametric Spatial Autoregressive Models With Endogenous Regressors: With an Application to Crime Data," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 36(1), pages 160-172, January.
    8. Malikov, Emir & Sun, Yiguo, 2017. "Semiparametric estimation and testing of smooth coefficient spatial autoregressive models," Journal of Econometrics, Elsevier, vol. 199(1), pages 12-34.
    9. Su, Liangjun & Yang, Zhenlin, 2015. "QML estimation of dynamic panel data models with spatial errors," Journal of Econometrics, Elsevier, vol. 185(1), pages 230-258.
    10. Luo, Guowang & Wu, Mixia & Pang, Zhen, 2022. "Estimation of spatial autoregressive models with covariate measurement errors," Journal of Multivariate Analysis, Elsevier, vol. 192(C).
    11. Sun, Yiguo & Malikov, Emir, 2018. "Estimation and inference in functional-coefficient spatial autoregressive panel data models with fixed effects," Journal of Econometrics, Elsevier, vol. 203(2), pages 359-378.
    12. Sanying Feng & Tiejun Tong & Sung Nok Chiu, 2023. "Statistical Inference for Partially Linear Varying Coefficient Spatial Autoregressive Panel Data Model," Mathematics, MDPI, vol. 11(22), pages 1-19, November.
    13. Yuxue Sheng & James Paul LeSage, 2021. "Interpreting spatial regression models with multiplicative interaction explanatory variables," Journal of Geographical Systems, Springer, vol. 23(3), pages 333-360, July.
    14. Zhang Yuanqing, 2014. "Estimation of Partially Specified Spatial Autoregressive Model," Journal of Systems Science and Information, De Gruyter, vol. 2(3), pages 226-235, June.
    15. Roberto Basile, 2014. "Regional productivity growth in Europe: a Schumpeterian perspective," Gecomplexity Discussion Paper Series 1, Action IS1104 "The EU in the new complex geography of economic systems: models, tools and policy evaluation", revised Nov 2014.
    16. Fang Lu & Jing Yang & Xuewen Lu, 2022. "One-step oracle procedure for semi-parametric spatial autoregressive model and its empirical application to Boston housing price data," Empirical Economics, Springer, vol. 62(6), pages 2645-2671, June.
    17. Wei, Chuanhua & Guo, Shuang & Zhai, Shufen, 2017. "Statistical inference of partially linear varying coefficient spatial autoregressive models," Economic Modelling, Elsevier, vol. 64(C), pages 553-559.
    18. Xuan, Liang & Jiti, Gao & xiaodong, Gong, 2021. "Semiparametric Spatial Autoregressive Panel Data Model with Fixed Effects and Time-Varying Coefficients," MPRA Paper 108497, University Library of Munich, Germany, revised 30 May 2021.
    19. Sun, Yiguo, 2016. "Functional-coefficient spatial autoregressive models with nonparametric spatial weights," Journal of Econometrics, Elsevier, vol. 195(1), pages 134-153.
    20. Zhengyu Zhang, 2013. "A Pairwise Difference Estimator for Partially Linear Spatial Autoregressive Models," Spatial Economic Analysis, Taylor & Francis Journals, vol. 8(2), pages 176-194, June.
    21. Huang, Danyang & Wang, Feifei & Zhu, Xuening & Wang, Hansheng, 2020. "Two-mode network autoregressive model for large-scale networks," Journal of Econometrics, Elsevier, vol. 216(1), pages 203-219.
    22. Kien C. Tran & Mike G. Tsionas, 2023. "Semiparametric estimation of a spatial autoregressive nonparametric stochastic frontier model," Journal of Spatial Econometrics, Springer, vol. 4(1), pages 1-28, December.
    23. Kunming Li & Liting Fang & Tao Lu, 2019. "Bayesian panel smooth transition model with spatial correlation," PLOS ONE, Public Library of Science, vol. 14(3), pages 1-12, March.
    24. Hou, Zhezhi & Zhao, Shunan & Kumbhakar, Subal C., 2023. "The GMM estimation of semiparametric spatial stochastic frontier models," European Journal of Operational Research, Elsevier, vol. 305(3), pages 1450-1464.
    25. Hongjie Wei & Yan Sun, 2017. "Heteroskedasticity-robust semi-parametric GMM estimation of a spatial model with space-varying coefficients," Spatial Economic Analysis, Taylor & Francis Journals, vol. 12(1), pages 113-128, January.
    26. Basile, Roberto & Durbán, María & Mínguez, Román & María Montero, Jose & Mur, Jesús, 2014. "Modeling regional economic dynamics: Spatial dependence, spatial heterogeneity and nonlinearities," Journal of Economic Dynamics and Control, Elsevier, vol. 48(C), pages 229-245.
    27. Sun, Yan, 2017. "Estimation of single-index model with spatial interaction," Regional Science and Urban Economics, Elsevier, vol. 62(C), pages 36-45.
    28. Yan-Yong Zhao & Ling-Ling Ge & Yuan Liu, 2025. "Estimation of panel data partially linear time-varying coefficient models with cross-sectional spatial autoregressive errors," Statistical Papers, Springer, vol. 66(1), pages 1-37, February.
    29. Gao, Zhaoxing & Ma, Yingying & Wang, Hansheng & Yao, Qiwei, 2019. "Banded spatio-temporal autoregressions," Journal of Econometrics, Elsevier, vol. 208(1), pages 211-230.
    30. Mustafa Koroglu & Yiguo Sun, 2016. "Functional-Coefficient Spatial Durbin Models with Nonparametric Spatial Weights: An Application to Economic Growth," Econometrics, MDPI, vol. 4(1), pages 1-16, February.
    31. Wolter, James Lewis, 2016. "Kernel estimation of hazard functions when observations have dependent and common covariates," Journal of Econometrics, Elsevier, vol. 193(1), pages 1-16.
    32. Cheng, Suli & Chen, Jianbao, 2023. "GMM estimation of partially linear additive spatial autoregressive model," Computational Statistics & Data Analysis, Elsevier, vol. 182(C).
    33. DUo Qin & Yimeng Liu, 2013. "Modelling Scale Effect in Crosssection Data:The Case of Hedonic Price Regression," Working Papers 184, Department of Economics, SOAS University of London, UK.
    34. Suli Cheng & Jianbao Chen, 2021. "Estimation of partially linear single-index spatial autoregressive model," Statistical Papers, Springer, vol. 62(1), pages 495-531, February.
    35. Tiziano Arduini & Eleonora Patacchini & Edoardo Rainone, 2015. "Parametric and Semiparametric IV Estimation of Network Models with Selectivity," EIEF Working Papers Series 1509, Einaudi Institute for Economics and Finance (EIEF), revised Oct 2015.
    36. Bing Su & Fukang Zhu & Ke Zhu, 2023. "Statistical inference for the logarithmic spatial heteroskedasticity model with exogenous variables," Papers 2301.06658, arXiv.org.
    37. Zhang, Yuanqing & Sun, Yanqing, 2015. "Estimation of partially specified dynamic spatial panel data models with fixed-effects," Regional Science and Urban Economics, Elsevier, vol. 51(C), pages 37-46.
    38. Guo Shuang & Wei Chuanhua, 2015. "Testing for Spatial Lag Effects in Varying Coefficient Spatial Autoregressive Models," Journal of Systems Science and Information, De Gruyter, vol. 3(6), pages 561-567, December.
    39. Bogui Li & Jianbao Chen & Shuangshuang Li, 2023. "Estimation of Fixed Effects Partially Linear Varying Coefficient Panel Data Regression Model with Nonseparable Space-Time Filters," Mathematics, MDPI, vol. 11(6), pages 1-24, March.
    40. Liu, Yu & Zhuang, Xiaoyang, 2023. "Shrinkage estimation of semi-parametric spatial autoregressive panel data model with fixed effects," Statistics & Probability Letters, Elsevier, vol. 194(C).
    41. Yunquan Song & Hang Su & Minmin Zhan, 2024. "Local Walsh-average-based Estimation and Variable Selection for Spatial Single-index Autoregressive Models," Networks and Spatial Economics, Springer, vol. 24(2), pages 313-339, June.
    42. Liangjun Su & Xi Qu, 2017. "Specification Test for Spatial Autoregressive Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(4), pages 572-584, October.
    43. James Wolter, 2015. "Kernel Estimation Of Hazard Functions When Observations Have Dependent and Common Covariates," Economics Series Working Papers 761, University of Oxford, Department of Economics.
    44. Ma, Yingying & Guo, Shaojun & Wang, Hansheng, 2023. "Sparse spatio-temporal autoregressions by profiling and bagging," Journal of Econometrics, Elsevier, vol. 232(1), pages 132-147.
    45. Kwok, Hon Ho, 2019. "Identification and estimation of linear social interaction models," Journal of Econometrics, Elsevier, vol. 210(2), pages 434-458.

  58. Su, Liangjun & Jin, Sainan, 2012. "Sieve estimation of panel data models with cross section dependence," Journal of Econometrics, Elsevier, vol. 169(1), pages 34-47.

    Cited by:

    1. Dong, Chaohua & Linton, Oliver, 2018. "Additive nonparametric models with time variable and both stationary and nonstationary regressors," Journal of Econometrics, Elsevier, vol. 207(1), pages 212-236.
    2. Xun Lu & Su Liangjun, 2015. "Shrinkage Estimation of Dynamic Panel Data Models with Interactive Fixed Effects," Working Papers 02-2015, Singapore Management University, School of Economics.
    3. Chaohua Dong & Jiti Gao & Bin Peng, 2018. "Series estimation for single-index models under constraints," Monash Econometrics and Business Statistics Working Papers 5/18, Monash University, Department of Econometrics and Business Statistics.
    4. Gioldasis, Georgios & Musolesi, Antonio & Simioni, Michel, 2023. "Interactive R&D spillovers: An estimation strategy based on forecasting-driven model selection," International Journal of Forecasting, Elsevier, vol. 39(1), pages 144-169.
    5. De Vos, Ignace & Everaert, Gerdie & Sarafidis, Vasilis, 2021. "A method for evaluating the rank condition for CCE estimators," MPRA Paper 112305, University Library of Munich, Germany, revised 09 Mar 2022.
    6. Gao, Jiti & Linton, Oliver & Peng, Bin, 2020. "Inference On A Semiparametric Model With Global Power Law And Local Nonparametric Trends," Econometric Theory, Cambridge University Press, vol. 36(2), pages 223-249, April.
    7. Jörg Breitung & Philipp Hansen, 2021. "Alternative estimation approaches for the factor augmented panel data model with small T," Empirical Economics, Springer, vol. 60(1), pages 327-351, January.
    8. Jia Chen & Jiti Gao & Degui Li, 2011. "Semiparametric Trending Panel Data Models with Cross-Sectional Dependence," Monash Econometrics and Business Statistics Working Papers 15/11, Monash University, Department of Econometrics and Business Statistics.
    9. Georgios Gioldasis & Antonio Musolesi & Michel Simioni, 2020. "Model uncertainty, nonlinearities and out-of-sample comparison: evidence from international technology diffusion," Working Papers hal-02790523, HAL.
    10. Liangjun Su & Sainan Jin & Yonghui Zhang, 2014. "Specification Test for Panel Data Models with Interactive Fixed Effects," Working Papers 08-2014, Singapore Management University, School of Economics.
    11. Su, Liangjun & Yang, Zhenlin, 2015. "QML estimation of dynamic panel data models with spatial errors," Journal of Econometrics, Elsevier, vol. 185(1), pages 230-258.
    12. Bin Peng & Giovanni Forchini, 2012. "Consistent Estimation of Panel Data Models with a Multi-factor Error Structure," School of Economics Discussion Papers 0112, School of Economics, University of Surrey.
    13. Feng, Guohua & Gao, Jiti & Peng, Bin & Zhang, Xiaohui, 2017. "A varying-coefficient panel data model with fixed effects: Theory and an application to US commercial banks," Journal of Econometrics, Elsevier, vol. 196(1), pages 68-82.
    14. Bing Jiang & Yanrong Yang & Jiti Gao & Cheng Hsiao, 2017. "Recursive estimation in large panel data models: Theory and practice," Monash Econometrics and Business Statistics Working Papers 5/17, Monash University, Department of Econometrics and Business Statistics.
    15. Ruiqi Liu & Ben Boukai & Zuofeng Shang, 2019. "Statistical Inference on Partially Linear Panel Model under Unobserved Linearity," Papers 1911.08830, arXiv.org.
    16. Miao, Ke & Su, Liangjun & Wang, Wendun, 2020. "Panel threshold regressions with latent group structures," Journal of Econometrics, Elsevier, vol. 214(2), pages 451-481.
    17. Katharina Hauck & Xiaohui Zhang, 2016. "Heterogeneity in the Effect of Common Shocks on Healthcare Expenditure Growth," Health Economics, John Wiley & Sons, Ltd., vol. 25(9), pages 1090-1103, September.
    18. Qingliang Fan & Zijian Guo & Ziwei Mei & Cun-Hui Zhang, 2023. "Inference for Nonlinear Endogenous Treatment Effects Accounting for High-Dimensional Covariate Complexity," Papers 2310.08063, arXiv.org, revised Jun 2024.
    19. Ye, Xiaoqing & Xu, Juan & Wu, Xiangjun, 2018. "Estimation of an unbalanced panel data Tobit model with interactive effects," Journal of choice modelling, Elsevier, vol. 28(C), pages 108-123.
    20. Chaohua Dong & Jiti Gao & Bin Peng, 2016. "Another Look at Single-Index Models Based on Series Estimation," Monash Econometrics and Business Statistics Working Papers 19/16, Monash University, Department of Econometrics and Business Statistics.
    21. Chaohua Dong & Jiti Gao & Bin Peng, 2015. "Partially Linear Panel Data Models with Cross-Sectional Dependence and Nonstationarity," Monash Econometrics and Business Statistics Working Papers 7/15, Monash University, Department of Econometrics and Business Statistics.
    22. Massimiliano Mazzanti & Antonio Musolesi, 2020. "A Semiparametric Analysis of Green Inventions and Environmental Policies," SEEDS Working Papers 0920, SEEDS, Sustainability Environmental Economics and Dynamics Studies, revised Jun 2020.
    23. Zongwu Cai & Ying Fang & Qiuhua Xu, 2020. "Testing Capital Asset Pricing Models using Functional-Coefficient Panel Data Models with Cross-Sectional Dependence," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202009, University of Kansas, Department of Economics, revised Jul 2020.
    24. Román Mínguez & María L. & Roberto Basile, 2016. "Spatio-Temporal Autoregressive Semiparametric Model for the analysis of regional economic data," Working Papers LuissLab 16126, Dipartimento di Economia e Finanza, LUISS Guido Carli.
    25. Massimiliano Mazzanti & Antonio Musolesi, 2020. "Modeling Green Knowledge Production and Environmental Policies with Semiparametric Panel Data Regression models," SEEDS Working Papers 1420, SEEDS, Sustainability Environmental Economics and Dynamics Studies, revised Sep 2020.
    26. Georgios Gioldasis & Antonio Musolesi & Michel Simioni, 2021. "Interactive R&D Spillovers: An estimation strategy based on forecasting-driven model selection," SEEDS Working Papers 0621, SEEDS, Sustainability Environmental Economics and Dynamics Studies, revised Jun 2021.
    27. Su, Liangjun & Ju, Gaosheng, 2018. "Identifying latent grouped patterns in panel data models with interactive fixed effects," Journal of Econometrics, Elsevier, vol. 206(2), pages 554-573.
    28. Eduardo A. Souza-Rodrigues, 2016. "Nonparametric Regression with Common Shocks," Econometrics, MDPI, vol. 4(3), pages 1-17, September.
    29. Georgios Gioldasis & Antonio Musolesi & Michel Simioni, 2019. "Nonparametric estimation of R&D international spillovers," Post-Print hal-02789474, HAL.
    30. Feng, Guohua & Gao, Jiti & Peng, Bin, 2022. "An integrated panel data approach to modelling economic growth," Journal of Econometrics, Elsevier, vol. 228(2), pages 379-397.
    31. Gao, J. & Linton, O. & Peng, B., 2022. "A Nonparametric Panel Model for Climate Data with Seasonal and Spatial Variation," Cambridge Working Papers in Economics 2239, Faculty of Economics, University of Cambridge.
    32. Christis Katsouris, 2023. "High Dimensional Time Series Regression Models: Applications to Statistical Learning Methods," Papers 2308.16192, arXiv.org.
    33. Su, Liangjun & Hoshino, Tadao, 2016. "Sieve instrumental variable quantile regression estimation of functional coefficient models," Journal of Econometrics, Elsevier, vol. 191(1), pages 231-254.
    34. Isabel Casas & Jiti Gao & Bin Peng & Shangyu Xie, 2019. "Time-Varying Income Elasticities of Healthcare Expenditure for the OECD and Eurozone," Monash Econometrics and Business Statistics Working Papers 28/19, Monash University, Department of Econometrics and Business Statistics.
    35. Guohua Feng & Jiti Gao & Bin Peng, 2019. "An Integrated Panel Data Approach to Modelling Economic Growth," Monash Econometrics and Business Statistics Working Papers 6/19, Monash University, Department of Econometrics and Business Statistics.
    36. Feng, Guohua & Peng, Bin & Su, Liangjun & Yang, Thomas Tao, 2019. "Semi-parametric single-index panel data models with interactive fixed effects: Theory and practice," Journal of Econometrics, Elsevier, vol. 212(2), pages 607-622.
    37. Artūras Juodis, 2022. "A regularization approach to common correlated effects estimation," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(4), pages 788-810, June.
    38. Dong, Chaohua & Gao, Jiti & Peng, Bin, 2015. "Semiparametric single-index panel data models with cross-sectional dependence," Journal of Econometrics, Elsevier, vol. 188(1), pages 301-312.
    39. Antonio Musolesi & Michel Simioni & Georgios Gioldasis, 2018. "Nonparametric estimation of international R&D spillovers," Working Papers 2018037, University of Ferrara, Department of Economics.
    40. Wolter, James Lewis, 2016. "Kernel estimation of hazard functions when observations have dependent and common covariates," Journal of Econometrics, Elsevier, vol. 193(1), pages 1-16.
    41. Chaohua Dong & Jiti Gao & Bin Peng, 2018. "Varying-coefficient panel data models with partially observed factor structure," Monash Econometrics and Business Statistics Working Papers 1/18, Monash University, Department of Econometrics and Business Statistics.
    42. Taining Wang & Jinjing Tian & Feng Yao, 2021. "Does high debt ratio influence Chinese firms’ performance? A semiparametric stochastic frontier approach with zero inefficiency," Empirical Economics, Springer, vol. 61(2), pages 587-636, August.
    43. Georgios Gioldasis & Antonio Musolesi & Michel Simioni, 2021. "Interactive R&D Spillovers: an estimation strategy based on forecasting-driven model selection," Working Papers hal-03224910, HAL.
    44. Difang Huang & Jiti Gao & Tatsushi Oka, 2022. "Semiparametric Single-Index Estimation for Average Treatment Effects," Monash Econometrics and Business Statistics Working Papers 10/22, Monash University, Department of Econometrics and Business Statistics.
    45. Georgios Gioldasis & Antonio Musolesi & Michel Simioni, 2018. "Nonparametric estimation of international R&D spillovers," SEEDS Working Papers 0318, SEEDS, Sustainability Environmental Economics and Dynamics Studies, revised Mar 2018.
    46. Román Mínguez & Roberto Basile & María Durbán, 2020. "An alternative semiparametric model for spatial panel data," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 29(4), pages 669-708, December.
    47. Cai, Zongwu & Fang, Ying & Xu, Qiuhua, 2022. "Testing capital asset pricing models using functional-coefficient panel data models with cross-sectional dependence," Journal of Econometrics, Elsevier, vol. 227(1), pages 114-133.
    48. Xiao Huang, 2013. "Nonparametric Estimation in Large Panels with Cross-Sectional Dependence," Econometric Reviews, Taylor & Francis Journals, vol. 32(5-6), pages 754-777, August.
    49. Raffaello Seri & Samuele Centorrino & Michele Bernasconi, 2019. "Nonparametric Estimation and Inference in Economic and Psychological Experiments," Papers 1904.11156, arXiv.org, revised Dec 2019.
    50. Georgios Gioldasis & Antonio Musolesi & Michel Simioni, 2020. "Model uncertainty, nonlinearities and out-of-sample comparison: evidence from international technology diffusion," SEEDS Working Papers 0120, SEEDS, Sustainability Environmental Economics and Dynamics Studies, revised Jan 2020.
    51. James Wolter, 2015. "Kernel Estimation Of Hazard Functions When Observations Have Dependent and Common Covariates," Economics Series Working Papers 761, University of Oxford, Department of Economics.
    52. Alexandra Soberon & Antonio Musolesi & Juan M. Rodriguez‐Poo, 2024. "A Semi‐parametric Panel Data Model with Common Factors and Spatial Dependence," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 86(4), pages 905-927, August.
    53. Ma, Yingying & Guo, Shaojun & Wang, Hansheng, 2023. "Sparse spatio-temporal autoregressions by profiling and bagging," Journal of Econometrics, Elsevier, vol. 232(1), pages 132-147.

  59. Long, Xiangdong & Su, Liangjun & Ullah, Aman, 2011. "Estimation and Forecasting of Dynamic Conditional Covariance: A Semiparametric Multivariate Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 29(1), pages 109-125.

    Cited by:

    1. Serra, Teresa & Gil, José M., 2012. "Biodiesel as a motor fuel price stabilization mechanism," Energy Policy, Elsevier, vol. 50(C), pages 689-698.
    2. Aslanidis, Nektarios & Martínez Ibáñez, Óscar, 2012. "Modelling world investment markets using threshold conditional correlation models," Working Papers 2072/203167, Universitat Rovira i Virgili, Department of Economics.
    3. Silvennoinen, Annastiina & Teräsvirta, Timo, 2024. "Consistency and asymptotic normality of maximum likelihood estimators of a multiplicative time-varying smooth transition correlation GARCH model," Econometrics and Statistics, Elsevier, vol. 32(C), pages 57-72.
    4. Mark J Jensen & John M Maheu, 2012. "Bayesian semiparametric multivariate GARCH modeling," Working Papers tecipa-458, University of Toronto, Department of Economics.
    5. Gardebroek, Cornelis & Hernandez, Manuel A., 2013. "Do energy prices stimulate food price volatility? Examining volatility transmission between US oil, ethanol and corn markets," Energy Economics, Elsevier, vol. 40(C), pages 119-129.
    6. Serra, Teresa, 2011. "Volatility spillovers between food and energy markets: A semiparametric approach," Energy Economics, Elsevier, vol. 33(6), pages 1155-1164.
    7. Aman Ullah & Mardi Dungey & Xiangdong Long & Yun Wang, 2014. "A Semiparametric Conditional Duration Model," Working Papers 201408, University of California at Riverside, Department of Economics.
    8. Jose Fernandez & Bruce Morley, 2015. "Interdependence among Agricultural Commodity Markets, Macroeconomic Factors, Crude Oil and Commodity Index," Department of Economics Working Papers 42/15, University of Bath, Department of Economics.
    9. Abdelradi, Fadi & Serra, Teresa, 2015. "Food–energy nexus in Europe: Price volatility approach," Energy Economics, Elsevier, vol. 48(C), pages 157-167.
    10. Tae-Hwy Lee & Millie Yi Mao & Aman Ullah, 2021. "Estimation of high-dimensional dynamic conditional precision matrices with an application to forecast combination," Econometric Reviews, Taylor & Francis Journals, vol. 40(10), pages 905-918, November.
    11. Dimitrios Thomakos & Johannes Klepsch & Dimitris N. Politis, 2020. "Model Free Inference on Multivariate Time Series with Conditional Correlations," Stats, MDPI, vol. 3(4), pages 1-26, November.
    12. Paul Catani & Timo Teräsvirta & Meiqun Yin, 2017. "A Lagrange multiplier test for testing the adequacy of constant conditional correlation GARCH model," Econometric Reviews, Taylor & Francis Journals, vol. 36(6-9), pages 599-621, October.
    13. Kotlyarova, Yulia & Schafgans, Marcia M. A. & Zinde‐Walsh, Victoria, 2011. "Adapting kernel estimation to uncertain smoothness," LSE Research Online Documents on Economics 42015, London School of Economics and Political Science, LSE Library.
    14. Zhang, Yongli & Rolling, Craig & Yang, Yuhong, 2021. "Estimating and forecasting dynamic correlation matrices: A nonlinear common factor approach," Journal of Multivariate Analysis, Elsevier, vol. 183(C).
    15. Kristoufek, Ladislav & Janda, Karel & Zilberman, David, 2012. "Relationship Between Prices of Food, Fuel and Biofuel," 131st Seminar, September 18-19, 2012, Prague, Czech Republic 135793, European Association of Agricultural Economists.
    16. Pick Schen Yip & Robert Brooks & Hung Xuan Do & Duc Khuong Nguyen, 2019. "Dynamic Volatility Spillover Effect between Oil and Agricultural Products," Working Papers 2019-009, Department of Research, Ipag Business School.
    17. Serra, Teresa, 2012. "Biofuel-related price volatility literature: a review and new approaches," 2012 Conference, August 18-24, 2012, Foz do Iguacu, Brazil 126057, International Association of Agricultural Economists.
    18. Yan Li & Liangjun Su & Yuewu Xu, 2014. "A Combined Approach to the Inference of Conditional Factor Models," Working Papers 10-2014, Singapore Management University, School of Economics.
    19. Aslanidis, Nektarios & Martinez, Oscar, 2021. "Correlation regimes in international equity and bond returns," Economic Modelling, Elsevier, vol. 97(C), pages 397-410.
    20. Gardebroek, Cornelis & Hernandez, Manuel A. & Robles, Miguel, 2013. "Market interdependence and volatility transmission among major crops," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. 150119, Agricultural and Applied Economics Association.
    21. López Cabrera, Brenda & Schulz, Franziska, 2013. "Volatility linkages between energy and agricultural commodity prices," SFB 649 Discussion Papers 2013-042, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    22. Matteo Barigozzi & Christian T. Brownlees & Giampiero M. Gallo & David Veredas, 2014. "Disentangling Systematic and Idiosyncratic Dynamics in Panels of Volatility Measures," Econometrics Working Papers Archive 2014_02, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti", revised Feb 2014.
    23. Kristoufek, Ladislav & Janda, Karel & Zilberman, David, 2012. "Correlations between biofuels and related commodities before and during the food crisis: A taxonomy perspective," Energy Economics, Elsevier, vol. 34(5), pages 1380-1391.
    24. Lu, Xun & Su, Liangjun, 2015. "Jackknife model averaging for quantile regressions," Journal of Econometrics, Elsevier, vol. 188(1), pages 40-58.
    25. Teresa Serra & José M. Gil, 2013. "Price volatility in food markets: can stock building mitigate price fluctuations?," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 40(3), pages 507-528, July.
    26. Amer Ait Sidhoum & Teresa Serra, 2016. "Volatility Spillovers in the Spanish Food Marketing Chain: The Case of Tomato," Agribusiness, John Wiley & Sons, Ltd., vol. 32(1), pages 45-63, January.
    27. José Fernández, 2015. "Interdependence among Agricultural Commodity Markets, Macroeconomic Factors, Crude Oil and Commodity Index," Bristol Economics Discussion Papers 15/666, School of Economics, University of Bristol, UK.

  60. Peter C. B. Phillips & Liangjun Su, 2011. "Non‐parametric regression under location shifts," Econometrics Journal, Royal Economic Society, vol. 14(3), pages 457-486, October.

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    1. Gao, Jiti & Phillips, Peter C.B., 2013. "Semiparametric estimation in triangular system equations with nonstationarity," Journal of Econometrics, Elsevier, vol. 176(1), pages 59-79.
    2. Ping Yu & Peter C.B. Phillips, 2014. "Threshold Regression with Endogeneity," Cowles Foundation Discussion Papers 1966, Cowles Foundation for Research in Economics, Yale University.

  61. Su, Liangjun & White, Halbert, 2010. "Testing Structural Change In Partially Linear Models," Econometric Theory, Cambridge University Press, vol. 26(6), pages 1761-1806, December.

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    1. Lu, Xun & White, Halbert, 2014. "Robustness checks and robustness tests in applied economics," Journal of Econometrics, Elsevier, vol. 178(P1), pages 194-206.
    2. Su, Liangjun & White, Halbert, 2014. "Testing conditional independence via empirical likelihood," Journal of Econometrics, Elsevier, vol. 182(1), pages 27-44.
    3. Liangjun Su & Stefan Hoderlein & Halbert White, 2013. "Testing Monotonicity in Unobservables with Panel Data," Boston College Working Papers in Economics 892, Boston College Department of Economics, revised 01 Feb 2016.
    4. Huang, Meng & Sun, Yixiao & White, Hal, 2013. "A Flexible Nonparametric Test for Conditional Independence," University of California at San Diego, Economics Working Paper Series qt3pt89204, Department of Economics, UC San Diego.
    5. Su, Liangjun & Hoshino, Tadao, 2016. "Sieve instrumental variable quantile regression estimation of functional coefficient models," Journal of Econometrics, Elsevier, vol. 191(1), pages 231-254.
    6. Stefan Sperlich, 2013. "Comments on: An updated review of Goodness-of-Fit tests for regression models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 22(3), pages 419-427, September.
    7. Fu, Zhonghao & Hong, Yongmiao, 2019. "A model-free consistent test for structural change in regression possibly with endogeneity," Journal of Econometrics, Elsevier, vol. 211(1), pages 206-242.
    8. Qian, Junhui & Su, Liangjun, 2016. "Shrinkage estimation of common breaks in panel data models via adaptive group fused Lasso," Journal of Econometrics, Elsevier, vol. 191(1), pages 86-109.
    9. Stefan Sperlich, 2014. "On the choice of regularization parameters in specification testing: a critical discussion," Empirical Economics, Springer, vol. 47(2), pages 427-450, September.

  62. Su, Liangjun & Jin, Sainan, 2010. "Profile quasi-maximum likelihood estimation of partially linear spatial autoregressive models," Journal of Econometrics, Elsevier, vol. 157(1), pages 18-33, July.

    Cited by:

    1. Bent Jesper Christensen & Christian M. Dahl & Emma M. Iglesias, 2008. "Semiparametric Inference in a GARCH-in-Mean Model," CREATES Research Papers 2008-46, Department of Economics and Business Economics, Aarhus University.
    2. Zhiyong Chen & Jianbao Chen, 2022. "Bayesian analysis of partially linear, single-index, spatial autoregressive models," Computational Statistics, Springer, vol. 37(1), pages 327-353, March.
    3. Su, Liangjun, 2012. "Semiparametric GMM estimation of spatial autoregressive models," Journal of Econometrics, Elsevier, vol. 167(2), pages 543-560.
    4. Jianbao Chen & Suli Cheng, 2021. "GMM Estimation of a Partially Linear Additive Spatial Error Model," Mathematics, MDPI, vol. 9(6), pages 1-28, March.
    5. Tizheng Li & Xiaojuan Kang, 2022. "Variable selection of higher-order partially linear spatial autoregressive model with a diverging number of parameters," Statistical Papers, Springer, vol. 63(1), pages 243-285, February.
    6. Qiong Pang & Xijian Hu, 2024. "INLA Estimation of Semi-Variable Coefficient Spatial Lag Model—Analysis of PM2.5 Influencing Factors in the Context of Urbanization in China," Mathematics, MDPI, vol. 12(7), pages 1-24, March.
    7. Yang, Zhenlin, 2015. "A general method for third-order bias and variance corrections on a nonlinear estimator," Journal of Econometrics, Elsevier, vol. 186(1), pages 178-200.
    8. Xuan Liang & Jiti Gao & Xiaodong Gong, 2019. "Time-Varying Coefficient Spatial Autoregressive Panel Data Model with Fixed Effects," Monash Econometrics and Business Statistics Working Papers 26/19, Monash University, Department of Econometrics and Business Statistics.
    9. Tadao Hoshino, 2018. "Semiparametric Spatial Autoregressive Models With Endogenous Regressors: With an Application to Crime Data," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 36(1), pages 160-172, January.
    10. Malikov, Emir & Sun, Yiguo, 2017. "Semiparametric estimation and testing of smooth coefficient spatial autoregressive models," Journal of Econometrics, Elsevier, vol. 199(1), pages 12-34.
    11. Su, Liangjun & Yang, Zhenlin, 2015. "QML estimation of dynamic panel data models with spatial errors," Journal of Econometrics, Elsevier, vol. 185(1), pages 230-258.
    12. Luo, Guowang & Wu, Mixia & Pang, Zhen, 2022. "Estimation of spatial autoregressive models with covariate measurement errors," Journal of Multivariate Analysis, Elsevier, vol. 192(C).
    13. Kunming Li & Liting Fang, 2024. "Bayesian Estimation of the Semiparametric Spatial Lag Model," Mathematics, MDPI, vol. 12(14), pages 1-17, July.
    14. Yuping Hu & Siyu Wu & Sanying Feng & Junliang Jin, 2020. "Estimation in Partial Functional Linear Spatial Autoregressive Model," Mathematics, MDPI, vol. 8(10), pages 1-12, October.
    15. Sun, Yiguo & Malikov, Emir, 2018. "Estimation and inference in functional-coefficient spatial autoregressive panel data models with fixed effects," Journal of Econometrics, Elsevier, vol. 203(2), pages 359-378.
    16. Sanying Feng & Tiejun Tong & Sung Nok Chiu, 2023. "Statistical Inference for Partially Linear Varying Coefficient Spatial Autoregressive Panel Data Model," Mathematics, MDPI, vol. 11(22), pages 1-19, November.
    17. Mengqi Zhang & Boping Tian, 2023. "Profile Maximum Likelihood Estimation of Single-Index Spatial Dynamic Panel Data Model," Mathematics, MDPI, vol. 11(13), pages 1-16, July.
    18. Yuxue Sheng & James Paul LeSage, 2021. "Interpreting spatial regression models with multiplicative interaction explanatory variables," Journal of Geographical Systems, Springer, vol. 23(3), pages 333-360, July.
    19. Roberto Basile, 2014. "Regional productivity growth in Europe: a Schumpeterian perspective," Gecomplexity Discussion Paper Series 1, Action IS1104 "The EU in the new complex geography of economic systems: models, tools and policy evaluation", revised Nov 2014.
    20. Fang Lu & Jing Yang & Xuewen Lu, 2022. "One-step oracle procedure for semi-parametric spatial autoregressive model and its empirical application to Boston housing price data," Empirical Economics, Springer, vol. 62(6), pages 2645-2671, June.
    21. Wei, Chuanhua & Guo, Shuang & Zhai, Shufen, 2017. "Statistical inference of partially linear varying coefficient spatial autoregressive models," Economic Modelling, Elsevier, vol. 64(C), pages 553-559.
    22. Xuan, Liang & Jiti, Gao & xiaodong, Gong, 2021. "Semiparametric Spatial Autoregressive Panel Data Model with Fixed Effects and Time-Varying Coefficients," MPRA Paper 108497, University Library of Munich, Germany, revised 30 May 2021.
    23. Gupta, Abhimanyu, 2019. "Estimation Of Spatial Autoregressions With Stochastic Weight Matrices," Econometric Theory, Cambridge University Press, vol. 35(2), pages 417-463, April.
    24. Yueqin Wu & Yan Sun, 2017. "Shrinkage estimation of the linear model with spatial interaction," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 80(1), pages 51-68, January.
    25. Konstantinidi, Antri & Kourtellos, Andros & Sun, Yiguo, 2023. "Social threshold regression," Journal of Econometrics, Elsevier, vol. 235(2), pages 2057-2081.
    26. Gupta, A, 2015. "Nonparametric specification testing via the trinity of tests," Economics Discussion Papers 23824, University of Essex, Department of Economics.
    27. Sun, Yiguo, 2016. "Functional-coefficient spatial autoregressive models with nonparametric spatial weights," Journal of Econometrics, Elsevier, vol. 195(1), pages 134-153.
    28. Zhengyu Zhang, 2013. "A Pairwise Difference Estimator for Partially Linear Spatial Autoregressive Models," Spatial Economic Analysis, Taylor & Francis Journals, vol. 8(2), pages 176-194, June.
    29. Hongjie Wei & Yan Sun, 2017. "Heteroskedasticity-robust semi-parametric GMM estimation of a spatial model with space-varying coefficients," Spatial Economic Analysis, Taylor & Francis Journals, vol. 12(1), pages 113-128, January.
    30. Basile, Roberto & Durbán, María & Mínguez, Román & María Montero, Jose & Mur, Jesús, 2014. "Modeling regional economic dynamics: Spatial dependence, spatial heterogeneity and nonlinearities," Journal of Economic Dynamics and Control, Elsevier, vol. 48(C), pages 229-245.
    31. Sun, Yan, 2017. "Estimation of single-index model with spatial interaction," Regional Science and Urban Economics, Elsevier, vol. 62(C), pages 36-45.
    32. Wolter, James Lewis, 2016. "Kernel estimation of hazard functions when observations have dependent and common covariates," Journal of Econometrics, Elsevier, vol. 193(1), pages 1-16.
    33. Cheng, Suli & Chen, Jianbao, 2023. "GMM estimation of partially linear additive spatial autoregressive model," Computational Statistics & Data Analysis, Elsevier, vol. 182(C).
    34. Suli Cheng & Jianbao Chen, 2021. "Estimation of partially linear single-index spatial autoregressive model," Statistical Papers, Springer, vol. 62(1), pages 495-531, February.
    35. Ruiqin Tian & Miaojie Xia & Dengke Xu, 2024. "Profile quasi-maximum likelihood estimation for semiparametric varying-coefficient spatial autoregressive panel models with fixed effects," Statistical Papers, Springer, vol. 65(8), pages 5109-5143, October.
    36. Zhang, Yuanqing & Sun, Yanqing, 2015. "Estimation of partially specified dynamic spatial panel data models with fixed-effects," Regional Science and Urban Economics, Elsevier, vol. 51(C), pages 37-46.
    37. Ke Wang & Dehui Wang, 2024. "Estimation for partially linear single-index spatial autoregressive model with covariate measurement errors," Statistical Papers, Springer, vol. 65(7), pages 4201-4241, September.
    38. Giuseppe Arbia, 2011. "A Lustrum of SEA: Recent Research Trends Following the Creation of the Spatial Econometrics Association (2007--2011)," Spatial Economic Analysis, Taylor & Francis Journals, vol. 6(4), pages 377-395, July.
    39. Guo Shuang & Wei Chuanhua, 2015. "Testing for Spatial Lag Effects in Varying Coefficient Spatial Autoregressive Models," Journal of Systems Science and Information, De Gruyter, vol. 3(6), pages 561-567, December.
    40. Bogui Li & Jianbao Chen & Shuangshuang Li, 2023. "Estimation of Fixed Effects Partially Linear Varying Coefficient Panel Data Regression Model with Nonseparable Space-Time Filters," Mathematics, MDPI, vol. 11(6), pages 1-24, March.
    41. Liu, Yu & Zhuang, Xiaoyang, 2023. "Shrinkage estimation of semi-parametric spatial autoregressive panel data model with fixed effects," Statistics & Probability Letters, Elsevier, vol. 194(C).
    42. Zhang, Xinyu & Yu, Jihai, 2018. "Spatial weights matrix selection and model averaging for spatial autoregressive models," Journal of Econometrics, Elsevier, vol. 203(1), pages 1-18.
    43. Bogui Li & Jianbao Chen & Hao Chen, 2024. "Estimation of fixed effects semiparametric single-index panel model with spatio-temporal correlated errors," Statistical Papers, Springer, vol. 65(8), pages 4915-4953, October.
    44. Yunquan Song & Hang Su & Minmin Zhan, 2024. "Local Walsh-average-based Estimation and Variable Selection for Spatial Single-index Autoregressive Models," Networks and Spatial Economics, Springer, vol. 24(2), pages 313-339, June.
    45. Liangjun Su & Xi Qu, 2017. "Specification Test for Spatial Autoregressive Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(4), pages 572-584, October.
    46. Sun, Yanqing & Zhang, Yuanqing & Huang, Jianhua Z., 2019. "Estimation of a semiparametric varying-coefficient mixed regressive spatial autoregressive model," Econometrics and Statistics, Elsevier, vol. 9(C), pages 140-155.
    47. James Wolter, 2015. "Kernel Estimation Of Hazard Functions When Observations Have Dependent and Common Covariates," Economics Series Working Papers 761, University of Oxford, Department of Economics.
    48. B. Fingleton & M. Abreu & P. Cheshire & H. Garretsen & D. Igliori & J. Le Gallo & P. McCann & John McCombie & V. Monastiriotis & M. Roberts & J. Yu, 2013. "Editorial," Spatial Economic Analysis, Taylor & Francis Journals, vol. 8(2), pages 113-119, June.
    49. Kwok, Hon Ho, 2019. "Identification and estimation of linear social interaction models," Journal of Econometrics, Elsevier, vol. 210(2), pages 434-458.
    50. Abhimanyu Gupta & Xi Qu, 2021. "Consistent specification testing under spatial dependence," Papers 2101.10255, arXiv.org, revised Aug 2022.

  63. Mishra, Santosh & Su, Liangjun & Ullah, Aman, 2010. "Semiparametric Estimator of Time Series Conditional Variance," Journal of Business & Economic Statistics, American Statistical Association, vol. 28(2), pages 256-274.

    Cited by:

    1. Jaromír Kukal & Tran Van Quang, 2014. "Neparametrický heuristický přístup k odhadu modelu GARCH-M a jeho výhody [Estimating a GARCH-M Model by a Non-Parametric Heuristic Method and Its Advantages]," Politická ekonomie, Prague University of Economics and Business, vol. 2014(1), pages 100-116.
    2. Cristina Amado & Timo Teräsvirta, 2011. "Modelling Volatility by Variance Decomposition," NIPE Working Papers 01/2011, NIPE - Universidade do Minho.
    3. Aman Ullah & Mardi Dungey & Xiangdong Long & Yun Wang, 2014. "A Semiparametric Conditional Duration Model," Working Papers 201408, University of California at Riverside, Department of Economics.
    4. Matthieu Garcin & Clément Goulet, 2017. "Non-parametric news impact curve: a variational approach," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-01244292, HAL.
    5. Cristina Amado & Annastiina Silvennoinen & Timo Teräsvirta, 2018. "Models with Multiplicative Decomposition of Conditional Variances and Correlations," CREATES Research Papers 2018-14, Department of Economics and Business Economics, Aarhus University.
    6. Li, Yan & Yang, Liyan, 2011. "Testing conditional factor models: A nonparametric approach," Journal of Empirical Finance, Elsevier, vol. 18(5), pages 972-992.
    7. d’Addona, Stefano & Khanom, Najrin, 2022. "Estimating tail-risk using semiparametric conditional variance with an application to meme stocks," International Review of Economics & Finance, Elsevier, vol. 82(C), pages 241-260.
    8. Niklas Ahlgren & Alexander Back & Timo Terasvirta, 2024. "A new GARCH model with a deterministic time-varying intercept," Papers 2410.03239, arXiv.org, revised Oct 2024.
    9. Justin Dang & Aman Ullah, 2021. "Machine Learning Based Semiparametric Time Series Conditional Variance: Estimation and Forecasting," Working Papers 202204, University of California at Riverside, Department of Economics, revised Jan 2022.
    10. Yan Li & Liangjun Su & Yuewu Xu, 2014. "A Combined Approach to the Inference of Conditional Factor Models," Working Papers 10-2014, Singapore Management University, School of Economics.
    11. Matthieu Garcin & Clément Goulet, 2015. "A fully non-parametric heteroskedastic model," Documents de travail du Centre d'Economie de la Sorbonne 15086, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    12. Matthieu Garcin & Clément Goulet, 2017. "Non-parametric news impact curve: a variational approach," Post-Print halshs-01244292, HAL.
    13. Yu, Jun, 2012. "A semiparametric stochastic volatility model," Journal of Econometrics, Elsevier, vol. 167(2), pages 473-482.
    14. Cristina Amado & Timo Teräsvirta, 2017. "Specification and testing of multiplicative time-varying GARCH models with applications," Econometric Reviews, Taylor & Francis Journals, vol. 36(4), pages 421-446, April.
    15. Enno Mammen & Jens Perch Nielsen & Michael Scholz & Stefan Sperlich, 2019. "Conditional Variance Forecasts for Long-Term Stock Returns," Risks, MDPI, vol. 7(4), pages 1-22, November.
    16. Lu, Xun & Su, Liangjun, 2015. "Jackknife model averaging for quantile regressions," Journal of Econometrics, Elsevier, vol. 188(1), pages 40-58.
    17. Kaiping Wang, 2014. "Modeling Stock Index Returns using Semi-Parametric Approach with Multiplicative Adjustment," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 65-75, December.

  64. Su, Liangjun & Ullah, Aman, 2009. "Testing Conditional Uncorrelatedness," Journal of Business & Economic Statistics, American Statistical Association, vol. 27, pages 18-29.

    Cited by:

    1. Lee, Jungyoon & Robinson, Peter, 2015. "Panel nonparametric regression with fixed effects," LSE Research Online Documents on Economics 61431, London School of Economics and Political Science, LSE Library.
    2. Lee, Jungyoon & Robinson, Peter M., 2015. "Panel nonparametric regression with fixed effects," Journal of Econometrics, Elsevier, vol. 188(2), pages 346-362.
    3. Guangming Pan & Jiti Gao & Yanrong Yang & Meihui Guo, 2015. "Cross-sectional Independence Test for a Class of Parametric Panel Data Models," Monash Econometrics and Business Statistics Working Papers 17/15, Monash University, Department of Econometrics and Business Statistics.
    4. Xiangdong Long & Liangjun Su & Aman Ullah, 2009. "Estimation and Forecasting of Dynamic Conditional Covariance: A Semiparametric Multivariate Model Variables with Econometric Applications," Working Papers 200908, University of California at Riverside, Department of Economics, revised Jul 2009.

  65. Su, Liangjun & Ullah, Aman, 2008. "Local polynomial estimation of nonparametric simultaneous equations models," Journal of Econometrics, Elsevier, vol. 144(1), pages 193-218, May.

    Cited by:

    1. Xin Geng & Carlos Martins-Filho & Feng Yao, 2018. "Estimation of a Partially Linear Regression in Triangular Systems," Working Papers 18-05, Department of Economics, West Virginia University.
    2. Jiti Gao & Peter C.B. Phillips, 2013. "Functional Coefficient Nonstationary Regression with Non- and Semi-Parametric Cointegration," Monash Econometrics and Business Statistics Working Papers 16/13, Monash University, Department of Econometrics and Business Statistics.
    3. Ying-Ying Lee, 2018. "Partial Mean Processes with Generated Regressors: Continuous Treatment Effects and Nonseparable Models," Papers 1811.00157, arXiv.org.
    4. Uddin, Md. Main & Mishra, Vinod & Smyth, Russell, 2020. "Income inequality and CO2 emissions in the G7, 1870–2014: Evidence from non-parametric modelling," Energy Economics, Elsevier, vol. 88(C).
    5. Artem Prokhorov & Kien C. Tran & Mike G. Tsionas, 2021. "Estimation of semi- and nonparametric stochastic frontier models with endogenous regressors," Empirical Economics, Springer, vol. 60(6), pages 3043-3068, June.
    6. Jesús Peiró-Palomino, 2016. "Social Capital and Economic Growth in Europe: Nonlinear Trends and Heterogeneous Regional Effects," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 78(5), pages 717-751, October.
    7. Francesco Bravo & David Jacho-Chavez, 2011. "Empirical Likelihood for Efficient Semiparametric Average Treatment Effects," Econometric Reviews, Taylor & Francis Journals, vol. 30(1), pages 1-24.
    8. Battisti, Michele & Gatto, Massimo Del & Parmeter, Christopher F., 2022. "Skill-biased technical change and labor market inefficiency," Journal of Economic Dynamics and Control, Elsevier, vol. 139(C).
    9. Alyssa Carlson, 2020. "Relaxing Conditional Independence in an Endogenous Binary Response Model," Working Papers 2008, Department of Economics, University of Missouri.
    10. Das, Monica & Basu, Sudip Ranjan, 2022. "Understanding the relationship between income inequality and pollution: A fresh perspective with cross-country evidence," World Development Perspectives, Elsevier, vol. 26(C).
    11. Phillips, Peter C.B. & Li, Degui & Gao, Jiti, 2017. "Estimating smooth structural change in cointegration models," Journal of Econometrics, Elsevier, vol. 196(1), pages 180-195.
    12. Manuel Wiesenfarth & Carlos Matías Hisgen & Thomas Kneib & Carmen Cadarso-Suarez, 2012. "Bayesian Nonparametric Instrumental Variable Regression based on Penalized Splines and Dirichlet Process Mixtures," Courant Research Centre: Poverty, Equity and Growth - Discussion Papers 127, Courant Research Centre PEG.
    13. Daniel J. Henderson & Anne-Charlotte Souto, 2018. "An Introduction to Nonparametric Regression for Labor Economists," Journal of Labor Research, Springer, vol. 39(4), pages 355-382, December.
    14. Jingping Gu & Qi Li & Jui-Chung Yang, 2015. "Multivariate Local Polynomial Kernel Estimators: Leading Bias and Asymptotic Distribution," Econometric Reviews, Taylor & Francis Journals, vol. 34(6-10), pages 979-1010, December.
    15. Qingliang Fan & Zijian Guo & Ziwei Mei & Cun-Hui Zhang, 2023. "Inference for Nonlinear Endogenous Treatment Effects Accounting for High-Dimensional Covariate Complexity," Papers 2310.08063, arXiv.org, revised Jun 2024.
    16. Kim, Namhyun & W. Saart, Patrick, 2021. "Estimation in partially linear semiparametric models with parametric and/or nonparametric endogeneity," Cardiff Economics Working Papers E2021/9, Cardiff University, Cardiff Business School, Economics Section.
    17. Durga P. Gautam, 2014. "Remittances and Governance: Does the Government Free Ride?," Working Papers 14-40, Department of Economics, West Virginia University.
    18. David Jacho-Chavez & Arthur Lewbel & Oliver Linton, 2006. "Identification and Nonparametric Estimation of a Transformed Additively Separable Model," Boston College Working Papers in Economics 652, Boston College Department of Economics, revised 26 Nov 2008.
    19. Patrick Saart & Jiti Gao, 2012. "Semiparametric Methods in Nonlinear Time Series Analysis: A Selective Review," Monash Econometrics and Business Statistics Working Papers 21/12, Monash University, Department of Econometrics and Business Statistics.
    20. Das, Monica & Basu, Sudip R., 2023. "Inclusive bank based financial development in countries with special needs: A semiparametric analysis," Economic Analysis and Policy, Elsevier, vol. 80(C), pages 740-753.
    21. : Daniel J. Henderson & Chris Papageorgiou & Christopher F. Parmeter, 2012. "Who Benefits from Financial Development? New Methods, New Evidence," Working Papers 2013-07, University of Miami, Department of Economics.
    22. Kai Sun, 2015. "Constrained nonparametric estimation of input distance function," Journal of Productivity Analysis, Springer, vol. 43(1), pages 85-97, February.
    23. Jinjing Tian & Taining Wang & Feng Yao, 2024. "Excessive External Borrowing in China: Evidence from a Nonparametric Threshold Regression Model with Fixed Effects," Mathematics, MDPI, vol. 12(23), pages 1-28, November.
    24. Martins-Filho, Carlos & Yao, Feng, 2012. "Kernel-based estimation of semiparametric regression in triangular systems," Economics Letters, Elsevier, vol. 115(1), pages 24-27.
    25. Gao, Jiti & Phillips, Peter C.B., 2013. "Semiparametric estimation in triangular system equations with nonstationarity," Journal of Econometrics, Elsevier, vol. 176(1), pages 59-79.
    26. Ghazouani, Tarek, 2022. "Dynamic impact of globalization on renewable energy consumption: Non-parametric modelling evidence," Technological Forecasting and Social Change, Elsevier, vol. 185(C).
    27. Delgado, Michael S. & Parmeter, Christopher F., 2014. "A simple estimator for partial linear regression with endogenous nonparametric variables," Economics Letters, Elsevier, vol. 124(1), pages 100-103.
    28. Jiti Gao & Peter C.B. Phillips, 2011. "Semiparametric Estimation in Multivariate Nonstationary Time Series Models," Monash Econometrics and Business Statistics Working Papers 17/11, Monash University, Department of Econometrics and Business Statistics.
    29. Koo, Chao, 2018. "Essays on functional coefficient models," Other publications TiSEM ba87b8a5-3c55-40ec-967d-9, Tilburg University, School of Economics and Management.
    30. Kim Kyoo il & Petrin Amil, 2022. "A Generalized Non-Parametric Instrumental Variable-Control Function Approach to Estimation in Nonlinear Settings," Journal of Econometric Methods, De Gruyter, vol. 11(1), pages 91-125, January.
    31. Lee, Chi-Chuan & Lee, Chien-Chiang & Chiou, Yan-Yu, 2017. "Insurance activities, globalization, and economic growth: New methods, new evidence," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 51(C), pages 155-170.
    32. Nicholas Marinucci & Kris Ivanovski, 2023. "Does Inequality Affect Climate Change? A Regional and Sectoral Analysis," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 166(3), pages 705-729, April.
    33. Sefa Awaworyi Churchill & Bin Peng & Russell Smyth & Quanda Zhang, 2022. "R&D intensity and income inequality in the G7: 1870–2016," Scottish Journal of Political Economy, Scottish Economic Society, vol. 69(3), pages 263-282, July.
    34. Jiti Gao & Peter C.B. Phillips, 2013. "Functional Coefficient Nonstationary Regression," Cowles Foundation Discussion Papers 1911, Cowles Foundation for Research in Economics, Yale University.
    35. Zongwu Cai & Qi Li, 2013. "Some Recent Develop- ments on Nonparametric Econometrics," Working Papers 2013-10-14, Wang Yanan Institute for Studies in Economics (WISE), Xiamen University.
    36. Anjan K. Saha & Vinod Mishra & Russell Smyth, 2021. "Financial development and top income shares in OECD countries," Southern Economic Journal, John Wiley & Sons, vol. 87(3), pages 952-978, January.
    37. Awaworyi Churchill, Sefa & Inekwe, John & Ivanovski, Kris, 2021. "R&D expenditure and energy consumption in OECD nations," Energy Economics, Elsevier, vol. 100(C).
    38. Camarero, Mariam & Peiró-Palomino, Jesús & Tamarit, Cecilio, 2019. "Growth in a time of external imbalances," Economic Modelling, Elsevier, vol. 79(C), pages 262-275.
    39. Kumbhakar, Subal C. & Li, Mingyang & Lien, Gudbrand, 2023. "Do subsidies matter in productivity and profitability changes?," Economic Modelling, Elsevier, vol. 123(C).
    40. Ying-Ying Lee, 2014. "Partial Mean Processes with Generated Regressors: Continuous Treatment Effects and Nonseparable Models," Economics Series Working Papers 706, University of Oxford, Department of Economics.

  66. Su, Liangjun & White, Halbert, 2008. "A Nonparametric Hellinger Metric Test For Conditional Independence," Econometric Theory, Cambridge University Press, vol. 24(4), pages 829-864, August.

    Cited by:

    1. Chen, Bin & Hong, Yongmiao, 2012. "Testing For The Markov Property In Time Series," Econometric Theory, Cambridge University Press, vol. 28(1), pages 130-178, February.
    2. Su, Liangjun & White, Halbert, 2014. "Testing conditional independence via empirical likelihood," Journal of Econometrics, Elsevier, vol. 182(1), pages 27-44.
    3. Xu, Kai & Cheng, Qing, 2024. "Test of conditional independence in factor models via Hilbert–Schmidt independence criterion," Journal of Multivariate Analysis, Elsevier, vol. 199(C).
    4. Taoufik Bouezmarni & Mohamed Doukali & Abderrahim Taamouti, 2023. "Testing Granger Non-Causality in Expectiles," University of East Anglia School of Economics Working Paper Series 2023-02, School of Economics, University of East Anglia, Norwich, UK..
    5. Xiaojun Song & Haoyu Wei, 2021. "Nonparametric Tests of Conditional Independence for Time Series," Papers 2110.04847, arXiv.org.
    6. Tsuyoshi Kunihama & David B. Dunson, 2016. "Nonparametric Bayes inference on conditional independence," Biometrika, Biometrika Trust, vol. 103(1), pages 35-47.
    7. Sungwon Lee & Joon H. Ro, 2020. "Nonparametric Tests for Conditional Quantile Independence with Duration Outcomes," Working Papers 2013, Nam Duck-Woo Economic Research Institute, Sogang University (Former Research Institute for Market Economy).
    8. Wang, Hongfei & Liu, Binghui & Feng, Long & Ma, Yanyuan, 2024. "Rank-based max-sum tests for mutual independence of high-dimensional random vectors," Journal of Econometrics, Elsevier, vol. 238(1).
    9. Semei Coronado & Rebeca Jim'enez-Rodr'iguez & Omar Rojas, 2015. "An empirical analysis of the relationships between crude oil, gold and stock markets," Papers 1510.07599, arXiv.org, revised May 2016.
    10. Huang, Meng & Sun, Yixiao & White, Hal, 2013. "A Flexible Nonparametric Test for Conditional Independence," University of California at San Diego, Economics Working Paper Series qt3pt89204, Department of Economics, UC San Diego.
    11. Joeri Smits & Jeffrey S. Racine, 2013. "Testing Exclusion Restrictions in Nonseparable Triangular Models," Department of Economics Working Papers 2013-02, McMaster University.
    12. Dong, Hao & Taylor, Luke, 2022. "Nonparametric Significance Testing In Measurement Error Models," Econometric Theory, Cambridge University Press, vol. 38(3), pages 454-496, June.
    13. Hoderlein, Stefan & Su, Liangjun & White, Halbert & Yang, Thomas Tao, 2016. "Testing for monotonicity in unobservables under unconfoundedness," Journal of Econometrics, Elsevier, vol. 193(1), pages 183-202.
    14. Cheng, Yu-Hsiang & Huang, Tzee-Ming, 2012. "A conditional independence test for dependent data based on maximal conditional correlation," Journal of Multivariate Analysis, Elsevier, vol. 107(C), pages 210-226.
    15. Gaurab Aryal & Isabelle Perrigne & Quang Vuong, 2015. "Identification of Insurance Models with Multidimensional Screening," Papers 1508.02919, arXiv.org, revised Jan 2016.
    16. Bertrand Candelon & Sessi Tokpavi, 2016. "A Nonparametric Test for Granger Causality in Distribution With Application to Financial Contagion," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(2), pages 240-253, April.
    17. Zhou, Yeqing & Liu, Jingyuan & Zhu, Liping, 2020. "Test for conditional independence with application to conditional screening," Journal of Multivariate Analysis, Elsevier, vol. 175(C).
    18. Hobæk Haff, Ingrid & Segers, Johan, 2015. "Nonparametric estimation of pair-copula constructions with the empirical pair-copula," Computational Statistics & Data Analysis, Elsevier, vol. 84(C), pages 1-13.
    19. Taoufik Bouezmarni & Jeroen V.K. Rombouts & Abderrahim Taamouti, 2011. "Nonparametric Copula-Based Test for Conditional Independence with Applications to Granger Causality," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(2), pages 275-287, October.
    20. Bianchi, Pascal & Elgui, Kevin & Portier, François, 2023. "Conditional independence testing via weighted partial copulas," Journal of Multivariate Analysis, Elsevier, vol. 193(C).
    21. Patra, Rohit K. & Sen, Bodhisattva & Székely, Gábor J., 2016. "On a nonparametric notion of residual and its applications," Statistics & Probability Letters, Elsevier, vol. 109(C), pages 208-213.
    22. Taoufik Bouezmarni & Abderrahim Taamouti, 2014. "Nonparametric tests for conditional independence using conditional distributions," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 26(4), pages 697-719, December.
    23. Sokbae Lee & Yoon-Jae Whang, 2009. "Nonparametric Tests of Conditional Treatment Effects," Cowles Foundation Discussion Papers 1740, Cowles Foundation for Research in Economics, Yale University.
    24. Li, Haiqi & Zhong, Wanling & Park, Sung Y., 2016. "Generalized cross-spectral test for nonlinear Granger causality with applications to money–output and price–volume relations," Economic Modelling, Elsevier, vol. 52(PB), pages 661-671.
    25. Ersin Sünbül, 2023. "Linear and Nonlinear Relationship Between Real Exchange Rate, Real Interest Rate and Consumer Price Index: An Empirical Application for Countries with Different Levels of Development," Scientific Annals of Economics and Business (continues Analele Stiintifice), Alexandru Ioan Cuza University, Faculty of Economics and Business Administration, vol. 70(1), pages 57-70, March.
    26. Samuele Centorrino & Jean-Pierre Florens, 2014. "Nonparametric Instrumental Variable Estimation of Binary Response Models," Department of Economics Working Papers 14-07, Stony Brook University, Department of Economics.
    27. Liu, Nianqing & Vuong, Quang & Xu, Haiqing, 2017. "Rationalization and identification of binary games with correlated types," Journal of Econometrics, Elsevier, vol. 201(2), pages 249-268.
    28. Massa, Ricardo & Rosellón, Juan, 2020. "Linear and nonlinear Granger causality between electricity production and economic performance in Mexico," Energy Policy, Elsevier, vol. 142(C).
    29. Xuehu Zhu & Jun Lu & Jun Zhang & Lixing Zhu, 2021. "Testing for conditional independence: A groupwise dimension reduction‐based adaptive‐to‐model approach," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 48(2), pages 549-576, June.
    30. Fan, Jianqing & Feng, Yang & Xia, Lucy, 2020. "A projection-based conditional dependence measure with applications to high-dimensional undirected graphical models," Journal of Econometrics, Elsevier, vol. 218(1), pages 119-139.
    31. Ai, Chunrong & Sun, Li-Hsien & Zhang, Zheng & Zhu, Liping, 2024. "Testing unconditional and conditional independence via mutual information," Journal of Econometrics, Elsevier, vol. 240(2).
    32. Györfi, László & Walk, Harro, 2012. "Strongly consistent nonparametric tests of conditional independence," Statistics & Probability Letters, Elsevier, vol. 82(6), pages 1145-1150.
    33. Poirier, Alexandre, 2017. "Efficient estimation in models with independence restrictions," Journal of Econometrics, Elsevier, vol. 196(1), pages 1-22.
    34. Polanco-Martínez, J.M. & Fernández-Macho, J. & Neumann, M.B. & Faria, S.H., 2018. "A pre-crisis vs. crisis analysis of peripheral EU stock markets by means of wavelet transform and a nonlinear causality test," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 1211-1227.
    35. Zhang, Yaowu & Zhou, Yeqing & Zhu, Liping, 2024. "A post-screening diagnostic study for ultrahigh dimensional data," Journal of Econometrics, Elsevier, vol. 239(2).
    36. Josué M. Polanco-Martínez & Luis M. Abadie, 2016. "Analyzing Crude Oil Spot Price Dynamics versus Long Term Future Prices: A Wavelet Analysis Approach," Energies, MDPI, vol. 9(12), pages 1-19, December.
    37. Su, Liangjun & Zheng, Xin, 2017. "A martingale-difference-divergence-based test for specification," Economics Letters, Elsevier, vol. 156(C), pages 162-167.

  67. Su, Liangjun & Xiao, Zhijie, 2008. "Testing for parameter stability in quantile regression models," Statistics & Probability Letters, Elsevier, vol. 78(16), pages 2768-2775, November.

    Cited by:

    1. Galvao Jr., Antonio F., 2009. "Unit root quantile autoregression testing using covariates," Journal of Econometrics, Elsevier, vol. 152(2), pages 165-178, October.
    2. Christis Katsouris, 2023. "Structural Break Detection in Quantile Predictive Regression Models with Persistent Covariates," Papers 2302.05193, arXiv.org.
    3. Tang, Yanlin & Song, Xinyuan & Zhu, Zhongyi, 2015. "Threshold effect test in censored quantile regression," Statistics & Probability Letters, Elsevier, vol. 105(C), pages 149-156.
    4. Tatsushi Oka & Pierre Perron, 2016. "Testing for Common Breaks in a Multiple Equations System," Papers 1606.00092, arXiv.org, revised Jan 2018.
    5. Fuertes, Ana-Maria & Olmo, Jose, 2013. "Optimally harnessing inter-day and intra-day information for daily value-at-risk prediction," International Journal of Forecasting, Elsevier, vol. 29(1), pages 28-42.
    6. Liwen Zhang & Huixia Judy Wang & Zhongyi Zhu, 2017. "Composite change point estimation for bent line quantile regression," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 69(1), pages 145-168, February.
    7. Yannick Hoga, 2024. "Persistence-Robust Break Detection in Predictive Quantile and CoVaR Regressions," Papers 2410.05861, arXiv.org.
    8. Antonio Galvao & Kengo Kato & Gabriel Montes-Rojas & Jose Olmo, 2014. "Testing linearity against threshold effects: uniform inference in quantile regression," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 66(2), pages 413-439, April.
    9. Oka, Tatsushi & Qu, Zhongjun, 2011. "Estimating structural changes in regression quantiles," Journal of Econometrics, Elsevier, vol. 162(2), pages 248-267, June.
    10. Jin, Hao & Tian, Zheng & Qin, Ruibing, 2009. "Bootstrap tests for structural change with infinite variance observations," Statistics & Probability Letters, Elsevier, vol. 79(19), pages 1985-1995, October.
    11. Liu, Weiqiang, 2023. "A consistent nonparametric test for the structure change in quantile regression," Economics Letters, Elsevier, vol. 228(C).
    12. Zhou, Mi & Wang, Huixia Judy & Tang, Yanlin, 2015. "Sequential change point detection in linear quantile regression models," Statistics & Probability Letters, Elsevier, vol. 100(C), pages 98-103.
    13. Alexander Aue & Rex C. Y. Cheung & Thomas C. M. Lee & Ming Zhong, 2014. "Segmented Model Selection in Quantile Regression Using the Minimum Description Length Principle," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(507), pages 1241-1256, September.

  68. Su, Liangjun & White, Halbert, 2007. "A consistent characteristic function-based test for conditional independence," Journal of Econometrics, Elsevier, vol. 141(2), pages 807-834, December.
    See citations under working paper version above.
  69. Su, Liangjun & Ullah, Aman, 2007. "More efficient estimation of nonparametric panel data models with random effects," Economics Letters, Elsevier, vol. 96(3), pages 375-380, September.

    Cited by:

    1. Lee, Lung-fei & Yu, Jihai, 2015. "Estimation of fixed effects panel regression models with separable and nonseparable space–time filters," Journal of Econometrics, Elsevier, vol. 184(1), pages 174-192.
    2. Qian, Junhui & Wang, Le, 2009. "Estimating Semiparametric Panel Data Models by Marginal Integration," MPRA Paper 18850, University Library of Munich, Germany.
    3. Bang-Qiang He & Xing-Jian Hong & Guo-Liang Fan, 2020. "Penalized empirical likelihood for partially linear errors-in-variables panel data models with fixed effects," Statistical Papers, Springer, vol. 61(6), pages 2351-2381, December.
    4. Tomasz Czekaj & Arne Henningsen, 2013. "Panel Data Specifications in Nonparametric Kernel Regression: An Application to Production Functions," IFRO Working Paper 2013/5, University of Copenhagen, Department of Food and Resource Economics.
    5. Christopher F. Parmeter & Jeffrey S. Racine, 2018. "Nonparametric Estimation and Inference for Panel Data Models," Department of Economics Working Papers 2018-02, McMaster University.
    6. Bin Zhou & Qinfeng Xu & Jinhong You, 2011. "Efficient estimation for error component seemingly unrelated nonparametric regression models," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 73(1), pages 121-138, January.
    7. Shujie Ma & Jeffrey S. Racine & Aman Ullah, 2015. "Nonparametric Regression-Spline Random Effects Models," Department of Economics Working Papers 2015-10, McMaster University.
    8. Li, Gaorong & Peng, Heng & Tong, Tiejun, 2013. "Simultaneous confidence band for nonparametric fixed effects panel data models," Economics Letters, Elsevier, vol. 119(3), pages 229-232.
    9. Serfas, D., 2018. "an ex-post econometric analysis of the abolishment of the canadian wheat board," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 277286, International Association of Agricultural Economists.
    10. Bosupeng, Mpho, 2015. "Exports Multiplicity and The Dutch Disease," MPRA Paper 77919, University Library of Munich, Germany, revised 2015.
    11. Gholamreza Hajargasht, 2009. "Nonparametric Panel Data Models, A Penalized Spline Approach," CEPA Working Papers Series WP052009, School of Economics, University of Queensland, Australia.
    12. Liangjun Su & Aman Ullah & Yun Wang, 2013. "Nonparametric regression estimation with general parametric error covariance: a more efficient two-step estimator," Empirical Economics, Springer, vol. 45(2), pages 1009-1024, October.

  70. Su, Liangjun, 2006. "A simple test for multivariate conditional symmetry," Economics Letters, Elsevier, vol. 93(3), pages 374-378, December.

    Cited by:

    1. Nadarajah, Saralees & Chan, Stephen & Afuecheta, Emmanuel, 2013. "On the characteristic function for asymmetric Student t distributions," Economics Letters, Elsevier, vol. 121(2), pages 271-274.
    2. Henderson, Daniel J. & Parmeter, Christopher F., 2015. "A consistent bootstrap procedure for nonparametric symmetry tests," Economics Letters, Elsevier, vol. 131(C), pages 78-82.
    3. Niu, Cuizhen & Guo, Xu & Li, Yong & Zhu, Lixing, 2018. "Pairwise distance-based tests for conditional symmetry," Computational Statistics & Data Analysis, Elsevier, vol. 128(C), pages 145-162.
    4. Šárka Hudecová & Miroslav Šiman, 2021. "Testing symmetry around a subspace," Statistical Papers, Springer, vol. 62(5), pages 2491-2508, October.

  71. Sainan Jin & Wanjun Jiang & Liangjun Su & Jianying Hu, 2006. "The Rise in House Prices in China: Bubbles or Fundamentals?," Economics Bulletin, AccessEcon, vol. 3(7), pages 1-8.

    Cited by:

    1. Leung, Charles Ka Yui & Tang, Edward Chi Ho, 2013. "Speculating China economic growth through Hong Kong? Evidence from the stock market IPO and real estate markets," MPRA Paper 46346, University Library of Munich, Germany.
    2. Mantu Kumar Mahalik & Hrushikesh Mallick, 2016. "Are house prices guided by fundamentals or speculative factors? An empirical inquiry for India," International Journal of Economic Policy in Emerging Economies, Inderscience Enterprises Ltd, vol. 9(1), pages 47-64.
    3. Iris Claus & Les Oxley & Jie Chen & Xuehui Han, 2014. "The Evolution Of The Housing Market And Its Socioeconomic Impacts In The Post-Reform People'S Republic Of China: A Survey Of The Literature," Journal of Economic Surveys, Wiley Blackwell, vol. 28(4), pages 652-670, September.
    4. Lilia Karnizova, 2013. "Letting the speculative and the news views of the Japanese business cycle compete," Economics Bulletin, AccessEcon, vol. 33(2), pages 1146-1158.
    5. Alessio Ciarlone, 2012. "House price cycles in emerging economies," Temi di discussione (Economic working papers) 863, Bank of Italy, Economic Research and International Relations Area.
    6. Mei Liu & Qing-Ping Ma, 2021. "Determinants of house prices in China: a panel-corrected regression approach," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 67(1), pages 47-72, August.
    7. Mary Riddel, 2011. "Are Housing Bubbles Contagious? A Case Study of Las Vegas and Los Angeles Home Prices," Land Economics, University of Wisconsin Press, vol. 87(1), pages 126-144.

  72. Su, Liangjun & Ullah, Aman, 2006. "Profile likelihood estimation of partially linear panel data models with fixed effects," Economics Letters, Elsevier, vol. 92(1), pages 75-81, July.

    Cited by:

    1. António Afonso & Michael G. Arghyrou & María Dolores Gadea & Alexandros Kontonikas, 2017. ""Whatever it takes" to resolve the European sovereign debt crisis? Bond pricing regime switches and monetary policy effects," Working Papers REM 2017/02, ISEG - Lisbon School of Economics and Management, REM, Universidade de Lisboa.
    2. Andreas Heinen & M. Hamadi, 2015. "Firm Performance when Ownership is very Concentrated: Evidence from a Semiparametric Panel," Post-Print hal-02979991, HAL.
    3. Su, Liangjun, 2012. "Semiparametric GMM estimation of spatial autoregressive models," Journal of Econometrics, Elsevier, vol. 167(2), pages 543-560.
    4. Baglan, Deniz & Ege Yazgan, M. & Yilmazkuday, Hakan, 2016. "Relative price variability and inflation: New evidence," Journal of Macroeconomics, Elsevier, vol. 48(C), pages 263-282.
    5. Bernoth, Kerstin & Erdogan, Burcu, 2010. "Sovereign bond yield spreads: a time-varying coefficient approach," Discussion Papers 289, European University Viadrina Frankfurt (Oder), Department of Business Administration and Economics.
    6. Zhang, Junhua & Feng, Sanying & Li, Gaorong & Lian, Heng, 2011. "Empirical likelihood inference for partially linear panel data models with fixed effects," Economics Letters, Elsevier, vol. 113(2), pages 165-167.
    7. Musolesi Antonio & Mazzanti Massimiliano, 2014. "Nonlinearity, heterogeneity and unobserved effects in the carbon dioxide emissions-economic development relation for advanced countries," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 18(5), pages 521-541, December.
    8. Baglan, Deniz & Yoldas, Emre, 2014. "Non-linearity in the inflation–growth relationship in developing economies: Evidence from a semiparametric panel model," Economics Letters, Elsevier, vol. 125(1), pages 93-96.
    9. Benjamin Owusu & Bettina Bökemeier & Alfred Greiner, 2023. "Assessing nonlinearities and heterogeneity in debt sustainability analysis: a panel spline approach," Empirical Economics, Springer, vol. 64(3), pages 1315-1346, March.
    10. Zhou, Jianhua & Parmeter, Christopher F. & Kumbhakar, Subal C., 2020. "Nonparametric estimation of the determinants of inefficiency in the presence of firm heterogeneity," European Journal of Operational Research, Elsevier, vol. 286(3), pages 1142-1152.
    11. Jia Chen & Jiti Gao & Degui Li, 2011. "Semiparametric Trending Panel Data Models with Cross-Sectional Dependence," Monash Econometrics and Business Statistics Working Papers 15/11, Monash University, Department of Econometrics and Business Statistics.
    12. Elkhan Richard Sadik-Zada & Wilhelm Loewenstein, 2020. "Drivers of CO 2 -Emissions in Fossil Fuel Abundant Settings: (Pooled) Mean Group and Nonparametric Panel Analyses," Energies, MDPI, vol. 13(15), pages 1-24, August.
    13. Xuan Liang & Jiti Gao & Xiaodong Gong, 2019. "Time-Varying Coefficient Spatial Autoregressive Panel Data Model with Fixed Effects," Monash Econometrics and Business Statistics Working Papers 26/19, Monash University, Department of Econometrics and Business Statistics.
    14. Qian, Junhui & Wang, Le, 2009. "Estimating Semiparametric Panel Data Models by Marginal Integration," MPRA Paper 18850, University Library of Munich, Germany.
    15. Bang-Qiang He & Xing-Jian Hong & Guo-Liang Fan, 2020. "Penalized empirical likelihood for partially linear errors-in-variables panel data models with fixed effects," Statistical Papers, Springer, vol. 61(6), pages 2351-2381, December.
    16. Henderson, Daniel J. & Carroll, Raymond J. & Li, Qi, 2008. "Nonparametric estimation and testing of fixed effects panel data models," Journal of Econometrics, Elsevier, vol. 144(1), pages 257-275, May.
    17. Minzhi Wu & Emili Tortosa-Ausina, 2020. "Bank Diversification and Focus in Disruptive Times: China, 2007–2018," Working Papers 2020/21, Economics Department, Universitat Jaume I, Castellón (Spain).
    18. Arghyrou, Michael G & Gadea, Mar a Dolores, 2019. "Private bank deposits and macro/fiscal risk in the euro-area," Cardiff Economics Working Papers E2019/6, Cardiff University, Cardiff Business School, Economics Section.
    19. Geng, Xin & Janssens, Wendy & Kramer, Berber, 2018. "Liquid milk: Cash Constraints and Recurring Savings among Dairy Farmers in Kenya," 2018 Annual Meeting, August 5-7, Washington, D.C. 273823, Agricultural and Applied Economics Association.
    20. Rui Li & Yuanyuan Zhang, 2021. "Two-stage estimation and simultaneous confidence band in partially nonlinear additive model," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 84(8), pages 1109-1140, November.
    21. Suigen Yang & Xiujuan Yang & Xuefei Wang, 2024. "Estimation and Simultaneous Confidence Bands for Fixed-Effects Panel Data Partially Linear Models," Mathematics, MDPI, vol. 12(23), pages 1-18, November.
    22. Hu, Xuemei, 2017. "Semi-parametric inference for semi-varying coefficient panel data model with individual effects," Journal of Multivariate Analysis, Elsevier, vol. 154(C), pages 262-281.
    23. Pei, Youquan & Huang, Tao & You, Jinhong, 2018. "Nonparametric fixed effects model for panel data with locally stationary regressors," Journal of Econometrics, Elsevier, vol. 202(2), pages 286-305.
    24. Mingming Jiang, 2014. "Saving–investment Association and Regional Capital Mobility in China: A Nonparametric Panel Approach," Pacific Economic Review, Wiley Blackwell, vol. 19(2), pages 184-200, May.
    25. Malikov, Emir & Kumbhakar, Subal C. & Sun, Yiguo, 2013. "Varying Coefficient Panel Data Model in the Presence of Endogenous Selectivity and Fixed Effects," MPRA Paper 55993, University Library of Munich, Germany.
    26. Christopher F. Parmeter & Jeffrey S. Racine, 2018. "Nonparametric Estimation and Inference for Panel Data Models," Department of Economics Working Papers 2018-02, McMaster University.
    27. Zhang, Junjie & Wang, Can, 2011. "Co-benefits and additionality of the clean development mechanism: An empirical analysis," Journal of Environmental Economics and Management, Elsevier, vol. 62(2), pages 140-154, September.
    28. Wei, Chuanhua & Guo, Shuang & Zhai, Shufen, 2017. "Statistical inference of partially linear varying coefficient spatial autoregressive models," Economic Modelling, Elsevier, vol. 64(C), pages 553-559.
    29. Geng, Xin & Janssens, Wendy & Kramer, Berber, 2023. "Liquid milk: Savings, insurance and side-selling in cooperatives," Journal of Development Economics, Elsevier, vol. 165(C).
    30. Aman Ullah & Yoonseok Lee & Debasri Mukherjee, 2018. "Nonparametric Estimation of the Marginal Effect in Fixed-Effect Panel Data Models," Working Papers 201901, University of California at Riverside, Department of Economics.
    31. Xuan, Liang & Jiti, Gao & xiaodong, Gong, 2021. "Semiparametric Spatial Autoregressive Panel Data Model with Fixed Effects and Time-Varying Coefficients," MPRA Paper 108497, University Library of Munich, Germany, revised 30 May 2021.
    32. G. Arghyrou, Michael & Gadea, Maria-Dolores & Kontonikas, Alexandros, 2024. "Private bank deposits and macro/fiscal risk in the euro-area," Journal of International Money and Finance, Elsevier, vol. 140(C).
    33. Gong, Binlei, 2018. "Agricultural reforms and production in China: Changes in provincial production function and productivity in 1978–2015," Journal of Development Economics, Elsevier, vol. 132(C), pages 18-31.
    34. Yichen Gao & Kunpeng Li, 2013. "Nonparametric estimation of fixed effects panel data models," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 25(3), pages 679-693, September.
    35. Aman Ullah & Tao Wang & Weixin Yao, 2021. "Modal regression for fixed effects panel data," Empirical Economics, Springer, vol. 60(1), pages 261-308, January.
    36. Baglan Deniz & Yoldas Emre, 2016. "Public debt and macroeconomic activity: a predictive analysis for advanced economies," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 20(3), pages 301-324, June.
    37. He, Bang-Qiang & Hong, Xing-Jian & Fan, Guo-Liang, 2017. "Block empirical likelihood for partially linear panel data models with fixed effects," Statistics & Probability Letters, Elsevier, vol. 123(C), pages 128-138.
    38. Masato Nishiwaki & Hyoeg Ug Kwon, 2013. "Are Losers Picked? An Empirical Analysis of Capacity Divestment and Production Reallocation in the Japanese Cement Industry," Journal of Industrial Economics, Wiley Blackwell, vol. 61(2), pages 430-467, June.
    39. Daniel J. Henderson, 2010. "A test for multimodality of regression derivatives with application to nonparametric growth regressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(3), pages 458-480.
    40. Tae-Hwy Lee & Bai Huang & Aman Ullah, 2018. "Combined Estimation of Semiparametric Panel Data Models," Working Papers 201915, University of California at Riverside, Department of Economics.
    41. Hao Xu & Peilin Wang & Kai Ding, 2024. "Transforming Agriculture: Empirical Insights into How the Digital Economy Elevates Agricultural Productivity in China," Sustainability, MDPI, vol. 16(23), pages 1-20, November.
    42. Li, Gaorong & Peng, Heng & Tong, Tiejun, 2013. "Simultaneous confidence band for nonparametric fixed effects panel data models," Economics Letters, Elsevier, vol. 119(3), pages 229-232.
    43. Li, Rui & Wan, Alan T.K. & You, Jinhong, 2016. "Semiparametric GMM estimation and variable selection in dynamic panel data models with fixed effects," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 401-423.
    44. Taining Wang & Feng Yao & Subal C. Kumbhakar, 2024. "A flexible stochastic production frontier model with panel data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(4), pages 564-588, June.
    45. Peter Pütz & Thomas Kneib, 2016. "A Penalized Spline Estimator for Fixed Effects Panel Data Models," SOEPpapers on Multidisciplinary Panel Data Research 827, DIW Berlin, The German Socio-Economic Panel (SOEP).
    46. Li, Cong & Liang, Zhongwen, 2015. "Asymptotics for nonparametric and semiparametric fixed effects panel models," Journal of Econometrics, Elsevier, vol. 185(2), pages 420-434.
    47. Feng, Sanying & He, Wenqi & Li, Feng, 2020. "Model detection and estimation for varying coefficient panel data models with fixed effects," Computational Statistics & Data Analysis, Elsevier, vol. 152(C).
    48. Su, Liangjun & Lu, Xun, 2013. "Nonparametric dynamic panel data models: Kernel estimation and specification testing," Journal of Econometrics, Elsevier, vol. 176(2), pages 112-133.
    49. Zongwu Cai & Linna Chen & Ying Fang, 2015. "Semiparametric Estimation of Partially Varying-Coefficient Dynamic Panel Data Models," Econometric Reviews, Taylor & Francis Journals, vol. 34(6-10), pages 695-719, December.
    50. Mishra, Sagarika & Narayan, Paresh Kumar, 2015. "A nonparametric model of financial system and economic growth," International Review of Economics & Finance, Elsevier, vol. 39(C), pages 175-191.
    51. Peter Pütz & Thomas Kneib, 2018. "A penalized spline estimator for fixed effects panel data models," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 102(2), pages 145-166, April.
    52. Ma, Shujie & Liang, Hua & Tsai, Chih-Ling, 2014. "Partially linear single index models for repeated measurements," Journal of Multivariate Analysis, Elsevier, vol. 130(C), pages 354-375.
    53. Xuemei Hu & Weiming Yang, 2019. "Semi-parametric small area inference in generalized semi-varying coefficient mixed effects models," Statistical Papers, Springer, vol. 60(4), pages 1039-1058, August.
    54. Lai, Peng & Li, Gaorong & Lian, Heng, 2013. "Semiparametric estimation of fixed effects panel data single-index model," Statistics & Probability Letters, Elsevier, vol. 83(6), pages 1595-1602.
    55. Bogui Li & Jianbao Chen & Shuangshuang Li, 2023. "Estimation of Fixed Effects Partially Linear Varying Coefficient Panel Data Regression Model with Nonseparable Space-Time Filters," Mathematics, MDPI, vol. 11(6), pages 1-24, March.
    56. Geng, Xin & Janssens, Wendy & Kramer, Berber N., 2017. "Liquid milk: Cash constraints and day-to-day intertemporal choice in financial diaries," IFPRI discussion papers 1602, International Food Policy Research Institute (IFPRI).
    57. De Monte Enrico, 2024. "Nonparametric Instrumental Regression with Two-Way Fixed Effects," Journal of Econometric Methods, De Gruyter, vol. 13(1), pages 49-66, January.
    58. Syed F. Mahmud & Murat Tiniç, 2018. "Herding in Chinese stock markets: a nonparametric approach," Empirical Economics, Springer, vol. 55(2), pages 679-711, September.
    59. Halder, Shaymal C. & Malikov, Emir, 2020. "Smoothed LSDV estimation of functional-coefficient panel data models with two-way fixed effects," Economics Letters, Elsevier, vol. 192(C).
    60. Lin, Zhongjian & Li, Qi & Sun, Yiguo, 2014. "A consistent nonparametric test of parametric regression functional form in fixed effects panel data models," Journal of Econometrics, Elsevier, vol. 178(P1), pages 167-179.
    61. Taining Wang & Jinjing Tian, 2020. "Recasting the trade impact on labor share: a fixed-effect semiparametric estimation study," Empirical Economics, Springer, vol. 58(5), pages 2465-2511, May.

  73. Su, Liangjun & Ullah, Aman, 2006. "More Efficient Estimation In Nonparametric Regression With Nonparametric Autocorrelated Errors," Econometric Theory, Cambridge University Press, vol. 22(1), pages 98-126, February.

    Cited by:

    1. Ioannis Kyriakou & Parastoo Mousavi & Jens Perch Nielsen & Michael Scholz, 2020. "Longer-Term Forecasting of Excess Stock Returns—The Five-Year Case," Mathematics, MDPI, vol. 8(6), pages 1-20, June.
    2. Ioannis Kyriakou & Parastoo Mousavi & Jens Perch Nielsen & Michael Scholz, 2021. "Short-Term Exuberance and Long-Term Stability: A Simultaneous Optimization of Stock Return Predictions for Short and Long Horizons," Mathematics, MDPI, vol. 9(6), pages 1-19, March.
    3. Liangjun Su & Stefan Hoderlein & Halbert White, 2013. "Testing Monotonicity in Unobservables with Panel Data," Boston College Working Papers in Economics 892, Boston College Department of Economics, revised 01 Feb 2016.
    4. Wei, Honglei & Zhang, Hongfan & Jiang, Hui & Huang, Lei, 2022. "On the semi-varying coefficient dynamic panel data model with autocorrelated errors," Computational Statistics & Data Analysis, Elsevier, vol. 173(C).
    5. Martins-Filho, Carlos & Yao, Feng, 2009. "Nonparametric regression estimation with general parametric error covariance," Journal of Multivariate Analysis, Elsevier, vol. 100(3), pages 309-333, March.
    6. Su, Liangjun & Ullah, Aman, 2008. "Local polynomial estimation of nonparametric simultaneous equations models," Journal of Econometrics, Elsevier, vol. 144(1), pages 193-218, May.
    7. Linton, Oliver & Xiao, Zhijie, 2019. "Efficient estimation of nonparametric regression in the presence of dynamic heteroskedasticity," Journal of Econometrics, Elsevier, vol. 213(2), pages 608-631.
    8. Ke Yang, 2012. "Multivariate Local Polynomial Regression With Autocorrelated Errors," Economics Bulletin, AccessEcon, vol. 32(4), pages 3298-3305.
    9. David Jacho-Chavez & Arthur Lewbel & Oliver Linton, 2006. "Identification and Nonparametric Estimation of a Transformed Additively Separable Model," Boston College Working Papers in Economics 652, Boston College Department of Economics, revised 26 Nov 2008.
    10. Liu, Jun M. & Chen, Rong & Yao, Qiwei, 2010. "Nonparametric transfer function models," Journal of Econometrics, Elsevier, vol. 157(1), pages 151-164, July.
    11. Tanujit Dey & Kun Ho Kim & Chae Young Lim, 2018. "Bayesian time series regression with nonparametric modeling of autocorrelation," Computational Statistics, Springer, vol. 33(4), pages 1715-1731, December.
    12. Su, Liangjun & Lu, Xun, 2013. "Nonparametric dynamic panel data models: Kernel estimation and specification testing," Journal of Econometrics, Elsevier, vol. 176(2), pages 112-133.
    13. Enno Mammen & Jens Perch Nielsen & Michael Scholz & Stefan Sperlich, 2019. "Conditional Variance Forecasts for Long-Term Stock Returns," Risks, MDPI, vol. 7(4), pages 1-22, November.
    14. Ioannis Kyriakou & Parastoo Mousavi & Jens Perch Nielsen & Michael Scholz, 2019. "Machine Learning for Forecasting Excess Stock Returns The Five-Year-View," Graz Economics Papers 2019-06, University of Graz, Department of Economics.
    15. Ioannis Kyriakou & Parastoo Mousavi & Jens Perch Nielsen & Michael Scholz, 2020. "Short-Term Exuberance and long-term stability: A simultaneous optimization of stock return predictions for short and long horizons," Graz Economics Papers 2020-20, University of Graz, Department of Economics.
    16. Qi Li & Jeffrey Scott Racine, 2006. "Nonparametric Econometrics: Theory and Practice," Economics Books, Princeton University Press, edition 1, volume 1, number 8355.
    17. Liangjun Su & Aman Ullah & Yun Wang, 2013. "Nonparametric regression estimation with general parametric error covariance: a more efficient two-step estimator," Empirical Economics, Springer, vol. 45(2), pages 1009-1024, October.

  74. Liangjun Su & Sainan Jin, 2005. "A Bootstrap Test for Conditional Symmetry," Annals of Economics and Finance, Society for AEF, vol. 6(2), pages 251-261, November.

    Cited by:

    1. Henderson, Daniel J. & Parmeter, Christopher F., 2015. "A consistent bootstrap procedure for nonparametric symmetry tests," Economics Letters, Elsevier, vol. 131(C), pages 78-82.

Chapters

  1. Liangjun Su & Yonghui Zhang, 2016. "Semiparametric Estimation of Partially Linear Dynamic Panel Data Models with Fixed Effects," Advances in Econometrics, in: Essays in Honor of Aman Ullah, volume 36, pages 137-204, Emerald Group Publishing Limited.

    Cited by:

    1. Chiang, Harold D. & Rodrigue, Joel & Sasaki, Yuya, 2023. "Post-Selection Inference In Three-Dimensional Panel Data," Econometric Theory, Cambridge University Press, vol. 39(3), pages 623-658, June.
    2. Hsiao, Cheng, 2018. "Panel models with interactive effects," Journal of Econometrics, Elsevier, vol. 206(2), pages 645-673.
    3. Wei, Honglei & Zhang, Hongfan & Jiang, Hui & Huang, Lei, 2022. "On the semi-varying coefficient dynamic panel data model with autocorrelated errors," Computational Statistics & Data Analysis, Elsevier, vol. 173(C).
    4. Ruiqi Liu & Ben Boukai & Zuofeng Shang, 2019. "Statistical Inference on Partially Linear Panel Model under Unobserved Linearity," Papers 1911.08830, arXiv.org.
    5. Huang, Wenxin & Jin, Sainan & Phillips, Peter C.B. & Su, Liangjun, 2020. "Nonstationary Panel Models with Latent Group Structures and Cross-Section Dependence," Economics and Statistics Working Papers 7-2020, Singapore Management University, School of Economics.
    6. Ye, Xiaoqing & Xu, Juan & Wu, Xiangjun, 2018. "Estimation of an unbalanced panel data Tobit model with interactive effects," Journal of choice modelling, Elsevier, vol. 28(C), pages 108-123.
    7. T. Thomson & S. Hossain, 2018. "Efficient Shrinkage for Generalized Linear Mixed Models Under Linear Restrictions," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 80(2), pages 385-410, August.
    8. Ayden Higgins & Federico Martellosio, 2019. "Shrinkage Estimation of Network Spillovers with Factor Structured Errors," Papers 1909.02823, arXiv.org, revised Nov 2021.
    9. Hyungsik Roger Moon & Martin Weidner, 2019. "Nuclear norm regularized estimation of panel regression models," CeMMAP working papers CWP14/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    10. Vogt, M. & Walsh, C. & Linton, O., 2022. "CCE Estimation of High-Dimensional Panel Data Models with Interactive Fixed Effects," Janeway Institute Working Papers 2218, Faculty of Economics, University of Cambridge.
    11. Feng, Guohua & Gao, Jiti & Peng, Bin, 2022. "An integrated panel data approach to modelling economic growth," Journal of Econometrics, Elsevier, vol. 228(2), pages 379-397.
    12. Yufeng Mao & Bin Peng & Mervyn J Silvapulle & Param Silvapulle & Yanrong Yang, 2021. "Decomposition of Bilateral Trade Flows Using a Three-Dimensional Panel Data Model," Monash Econometrics and Business Statistics Working Papers 7/21, Monash University, Department of Econometrics and Business Statistics.
    13. Cheng Hsiao & Yimeng Xie & Qiankun Zhou, 2021. "Factor dimension determination for panel interactive effects models: an orthogonal projection approach," Computational Statistics, Springer, vol. 36(2), pages 1481-1497, June.
    14. Yuki Takara & Shingo Takagi, 2023. "An empirical approach to measure unobserved cultural relations using music trade data," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 47(2), pages 205-245, June.

  2. Liangjun Su & Halbert L. White, 2012. "Conditional Independence Specification Testing for Dependent Processes with Local Polynomial Quantile Regression," Advances in Econometrics, in: Essays in Honor of Jerry Hausman, pages 355-434, Emerald Group Publishing Limited.

    Cited by:

    1. O‐Chia Chuang & Xiaojun Song & Abderrahim Taamouti, 2022. "Testing for Asymmetric Comovements," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 84(5), pages 1153-1180, October.

  3. Liangjun Su & Ye Chen & Aman Ullah, 2009. "Functional coefficient estimation with both categorical and continuous data," Advances in Econometrics, in: Nonparametric Econometric Methods, pages 131-167, Emerald Group Publishing Limited.

    Cited by:

    1. Tae-Hwy Lee & Shahnaz Parsaeian & Aman Ullah, 2022. "Forecasting under Structural Breaks Using Improved Weighted Estimation," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202212, University of Kansas, Department of Economics.

Books

  1. Racine, Jeffrey & Su, Liangjun & Ullah, Aman, 2014. "The Oxford Handbook of Applied Nonparametric and Semiparametric Econometrics and Statistics," OUP Catalogue, Oxford University Press, number 9780199857944.

    Cited by:

    1. Aman Ullah & Huansha Wang, 2013. "Parametric and Nonparametric Frequentist Model Selection and Model Averaging," Econometrics, MDPI, vol. 1(2), pages 1-23, September.
    2. Arthur Lewbel & Xun Tang, 2012. "Identification and Estimation of Games with Incomplete Information Using Excluded Regressors," Boston College Working Papers in Economics 808, Boston College Department of Economics, revised 05 Mar 2013.
    3. Hwang, Jungbin & Sun, Yixiao, 2016. "Simple, Robust, and Accurate F and t Tests in Cointegrated Systems," University of California at San Diego, Economics Working Paper Series qt82k1x4rd, Department of Economics, UC San Diego.
    4. Abdelaati Daouia & Jean-Pierre Florens & Léopold Simar, 2020. "Robust frontier estimation from noisy data: a Tikhonov regularization approach," Post-Print hal-02573853, HAL.
    5. Steven F. Koch & Jeffrey S. Racine, 2013. "Health Care Facility Choice and User Fee Abolition: Regression Discontinuity in a Multinomial Choice Setting," Working Papers 201353, University of Pretoria, Department of Economics.
    6. Deniz Ozabaci & Daniel Henderson, 2015. "Additive kernel estimates of returns to schooling," Empirical Economics, Springer, vol. 48(1), pages 227-251, February.
    7. Alexandra Ferreira‐Lopes & Luís Filipe Martins & Ruben Espanhol, 2020. "The relationship between tax rates and tax revenues in eurozone member countries ‐ exploring the Laffer curve," Bulletin of Economic Research, Wiley Blackwell, vol. 72(2), pages 121-145, April.
    8. Simioni, Michel & Thomas-Agnan, Christine & Trinh, Thi-Huong, 2017. "Calorie intake and income in China: New evidence using semiparametric modelling with generalized additive models," TSE Working Papers 17-826, Toulouse School of Economics (TSE).
    9. Arthur Lewbel, 2018. "The Identification Zoo - Meanings of Identification in Econometrics," Boston College Working Papers in Economics 957, Boston College Department of Economics, revised 14 Dec 2019.
    10. Feeny, Simon & Vuong, Vu, 2017. "Explaining Aid Project and Program Success: Findings from Asian Development Bank Interventions," World Development, Elsevier, vol. 90(C), pages 329-343.
    11. Pablo Mitnik & Victoria Bryant & David Grusky, 2018. "A Very Uneven Playing Field: Economic Mobility in the United States," Working Papers 2018-097, Human Capital and Economic Opportunity Working Group.
    12. Xavier D'Haultfoeuille & Arnaud Maurel & Yichong Zhang, 2014. "Extremal Quantile Regressions for Selection Models and the Black-White Wage Gap," NBER Working Papers 20257, National Bureau of Economic Research, Inc.
    13. Patrick Saart & Jiti Gao, 2012. "Semiparametric Methods in Nonlinear Time Series Analysis: A Selective Review," Monash Econometrics and Business Statistics Working Papers 21/12, Monash University, Department of Econometrics and Business Statistics.
    14. Lewbel, Arthur & Yang, Thomas Tao, 2016. "Identifying the average treatment effect in ordered treatment models without unconfoundedness," Journal of Econometrics, Elsevier, vol. 195(1), pages 1-22.
    15. Isabel Proença & Stefan Sperlich & Duygu Savaşcı, 2015. "Semi-mixed effects gravity models for bilateral trade," Empirical Economics, Springer, vol. 48(1), pages 361-387, February.
    16. Lewbel, Arthur & Lu, Xun & Su, Liangjun, 2015. "Specification testing for transformation models with an application to generalized accelerated failure-time models," Journal of Econometrics, Elsevier, vol. 184(1), pages 81-96.
    17. Steven Berry & Philip Haile, 2023. "Nonparametric Identification of Differentiated Products Demand Using Micro Data," Cowles Foundation Discussion Papers 2357, Cowles Foundation for Research in Economics, Yale University.
    18. Härdle, Wolfgang Karl & Prastyo, Dedy Dwi, 2013. "Default risk calculation based on predictor selection for the Southeast Asian industry," SFB 649 Discussion Papers 2013-037, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    19. Daniel J. Henderson & Léopold Simar & Le Wang, 2017. "The three s of public schools: irrelevant inputs, insufficient resources and inefficiency," Applied Economics, Taylor & Francis Journals, vol. 49(12), pages 1164-1184, March.
    20. Stefan Faridani, 2024. "Testing for Underpowered Literatures," Papers 2406.13122, arXiv.org.
    21. Xu, Ke-Li, 2018. "A semi-nonparametric estimator of regression discontinuity design with discrete duration outcomes," Journal of Econometrics, Elsevier, vol. 206(1), pages 258-278.
    22. Lu, Xun & Su, Liangjun, 2015. "Jackknife model averaging for quantile regressions," Journal of Econometrics, Elsevier, vol. 188(1), pages 40-58.
    23. Etayibtalnam Koudjom & Boris O. K. Lokonon & Aklesso Y. G. Egbendewe, 2024. "Climate Change, Malaria Prevalence and Cereal Yields in Sub-Saharan Africa," The European Journal of Development Research, Palgrave Macmillan;European Association of Development Research and Training Institutes (EADI), vol. 36(5), pages 1171-1197, October.
    24. Geraldine Henningsen & Arne Henningsen & Christian Henning, 2015. "Transaction costs and social networks in productivity measurement," Empirical Economics, Springer, vol. 48(1), pages 493-515, February.
    25. Dedy Dwi Prastyo & Härdle, Wolfgang Karl, 2014. "Localising forward intensities for multiperiod corporate default," SFB 649 Discussion Papers 2014-040, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    26. Nir Billfeld & Moshe Kim, 2019. "Semiparametric correction for endogenous truncation bias with Vox Populi based participation decision," Papers 1902.06286, arXiv.org.
    27. Michael S. Delgado & Nadine McCloud, 2017. "Foreign direct investment and the domestic capital stock: the good–bad role of higher institutional quality," Empirical Economics, Springer, vol. 53(4), pages 1587-1637, December.
    28. Olesen, O.B. & Ruggiero, J., 2018. "An improved Afriat–Diewert–Parkan nonparametric production function estimator," European Journal of Operational Research, Elsevier, vol. 264(3), pages 1172-1188.
    29. Simioni, Michel & Thomas-Agnan, Christine & Trinh, Thi-Huong, 2017. "A Fresh Look at the Nutrition Transition in Vietnam using Semiparametric Modeling," TSE Working Papers 17-842, Toulouse School of Economics (TSE).

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