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Sainan Jin

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. 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. 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.
    2. Bin Ping & Liangju Su & Yanrong Yang & Joakim Westerlund, 2023. "Interactive-effects panel-data models with general factors and regressors," French Stata Users' Group Meetings 2023 14, Stata Users Group.
    3. Yanbo Liu & Peter C. B. Phillips & Jun Yu, 2022. "A Panel Clustering Approach to Analyzing Bubble Behavior," Cowles Foundation Discussion Papers 2323, Cowles Foundation for Research in Economics, Yale University.
    4. Jiti Gao & Oliver Linton & Bin Peng, 2022. "A Nonparametric Panel Model for Climate Data with Seasonal and Spatial Variation," Monash Econometrics and Business Statistics Working Papers 9/22, Monash University, Department of Econometrics and Business Statistics.
    5. Saptorshee Kanto Chakraborty & Massimiliano Mazzanti, 2021. "Revisiting the literature on the dynamic Environmental Kuznets Curves using a latent structure approach," SEEDS Working Papers 0521, SEEDS, Sustainability Environmental Economics and Dynamics Studies, revised May 2021.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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).

  2. 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. Chaohua Dong & Jiti Gao & Oliver Linton & Bin Peng, 2020. "On the Time Trend of COVID-19: A Panel Data Study," Papers 2006.11060, arXiv.org, revised Jun 2020.
    2. 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).
    3. Artūras Juodis & Simas Kučinskas, 2023. "Quantifying noise in survey expectations," Quantitative Economics, Econometric Society, vol. 14(2), pages 609-650, May.
    4. 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.
    5. 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.
    6. Cahan, Ercument & Bai, Jushan & Ng, Serena, 2023. "Factor-based imputation of missing values and covariances in panel data of large dimensions," Journal of Econometrics, Elsevier, vol. 233(1), pages 113-131.
    7. 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).
    8. 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).
    9. 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.
    10. Yinchu Zhu, 2019. "How well can we learn large factor models without assuming strong factors?," Papers 1910.10382, arXiv.org, revised Nov 2019.
    11. 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.
    12. Jianqing Fan & Kunpeng Li & Yuan Liao, 2020. "Recent Developments on Factor Models and its Applications in Econometric Learning," Papers 2009.10103, arXiv.org.
    13. Jiti Gao & Oliver Linton & Bin Peng, 2022. "A Nonparametric Panel Model for Climate Data with Seasonal and Spatial Variation," Monash Econometrics and Business Statistics Working Papers 9/22, Monash University, Department of Econometrics and Business Statistics.
    14. Junting Duan & Markus Pelger & Ruoxuan Xiong, 2023. "Target PCA: Transfer Learning Large Dimensional Panel Data," Papers 2308.15627, arXiv.org.
    15. 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).
    16. 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).
    17. 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.
    18. Serena Ng & Susannah Scanlan, 2023. "Constructing High Frequency Economic Indicators by Imputation," Papers 2303.01863, arXiv.org, revised Oct 2023.
    19. Victor Chernozhukov & Christian Hansen & Yuan Liao & Yinchu Zhu, 2021. "Inference for Low-Rank Models," Papers 2107.02602, arXiv.org, revised Jan 2023.
    20. 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.

  3. 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. 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.
    2. 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).
    3. Saptorshee Kanto Chakraborty & Massimiliano Mazzanti, 2021. "Revisiting the literature on the dynamic Environmental Kuznets Curves using a latent structure approach," SEEDS Working Papers 0521, SEEDS, Sustainability Environmental Economics and Dynamics Studies, revised May 2021.
    4. 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.
    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.

  4. Peter C. B. Phillips & Sainan Jin, 2015. "Business Cycles, Trend Elimination, and the HP Filter," Cowles Foundation Discussion Papers 2005, Cowles Foundation for Research in Economics, Yale University.

    Cited by:

    1. Tomás Marinozzi & Leandro Nallar & Sergio A. Pernice, 2021. "Intuitive Mathematical Economics Series. Linear Algebra Techniques to Measure Business Cycles," CEMA Working Papers: Serie Documentos de Trabajo. 802, Universidad del CEMA.
    2. Joseph G. Haubrich, 2020. "How Cyclical Is Bank Capital?," Journal of Financial Services Research, Springer;Western Finance Association, vol. 58(1), pages 27-38, August.
    3. Markus Hertrich, 2019. "A Novel Housing Price Misalignment Indicator for Germany," German Economic Review, Verein für Socialpolitik, vol. 20(4), pages 759-794, November.
    4. Peter C. B. Phillips & Zhentao Shi, 2021. "Boosting: Why You Can Use The Hp Filter," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 62(2), pages 521-570, May.
    5. Nadav Ben Zeev, 2019. "Asymmetric Business Cycles In Emerging Market Economies," Working Papers 1909, Ben-Gurion University of the Negev, Department of Economics.
    6. Jia Li & Peter C. B. Phillips & Shuping Shi & Jun Yu, 2022. "Weak Identification of Long Memory with Implications for Inference," Cowles Foundation Discussion Papers 2334, Cowles Foundation for Research in Economics, Yale University.
    7. Sergio Destefanis & Matteo Fragetta & Emanuel Gasteiger, 2024. "Does one size fit all in the Euro Area? Some counterfactual evidence," Empirical Economics, Springer, vol. 67(4), pages 1615-1647, October.
    8. Neslihan Sakarya & Robert M. de Jong, 2022. "The spectral analysis of the Hodrick–Prescott filter," Journal of Time Series Analysis, Wiley Blackwell, vol. 43(3), pages 479-489, May.
    9. Özer Karagedikli & Dr John McDermott, 2016. "Inflation expectations and low inflation in New Zealand," Reserve Bank of New Zealand Discussion Paper Series DP2016/09, Reserve Bank of New Zealand.
    10. Peter C.B. Phillips & Zhentao Shi, 2019. "Boosting the Hodrick-Prescott Filter," Cowles Foundation Discussion Papers 2192, Cowles Foundation for Research in Economics, Yale University.
    11. Ye Lu & Adrian Pagan, 2023. "To Boost or Not to Boost? That is the Question," Working Papers 2023-05, University of Sydney, School of Economics.
    12. Kapetanios, George & Millard, Stephen & Petrova, Katerina & Price, Simon, 2019. "Time-varying cointegration and the UK great ratios," Bank of England working papers 789, Bank of England.
    13. Ingrid Groessl & Artur Tarassow, 2018. "A Microfounded Model of Money Demand Under Uncertainty, and some Empirical Evidence," Macroeconomics and Finance Series 201802, University of Hamburg, Department of Socioeconomics.
    14. Ben Zeev, Nadav, 2017. "Capital controls as shock absorbers," Journal of International Economics, Elsevier, vol. 109(C), pages 43-67.
    15. Peter C. B. Phillips & Sainan Jin, 2015. "Business Cycles, Trend Elimination, and the HP Filter," Cowles Foundation Discussion Papers 2005, Cowles Foundation for Research in Economics, Yale University.
    16. Daniel Buncic, 2020. "Econometric issues with Laubach and Williams' estimates of the natural rate of interest," Papers 2002.11583, arXiv.org, revised Aug 2020.
    17. Panizza, Ugo, 2022. "Do Countries Default in Bad Times? The Role of Alternative Detrending Techniques," CEPR Discussion Papers 17216, C.E.P.R. Discussion Papers.
    18. Zsuzsanna Hosszu & Gergely Lakos, 2022. "Early Warning Performance of Univariate Credit-to-GDP Gaps," MNB Occasional Papers 2022/142, Magyar Nemzeti Bank (Central Bank of Hungary).
    19. Hall, Viv B & Thomson, Peter, 2020. "Does Hamilton’s OLS regression provide a “better alternative” to the Hodrick-Prescott filter? A New Zealand Business Cycle Perspective," Working Paper Series 21070, Victoria University of Wellington, School of Economics and Finance.
    20. Ben Zeev, Nadav, 2019. "Global credit supply shocks and exchange rate regimes," Journal of International Economics, Elsevier, vol. 116(C), pages 1-32.
    21. Carlos D. Ramirez, 2024. "The effect of economic policy uncertainty under fractional integration," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 23(1), pages 89-110, January.
    22. Dmitrij Celov & Mariarosaria Comunale, 2022. "Business Cycles in the EU: A Comprehensive Comparison Across Methods," Advances in Econometrics, in: Essays in Honour of Fabio Canova, volume 44, pages 99-146, Emerald Group Publishing Limited.
    23. Kady Keita & Camelia Turcu, 2023. "Promoting Counter-Cyclical Fiscal Policy: Fiscal Rules Versus Institutions," Comparative Economic Studies, Palgrave Macmillan;Association for Comparative Economic Studies, vol. 65(4), pages 736-781, December.
    24. Egon Smeral, 2019. "Seasonal forecasting performance considering varying income elasticities in tourism demand," Tourism Economics, , vol. 25(3), pages 355-374, May.
    25. Baffes,John & Kabundi,Alain Ntumba, 2021. "Commodity Price Shocks : Order within Chaos ?," Policy Research Working Paper Series 9792, The World Bank.
    26. Yves Schueler, 2024. "Filtering economic time series: On the cyclical properties of Hamilton’s regression filter and the Hodrick-Prescott filter," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 54, October.
    27. Lolić, Ivana & Matošec, Marina & Sorić, Petar, 2024. "DIY google trends indicators in social sciences: A methodological note," Technology in Society, Elsevier, vol. 77(C).
    28. Giorgio Calcagnini & Germana Giombini & Giuseppe Travaglini, 2021. "The Productivity Gap Among Major European Countries, USA and Japan," Italian Economic Journal: A Continuation of Rivista Italiana degli Economisti and Giornale degli Economisti, Springer;Società Italiana degli Economisti (Italian Economic Association), vol. 7(1), pages 59-78, March.
    29. Eric Fesselmeyer & Haoming Liu & Alberto Salvo, 2022. "Declining discount rates in Singapore's market for privately developed apartments," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(2), pages 330-350, March.
    30. Lee, Seohyun, 2017. "Three essays on uncertainty: real and financial effects of uncertainty shocks," MPRA Paper 83617, University Library of Munich, Germany.
    31. James D. Hamilton, 2017. "Why You Should Never Use the Hodrick-Prescott Filter," NBER Working Papers 23429, National Bureau of Economic Research, Inc.
    32. Jylhä, Petri & Lof, Matthijs, 2022. "Mind the Basel gap," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 79(C).
    33. Hiroshi Yamada, 2023. "Quantile regression version of Hodrick–Prescott filter," Empirical Economics, Springer, vol. 64(4), pages 1631-1645, April.
    34. Dorel Dusmanescu & Jean Andrei & Gheorghe H. Popescu & Elvira Nica & Mirela Panait, 2016. "Heuristic Methodology for Estimating the Liquid Biofuel Potential of a Region," Energies, MDPI, vol. 9(9), pages 1-19, August.
    35. AMENDOLA, Adalgiso & DI SERIO, Mario & FRAGETTA, Matteo, 2018. "The Government Spending Multiplier at the Zero Lower Bound: Evidence from the Euro Area," CELPE Discussion Papers 153, CELPE - CEnter for Labor and Political Economics, University of Salerno, Italy.
    36. 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.
    37. Hall, Viv B & Thomson, Peter, 2022. "A boosted HP filter for business cycle analysis: evidence from New Zealand’s small open economy," Working Paper Series 21184, Victoria University of Wellington, School of Economics and Finance.
    38. Hendrickson, Joshua R. & Salter, Alexander William, 2016. "Money, liquidity, and the structure of production," Journal of Economic Dynamics and Control, Elsevier, vol. 73(C), pages 314-328.
    39. Fritz, Marlon, 2019. "Steady state adjusting trends using a data-driven local polynomial regression," Economic Modelling, Elsevier, vol. 83(C), pages 312-325.
    40. Kovačić, Zlatko & Vilotić, Miloš, 2017. "Assessing European business cycles synchronization," MPRA Paper 79990, University Library of Munich, Germany.
    41. Tilocca, Giuseppe & Sánchez, David & Torres-García, Miguel, 2024. "Applying the root cause analysis methodology to study the lack of market success of micro gas turbine systems," Applied Energy, Elsevier, vol. 360(C).
    42. Patricia Aranda-Cuéllar & José María López-Morales & María Jesús Such-Devesa, 2021. "Winter tourism dependence: A cyclical and cointegration analysis. Case study for the Alps," Tourism Economics, , vol. 27(7), pages 1540-1560, November.
    43. Haitham A. Al-Zoubi, 2024. "An affine model for short rates when monetary policy is path dependent," Review of Derivatives Research, Springer, vol. 27(2), pages 151-201, July.

  5. Sainan Jin & Valentina Corradi & Norman Swanson, 2015. "Robust Forecast Comparison," Departmental Working Papers 201502, Rutgers University, Department of Economics.

    Cited by:

    1. Arvanitis, Stelios & Post, Thierry & Potì, Valerio & Karabati, Selcuk, 2021. "Nonparametric tests for Optimal Predictive Ability," International Journal of Forecasting, Elsevier, vol. 37(2), pages 881-898.
    2. Norman R. Swanson & Weiqi Xiong, 2018. "Big data analytics in economics: What have we learned so far, and where should we go from here?," Canadian Journal of Economics, Canadian Economics Association, vol. 51(3), pages 695-746, August.
    3. Anghel, Dan Gabriel, 2021. "Data Snooping Bias in Tests of the Relative Performance of Multiple Forecasting Models," Journal of Banking & Finance, Elsevier, vol. 126(C).
    4. Sander Barendse & Andrew J. Patton, 2022. "Comparing Predictive Accuracy in the Presence of a Loss Function Shape Parameter," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(3), pages 1057-1069, June.
    5. Valentina Corradi & Sainan Jin & Norman R. Swanson, 2023. "Robust forecast superiority testing with an application to assessing pools of expert forecasters," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(4), pages 596-622, June.
    6. Yen, Yu-Min & Yen, Tso-Jung, 2021. "Testing forecast accuracy of expectiles and quantiles with the extremal consistent loss functions," International Journal of Forecasting, Elsevier, vol. 37(2), pages 733-758.
    7. Francis X. Diebold & Minchul Shin, 2017. "Assessing point forecast accuracy by stochastic error distance," Econometric Reviews, Taylor & Francis Journals, vol. 36(6-9), pages 588-598, October.
    8. Mehmet Pinar & Thanasis Stengos & Nikolas Topaloglou, 2022. "Stochastic dominance spanning and augmenting the human development index with institutional quality," Annals of Operations Research, Springer, vol. 315(1), pages 341-369, August.
    9. Post, Thierry & Karabatı, Selçuk & Arvanitis, Stelios, 2019. "Robust optimization of forecast combinations," International Journal of Forecasting, Elsevier, vol. 35(3), pages 910-926.
    10. Anyfantaki, Sofia & Arvanitis, Stelios & Topaloglou, Nikolas, 2021. "Diversification benefits in the cryptocurrency market under mild explosivity," European Journal of Operational Research, Elsevier, vol. 295(1), pages 378-393.

  6. 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. 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.
    2. Ambrogio Cesa-Bianchi & Jean Imbs & Jumana Saleheen, 2016. "Finance and Synchronization," Discussion Papers 1622, Centre for Macroeconomics (CFM).
    3. 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.
    4. 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.
    5. 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.
    6. 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).
    7. 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.
    8. Bai, Jushan, 2024. "Likelihood approach to dynamic panel models with interactive effects," Journal of Econometrics, Elsevier, vol. 240(1).
    9. 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.
    10. 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.
    11. Su, Liangjun & Zheng, Xin, 2017. "A martingale-difference-divergence-based test for specification," Economics Letters, Elsevier, vol. 156(C), pages 162-167.
    12. 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.
    13. 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.
    14. 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.
    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. 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. Juodis, Artūras & Sarafidis, Vasilis, 2022. "An incidental parameters free inference approach for panels with common shocks," Journal of Econometrics, Elsevier, vol. 229(1), pages 19-54.
    18. 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.
    19. Bai, Jushan & Li, Kunpeng, 2021. "Dynamic spatial panel data models with common shocks," Journal of Econometrics, Elsevier, vol. 224(1), pages 134-160.
    20. 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.
    21. 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.
    22. 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.
    23. 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.
    24. 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.
    25. 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.
    26. 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).
    27. 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.
    28. Christis Katsouris, 2023. "Optimal Estimation Methodologies for Panel Data Regression Models," Papers 2311.03471, arXiv.org, revised Nov 2023.
    29. 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.
    30. 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.

  7. 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.

  8. Peter C.B. Phillips & Sainan Jin, 2013. "Testing the Martingale Hypothesis," Cowles Foundation Discussion Papers 1912, Cowles Foundation for Research in Economics, Yale University.

    Cited by:

    1. Croonenbroeck, Carsten & Stadtmann, Georg, 2019. "Renewable generation forecast studies – Review and good practice guidance," Renewable and Sustainable Energy Reviews, Elsevier, vol. 108(C), pages 312-322.
    2. Adeyeye Patrick Olufemi & Aluko Olufemi Adewale & Migiro Stephen Oseko, 2017. "Efficiency of Foreign Exchange Markets in Sub-Saharan Africa in the Presence of Structural Break: A Linear and Non-Linear Testing Approach," Journal of Economics and Behavioral Studies, AMH International, vol. 9(4), pages 122-131.
    3. Daniel Borup & Martin Thyrsgaard, 2017. "Statistical tests for equal predictive ability across multiple forecasting methods," CREATES Research Papers 2017-19, Department of Economics and Business Economics, Aarhus University.
    4. Chang, Jinyuan & Jiang, Qing & Shao, Xiaofeng, 2023. "Testing the martingale difference hypothesis in high dimension," Journal of Econometrics, Elsevier, vol. 235(2), pages 972-1000.
    5. Wang, Qiying & Wu, Dongsheng & Zhu, Ke, 2018. "Model checks for nonlinear cointegrating regression," Journal of Econometrics, Elsevier, vol. 207(2), pages 261-284.
    6. Xuexin WANG, 2021. "Generalized Spectral Tests for High Dimensional Multivariate Martingale Difference Hypotheses," Working Papers 2021-11-06, Wang Yanan Institute for Studies in Economics (WISE), Xiamen University.
    7. Yi He & Sombut Jaidee & Jiti Gao, 2020. "Most Powerful Test against High Dimensional Free Alternatives," Monash Econometrics and Business Statistics Working Papers 13/20, Monash University, Department of Econometrics and Business Statistics.
    8. Guo, Xu & Li, Gao Rong & Wong, Wing Keung, 2014. "Specification Testing of Production Frontier Function in Stochastic Frontier Model," MPRA Paper 57999, University Library of Munich, Germany.

  9. Yixiao Sun & Peter C.B. Phillips & Sainan Jin, 2010. "Power Maximization and Size Control in Heteroskedasticity and Autocorrelation Robust Tests with Exponentiated Kernels," Cowles Foundation Discussion Papers 1749, Cowles Foundation for Research in Economics, Yale University.

    Cited by:

    1. Peter C. B. Phillips & Xiaohu Wang & Yonghui Zhang, 2019. "HAR Testing for Spurious Regression in Trend," Econometrics, MDPI, vol. 7(4), pages 1-28, December.
    2. Liu, Cheng & Sun, Yixiao, 2019. "A Simple and Trustworthy Asymptotic t Test in Difference-in-Differences Regressions," University of California at San Diego, Economics Working Paper Series qt0ck2109g, Department of Economics, UC San Diego.
    3. Pötscher, Benedikt M. & Preinerstorfer, David, 2018. "Controlling the size of autocorrelation robust tests," Journal of Econometrics, Elsevier, vol. 207(2), pages 406-431.
    4. Lu, Ye & Park, Joon Y., 2019. "Estimation of longrun variance of continuous time stochastic process using discrete sample," Journal of Econometrics, Elsevier, vol. 210(2), pages 236-267.
    5. Hwang, Jungbin & Sun, Yixiao, 2015. "Asymptotic F and t Tests in an Efficient GMM Setting," University of California at San Diego, Economics Working Paper Series qt1c62d8xf, Department of Economics, UC San Diego.
    6. Kolokotrones, Thomas & Stock, James H. & Walker, Christopher D., 2024. "Is Newey–West optimal among first-order kernels?," Journal of Econometrics, Elsevier, vol. 240(2).
    7. Sun, Yixiao, 2013. "Fixed-smoothing Asymptotics in a Two-step GMM Framework," University of California at San Diego, Economics Working Paper Series qt64x4z265, Department of Economics, UC San Diego.
    8. Hirukawa, Masayuki, 2023. "Robust Covariance Matrix Estimation in Time Series: A Review," Econometrics and Statistics, Elsevier, vol. 27(C), pages 36-61.
    9. Preinerstorfer, David & Pötscher, Benedikt M., 2013. "On Size and Power of Heteroscedasticity and Autocorrelation Robust Tests," MPRA Paper 45675, University Library of Munich, Germany.
    10. Preinerstorfer, David, 2014. "Finite Sample Properties of Tests Based on Prewhitened Nonparametric Covariance Estimators," MPRA Paper 58333, University Library of Munich, Germany.

  10. Yixiao Sun & Peter C. B. Phillips & Sainan Jin, 2006. "Optimal Bandwidth Selection in Heteroskedasticity-Autocorrelation Robust Testing," Cowles Foundation Discussion Papers 1545, Cowles Foundation for Research in Economics, Yale University.

    Cited by:

    1. Paulo Parente & Richard J. Smith, 2019. "Quasi-maximum likelihood and the kernel block bootstrap for nonlinear dynamic models," CeMMAP working papers CWP60/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    2. Jiang, Bibo & Lu, Ye & Park, Joon Y., 2018. "Testing for Stationarity at High Frequency," Working Papers 2018-09, University of Sydney, School of Economics.
    3. Robinson Kruse & Christian Leschinski & Michael Will, 2016. "Comparing Predictive Accuracy under Long Memory - With an Application to Volatility Forecasting," CREATES Research Papers 2016-17, Department of Economics and Business Economics, Aarhus University.
    4. Ross McKitrick & Timothy Vogelsang, 2011. "Multivariate trend comparisons between autocorrelated climate series with general trend regressors," Working Papers 1109, University of Guelph, Department of Economics and Finance.
    5. Laura Coroneo & Fabrizio Iacone, 2020. "Comparing predictive accuracy in small samples using fixed‐smoothing asymptotics," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(4), pages 391-409, June.
    6. Alessandro Casini & Pierre Perron, 2021. "Prewhitened Long-Run Variance Estimation Robust to Nonstationarity," Papers 2103.02235, arXiv.org, revised Aug 2024.
    7. Kajal Lahiri & Liu Yang, 2018. "Confidence Bands for ROC Curves With Serially Dependent Data," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 36(1), pages 115-130, January.
    8. Wang, Yulong & Xiao, Zhijie, 2022. "Estimation and inference about tail features with tail censored data," Journal of Econometrics, Elsevier, vol. 230(2), pages 363-387.
    9. Rho, Seunghwa & Vogelsang, Timothy J., 2021. "Inference in time series models using smoothed-clustered standard errors," Journal of Econometrics, Elsevier, vol. 224(1), pages 113-133.
    10. Gagnon, Marie-Hélène & Power, Gabriel J. & Toupin, Dominique, 2023. "The sum of all fears: Forecasting international returns using option-implied risk measures," Journal of Banking & Finance, Elsevier, vol. 146(C).
    11. Yixiao Sun, 2014. "Fixed-smoothing Asymptotics and AsymptoticFandtTests in the Presence of Strong Autocorrelation," Advances in Econometrics, in: Essays in Honor of Peter C. B. Phillips, volume 14, pages 23-63, Emerald Group Publishing Limited.
    12. Hwang, Jungbin & Sun, Yixiao, 2018. "Should we go one step further? An accurate comparison of one-step and two-step procedures in a generalized method of moments framework," Journal of Econometrics, Elsevier, vol. 207(2), pages 381-405.
    13. Xiaohong Chen & Zhipeng Liao, 2015. "Sieve Semiparametric Two-Step GMM under Weak Dependence," Cowles Foundation Discussion Papers 2012, Cowles Foundation for Research in Economics, Yale University.
    14. Sebastian Calonico & Matias D. Cattaneo & Max H. Farrell, 2018. "Coverage Error Optimal Confidence Intervals for Local Polynomial Regression," Papers 1808.01398, arXiv.org, revised Jul 2021.
    15. Leandro M. Magnusson & Sophocles Mavroeidis, 2010. "Identification‐Robust Minimum Distance Estimation of the New Keynesian Phillips Curve," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 42(2‐3), pages 465-481, March.
    16. Vogelsang, Timothy & Nawaz, Nasreen, 2015. "Estimation and Inference of Linear Trend Slope Ratios with an Application to Global Temperature Data," MPRA Paper 117435, University Library of Munich, Germany.
    17. Xu, Ke-Li, 2012. "Robustifying multivariate trend tests to nonstationary volatility," Journal of Econometrics, Elsevier, vol. 169(2), pages 147-154.
    18. Sun, Yixiao, 2011. "Robust trend inference with series variance estimator and testing-optimal smoothing parameter," Journal of Econometrics, Elsevier, vol. 164(2), pages 345-366, October.
    19. Julian Martinez-Iriarte & Yixiao Sun & Xuexin Wang, 2019. "Asymptotic F Tests under Possibly Weak Identification," Working Papers 2019-03-12, Wang Yanan Institute for Studies in Economics (WISE), Xiamen University.
    20. Yi-Ting Chen & Zhongjun Qu, 2015. "M Tests with a New Normalization Matrix," Econometric Reviews, Taylor & Francis Journals, vol. 34(5), pages 617-652, May.
    21. Liu, Cheng & Sun, Yixiao, 2019. "A Simple and Trustworthy Asymptotic t Test in Difference-in-Differences Regressions," University of California at San Diego, Economics Working Paper Series qt0ck2109g, Department of Economics, UC San Diego.
    22. Xiaoqing Ye & Yixiao Sun, 2018. "Heteroskedasticity- and autocorrelation-robust F and t tests in Stata," Stata Journal, StataCorp LP, vol. 18(4), pages 951-980, December.
    23. Jungbin Hwang & Gonzalo Valdés, 2020. "Low Frequency Cointegrating Regression in the Presence of Local to Unity Regressors and Unknown Form of Serial Dependence," Working papers 2020-03, University of Connecticut, Department of Economics, revised Aug 2020.
    24. Yixiao Sun & Xuexin Wang, 2019. "An Asymptotically F-Distributed Chow Test in the Presence of Heteroscedasticity and Autocorrelation," Papers 1911.03771, arXiv.org.
    25. Landajo, Manuel & Presno, María José, 2010. "Nonparametric pseudo-Lagrange multiplier stationarity testing," MPRA Paper 25659, University Library of Munich, Germany.
    26. Hoerova, Marie & Bekaert, Geert, 2014. "The VIX, the variance premium and stock market volatility," Working Paper Series 1675, European Central Bank.
    27. Sun, Yixiao & Yang, Jingjing, 2020. "Testing-optimal kernel choice in HAR inference," Journal of Econometrics, Elsevier, vol. 219(1), pages 123-136.
    28. Balvers, Ronald & Du, Ding & Zhao, Xiaobing, 2017. "Temperature shocks and the cost of equity capital: Implications for climate change perceptions," Journal of Banking & Finance, Elsevier, vol. 77(C), pages 18-34.
    29. Xiaofeng Shao, 2010. "A self‐normalized approach to confidence interval construction in time series," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 72(3), pages 343-366, June.
    30. Wenger, Kai & Leschinski, Christian & Sibbertsen, Philipp, 2017. "Change-in-Mean Tests in Long-memory Time Series: A Review of Recent Developments," Hannover Economic Papers (HEP) dp-598, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    31. Mertens, Elmar, 2012. "Are spectral estimators useful for long-run restrictions in SVARs?," Journal of Economic Dynamics and Control, Elsevier, vol. 36(12), pages 1831-1844.
    32. Bester, C. Alan & Conley, Timothy G. & Hansen, Christian B., 2011. "Inference with dependent data using cluster covariance estimators," Journal of Econometrics, Elsevier, vol. 165(2), pages 137-151.
    33. Sun, Yixiao & Kaplan, David M., 2011. "A New Asymptotic Theory for Vector Autoregressive Long-run Variance Estimation and Autocorrelation Robust Testing," University of California at San Diego, Economics Working Paper Series qt8cx0t4gc, Department of Economics, UC San Diego.
    34. 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.
    35. Zhang, Xianyang & Shao, Xiaofeng, 2013. "On a general class of long run variance estimators," Economics Letters, Elsevier, vol. 120(3), pages 437-441.
    36. Saraswata Chaudhuri & Eric Renault, 2015. "Shrinkage of Variance for Minimum Distance Based Tests," Econometric Reviews, Taylor & Francis Journals, vol. 34(3), pages 328-351, March.
    37. Daniel Wilhelm, 2014. "Optimal bandwidth selection for robust generalized method of moments estimation," CeMMAP working papers 15/14, Institute for Fiscal Studies.
    38. Müller, Ulrich K. & Watson, Mark W., 2013. "Low-frequency robust cointegration testing," Journal of Econometrics, Elsevier, vol. 174(2), pages 66-81.
    39. Sun, Yixiao & Phillips, Peter C.B. & Jin, Sainan, 2011. "Power Maximization And Size Control In Heteroskedasticity And Autocorrelation Robust Tests With Exponentiated Kernels," Econometric Theory, Cambridge University Press, vol. 27(6), pages 1320-1368, December.
    40. Driouchi, Tarik & So, Raymond H.Y. & Trigeorgis, Lenos, 2020. "Investor ambiguity, systemic banking risk and economic activity: The case of too-big-to-fail," Journal of Corporate Finance, Elsevier, vol. 62(C).
    41. McElroy, Tucker S. & Politis, Dimitris N., 2014. "Spectral density and spectral distribution inference for long memory time series via fixed-b asymptotics," Journal of Econometrics, Elsevier, vol. 182(1), pages 211-225.
    42. Pellatt, Daniel F. & Sun, Yixiao, 2023. "Asymptotic F test in regressions with observations collected at high frequency over long span," Journal of Econometrics, Elsevier, vol. 235(2), pages 1281-1309.
    43. Han, Heejoon & Linton, Oliver & Oka, Tatsushi & Whang, Yoon-Jae, 2016. "The cross-quantilogram: Measuring quantile dependence and testing directional predictability between time series," Journal of Econometrics, Elsevier, vol. 193(1), pages 251-270.
    44. Daniel J. Nordman & Helle Bunzel & Soumendra N. Lahiri, 2012. "A Non-standard Empirical Likelihood for Time Series," CREATES Research Papers 2012-55, Department of Economics and Business Economics, Aarhus University.
    45. Min Seong Kim & Yixiao Sun & Jingjing Yang, 2015. "A Fixed-bandwidth View of the Pre-asymptotic Inference for Kernel Smoothing with Time Series Data," Working Papers 049, Toronto Metropolitan University, Department of Economics.
    46. Jungbin Hwang & Gonzalo Valdés, 2020. "Finite-sample Corrected Inference for Two-step GMM in Time Series," Working papers 2020-02, University of Connecticut, Department of Economics.
    47. 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.
    48. Zhang, Xianyang, 2016. "Fixed-smoothing asymptotics in the generalized empirical likelihood estimation framework," Journal of Econometrics, Elsevier, vol. 193(1), pages 123-146.
    49. Javier Hualde & Fabrizio Iacone, 2015. "Autocorrelation robust inference using the Daniell kernel with fixed bandwidth," Discussion Papers 15/14, Department of Economics, University of York.
    50. Politis, D N, 2009. "Higher-Order Accurate, Positive Semi-definite Estimation of Large-Sample Covariance and Spectral Density Matrices," University of California at San Diego, Economics Working Paper Series qt66w826hz, Department of Economics, UC San Diego.
    51. Jin Lee, 2012. "Nonparametric Testing for Long-Run Neutrality with Applications to US Money and Output Data," Computational Economics, Springer;Society for Computational Economics, vol. 40(2), pages 183-202, August.
    52. Ulrich K. Müller, 2014. "HAC Corrections for Strongly Autocorrelated Time Series," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 32(3), pages 311-322, July.
    53. Manuel Landajo & María José Presno, 2010. "Stationarity testing under nonlinear models. Some asymptotic results," Journal of Time Series Analysis, Wiley Blackwell, vol. 31(5), pages 392-405, September.
    54. Kim, Min Seong & Sun, Yixiao, 2011. "Spatial heteroskedasticity and autocorrelation consistent estimation of covariance matrix," Journal of Econometrics, Elsevier, vol. 160(2), pages 349-371, February.
    55. Sun, Yixiao & Kim, Min Seong, 2012. "Simple and powerful GMM over-identification tests with accurate size," Journal of Econometrics, Elsevier, vol. 166(2), pages 267-281.
    56. McElroy, Tucker S. & Politis, Dimitris N., 2012. "Distribution Theory for the Studentized Mean for Long, Short, and Negative Memory Time Series," University of California at San Diego, Economics Working Paper Series qt35c7r55c, Department of Economics, UC San Diego.
    57. Xiaohong Chen & Sokbae Lee & Yuan Liao & Myung Hwan Seo & Youngki Shin & Myunghyun Song, 2023. "SGMM: Stochastic Approximation to Generalized Method of Moments," Papers 2308.13564, arXiv.org, revised Oct 2023.
    58. Pötscher, Benedikt M. & Preinerstorfer, David, 2018. "Controlling the size of autocorrelation robust tests," Journal of Econometrics, Elsevier, vol. 207(2), pages 406-431.
    59. Sokbae Lee & Yuan Liao & Myung Hwan Seo & Youngki Shin, 2022. "Fast Inference for Quantile Regression with Tens of Millions of Observations," Papers 2209.14502, arXiv.org, revised Oct 2023.
    60. Hwang, Jungbin & Valdés, Gonzalo, 2023. "Finite-sample corrected inference for two-step GMM in time series," Journal of Econometrics, Elsevier, vol. 234(1), pages 327-352.
    61. McCulloch, J. Huston, 2016. "Moment Ratio estimation of autoregressive/unit root parameters and autocorrelation-consistent standard errors," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 712-733.
    62. Kim, Min Seong & Sun, Yixiao, 2013. "Heteroskedasticity and spatiotemporal dependence robust inference for linear panel models with fixed effects," Journal of Econometrics, Elsevier, vol. 177(1), pages 85-108.
    63. Lu, Ye & Park, Joon Y., 2019. "Estimation of longrun variance of continuous time stochastic process using discrete sample," Journal of Econometrics, Elsevier, vol. 210(2), pages 236-267.
    64. Daniel Wilhelm, 2014. "Optimal bandwidth selection for robust generalized method of moments estimation," CeMMAP working papers CWP15/14, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    65. Hwang, Jungbin & Sun, Yixiao, 2015. "Asymptotic F and t Tests in an Efficient GMM Setting," University of California at San Diego, Economics Working Paper Series qt1c62d8xf, Department of Economics, UC San Diego.
    66. Ray, Surajit & Savin, N.E. & Tiwari, Ashish, 2009. "Testing the CAPM revisited," Journal of Empirical Finance, Elsevier, vol. 16(5), pages 721-733, December.
    67. Kolokotrones, Thomas & Stock, James H. & Walker, Christopher D., 2024. "Is Newey–West optimal among first-order kernels?," Journal of Econometrics, Elsevier, vol. 240(2).
    68. Ulrich K. Müller & Mark W. Watson, 2020. "Low-Frequency Analysis of Economic Time Series," Working Papers 2020-13, Princeton University. Economics Department..
    69. Annika Betken, 2016. "Testing for Change-Points in Long-Range Dependent Time Series by Means of a Self-Normalized Wilcoxon Test," Journal of Time Series Analysis, Wiley Blackwell, vol. 37(6), pages 785-809, November.
    70. Matei Demetrescu & Christoph Hanck & Robinson Kruse, 2016. "Fixed-b Inference in the Presence of Time-Varying Volatility," CREATES Research Papers 2016-01, Department of Economics and Business Economics, Aarhus University.
    71. Sun, Yixiao, 2013. "Fixed-smoothing Asymptotics in a Two-step GMM Framework," University of California at San Diego, Economics Working Paper Series qt64x4z265, Department of Economics, UC San Diego.
    72. Sun, Yixiao, 2014. "Let’s fix it: Fixed-b asymptotics versus small-b asymptotics in heteroskedasticity and autocorrelation robust inference," Journal of Econometrics, Elsevier, vol. 178(P3), pages 659-677.
    73. Vogelsang, Timothy J., 2012. "Heteroskedasticity, autocorrelation, and spatial correlation robust inference in linear panel models with fixed-effects," Journal of Econometrics, Elsevier, vol. 166(2), pages 303-319.
    74. Dayton M. Lambert & Kevin T. McNamara, 2009. "Location determinants of food manufacturers in the United States, 2000–2004: are nonmetropolitan counties competitive?," Agricultural Economics, International Association of Agricultural Economists, vol. 40(6), pages 617-630, November.
    75. Hirukawa, Masayuki, 2023. "Robust Covariance Matrix Estimation in Time Series: A Review," Econometrics and Statistics, Elsevier, vol. 27(C), pages 36-61.
    76. Grigory Franguridi & Bulat Gafarov & Kaspar Wüthrich, 2021. "Conditional Quantile Estimators: A Small Sample Theory," CESifo Working Paper Series 9046, CESifo.
    77. Boudoukh, Jacob & Israel, Ronen & Richardson, Matthew, 2022. "Biases in long-horizon predictive regressions," Journal of Financial Economics, Elsevier, vol. 145(3), pages 937-969.
    78. Jungbin Hwang, 2017. "Simple and Trustworthy Cluster-Robust GMM Inference," Working papers 2017-19, University of Connecticut, Department of Economics, revised Aug 2020.
    79. David M. Kaplan, 2013. "Improved Quantile Inference Via Fixed-Smoothing Asymptotics And Edgeworth Expansion," Working Papers 1313, Department of Economics, University of Missouri.
    80. Manuel Landajo & María Presno, 2013. "Nonparametric pseudo-Lagrange multiplier stationarity testing," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 65(1), pages 125-147, February.
    81. Hwang, Jungbin, 2021. "Simple and trustworthy cluster-robust GMM inference," Journal of Econometrics, Elsevier, vol. 222(2), pages 993-1023.
    82. Vogelsang, Timothy J. & Wagner, Martin, 2011. "Integrated Modified OLS Estimation and Fixed-b Inference for Cointegrating Regressions," Economics Series 263, Institute for Advanced Studies.
    83. Kaicheng Chen & Timothy J. Vogelsang, 2023. "Fixed-b Asymptotics for Panel Models with Two-Way Clustering," Papers 2309.08707, arXiv.org, revised Aug 2024.
    84. Xuexin Wang & Yixiao Sun, 2020. "An Asymptotic F Test for Uncorrelatedness in the Presence of Time Series Dependence," Journal of Time Series Analysis, Wiley Blackwell, vol. 41(4), pages 536-550, July.
    85. Zhang, Jingsi & Jiang, Wenxin & Shao, Xiaofeng, 2013. "Bayesian model selection based on parameter estimates from subsamples," Statistics & Probability Letters, Elsevier, vol. 83(4), pages 979-986.
    86. Pellatt , Daniel & Sun, Yixiao, 2020. "Asymptotic F test in Regressions with Observations Collected at High Frequency over Long Span," University of California at San Diego, Economics Working Paper Series qt19f0d9wz, Department of Economics, UC San Diego.
    87. Yang, Jingjing & Vogelsang, Timothy J., 2018. "Finite sample performance of a long run variance estimator based on exactly (almost) unbiased autocovariance estimators," Economics Letters, Elsevier, vol. 165(C), pages 21-27.
    88. Casini, Alessandro, 2023. "Theory of evolutionary spectra for heteroskedasticity and autocorrelation robust inference in possibly misspecified and nonstationary models," Journal of Econometrics, Elsevier, vol. 235(2), pages 372-392.
    89. Casini, Alessandro, 2024. "The fixed-b limiting distribution and the ERP of HAR tests under nonstationarity," Journal of Econometrics, Elsevier, vol. 238(2).
    90. Chambers, Marcus J., 2013. "Jackknife estimation of stationary autoregressive models," Journal of Econometrics, Elsevier, vol. 172(1), pages 142-157.
    91. Eben Lazarus & Daniel J. Lewis & James H. Stock, 2021. "The Size‐Power Tradeoff in HAR Inference," Econometrica, Econometric Society, vol. 89(5), pages 2497-2516, September.
    92. Travaglini, Guido, 2010. "Dynamic Econometric Testing of Climate Change and of its Causes," MPRA Paper 23600, University Library of Munich, Germany.
    93. Hualde, Javier & Iacone, Fabrizio, 2017. "Fixed bandwidth asymptotics for the studentized mean of fractionally integrated processes," Economics Letters, Elsevier, vol. 150(C), pages 39-43.
    94. Preinerstorfer, David & Pötscher, Benedikt M., 2013. "On Size and Power of Heteroscedasticity and Autocorrelation Robust Tests," MPRA Paper 45675, University Library of Munich, Germany.
    95. Cheol-Keun Cho & Timothy J. Vogelsang, 2016. "Fixed- b Inference for Testing Structural Change in a Time Series Regression," Econometrics, MDPI, vol. 5(1), pages 1-26, December.
    96. Muller, Ulrich K., 2007. "A theory of robust long-run variance estimation," Journal of Econometrics, Elsevier, vol. 141(2), pages 1331-1352, December.
    97. Maxwell L. King & Sivagowry Sriananthakumar, 2015. "Point Optimal Testing: A Survey of the Post 1987 Literature," Monash Econometrics and Business Statistics Working Papers 5/15, Monash University, Department of Econometrics and Business Statistics.
    98. Wenger, Kai & Less, Vivien, 2020. "A modified Wilcoxon test for change points in long-range dependent time series," Economics Letters, Elsevier, vol. 192(C).
    99. Kin Wai Chan & Chun Yip Yau, 2017. "High-order Corrected Estimator of Asymptotic Variance with Optimal Bandwidth," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 44(4), pages 866-898, December.
    100. Preinerstorfer, David, 2014. "Finite Sample Properties of Tests Based on Prewhitened Nonparametric Covariance Estimators," MPRA Paper 58333, University Library of Munich, Germany.
    101. Masao Ogaki & Sungwook Park, 2007. "Long-run real exchange rate changes and the properties of the variance of k-differences," Working Papers 07-05, Ohio State University, Department of Economics.
    102. Alessandro Casini, 2021. "The Fixed-b Limiting Distribution and the ERP of HAR Tests Under Nonstationarity," Papers 2111.14590, arXiv.org, revised Aug 2024.

  11. Sun, Yixiao X & Phillips, Peter C. B. & Jin, Sainan, 2005. "Optimal Bandwidth Selection in Heteroskedasticity-Autocorrelation Robust Testing∗," University of California at San Diego, Economics Working Paper Series qt16b3j2hd, Department of Economics, UC San Diego.

    Cited by:

    1. Nigar Hashimzade & Timothy J. Vogelsang, 2008. "Fixed‐b asymptotic approximation of the sampling behaviour of nonparametric spectral density estimators," Journal of Time Series Analysis, Wiley Blackwell, vol. 29(1), pages 142-162, January.

  12. Peter C.B. Phillips & Yixiao Sun & Sainan Jin, 2005. "Improved HAR Inference," Cowles Foundation Discussion Papers 1513, Cowles Foundation for Research in Economics, Yale University.

    Cited by:

    1. Barbier de la Serre, A. & Frappa, S. & Montornès, J. & Murez, M., 2008. "La transmission des taux de marché aux taux bancaires : une estimation sur données individuelles françaises," Working papers 194, Banque de France.
    2. Surajit Ray & N. E. Savin, 2008. "The performance of heteroskedasticity and autocorrelation robust tests: a Monte Carlo study with an application to the three-factor Fama-French asset-pricing model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(1), pages 91-109.
    3. Sainan Jin & Peter C.B. Phillips & Yixiao Sun, 2005. "A New Approach to Robust Inference in Cointegration," Cowles Foundation Discussion Papers 1538, Cowles Foundation for Research in Economics, Yale University.

  13. Sainan Jin & Peter C.B. Phillips & Yixiao Sun, 2005. "A New Approach to Robust Inference in Cointegration," Cowles Foundation Discussion Papers 1538, Cowles Foundation for Research in Economics, Yale University.

    Cited by:

    1. Javier Hualde & Fabrizio Iacone, 2015. "Small-b and Fixed-b Asymptotics for Weighted Covariance Estimation in Fractional Cointegration," Journal of Time Series Analysis, Wiley Blackwell, vol. 36(4), pages 528-540, July.
    2. 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.
    3. Pellatt, Daniel F. & Sun, Yixiao, 2023. "Asymptotic F test in regressions with observations collected at high frequency over long span," Journal of Econometrics, Elsevier, vol. 235(2), pages 1281-1309.
    4. Vogelsang, Timothy J. & Wagner, Martin, 2011. "Integrated Modified OLS Estimation and Fixed-b Inference for Cointegrating Regressions," Economics Series 263, Institute for Advanced Studies.
    5. Pellatt , Daniel & Sun, Yixiao, 2020. "Asymptotic F test in Regressions with Observations Collected at High Frequency over Long Span," University of California at San Diego, Economics Working Paper Series qt19f0d9wz, Department of Economics, UC San Diego.
    6. Qunyong Wang & Na Wu, 2012. "Long-run covariance and its applications in cointegration regression," Stata Journal, StataCorp LP, vol. 12(3), pages 525-542, September.

  14. Peter C.B. Phillips & Sainan Jin & Ling Hu, 2005. "Nonstationary Discrete Choice: A Corrigendum and Addendum," Cowles Foundation Discussion Papers 1516, Cowles Foundation for Research in Economics, Yale University.

    Cited by:

    1. Ioannis Kasparis & Peter C.B. Phillips & Tassos Magdalinos, 2012. "Non-linearity Induced Weak Instrumentation," University of Cyprus Working Papers in Economics 02-2012, University of Cyprus Department of Economics.
    2. Rebeca I. Muñoz Torres & David Shepherd, 2014. "Inflation Targeting and the Consistency of Monetary Policy Decisions in Mexico: an Empirical Analysis with Discrete Choice Models," Manchester School, University of Manchester, vol. 82, pages 21-46, December.
    3. Marmer, Vadim, 2008. "Nonlinearity, nonstationarity, and spurious forecasts," Journal of Econometrics, Elsevier, vol. 142(1), pages 1-27, January.
    4. Xu, Peng, 2015. "Testing for joint significance in nonstationary ordered choice model," Economics Letters, Elsevier, vol. 130(C), pages 5-8.
    5. Helmut Herwartz & Konstantin A. Kholodilin, 2011. "In-Sample and Out-of-Sample Prediction of Stock Market Bubbles: Cross-Sectional Evidence," Discussion Papers of DIW Berlin 1173, DIW Berlin, German Institute for Economic Research.
    6. Hyeongwoo Kim, 2014. "Estimating Interest Rate Setting Behavior in Korea: An Ordered Probit Model Approach," Auburn Economics Working Paper Series auwp2014-02, Department of Economics, Auburn University.
    7. Hyeongwoo Kim & John Jackson & Richard Saba, 2009. "Forecasting the FOMC's interest rate setting behavior: a further analysis," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 28(2), pages 145-165.
    8. Peter C.B. Phillips & Sainan Jin & Ling Hu, 2005. "Nonstationary Discrete Choice: A Corrigendum and Addendum," Cowles Foundation Discussion Papers 1516, Cowles Foundation for Research in Economics, Yale University.
    9. de Jong, Robert & Hu, Ling, 2011. "A note on nonlinear models with integrated regressors and convergence order results," Economics Letters, Elsevier, vol. 111(1), pages 23-25, April.
    10. Jin, Sainan, 2009. "Discrete choice modeling with nonstationary panels applied to exchange rate regime choice," Journal of Econometrics, Elsevier, vol. 150(2), pages 312-321, June.
    11. Nojković, Aleksandra & Petrović, Pavle, 2015. "Monetary policy rule in inflation targeting emerging European countries: A discrete choice approach," Journal of Policy Modeling, Elsevier, vol. 37(4), pages 577-595.
    12. Jef Boeckx, 2011. "Estimating monetary policy reaction functions : A discrete choice approach," Working Paper Research 210, National Bank of Belgium.

  15. Phillips, Peter C.B. & Sun, Yixiao & Jin, Sainan, 2004. "Consistent HAC Estimation and Robust Regression Testing Using Sharp Origin Kernels with No Truncation," University of California at San Diego, Economics Working Paper Series qt6d36x00z, Department of Economics, UC San Diego.

    Cited by:

    1. Harding, Don & Pagan, Adrian, 2006. "Synchronization of cycles," Journal of Econometrics, Elsevier, vol. 132(1), pages 59-79, May.
    2. Surajit Ray & N. E. Savin, 2008. "The performance of heteroskedasticity and autocorrelation robust tests: a Monte Carlo study with an application to the three-factor Fama-French asset-pricing model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(1), pages 91-109.
    3. Peter C.B. Phillips & Yixiao Sun & Sainan Jin, 2005. "Improved HAR Inference," Cowles Foundation Discussion Papers 1513, Cowles Foundation for Research in Economics, Yale University.
    4. Richard Smith, 2004. "Automatic positive semi-definite HAC covariance matrix and GMM estimation," CeMMAP working papers CWP17/04, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    5. Baddeley, M. & Fingleton, B., 2008. "Globalisation and Wage Differentials: A Spatial Analysis," Cambridge Working Papers in Economics 0845, Faculty of Economics, University of Cambridge.
    6. Justin Doran & Bernard Fingleton, 2018. "US Metropolitan Area Resilience: Insights from dynamic spatial panel estimation," Environment and Planning A, , vol. 50(1), pages 111-132, February.
    7. João Valle e Azevedo & João Tovar Jalles, 2011. "Rational vs. Professional Forecasts," Working Papers w201114, Banco de Portugal, Economics and Research Department.
    8. Richard Smith, 2004. "Automatic positive semi-definite HAC covariance matrix and GMM estimation," CeMMAP working papers 17/04, Institute for Fiscal Studies.
    9. Thieu, Le Quyen, 2016. "Variance targeting estimation of the BEKK-X model," MPRA Paper 75572, University Library of Munich, Germany.
    10. Hansen, Christian B., 2007. "Asymptotic properties of a robust variance matrix estimator for panel data when T is large," Journal of Econometrics, Elsevier, vol. 141(2), pages 597-620, December.
    11. Jen-Je Su, 2005. "On the size and power of testing for no autocorrelation under weak assumptions," Applied Financial Economics, Taylor & Francis Journals, vol. 15(4), pages 247-257.
    12. Thieu, Le Quyen, 2016. "Equation by equation estimation of the semi-diagonal BEKK model with covariates," MPRA Paper 75582, University Library of Munich, Germany.

  16. Phillips, Peter C.B. & Sun, Yixiao & Jin, Sainan, 2004. "Spectral Density Estimation and Robust Hypothesis Testing Using Steep Origin Kernels Without Truncation," University of California at San Diego, Economics Working Paper Series qt6mf9q2rt, Department of Economics, UC San Diego.

    Cited by:

    1. Surajit Ray & N. E. Savin, 2008. "The performance of heteroskedasticity and autocorrelation robust tests: a Monte Carlo study with an application to the three-factor Fama-French asset-pricing model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(1), pages 91-109.
    2. Wei-Ming Lee & Chung-Ming Kuan, 2006. "Testing Over-Identifying Restrictions without Consistent Estimation of the Asymptotic Covariance Matrix," IEAS Working Paper : academic research 06-A009, Institute of Economics, Academia Sinica, Taipei, Taiwan.
    3. Sun, Yixiao, 2011. "Robust trend inference with series variance estimator and testing-optimal smoothing parameter," Journal of Econometrics, Elsevier, vol. 164(2), pages 345-366, October.
    4. Pesaran, M. Hashem & Timmermann, Allan, 2006. "Testing Dependence among Serially Correlated Multi-Category Variables," IZA Discussion Papers 2196, Institute of Labor Economics (IZA).
    5. Elmar Mertens, 2010. "Are spectral estimators useful for implementing long-run restrictions in SVARs?," Finance and Economics Discussion Series 2010-09, Board of Governors of the Federal Reserve System (U.S.).
    6. Yang, Lixiong & Lee, Chingnun & Shie, Fu Shuen, 2014. "How close a relationship does a capital market have with other markets? A reexamination based on the equal variance test," Pacific-Basin Finance Journal, Elsevier, vol. 26(C), pages 198-226.
    7. Xiaofeng Shao, 2010. "A self‐normalized approach to confidence interval construction in time series," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 72(3), pages 343-366, June.
    8. Mertens, Elmar, 2012. "Are spectral estimators useful for long-run restrictions in SVARs?," Journal of Economic Dynamics and Control, Elsevier, vol. 36(12), pages 1831-1844.
    9. Guay, Alain & Guerre, Emmanuel & Lazarová, Štěpána, 2013. "Robust adaptive rate-optimal testing for the white noise hypothesis," Journal of Econometrics, Elsevier, vol. 176(2), pages 134-145.
    10. Hanck, Christoph & Demetrescu, Matei & Kruse, Robinson, 2015. "Fixed-b Asymptotics for t-Statistics in the Presence of Time-Varying Volatility," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 112916, Verein für Socialpolitik / German Economic Association.
    11. Sun, Yixiao & Phillips, Peter C.B. & Jin, Sainan, 2011. "Power Maximization And Size Control In Heteroskedasticity And Autocorrelation Robust Tests With Exponentiated Kernels," Econometric Theory, Cambridge University Press, vol. 27(6), pages 1320-1368, December.
    12. McElroy, Tucker S. & Politis, Dimitris N., 2014. "Spectral density and spectral distribution inference for long memory time series via fixed-b asymptotics," Journal of Econometrics, Elsevier, vol. 182(1), pages 211-225.
    13. Politis, D N, 2009. "Higher-Order Accurate, Positive Semi-definite Estimation of Large-Sample Covariance and Spectral Density Matrices," University of California at San Diego, Economics Working Paper Series qt66w826hz, Department of Economics, UC San Diego.
    14. Pötscher, Benedikt M. & Preinerstorfer, David, 2018. "Controlling the size of autocorrelation robust tests," Journal of Econometrics, Elsevier, vol. 207(2), pages 406-431.
    15. Lu, Ye & Park, Joon Y., 2019. "Estimation of longrun variance of continuous time stochastic process using discrete sample," Journal of Econometrics, Elsevier, vol. 210(2), pages 236-267.
    16. Ray, Surajit & Savin, N.E. & Tiwari, Ashish, 2009. "Testing the CAPM revisited," Journal of Empirical Finance, Elsevier, vol. 16(5), pages 721-733, December.
    17. Kolokotrones, Thomas & Stock, James H. & Walker, Christopher D., 2024. "Is Newey–West optimal among first-order kernels?," Journal of Econometrics, Elsevier, vol. 240(2).
    18. Matei Demetrescu & Christoph Hanck & Robinson Kruse, 2016. "Fixed-b Inference in the Presence of Time-Varying Volatility," CREATES Research Papers 2016-01, Department of Economics and Business Economics, Aarhus University.
    19. Sun, Yixiao, 2013. "Fixed-smoothing Asymptotics in a Two-step GMM Framework," University of California at San Diego, Economics Working Paper Series qt64x4z265, Department of Economics, UC San Diego.
    20. Hirukawa, Masayuki, 2023. "Robust Covariance Matrix Estimation in Time Series: A Review," Econometrics and Statistics, Elsevier, vol. 27(C), pages 36-61.
    21. Shin-Kun Peng & Takatoshi Tabuchi, 2005. "Spatial Competition in Variety and Number of Stores," CIRJE F-Series CIRJE-F-360, CIRJE, Faculty of Economics, University of Tokyo.
    22. Ulrich K. Müller & Mark W. Watson, 2015. "Low-Frequency Econometrics," NBER Working Papers 21564, National Bureau of Economic Research, Inc.
    23. Steigerwald, Douglas G & Erb, Jack, 2007. "Accurately Sized Test Statistics with Misspecified Conditional Homoskedasticity," University of California at Santa Barbara, Economics Working Paper Series qt5rv0z5dz, Department of Economics, UC Santa Barbara.
    24. Qihui Chen & Zheng Fang, 2018. "Improved Inference on the Rank of a Matrix," Papers 1812.02337, arXiv.org, revised Mar 2019.
    25. Preinerstorfer, David & Pötscher, Benedikt M., 2013. "On Size and Power of Heteroscedasticity and Autocorrelation Robust Tests," MPRA Paper 45675, University Library of Munich, Germany.

  17. Peter C.B. Phillips & Yixiao Sun & Sainan Jin, 2003. "Long Run Variance Estimation Using Steep Origin Kernels without Truncation," Cowles Foundation Discussion Papers 1437, Cowles Foundation for Research in Economics, Yale University.

    Cited by:

    1. Masayuki Hirukawa, 2006. "A Modified Nonparametric Prewhitened Covariance Estimator," Journal of Time Series Analysis, Wiley Blackwell, vol. 27(3), pages 441-476, May.
    2. Peter C.B. Phillips & Yixiao Sun & Sainan Jin, 2005. "Improved HAR Inference," Cowles Foundation Discussion Papers 1513, Cowles Foundation for Research in Economics, Yale University.
    3. Ole E. Barndorff-Nielsen & Peter Reinhard Hansen & Asger Lunde & Neil Shephard, 2006. "Designing realised kernels to measure the ex-post variation of equity prices in the presence of noise," Economics Papers 2006-W03, Economics Group, Nuffield College, University of Oxford.

  18. Sainan Jin & Peter C.B. Phillips, 2002. "The KPSS Test with Seasonal Dummies," Cowles Foundation Discussion Papers 1373, Cowles Foundation for Research in Economics, Yale University.

    Cited by:

    1. Haldrup, Niels & Nielsen, Morten Orregaard, 2006. "A regime switching long memory model for electricity prices," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 349-376.
    2. Halunga, Andreea G. & Osborn, Denise R. & Sensier, Marianne, 2009. "Changes in the order of integration of US and UK inflation," Economics Letters, Elsevier, vol. 102(1), pages 30-32, January.
    3. Vasilii Erokhin & Tianming Gao, 2020. "Impacts of COVID-19 on Trade and Economic Aspects of Food Security: Evidence from 45 Developing Countries," IJERPH, MDPI, vol. 17(16), pages 1-28, August.
    4. Natasha Kang & Vadim Marmer, 2020. "Modeling Long Cycles," Papers 2010.13877, arXiv.org, revised Sep 2023.
    5. Lujia Bai & Weichi Wu, 2021. "Detecting long-range dependence for time-varying linear models," Papers 2110.08089, arXiv.org, revised Mar 2023.
    6. Choudhry, Taufiq, 2003. "Stock market volatility and the US consumer expenditure," Journal of Macroeconomics, Elsevier, vol. 25(3), pages 367-385, September.
    7. Matei Demetrescu & Uwe Hassler, 2007. "Effect of neglected deterministic seasonality on unit root tests," Statistical Papers, Springer, vol. 48(3), pages 385-402, September.
    8. Josep Carrion-i-Silvestre & Andreu Sansó, 2006. "A guide to the computation of stationarity tests," Empirical Economics, Springer, vol. 31(2), pages 433-448, June.
    9. Joseph Ross, 2021. "Stationarity Statistics on Rolling Windows," Computational Economics, Springer;Society for Computational Economics, vol. 57(2), pages 655-691, February.
    10. Harvey, A. & Thiele, S., 2017. "Co-integration and control: assessing the impact of events using time series data," Cambridge Working Papers in Economics 1731, Faculty of Economics, University of Cambridge.

Articles

  1. 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.
  2. 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.
  3. Peter C. B. Phillips & Sainan Jin, 2021. "Business Cycles, Trend Elimination, And The Hp Filter," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 62(2), pages 469-520, May.
    See citations under working paper version above.
  4. 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.
  5. 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. Xiaorong Yang & Jia Chen & Degui Li & Runze Li, 2024. "Functional-Coefficient Quantile Regression for Panel Data with Latent Group Structure," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 42(3), pages 1026-1040, July.
    2. Huang, Danyang & Hu, Wei & Jing, Bingyi & Zhang, Bo, 2023. "Grouped spatial autoregressive model," Computational Statistics & Data Analysis, Elsevier, vol. 178(C).
    3. 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.
    4. 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.
    5. 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.
    6. Okui, Ryo & Wang, Wendun, 2021. "Heterogeneous structural breaks in panel data models," Journal of Econometrics, Elsevier, vol. 220(2), pages 447-473.
    7. Yiren Wang & Liangjun Su & Yichong Zhang, 2022. "Low-rank Panel Quantile Regression: Estimation and Inference," Papers 2210.11062, arXiv.org.
    8. 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.
    9. 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.
    10. Boyuan Zhang, 2020. "Forecasting with Bayesian Grouped Random Effects in Panel Data," Papers 2007.02435, arXiv.org, revised Oct 2020.
    11. 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).
    12. 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).
    13. Wang, Wuyi & Su, Liangjun, 2021. "Identifying latent group structures in nonlinear panels," Journal of Econometrics, Elsevier, vol. 220(2), pages 272-295.
    14. 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.
    15. 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.
    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. 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.
    18. 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.
    19. Mehrabani, Ali, 2023. "Estimation and identification of latent group structures in panel data," Journal of Econometrics, Elsevier, vol. 235(2), pages 1464-1482.
    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. Daniel Czarnowske, 2022. "A Classifier-Lasso Approach for Estimating Production Functions with Latent Group Structures," Papers 2203.02220, arXiv.org.
    22. Zhan Gao & Zhentao Shi, 2021. "Implementing Convex Optimization in R: Two Econometric Examples," Computational Economics, Springer;Society for Computational Economics, vol. 58(4), pages 1127-1135, December.
    23. Boyuan Zhang, 2022. "Incorporating Prior Knowledge of Latent Group Structure in Panel Data Models," Papers 2211.16714, arXiv.org, revised Oct 2023.
    24. Freeman, Hugo & Weidner, Martin, 2023. "Linear panel regressions with two-way unobserved heterogeneity," Journal of Econometrics, Elsevier, vol. 237(1).
    25. Katerina Chrysikou & George Kapetanios, 2024. "Heterogeneous Grouping Structures in Panel Data," Papers 2407.19509, arXiv.org.
    26. Oh, Dong Hwan & Patton, Andrew J., 2023. "Dynamic factor copula models with estimated cluster assignments," Journal of Econometrics, Elsevier, vol. 237(2).
    27. 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.
    28. 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.

  6. Jin, Sainan & Corradi, Valentina & Swanson, Norman R., 2017. "Robust Forecast Comparison," Econometric Theory, Cambridge University Press, vol. 33(6), pages 1306-1351, December.
    See citations under working paper version above.
  7. 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, O. & Xiao, Z., 2019. "Efficient Estimation of Nonparametric Regression in The Presence of Dynamic Heteroskedasticity," Cambridge Working Papers in Economics 1907, Faculty of Economics, University of Cambridge.
    2. 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.

  8. 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.
  9. 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.
  10. Peter C. B. Phillips & Sainan Jin, 2014. "Testing the Martingale Hypothesis," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 32(4), pages 537-554, October.
    See citations under working paper version above.
  11. 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. 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.
    4. Giannone, Domenico & Lenza, Michele & Primiceri, Giorgio, 2017. "Economic Predictions with Big Data: The Illusion Of Sparsity," CEPR Discussion Papers 12256, C.E.P.R. Discussion Papers.
    5. 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).
    6. 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.
    7. 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.
    8. Lenza, Michele & Moutachaker, Inès & Paredes, Joan, 2023. "Density forecasts of inflation: a quantile regression forest approach," Working Paper Series 2830, European Central Bank.
    9. Lu, Xun & Su, Liangjun, 2015. "Jackknife model averaging for quantile regressions," Journal of Econometrics, Elsevier, vol. 188(1), pages 40-58.
    10. 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.
    11. Ribeiro, Pinho J., 2017. "Selecting exchange rate fundamentals by bootstrap," International Journal of Forecasting, Elsevier, vol. 33(4), pages 894-914.
    12. 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.
    13. 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.
    14. 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.
    15. 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.

  12. 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. 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.
    2. Christopher F. Parmeter & Jeffrey S. Racine, 2018. "Nonparametric Estimation and Inference for Panel Data Models," Department of Economics Working Papers 2018-02, McMaster University.
    3. 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.
    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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. 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.

  13. 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. 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.
    2. 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.
    3. 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.
    4. Ruiqi Liu & Ben Boukai & Zuofeng Shang, 2019. "Statistical Inference on Partially Linear Panel Model under Unobserved Linearity," Papers 1911.08830, arXiv.org.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. 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.
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    23. 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.
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    25. Jiti Gao & Oliver Linton & Bin Peng, 2022. "A Nonparametric Panel Model for Climate Data with Seasonal and Spatial Variation," Monash Econometrics and Business Statistics Working Papers 9/22, Monash University, Department of Econometrics and Business Statistics.
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    28. Chaohua Dong & Oliver Linton, 2017. "Additive nonparametric models with time variable and both stationary and nonstationary regressions," CeMMAP working papers CWP59/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    29. 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.
    30. 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.
    31. Miao, Ke & Su, Liangjun & Wang, Wendun, 2020. "Panel threshold regressions with latent group structures," Journal of Econometrics, Elsevier, vol. 214(2), pages 451-481.
    32. 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.
    33. 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.
    34. 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.
    35. 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.
    36. Christis Katsouris, 2023. "High Dimensional Time Series Regression Models: Applications to Statistical Learning Methods," Papers 2308.16192, arXiv.org.
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    39. 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.
    40. 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.
    41. 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.
    42. 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.
    43. 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.
    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, 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.
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    47. 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.
    48. 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.
    49. 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.
    50. 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.
    51. Eduardo A. Souza-Rodrigues, 2016. "Nonparametric Regression with Common Shocks," Econometrics, MDPI, vol. 4(3), pages 1-17, September.
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  14. Sun, Yixiao & Phillips, Peter C.B. & Jin, Sainan, 2011. "Power Maximization And Size Control In Heteroskedasticity And Autocorrelation Robust Tests With Exponentiated Kernels," Econometric Theory, Cambridge University Press, vol. 27(6), pages 1320-1368, December.
    See citations under working paper version above.
  15. 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. 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.
    2. Christensen, Bent Jesper & Dahl, Christian M. & Iglesias, Emma M., 2012. "Semiparametric inference in a GARCH-in-mean model," Journal of Econometrics, Elsevier, vol. 167(2), pages 458-472.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. Sun, Yiguo, 2016. "Functional-coefficient spatial autoregressive models with nonparametric spatial weights," Journal of Econometrics, Elsevier, vol. 195(1), pages 134-153.
    9. 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.
    10. Suli Cheng & Jianbao Chen, 2021. "Estimation of partially linear single-index spatial autoregressive model," Statistical Papers, Springer, vol. 62(1), pages 495-531, February.
    11. 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.
    12. Kwok, Hon Ho, 2019. "Identification and estimation of linear social interaction models," Journal of Econometrics, Elsevier, vol. 210(2), pages 434-458.
    13. 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.
    14. Gupta, Abhimanyu, 2019. "Estimation Of Spatial Autoregressions With Stochastic Weight Matrices," Econometric Theory, Cambridge University Press, vol. 35(2), pages 417-463, April.
    15. 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.
    16. 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.
    17. 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.
    18. 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.
    19. Sun, Yiguo & Malikov, Emir, 2017. "Estimation and Inference in Functional-Coefficient Spatial Autoregressive Panel Data Models with Fixed Effects," MPRA Paper 83671, University Library of Munich, Germany.
    20. 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.
    21. 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.
    22. 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.
    23. Gupta, Abhimanyu, 2018. "Nonparametric specification testing via the trinity of tests," Journal of Econometrics, Elsevier, vol. 203(1), pages 169-185.
    24. Su, Liangjun, 2012. "Semiparametric GMM estimation of spatial autoregressive models," Journal of Econometrics, Elsevier, vol. 167(2), pages 543-560.
    25. Jianbao Chen & Suli Cheng, 2021. "GMM Estimation of a Partially Linear Additive Spatial Error Model," Mathematics, MDPI, vol. 9(6), pages 1-28, March.
    26. Luo, Guowang & Wu, Mixia & Pang, Zhen, 2022. "Estimation of spatial autoregressive models with covariate measurement errors," Journal of Multivariate Analysis, Elsevier, vol. 192(C).
    27. 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.
    28. Malikov, Emir & Sun, Yiguo, 2017. "Semiparametric Estimation and Testing of Smooth Coefficient Spatial Autoregressive Models," MPRA Paper 77253, University Library of Munich, Germany.
    29. 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.
    30. 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.
    31. 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.
    32. 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.
    33. 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.
    34. 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.
    35. Konstantinidi, Antri & Kourtellos, Andros & Sun, Yiguo, 2023. "Social threshold regression," Journal of Econometrics, Elsevier, vol. 235(2), pages 2057-2081.
    36. 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.
    37. 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.
    38. 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.
    39. 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.
    40. Abhimanyu Gupta & Xi Qu, 2021. "Consistent specification testing under spatial dependence," Papers 2101.10255, arXiv.org, revised Aug 2022.
    41. 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.
    42. Kunming Li & Liting Fang, 2024. "Bayesian Estimation of the Semiparametric Spatial Lag Model," Mathematics, MDPI, vol. 12(14), pages 1-17, July.
    43. Sun, Yan, 2017. "Estimation of single-index model with spatial interaction," Regional Science and Urban Economics, Elsevier, vol. 62(C), pages 36-45.
    44. 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.
    45. 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.
    46. 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.
    47. 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.
    48. Cheng, Suli & Chen, Jianbao, 2023. "GMM estimation of partially linear additive spatial autoregressive model," Computational Statistics & Data Analysis, Elsevier, vol. 182(C).
    49. 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.
    50. 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).

  16. Jin, Sainan, 2009. "Discrete choice modeling with nonstationary panels applied to exchange rate regime choice," Journal of Econometrics, Elsevier, vol. 150(2), pages 312-321, June.

    Cited by:

    1. Liu, Xiaohui & Zhang, Jing, 2015. "Export diversification and exchange-rate regimes: Evidences from 72 developing countries," MPRA Paper 66448, University Library of Munich, Germany.
    2. Chu, Chia-Shang J. & Liu, Nan & Zhang, Lina, 2017. "Significance test in nonstationary logit panel model with serially correlated dependent variable," Economics Letters, Elsevier, vol. 159(C), pages 37-41.

  17. Yixiao Sun & Peter C. B. Phillips & Sainan Jin, 2008. "Optimal Bandwidth Selection in Heteroskedasticity-Autocorrelation Robust Testing," Econometrica, Econometric Society, vol. 76(1), pages 175-194, January.
    See citations under working paper version above.
  18. Phillips, Peter C.B. & Jin, Sainan & Hu, Ling, 2007. "Nonstationary discrete choice: A corrigendum and addendum," Journal of Econometrics, Elsevier, vol. 141(2), pages 1115-1130, December.
    See citations under working paper version above.
  19. Peter C. B. Phillips & Yixiao Sun & Sainan Jin, 2006. "Spectral Density Estimation And Robust Hypothesis Testing Using Steep Origin Kernels Without Truncation," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 47(3), pages 837-894, August.
    See citations under working paper version above.
  20. Jin, Sainan & Phillips, Peter C.B. & Sun, Yixiao, 2006. "A new approach to robust inference in cointegration," Economics Letters, Elsevier, vol. 91(2), pages 300-306, May.
    See citations under working paper version above.
  21. 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. 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.
    2. Alessio Ciarlone, 2015. "House price cycles in emerging economies," Studies in Economics and Finance, Emerald Group Publishing Limited, vol. 32(1), pages 17-52, March.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.

  22. 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.

  23. Phillips, Peter C. B. & Jin, Sainan, 2002. "The KPSS test with seasonal dummies," Economics Letters, Elsevier, vol. 77(2), pages 239-243, October.
    See citations under working paper version above.
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