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Zhipeng Liao

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.

Blog mentions

As found by EconAcademics.org, the blog aggregator for Economics research:
  1. Zhipeng Liao & Peter C.B. Phillips, 2012. "Automated Estimation of Vector Error Correction Models," Cowles Foundation Discussion Papers 1873, Cowles Foundation for Research in Economics, Yale University.

    Mentioned in:

    1. My "Must Read" List
      by Dave Giles in Econometrics Beat: Dave Giles' Blog on 2012-09-27 06:33:00

Working papers

  1. 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.

    Cited by:

    1. Luciano de Castro & Antonio F. Galvao & David M. Kaplan & Xin Liu, 2017. "Smoothed GMM for quantile models," Papers 1707.03436, arXiv.org, revised Feb 2018.
    2. Firpo, Sergio & Galvao, Antonio F. & Pinto, Cristine & Poirier, Alexandre & Sanroman, Graciela, 2022. "GMM quantile regression," Journal of Econometrics, Elsevier, vol. 230(2), pages 432-452.
    3. Xiaohong Chen & Yin Jia Jeff Qiu, 2016. "Methods for Nonparametric and Semiparametric Regressions with Endogeneity: A Gentle Guide," Annual Review of Economics, Annual Reviews, vol. 8(1), pages 259-290, October.
    4. Victor Chernozhukov & Juan Carlos Escanciano & Hidehiko Ichimura & Whitney K. Newey & James M. Robins, 2022. "Locally Robust Semiparametric Estimation," Econometrica, Econometric Society, vol. 90(4), pages 1501-1535, July.
    5. Chaohua Dong & Jiti Gao & Oliver Linton, 2018. "High dimensional semiparametric moment restriction models," CeMMAP working papers CWP04/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    6. Jiafeng Chen & Xiaohong Chen & Elie Tamer, 2021. "Efficient Estimation in NPIV Models: A Comparison of Various Neural Networks-Based Estimators," Papers 2110.06763, arXiv.org, revised Oct 2022.
    7. Hidehiko Ichimura & Whitney K. Newey, 2017. "The influence function of semiparametric estimators," CeMMAP working papers 06/17, Institute for Fiscal Studies.
    8. Chen, Jiafeng & Ritzwoller, David M., 2023. "Semiparametric estimation of long-term treatment effects," Journal of Econometrics, Elsevier, vol. 237(2).
    9. Jean-Jacques Forneron, 2023. "Noisy, Non-Smooth, Non-Convex Estimation of Moment Condition Models," Papers 2301.07196, arXiv.org, revised Feb 2023.
    10. Chen, Jiafeng & Chen, Xiaohong & Tamer, Elie, 2023. "Efficient estimation of average derivatives in NPIV models: Simulation comparisons of neural network estimators," Journal of Econometrics, Elsevier, vol. 235(2), pages 1848-1875.
    11. Chen, Xiaohong & Liu, Ying & Ma, Shujie & Zhang, Zheng, 2024. "Causal inference of general treatment effects using neural networks with a diverging number of confounders," Journal of Econometrics, Elsevier, vol. 238(1).
    12. Jiafeng Chen & Xiaohong Chen & Elie Tamer, 2021. "Efficient Estimation of Average Derivatives in NPIV Models: Simulation Comparisons of Neural Network Estimators," Cowles Foundation Discussion Papers 2319, Cowles Foundation for Research in Economics, Yale University.
    13. Liu, Lin & Mukherjee, Rajarshi & Robins, James M., 2024. "Assumption-lean falsification tests of rate double-robustness of double-machine-learning estimators," Journal of Econometrics, Elsevier, vol. 240(2).
    14. Zhao, Puying & Haziza, David & Wu, Changbao, 2020. "Survey weighted estimating equation inference with nuisance functionals," Journal of Econometrics, Elsevier, vol. 216(2), pages 516-536.
    15. Minji Bang & Wayne Yuan Gao & Andrew Postlewaite & Holger Sieg, 2021. "Using Monotonicity Restrictions to Identify Models with Partially Latent Covariates," Papers 2101.05847, arXiv.org, revised Jun 2022.
    16. Luciano de Castro & Antonio F. Galvao & David M. Kaplan, 2017. "Smoothed instrumental variables quantile regression, with estimation of quantile Euler equations," Working Papers 1710, Department of Economics, University of Missouri, revised 28 Feb 2018.
    17. Francesco Bravo, 2022. "Misspecified semiparametric model selection with weakly dependent observations," Journal of Time Series Analysis, Wiley Blackwell, vol. 43(4), pages 558-586, July.
    18. Jean-Jacques Forneron, 2019. "A Sieve-SMM Estimator for Dynamic Models," Papers 1902.01456, arXiv.org, revised Jan 2023.
    19. Ganesh Karapakula, 2023. "Stable Probability Weighting: Large-Sample and Finite-Sample Estimation and Inference Methods for Heterogeneous Causal Effects of Multivalued Treatments Under Limited Overlap," Papers 2301.05703, arXiv.org, revised Jan 2023.
    20. Greg Lewis & Vasilis Syrgkanis, 2018. "Adversarial Generalized Method of Moments," Papers 1803.07164, arXiv.org, revised Apr 2018.

  2. Xu Cheng & Zhipeng Liao & Frank Schorfheide, 2013. "Shrinkage estimation of high-dimensional factor models with structural instabilities," Working Papers 14-4, Federal Reserve Bank of Philadelphia.

    Cited by:

    1. Ma, Shujie & Su, Liangjun, 2018. "Estimation of large dimensional factor models with an unknown number of breaks," Journal of Econometrics, Elsevier, vol. 207(1), pages 1-29.
    2. Badi Baltagi & Qu Feng & Chihwa Kao, 2019. "Structural Changes in Heterogeneous Panels with Endogenous Regressors," Center for Policy Research Working Papers 214, Center for Policy Research, Maxwell School, Syracuse University.
    3. Laurent Callot & Johannes Tang Kristensen, 2016. "Regularized Estimation of Structural Instability in Factor Models: The US Macroeconomy and the Great Moderation," Advances in Econometrics, in: Dynamic Factor Models, volume 35, pages 437-479, Emerald Group Publishing Limited.
    4. Kose, M. Ayhan & Ha, Jongrim & Ohnsorge, Franziska, 2021. "One-Stop Source: A Global Database of Inflation," CEPR Discussion Papers 16327, C.E.P.R. Discussion Papers.
    5. Matteo Barigozzi & Daniele Massacci, 2022. "Modelling Large Dimensional Datasets with Markov Switching Factor Models," Papers 2210.09828, arXiv.org, revised Dec 2024.
    6. Duan, Jiangtao & Bai, Jushan & Han, Xu, 2023. "Quasi-maximum likelihood estimation of break point in high-dimensional factor models," Journal of Econometrics, Elsevier, vol. 233(1), pages 209-236.
    7. Yohei Yamamoto, 2016. "Forecasting With Nonspurious Factors in U.S. Macroeconomic Time Series," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(1), pages 81-106, January.
    8. Wang, Lu & Zhou, Ruichao & Wu, Jianhong, 2021. "Determining the number of breaks in large dimensional factor models with structural changes," Economics Letters, Elsevier, vol. 199(C).
    9. Han, Xu & Inoue, Atsushi, 2015. "Tests For Parameter Instability In Dynamic Factor Models," Econometric Theory, Cambridge University Press, vol. 31(5), pages 1117-1152, October.
    10. Tatsushi Oka & Pierre Perron, 2016. "Testing for Common Breaks in a Multiple Equations System," Papers 1606.00092, arXiv.org, revised Jan 2018.
    11. Su, Liangjun & Wang, Xia, 2017. "On time-varying factor models: Estimation and testing," Journal of Econometrics, Elsevier, vol. 198(1), pages 84-101.
    12. Alessandro Casini & Pierre Perron, 2018. "Structural Breaks in Time Series," Boston University - Department of Economics - Working Papers Series WP2019-02, Boston University - Department of Economics.
    13. Barbara Rossi, 2019. "Forecasting in the presence of instabilities: How do we know whether models predict well and how to improve them," Economics Working Papers 1711, Department of Economics and Business, Universitat Pompeu Fabra, revised Jul 2021.
    14. Chou, Ray Yeutien & Yen, Tso-Jung & Yen, Yu-Min, 2020. "Macroeconomic forecasting using approximate factor models with outliers," International Journal of Forecasting, Elsevier, vol. 36(2), pages 267-291.
    15. Hyungsik Roger Moon & Martin Weidner, 2019. "Nuclear norm regularized estimation of panel regression models," CeMMAP working papers CWP14/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    16. Badi H. Baltagi & Chihwa Kao & Fa Wang, 2016. "The Identification and Estimation of a Large Factor Model with Structural Instability," Center for Policy Research Working Papers 194, Center for Policy Research, Maxwell School, Syracuse University.
    17. Bai, Jushan & Duan, Jiangtao & Han, Xu, 2024. "The likelihood ratio test for structural changes in factor models," Journal of Econometrics, Elsevier, vol. 238(2).
    18. Fu, Zhonghao & Hong, Yongmiao & Wang, Xia, 2023. "Testing for structural changes in large dimensional factor models via discrete Fourier transform," Journal of Econometrics, Elsevier, vol. 233(1), pages 302-331.
    19. Okui, Ryo & Wang, Wendun, 2021. "Heterogeneous structural breaks in panel data models," Journal of Econometrics, Elsevier, vol. 220(2), pages 447-473.
    20. Christis Katsouris, 2023. "High Dimensional Time Series Regression Models: Applications to Statistical Learning Methods," Papers 2308.16192, arXiv.org.
    21. Thomas Despois & Catherine Doz, 2021. "Identifying and interpreting the factors in factor models via sparsity: Different approaches," PSE Working Papers halshs-02235543, HAL.
    22. Matteo Barigozzi & Lorenzo Trapani, 2018. "Sequential testing for structural stability in approximate factor models," Discussion Papers 18/04, University of Nottingham, Granger Centre for Time Series Econometrics.
    23. Maxime Leroux & Rachidi Kotchoni & Dalibor Stevanovic, 2017. "Forecasting economic activity in data-rich environment," Working Papers hal-04141668, HAL.
    24. Catherine Doz & Peter Fuleky, 2019. "Dynamic Factor Models," Working Papers halshs-02262202, HAL.
    25. Marcelo C. Medeiros & Eduardo F. Mendes, 2015. "l1-Regularization of High-Dimensional Time-Series Models with Flexible Innovations," Textos para discussão 636, Department of Economics PUC-Rio (Brazil).
    26. Bai, Jushan & Han, Xu & Shi, Yutang, 2020. "Estimation and inference of change points in high-dimensional factor models," Journal of Econometrics, Elsevier, vol. 219(1), pages 66-100.
    27. Yiren Wang & Liangjun Su & Yichong Zhang, 2022. "Low-rank Panel Quantile Regression: Estimation and Inference," Papers 2210.11062, arXiv.org.
    28. Chen, Liang, 2015. "Estimating the common break date in large factor models," Economics Letters, Elsevier, vol. 131(C), pages 70-74.
    29. Matteo Barigozzi & Marc Hallin, 2023. "Dynamic Factor Models: a Genealogy," Papers 2310.17278, arXiv.org, revised Jan 2024.
    30. Boudt, Kris & Heyndels, Ewoud, 2024. "Robust interactive fixed effects," Econometrics and Statistics, Elsevier, vol. 29(C), pages 206-223.
    31. Barigozzi, Matteo & Cho, Haeran & Fryzlewicz, Piotr, 2018. "Simultaneous multiple change-point and factor analysis for high-dimensional time series," LSE Research Online Documents on Economics 88110, London School of Economics and Political Science, LSE Library.
    32. Jianqing Fan & Kunpeng Li & Yuan Liao, 2020. "Recent Developments on Factor Models and its Applications in Econometric Learning," Papers 2009.10103, arXiv.org.
    33. Jaeheon Jung, 2019. "Estimating a Large Covariance Matrix in Time-varying Factor Models," Papers 1910.11965, arXiv.org.
    34. Marcellino, Massimiliano & Aastveit, Knut Are & Carriero, Andrea & Clark, Todd, 2016. "Have Standard VARs Remained Stable Since the Crisis?," CEPR Discussion Papers 11558, C.E.P.R. Discussion Papers.
    35. M. Chudý & S. Karmakar & W. B. Wu, 2020. "Long-term prediction intervals of economic time series," Empirical Economics, Springer, vol. 58(1), pages 191-222, January.
    36. Pierre Guérin & Danilo Leiva-Leon & Massimiliano Marcellino, 2017. "Markov-switching three-pass regression filter," Working Papers 1748, Banco de España.
    37. Baltagi, Badi H. & Kao, Chihwa & Wang, Fa, 2016. "Estimating and testing high dimensional factor models with multiple structural changes," MPRA Paper 98489, University Library of Munich, Germany, revised 26 Jul 2019.
    38. 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).
    39. Matthew F. Dixon & Nicholas G. Polson & Kemen Goicoechea, 2022. "Deep Partial Least Squares for Empirical Asset Pricing," Papers 2206.10014, arXiv.org.
    40. Rachidi Kotchoni & Maxime Leroux & Dalibor Stevanovic, 2019. "Macroeconomic Forecast Accuracy in data-rich environment," Post-Print hal-02435757, HAL.
    41. Simon Freyaldenhoven, 2020. "Identification Through Sparsity in Factor Models," Working Papers 20-25, Federal Reserve Bank of Philadelphia.
    42. Urga, Giovanni & Wang, Fa, 2022. "Estimation and Inference for High Dimensional Factor Model with Regime Switching," MPRA Paper 117012, University Library of Munich, Germany, revised 10 Apr 2023.
    43. Han, Chirok & Kim, Dukpa, 2020. "Testing for the null of block zero restrictions in common factor models," Economics Letters, Elsevier, vol. 188(C).
    44. Thomas Despois & Catherine Doz, 2021. "Identifying and interpreting the factors in factor models via sparsity: Different approaches," Working Papers halshs-02235543, HAL.
    45. Smith, Simon C. & Timmermann, Allan & Zhu, Yinchu, 2019. "Variable selection in panel models with breaks," Journal of Econometrics, Elsevier, vol. 212(1), pages 323-344.
    46. Pablo Guerrón-Quintana & Alexey Khazanov & Molin Zhong, 2023. "Financial and Macroeconomic Data Through the Lens of a Nonlinear Dynamic Factor Model," Finance and Economics Discussion Series 2023-027, Board of Governors of the Federal Reserve System (U.S.).
    47. Li, Degui, 2024. "Estimation of Large Dynamic Covariance Matrices: A Selective Review," Econometrics and Statistics, Elsevier, vol. 29(C), pages 16-30.
    48. Wang, Lu & Wu, Jianhong, 2022. "Estimation of high-dimensional factor models with multiple structural changes," Economic Modelling, Elsevier, vol. 108(C).
    49. Urga, Giovanni & Wang, Fa, 2022. "Estimation and inference for high dimensional factor model with regime switching," MPRA Paper 113172, University Library of Munich, Germany.
    50. Markus Pelger & Ruoxuan Xiong, 2018. "State-Varying Factor Models of Large Dimensions," Papers 1807.02248, arXiv.org, revised Oct 2020.
    51. Qu, Ritong & Timmermann, Allan & Zhu, Yinchu, 2023. "Comparing forecasting performance in cross-sections," Journal of Econometrics, Elsevier, vol. 237(2).
    52. Wu, Jianhong, 2021. "Estimation of high dimensional factor model with multiple threshold-type regime shifts," Computational Statistics & Data Analysis, Elsevier, vol. 157(C).
    53. Cui, Junfeng & Wang, Guanghui & Zou, Changliang & Wang, Zhaojun, 2023. "Change-point testing for parallel data sets with FDR control," Computational Statistics & Data Analysis, Elsevier, vol. 182(C).
    54. Chou, Ray Yeutien & Yen, Tso-Jung & Yen, Yu-Min, 2017. "Risk evaluations with robust approximate factor models," Journal of Banking & Finance, Elsevier, vol. 82(C), pages 244-264.
    55. Chen, Likai & Wang, Weining & Wu, Wei Biao, 2017. "Dynamic semiparametric factor model with a common break," SFB 649 Discussion Papers 2017-026, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    56. Bai, Jushan & Li, Kunpeng & Lu, Lina, 2014. "Estimation and inference of FAVAR models," MPRA Paper 60960, University Library of Munich, Germany.
    57. Ma, Chenchen & Tu, Yundong, 2023. "Shrinkage estimation of multiple threshold factor models," Journal of Econometrics, Elsevier, vol. 235(2), pages 1876-1892.
    58. Chen, Sanpan & Cui, Guowei & Zhang, Jianhua, 2017. "On testing for structural break of coefficients in factor-augmented regression models," Economics Letters, Elsevier, vol. 161(C), pages 141-145.
    59. Lumsdaine, Robin L. & Okui, Ryo & Wang, Wendun, 2023. "Estimation of panel group structure models with structural breaks in group memberships and coefficients," Journal of Econometrics, Elsevier, vol. 233(1), pages 45-65.
    60. Wang, Hanchao & Peng, Bin & Li, Degui & Leng, Chenlei, 2021. "Nonparametric estimation of large covariance matrices with conditional sparsity," Journal of Econometrics, Elsevier, vol. 223(1), pages 53-72.
    61. Urga, Giovanni & Wang, Fa, 2024. "Estimation and inference for high dimensional factor model with regime switching," Journal of Econometrics, Elsevier, vol. 241(2).
    62. Ma, Chenchen & Tu, Yundong, 2023. "Group fused Lasso for large factor models with multiple structural breaks," Journal of Econometrics, Elsevier, vol. 233(1), pages 132-154.

  3. Xu Cheng & Zhipeng Liao & Ruoyao Shi, 2013. "Uniform Asymptotic Risk of Averaging GMM Estimator Robust to Misspecification, Second Version," PIER Working Paper Archive 15-017, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 25 Mar 2015.

    Cited by:

    1. Phillip Heiler & Jana Mareckova, 2019. "Shrinkage for Categorical Regressors," Papers 1901.01898, arXiv.org.
    2. Toru Kitagawa & Chris Muris, 2015. "Model averaging in semiparametric estimation of treatment effects," CeMMAP working papers CWP46/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    3. Francis J. DiTraglia, 2011. "Using Invalid Instruments on Purpose: Focused Moment Selection and Averaging for GMM, Second Version," PIER Working Paper Archive 14-045, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 09 Dec 2014.

  4. Zhipeng Liao & Peter C.B. Phillips, 2012. "Automated Estimation of Vector Error Correction Models," Cowles Foundation Discussion Papers 1873, Cowles Foundation for Research in Economics, Yale University.

    Cited by:

    1. Xun Lu & Su Liangjun, 2015. "Shrinkage Estimation of Dynamic Panel Data Models with Interactive Fixed Effects," Working Papers 02-2015, Singapore Management University, School of Economics.
    2. Tu, Yundong & Yi, Yanping, 2017. "Forecasting cointegrated nonstationary time series with time-varying variance," Journal of Econometrics, Elsevier, vol. 196(1), pages 83-98.
    3. Marie Levakova & Susanne Ditlevsen, 2024. "Penalisation Methods in Fitting High‐Dimensional Cointegrated Vector Autoregressive Models: A Review," International Statistical Review, International Statistical Institute, vol. 92(2), pages 160-193, August.
    4. Liang, Chong & Schienle, Melanie, 2019. "Determination of vector error correction models in high dimensions," Working Paper Series in Economics 124, Karlsruhe Institute of Technology (KIT), Department of Economics and Management.
    5. Thilo Reinschlussel & Martin C. Arnold, 2024. "Information-Enriched Selection of Stationary and Non-Stationary Autoregressions using the Adaptive Lasso," Papers 2402.16580, arXiv.org, revised Jul 2024.
    6. Christian Brownlees & Gu{dh}mundur Stef'an Gu{dh}mundsson, 2021. "Performance of Empirical Risk Minimization for Linear Regression with Dependent Data," Papers 2104.12127, arXiv.org, revised May 2023.
    7. Andrii Babii & Eric Ghysels & Jonas Striaukas, 2024. "High-Dimensional Granger Causality Tests with an Application to VIX and News," Journal of Financial Econometrics, Oxford University Press, vol. 22(3), pages 605-635.
    8. Lee, Ji Hyung & Shi, Zhentao & Gao, Zhan, 2022. "On LASSO for predictive regression," Journal of Econometrics, Elsevier, vol. 229(2), pages 322-349.
    9. Peter C.B. Phillips & Zhipeng Liao, 2012. "Series Estimation of Stochastic Processes: Recent Developments and Econometric Applications," Cowles Foundation Discussion Papers 1871, Cowles Foundation for Research in Economics, Yale University.
    10. Rui Fan & Ji Hyung Lee & Youngki Shin, 2021. "Predictive Quantile Regression with Mixed Roots and Increasing Dimensions: The ALQR Approach," Papers 2101.11568, arXiv.org, revised Dec 2022.
    11. Lin, Yingqian & Tu, Yundong & Yao, Qiwei, 2020. "Estimation for double-nonlinear cointegration," LSE Research Online Documents on Economics 103830, London School of Economics and Political Science, LSE Library.
    12. Thurner, Thomas & Fursov, Konstantin & Nefedova, Alena, 2022. "Early adopters of new transportation technologies: Attitudes of Russia’s population towards car sharing, the electric car and autonomous driving," Transportation Research Part A: Policy and Practice, Elsevier, vol. 155(C), pages 403-417.
    13. Romanowski, Carol & Raj, Rajendra & Schneider, Jennifer & Mishra, Sumita & Shivshankar, Vinay & Ayengar, Srikant & Cueva, Fernando, 2015. "Regional response to large-scale emergency events: Building on historical data," International Journal of Critical Infrastructure Protection, Elsevier, vol. 11(C), pages 12-21.
    14. Koo, Bonsoo & Anderson, Heather M. & Seo, Myung Hwan & Yao, Wenying, 2020. "High-dimensional predictive regression in the presence of cointegration," Journal of Econometrics, Elsevier, vol. 219(2), pages 456-477.
    15. Tu, Yundong & Yao, Qiwei & Zhang, Rongmao, 2020. "Error-correction factor models for high-dimensional cointegrated time series," LSE Research Online Documents on Economics 106994, London School of Economics and Political Science, LSE Library.
    16. Qihui Chen & Zheng Fang, 2018. "Improved Inference on the Rank of a Matrix," Papers 1812.02337, arXiv.org, revised Mar 2019.
    17. Renjie Lu & Philip L.H. Yu & Xiaohang Wang, 2020. "Sparse vector error correction models with application to cointegration‐based trading," Australian & New Zealand Journal of Statistics, Australian Statistical Publishing Association Inc., vol. 62(3), pages 297-321, September.
    18. Wilms, Ines & Croux, Christophe, 2016. "Forecasting using sparse cointegration," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1256-1267.
    19. She, Rui & Ling, Shiqing, 2020. "Inference in heavy-tailed vector error correction models," Journal of Econometrics, Elsevier, vol. 214(2), pages 433-450.
    20. Bergamelli, Michele & Bianchi, Annamaria & Khalaf, Lynda & Urga, Giovanni, 2019. "Combining p-values to test for multiple structural breaks in cointegrated regressions," Journal of Econometrics, Elsevier, vol. 211(2), pages 461-482.
    21. Smeekes, Stephan & Wijler, Etiënne, 2016. "Macroeconomic Forecasting Using Penalized Regression Methods," Research Memorandum 039, Maastricht University, Graduate School of Business and Economics (GSBE).
    22. Medeiros, Marcelo C. & Mendes, Eduardo F., 2016. "ℓ1-regularization of high-dimensional time-series models with non-Gaussian and heteroskedastic errors," Journal of Econometrics, Elsevier, vol. 191(1), pages 255-271.
    23. Smeekes, Stephan & Wijler, Etienne, 2021. "An automated approach towards sparse single-equation cointegration modelling," Journal of Econometrics, Elsevier, vol. 221(1), pages 247-276.
    24. Chatterjee, A. & Gupta, S. & Lahiri, S.N., 2015. "On the residual empirical process based on the ALASSO in high dimensions and its functional oracle property," Journal of Econometrics, Elsevier, vol. 186(2), pages 317-324.
    25. Etienne Wijler, 2022. "A restricted eigenvalue condition for unit-root non-stationary data," Papers 2208.12990, arXiv.org.
    26. Lieb, Lenard & Smeekes, Stephan, 2017. "Inference for Impulse Responses under Model Uncertainty," Research Memorandum 022, Maastricht University, Graduate School of Business and Economics (GSBE).
    27. Qian, Junhui & Su, Liangjun, 2016. "Shrinkage estimation of common breaks in panel data models via adaptive group fused Lasso," Journal of Econometrics, Elsevier, vol. 191(1), pages 86-109.
    28. David Neto, 2023. "Penalized leads-and-lags cointegrating regression: a simulation study and two empirical applications," Empirical Economics, Springer, vol. 65(2), pages 949-971, August.
    29. Lin, Yingqian & Tu, Yundong & Yao, Qiwei, 2020. "Estimation for double-nonlinear cointegration," Journal of Econometrics, Elsevier, vol. 216(1), pages 175-191.

  5. Xiaohong Chen & Zhipeng Liao & Yixiao Sun, 2012. "Sieve Inference on Semi-nonparametric Time Series Models," Cowles Foundation Discussion Papers 1849, Cowles Foundation for Research in Economics, Yale University.

    Cited by:

    1. Xiaohong Chen & Demian Pouzo, 2013. "Sieve Quasi Likelihood Ratio Inference on Semi/nonparametric Conditional Moment Models," Cowles Foundation Discussion Papers 1897, Cowles Foundation for Research in Economics, Yale University.
    2. Xiaohong Chen & Jinyong Hahn & Zhipeng Liao, 2012. "Asymptotic Efficiency of Semiparametric Two-step GMM," Cowles Foundation Discussion Papers 1880, Cowles Foundation for Research in Economics, Yale University.
    3. Peter C.B. Phillips & Zhipeng Liao, 2012. "Series Estimation of Stochastic Processes: Recent Developments and Econometric Applications," Cowles Foundation Discussion Papers 1871, Cowles Foundation for Research in Economics, Yale University.
    4. Xiaohong Chen & Yin Jia Jeff Qiu, 2016. "Methods for Nonparametric and Semiparametric Regressions with Endogeneity: A Gentle Guide," Annual Review of Economics, Annual Reviews, vol. 8(1), pages 259-290, October.
    5. Lee, Jungyoon & Robinson, Peter M., 2016. "Series estimation under cross-sectional dependence," Journal of Econometrics, Elsevier, vol. 190(1), pages 1-17.
    6. Yining Chen, 2015. "Semiparametric Time Series Models with Log-concave Innovations: Maximum Likelihood Estimation and its Consistency," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 42(1), pages 1-31, March.

  6. Xu Cheng & Zhipeng Liao, 2012. "Select the Valid and Relevant Moments: A One-Step Procedure for GMM with Many Moments," PIER Working Paper Archive 12-045, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.

    Cited by:

    1. Yoonseok Lee & Mehmet Caner & Xu Han, 2015. "Adaptive Elastic Net GMM Estimation with Many Invalid Moment Conditions: Simultaneous Model and Moment Selection," Center for Policy Research Working Papers 177, Center for Policy Research, Maxwell School, Syracuse University.
    2. Michael Creel & Dennis Kristensen, 2015. "On Selection of Statistics for Approximate Bayesian Computing or the Method of Simulated Moments," UFAE and IAE Working Papers 950.15, Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC), revised 27 Feb 2015.
    3. Federico A. Bugni & Mehmet Caner & Anders Bredahl Kock & Soumendra Lahiri, 2016. "Inference in partially identified models with many moment inequalities using Lasso," CREATES Research Papers 2016-12, Department of Economics and Business Economics, Aarhus University.
    4. Xu Cheng & Zhipeng Liao & Ruoyao Shi, 2013. "Uniform Asymptotic Risk of Averaging GMM Estimator Robust to Misspecification, Second Version," PIER Working Paper Archive 15-017, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 25 Mar 2015.
    5. Caner, Mehmet & Fan, Qingliang, 2015. "Hybrid generalized empirical likelihood estimators: Instrument selection with adaptive lasso," Journal of Econometrics, Elsevier, vol. 187(1), pages 256-274.
    6. Mehmet Caner & Esfandiar Maasoumi & Juan Andrés Riquelme, 2016. "Moment and IV Selection Approaches: A Comparative Simulation Study," Econometric Reviews, Taylor & Francis Journals, vol. 35(8-10), pages 1562-1581, December.

  7. Xiaohong Chen & Jinyong Hahn & Zhipeng Liao, 2012. "Asymptotic Efficiency of Semiparametric Two-step GMM," Cowles Foundation Discussion Papers 1880, Cowles Foundation for Research in Economics, Yale University.

    Cited by:

    1. Karun Adusumilli & Dita Eckardt, 2019. "Temporal-Difference estimation of dynamic discrete choice models," Papers 1912.09509, arXiv.org, revised Dec 2022.
    2. Xiaohong Chen & Andres Santos, 2015. "Overidentification in Regular Models," Cowles Foundation Discussion Papers 1999, Cowles Foundation for Research in Economics, Yale University.
    3. Michael Jansson & Demian Pouzo, 2019. "Towards a general large sample theory for regularized estimators," CeMMAP working papers CWP63/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    4. Sokbae Lee & Bernard Salani'e, 2020. "Treatment Effects with Targeting Instruments," Papers 2007.10432, arXiv.org, revised Dec 2024.
    5. Luis Alvarez & Ciro Biderman, 2023. "The learning effects of subsidies to bundled goods: a semiparametric approach," Papers 2311.01217, arXiv.org, revised Jun 2024.
    6. Xiaohong Chen & Yin Jia Jeff Qiu, 2016. "Methods for Nonparametric and Semiparametric Regressions with Endogeneity: A Gentle Guide," Annual Review of Economics, Annual Reviews, vol. 8(1), pages 259-290, October.
    7. Sung Jae Jun & Sokbae Lee, 2020. "Causal Inference under Outcome-Based Sampling with Monotonicity Assumptions," Papers 2004.08318, arXiv.org, revised Oct 2023.
    8. Victor Chernozhukov & Juan Carlos Escanciano & Hidehiko Ichimura & Whitney K. Newey & James M. Robins, 2022. "Locally Robust Semiparametric Estimation," Econometrica, Econometric Society, vol. 90(4), pages 1501-1535, July.
    9. Vanhems, Anne & Van Keilegom, Ingrid, 2013. "Semiparametric transformation model with endogeneity: a control function approach," LIDAM Discussion Papers ISBA 2013018, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    10. Victor Aguirregabiria & Allan Collard-Wexler & Stephen P. Ryan, 2021. "Dynamic Games in Empirical Industrial Organization," Working Papers tecipa-706, University of Toronto, Department of Economics.
    11. Haitian Xie, 2020. "Efficient and Robust Estimation of the Generalized LATE Model," Papers 2001.06746, arXiv.org, revised Feb 2022.
    12. Xiaohong Chen & Demian Pouzo & James L. Powell, 2019. "Penalized Sieve GEL for Weighted Average Derivatives of Nonparametric Quantile IV Regressions," Papers 1902.10100, arXiv.org.
    13. Salanié, Bernard & Lee, Sokbae, 2020. "Filtered and Unfiltered Treatment Effects with Targeting Instruments," CEPR Discussion Papers 15092, C.E.P.R. Discussion Papers.
    14. Amandeep Singh & Ye Liu & Hema Yoganarasimhan, 2023. "Choice Models and Permutation Invariance: Demand Estimation in Differentiated Products Markets," Papers 2307.07090, arXiv.org, revised Feb 2024.
    15. Sung Jae Jun & Sokbae (Simon) Lee, 2022. "Identifying the effect of persuasion," CeMMAP working papers 24/22, Institute for Fiscal Studies.
    16. Hidehiko Ichimura & Whitney K. Newey, 2017. "The influence function of semiparametric estimators," CeMMAP working papers 06/17, Institute for Fiscal Studies.
    17. Ruoyao Shi, 2022. "An Averaging Estimator for Two Step M Estimation in Semiparametric Models," Working Papers 202211, University of California at Riverside, Department of Economics.
    18. Semenova, Vira, 2023. "Debiased machine learning of set-identified linear models," Journal of Econometrics, Elsevier, vol. 235(2), pages 1725-1746.
    19. Chen, Xiaohong & Hansen, Lars Peter & Hansen, Peter G., 2024. "Robust inference for moment condition models without rational expectations," Journal of Econometrics, Elsevier, vol. 243(1).
    20. Yusuke Narita & Shota Yasui & Kohei Yata, 2018. "Efficient Counterfactual Learning from Bandit Feedback," Cowles Foundation Discussion Papers 2155, Cowles Foundation for Research in Economics, Yale University.
    21. Sung Jae Jun & Sokbae (Simon) Lee, 2020. "Causal inference in case-control studies," CeMMAP working papers CWP19/20, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    22. Minji Bang & Wayne Yuan Gao & Andrew Postlewaite & Holger Sieg, 2021. "Using Monotonicity Restrictions to Identify Models with Partially Latent Covariates," Papers 2101.05847, arXiv.org, revised Jun 2022.
    23. Andrew Fleck & Edward Furman & Yang Shen, 2024. "Stochastic Loss Reserving: Dependence and Estimation," Papers 2410.14985, arXiv.org.
    24. Sung Jae Jun & Sokbae (Simon) Lee, 2024. "Learning the effect of persuasion via difference-in-differences," CeMMAP working papers 24/24, Institute for Fiscal Studies.
    25. Kai Quan Zhang & Hsing Hung Chen, 2017. "Environmental Performance and Financing Decisions Impact on Sustainable Financial Development of Chinese Environmental Protection Enterprises," Sustainability, MDPI, vol. 9(12), pages 1-14, December.
    26. Daniel A. Ackerberg & Kevin Caves & Garth Frazer, 2015. "Identification Properties of Recent Production Function Estimators," Econometrica, Econometric Society, vol. 83, pages 2411-2451, November.
    27. Lee, Sungwon, 2023. "Efficient estimation of a triangular system of equations for quantile regression," Economics Letters, Elsevier, vol. 226(C).
    28. Liqiong Chen & Antonio F. Galvao & Suyong Song, 2021. "Quantile Regression with Generated Regressors," Econometrics, MDPI, vol. 9(2), pages 1-35, April.
    29. Ganesh Karapakula, 2023. "Stable Probability Weighting: Large-Sample and Finite-Sample Estimation and Inference Methods for Heterogeneous Causal Effects of Multivalued Treatments Under Limited Overlap," Papers 2301.05703, arXiv.org, revised Jan 2023.

  8. Peter C.B. Phillips & Zhipeng Liao, 2012. "Series Estimation of Stochastic Processes: Recent Developments and Econometric Applications," Cowles Foundation Discussion Papers 1871, Cowles Foundation for Research in Economics, Yale University.

    Cited by:

    1. 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.

  9. Xu Cheng & Zhipeng Liao, 2011. "Select the Valid and Relevant Moments: An Information-Based LASSO for GMM with Many Moments, Second Version," PIER Working Paper Archive 13-062, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 21 Oct 2013.

    Cited by:

    1. DiTraglia, Francis J., 2016. "Using invalid instruments on purpose: Focused moment selection and averaging for GMM," Journal of Econometrics, Elsevier, vol. 195(2), pages 187-208.
    2. He, Yinghua, 2015. "Gaming the Boston School Choice Mechanism in Beijing," TSE Working Papers 15-551, Toulouse School of Economics (TSE), revised Sep 2017.
    3. Alastair R. Hall, 2015. "Econometricians Have Their Moments: GMM at 32," The Economic Record, The Economic Society of Australia, vol. 91(S1), pages 1-24, June.
    4. Mehmet Caner & Anders Bredahl Kock, 2013. "Oracle Inequalities for Convex Loss Functions with Non-Linear Targets," CREATES Research Papers 2013-51, Department of Economics and Business Economics, Aarhus University.
    5. Prosper Donovon & Alastair R. Hall, 2015. "GMM and Indirect Inference: An appraisal of their connections and new results on their properties under second order identification," Economics Discussion Paper Series 1505, Economics, The University of Manchester.
    6. Francis J. DiTraglia, 2011. "Using Invalid Instruments on Purpose: Focused Moment Selection and Averaging for GMM, Second Version," PIER Working Paper Archive 14-045, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 09 Dec 2014.
    7. Francis DiTraglia, 2011. "Using Invalid Instruments on Purpose: Focused Moment Selection and Averaging for GMM, Second Version," PIER Working Paper Archive 15-027, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 10 Aug 2015.
    8. Stephen G. Hall, & P. A. V. B. Swamy & George S. Tavlas, 2014. "On the Interpretation of Instrumental Variables in the Presence of Specification Errors," Discussion Papers in Economics 14/19, Division of Economics, School of Business, University of Leicester.

Articles

  1. Jia Li & Zhipeng Liao & Wenyu Zhou, 2023. "Uniform nonparametric inference for spatially dependent panel data: The xtnpsreg command," Stata Journal, StataCorp LP, vol. 23(1), pages 243-264, March.

    Cited by:

    1. Jiti Gao & Bin Peng & Wei Biao Wu & Yayi Yan, 2022. "Time-Varying Multivariate Causal Processes," Papers 2206.00409, arXiv.org.

  2. Cheng, Xu & Liao, Zhipeng, 2015. "Select the valid and relevant moments: An information-based LASSO for GMM with many moments," Journal of Econometrics, Elsevier, vol. 186(2), pages 443-464.

    Cited by:

    1. Xun Lu & Su Liangjun, 2015. "Shrinkage Estimation of Dynamic Panel Data Models with Interactive Fixed Effects," Working Papers 02-2015, Singapore Management University, School of Economics.
    2. Tomohiro Ando & Naoya Sueishi, 2019. "On the Convergence Rate of the SCAD-Penalized Empirical Likelihood Estimator," Econometrics, MDPI, vol. 7(1), pages 1-14, March.
    3. Hyunseung Kang & Youjin Lee & T. Tony Cai & Dylan S. Small, 2022. "Two robust tools for inference about causal effects with invalid instruments," Biometrics, The International Biometric Society, vol. 78(1), pages 24-34, March.
    4. Firpo, Sergio & Galvao, Antonio F. & Pinto, Cristine & Poirier, Alexandre & Sanroman, Graciela, 2022. "GMM quantile regression," Journal of Econometrics, Elsevier, vol. 230(2), pages 432-452.
    5. Windmeijer, F.; Farbmacher, H.; Davies, N.; Davey Smith, G.;, 2017. "On the Use of the Lasso for Instrumental Variables Estimation with Some Invalid Instruments," Health, Econometrics and Data Group (HEDG) Working Papers 17/22, HEDG, c/o Department of Economics, University of York.
    6. Guo, Zijian & Kang, Hyunseung & Cai, T. Tony & Small, Dylan S., 2018. "Testing endogeneity with high dimensional covariates," Journal of Econometrics, Elsevier, vol. 207(1), pages 175-187.
    7. Hao Hao & Bai Huang & Tae-Hwy Lee, 2022. "Model Averaging Estimation of Panel Data Models with Many Instruments and Boosting," Working Papers 202212, University of California at Riverside, Department of Economics.
    8. Timothy B. Armstrong & Michal Koles'r, 2018. "Sensitivity Analysis using Approximate Moment Condition Models," Cowles Foundation Discussion Papers 2158R, Cowles Foundation for Research in Economics, Yale University, revised Feb 2019.
    9. Antoine, Bertille & Renault, Eric, 2024. "GMM with Nearly-Weak Identification," Econometrics and Statistics, Elsevier, vol. 30(C), pages 36-59.
    10. Jonathan Chassot & Michael Creel, 2023. "Constructing Efficient Simulated Moments Using Temporal Convolutional Networks," Working Papers 1412, Barcelona School of Economics.
    11. Jinyuan Chang & Zhentao Shi & Jia Zhang, 2021. "Culling the herd of moments with penalized empirical likelihood," Papers 2108.03382, arXiv.org, revised May 2022.
    12. Hao Zeng & Wei Zhong & Xingbai Xu, 2024. "Transfer Learning for Spatial Autoregressive Models with Application to U.S. Presidential Election Prediction," Papers 2405.15600, arXiv.org, revised Sep 2024.
    13. Fabio Canova & Christian Matthes, 2021. "Dealing with misspecification in structural macroeconometric models," Quantitative Economics, Econometric Society, vol. 12(2), pages 313-350, May.
    14. Shi, Zhentao, 2016. "Econometric estimation with high-dimensional moment equalities," Journal of Econometrics, Elsevier, vol. 195(1), pages 104-119.
    15. Xu Cheng & Zhipeng Liao, 2011. "Select the Valid and Relevant Moments: An Information-Based LASSO for GMM with Many Moments, Second Version," PIER Working Paper Archive 13-062, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 21 Oct 2013.
    16. Qingliang Fan & Yaqian Wu, 2020. "Endogenous Treatment Effect Estimation with some Invalid and Irrelevant Instruments," Papers 2006.14998, arXiv.org.
    17. He, Yinghua, 2015. "Gaming the Boston School Choice Mechanism in Beijing," TSE Working Papers 15-551, Toulouse School of Economics (TSE), revised Sep 2017.
    18. Federico A. Bugni & Mehmet Caner & Anders Bredahl Kock & Soumendra Lahiri, 2016. "Inference in partially identified models with many moment inequalities using Lasso," CREATES Research Papers 2016-12, Department of Economics and Business Economics, Aarhus University.
    19. Tae-Hwy Lee & Tao Wang, 2023. "Estimation and Testing of Forecast Rationality with Many Moments," Working Papers 202307, University of California at Riverside, Department of Economics.
    20. Cizek, P. & Aquaro, M., 2015. "Robust Estimation and Moment Selection in Dynamic Fixed-effects Panel Data Models," Other publications TiSEM 39d0f613-007f-4d21-b1e2-b, Tilburg University, School of Economics and Management.
    21. Prosper Donovon & Alastair R. Hall, 2015. "GMM and Indirect Inference: An appraisal of their connections and new results on their properties under second order identification," Economics Discussion Paper Series 1505, Economics, The University of Manchester.
    22. Shantanu Gupta & Zachary C. Lipton & David Childers, 2021. "Efficient Online Estimation of Causal Effects by Deciding What to Observe," Papers 2108.09265, arXiv.org, revised Oct 2021.
    23. Bai Huang & Tae-Hwy Lee & Aman Ullah, 2017. "A combined estimator of regression models with measurement errors," Indian Economic Review, Springer, vol. 52(1), pages 73-91, December.
    24. Stéphane Bonhomme & Martin Weidner, 2020. "Minimizing Sensitivity to Model Misspecification," CeMMAP working papers CWP37/20, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    25. Prosper Dovonon & Firmin Doko Tchatoka & Michael Aguessy, 2019. "Relevant moment selection under mixed identification strength," School of Economics and Public Policy Working Papers 2019-04, University of Adelaide, School of Economics and Public Policy.
    26. Xu, Ning & Hong, Jian & Fisher, Timothy, 2016. "Model selection consistency from the perspective of generalization ability and VC theory with an application to Lasso," MPRA Paper 71670, University Library of Munich, Germany.
    27. David T. Frazier & Eric Renault, 2019. "Indirect Inference: Which Moments to Match?," Econometrics, MDPI, vol. 7(1), pages 1-17, March.
    28. Byunghoon Kang, 2018. "Higher Order Approximation of IV Estimators with Invalid Instruments," Working Papers 257105320, Lancaster University Management School, Economics Department.
    29. Gold, David & Lederer, Johannes & Tao, Jing, 2020. "Inference for high-dimensional instrumental variables regression," Journal of Econometrics, Elsevier, vol. 217(1), pages 79-111.
    30. Qingliang Fan & Zijian Guo & Ziwei Mei, 2022. "A Heteroskedasticity-Robust Overidentifying Restriction Test with High-Dimensional Covariates," Papers 2205.00171, arXiv.org, revised May 2024.
    31. Qian, Junhui & Su, Liangjun, 2016. "Shrinkage estimation of common breaks in panel data models via adaptive group fused Lasso," Journal of Econometrics, Elsevier, vol. 191(1), pages 86-109.
    32. Stephen G. Hall, & P. A. V. B. Swamy & George S. Tavlas, 2014. "On the Interpretation of Instrumental Variables in the Presence of Specification Errors," Discussion Papers in Economics 14/19, Division of Economics, School of Business, University of Leicester.
    33. Christis Katsouris, 2023. "Optimal Estimation Methodologies for Panel Data Regression Models," Papers 2311.03471, arXiv.org, revised Nov 2023.
    34. Stéphane Bonhomme & Martin Weidner, 2022. "Minimizing sensitivity to model misspecification," Quantitative Economics, Econometric Society, vol. 13(3), pages 907-954, July.
    35. Ruoyao Shi & Zhipeng Liao, 2018. "An Averaging GMM Estimator Robust to Misspecification," Working Papers 201803, University of California at Riverside, Department of Economics.

  3. Liao, Zhipeng & Phillips, Peter C. B., 2015. "Automated Estimation Of Vector Error Correction Models," Econometric Theory, Cambridge University Press, vol. 31(3), pages 581-646, June.
    See citations under working paper version above.
  4. Chen, Xiaohong & Liao, Zhipeng, 2015. "Sieve semiparametric two-step GMM under weak dependence," Journal of Econometrics, Elsevier, vol. 189(1), pages 163-186.
    See citations under working paper version above.
  5. Daniel Ackerberg & Xiaohong Chen & Jinyong Hahn & Zhipeng Liao, 2014. "Asymptotic Efficiency of Semiparametric Two-step GMM," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 81(3), pages 919-943.
    See citations under working paper version above.
  6. Chen, Xiaohong & Liao, Zhipeng & Sun, Yixiao, 2014. "Sieve inference on possibly misspecified semi-nonparametric time series models," Journal of Econometrics, Elsevier, vol. 178(P3), pages 639-658.

    Cited by:

    1. Bartalotti Otávio, 2019. "Regression Discontinuity and Heteroskedasticity Robust Standard Errors: Evidence from a Fixed-Bandwidth Approximation," Journal of Econometric Methods, De Gruyter, vol. 8(1), pages 1-26, January.
    2. Michael Jansson & Demian Pouzo, 2019. "Towards a general large sample theory for regularized estimators," CeMMAP working papers CWP63/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    3. Giovanni Compiani & Philip Haile & Marcelo Sant’Anna, 2020. "Common Values, Unobserved Heterogeneity, and Endogenous Entry in US Offshore Oil Lease Auctions," Journal of Political Economy, University of Chicago Press, vol. 128(10), pages 3872-3912.
    4. Chen, Xiaohong & Liao, Zhipeng, 2014. "Sieve M inference on irregular parameters," Journal of Econometrics, Elsevier, vol. 182(1), pages 70-86.
    5. Byunghoon Kang, 2017. "Inference in Nonparametric Series Estimation with Data-Dependent Undersmoothing," Working Papers 170712442, Lancaster University Management School, Economics Department.
    6. Ying Chen & Bo Li, 2017. "An Adaptive Functional Autoregressive Forecast Model to Predict Electricity Price Curves," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(3), pages 371-388, July.
    7. Lu, Zhentong & Shi, Xiaoxia & Tao, Jing, 2023. "Semi-nonparametric estimation of random coefficients logit model for aggregate demand," Journal of Econometrics, Elsevier, vol. 235(2), pages 2245-2265.
    8. Kim, Min Seong & Sun, Yixiao & Yang, Jingjing, 2016. "A Fixed-bandwidth View of the Pre-asymptotic Inference for Kernel Smoothing with Time Series Data," University of California at San Diego, Economics Working Paper Series qt2240n3n5, Department of Economics, UC San Diego.
    9. Erik Vogt, 2014. "Option-implied term structures," Staff Reports 706, Federal Reserve Bank of New York.
    10. James Wolter, 2015. "Asymptotics for Sieve Estimators of Hazard Rates: Estimating Hazard Functionals," Economics Series Working Papers 760, University of Oxford, Department of Economics.
    11. Byunghoon Kang, 2018. "Inference in Nonparametric Series Estimation with Specification Searches for the Number of Series Terms," Working Papers 240829404, Lancaster University Management School, Economics Department.
    12. Chen, Jiafeng & Ritzwoller, David M., 2023. "Semiparametric estimation of long-term treatment effects," Journal of Econometrics, Elsevier, vol. 237(2).
    13. 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.
    14. Wang, Qiao, 2023. "A simple nonparametric conditional quantile estimator for time series with thin tails," Economics Letters, Elsevier, vol. 232(C).
    15. Li, Jia & Liao, Zhipeng, 2020. "Uniform nonparametric inference for time series," Journal of Econometrics, Elsevier, vol. 219(1), pages 38-51.
    16. 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.
    17. Timothy Christensen, 2014. "Nonparametric Stochastic Discount Factor Decomposition," Papers 1412.4428, arXiv.org, revised May 2017.
    18. Chen, Xiaohong & Liao, Zhipeng, 2015. "Sieve semiparametric two-step GMM under weak dependence," Journal of Econometrics, Elsevier, vol. 189(1), pages 163-186.
    19. An, Yonghong & Hong, Shengjie & Zhang, Daiqiang, 2023. "A structural analysis of simple contracts," Journal of Econometrics, Elsevier, vol. 236(2).
    20. Timothy M. Christensen, 2015. "Nonparametric stochastic discount factor decomposition," CeMMAP working papers CWP24/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    21. Tobias Adrian & Nina Boyarchenko & Domenico Giannone, 2019. "Vulnerable Growth," American Economic Review, American Economic Association, vol. 109(4), pages 1263-1289, April.
    22. Byunghoon Kang, 2019. "Inference in Nonparametric Series Estimation with Specification Searches for the Number of Series Terms," Papers 1909.12162, arXiv.org, revised Feb 2020.
    23. Tobias Adrian & Richard K. Crump & Erik Vogt, 2019. "Nonlinearity and Flight‐to‐Safety in the Risk‐Return Trade‐Off for Stocks and Bonds," Journal of Finance, American Finance Association, vol. 74(4), pages 1931-1973, August.
    24. Xiaohong Chen & Timothy M. Christensen, 2014. "Optimal Uniform Convergence Rates and Asymptotic Normality for Series Estimators under Weak Dependence and Weak Conditions," Cowles Foundation Discussion Papers 1976, Cowles Foundation for Research in Economics, Yale University.
    25. Costanza Naguib & Patrick Gagliardini, 2023. "A Semi-nonparametric Copula Model for Earnings Mobility," Diskussionsschriften dp2302, Universitaet Bern, Departement Volkswirtschaft.
    26. Chen, Xiaohong & Huang, Zhuo & Yi, Yanping, 2021. "Efficient estimation of multivariate semi-nonparametric GARCH filtered copula models," Journal of Econometrics, Elsevier, vol. 222(1), pages 484-501.
    27. Jianqing Fan & Weining Wang & Yue Zhao, 2024. "Conditional nonparametric variable screening by neural factor regression," CeMMAP working papers 17/24, Institute for Fiscal Studies.
    28. Chaohua Dong & Jiti Gao & Bin Peng & Yundong Tu, 2021. "Multiple-index Nonstationary Time Series Models: Robust Estimation Theory and Practice," Papers 2111.02023, arXiv.org.
    29. Xiaohong Chen & Zhuo Huang & Yanping Yi, 2019. "Efficient Estimation of Multivariate Semi-nonparametric GARCH Filtered Copula Models," Cowles Foundation Discussion Papers 2215, Cowles Foundation for Research in Economics, Yale University.
    30. 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.
    31. Xiaohong Chen & Timothy M. Christensen, 2014. "Optimal uniform convergence rates and asymptotic normality for series estimators under weak dependence and weak conditions," CeMMAP working papers 46/14, Institute for Fiscal Studies.
    32. Chaohua Dong & Jiti Gao & Bin Peng & Yundong Tu, 2021. "Multiple-index Nonstationary Time Series Models: Robust Estimation Theory and Practice," Monash Econometrics and Business Statistics Working Papers 18/21, Monash University, Department of Econometrics and Business Statistics.

  7. Chen, Xiaohong & Liao, Zhipeng, 2014. "Sieve M inference on irregular parameters," Journal of Econometrics, Elsevier, vol. 182(1), pages 70-86.

    Cited by:

    1. Giovanni Compiani & Philip Haile & Marcelo Sant’Anna, 2020. "Common Values, Unobserved Heterogeneity, and Endogenous Entry in US Offshore Oil Lease Auctions," Journal of Political Economy, University of Chicago Press, vol. 128(10), pages 3872-3912.
    2. Byunghoon Kang, 2017. "Inference in Nonparametric Series Estimation with Data-Dependent Undersmoothing," Working Papers 170712442, Lancaster University Management School, Economics Department.
    3. Ming Li, 2021. "Identification and Estimation in a Time-Varying Endogenous Random Coefficient Panel Data Model," Papers 2110.00982, arXiv.org, revised Nov 2024.
    4. Hu, Yingyao & Schennach, Susanne & Shiu, Ji-Liang, 2022. "Identification of nonparametric monotonic regression models with continuous nonclassical measurement errors," Journal of Econometrics, Elsevier, vol. 226(2), pages 269-294.
    5. Byunghoon Kang, 2018. "Inference in Nonparametric Series Estimation with Specification Searches for the Number of Series Terms," Working Papers 240829404, Lancaster University Management School, Economics Department.
    6. Li, Jia & Liao, Zhipeng, 2020. "Uniform nonparametric inference for time series," Journal of Econometrics, Elsevier, vol. 219(1), pages 38-51.
    7. Blasques, Francisco & Hoogerkamp, Meindert Heres & Koopman, Siem Jan & van de Werve, Ilka, 2021. "Dynamic factor models with clustered loadings: Forecasting education flows using unemployment data," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1426-1441.
    8. Zhao, Weihua & Lian, Heng, 2016. "Local asymptotics for nonparametric quantile regression with regression splines," Statistics & Probability Letters, Elsevier, vol. 117(C), pages 209-215.
    9. Byunghoon Kang, 2019. "Inference in Nonparametric Series Estimation with Specification Searches for the Number of Series Terms," Papers 1909.12162, arXiv.org, revised Feb 2020.
    10. Xiaohong Chen & Timothy M. Christensen, 2014. "Optimal Uniform Convergence Rates and Asymptotic Normality for Series Estimators under Weak Dependence and Weak Conditions," Cowles Foundation Discussion Papers 1976, Cowles Foundation for Research in Economics, Yale University.
    11. Bu, Ruijun & Kim, Jihyun & Wang, Bin, 2023. "Uniform and Lp convergences for nonparametric continuous time regressions with semiparametric applications," Journal of Econometrics, Elsevier, vol. 235(2), pages 1934-1954.
    12. Laurent Delsol & Ingrid Van Keilegom, 2020. "Semiparametric M-estimation with non-smooth criterion functions," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 72(2), pages 577-605, April.
    13. Escanciano, Juan Carlos, 2023. "Irregular identification of structural models with nonparametric unobserved heterogeneity," Journal of Econometrics, Elsevier, vol. 234(1), pages 106-127.
    14. Nail Kashaev, 2022. "Identification and Estimation of Multinomial Choice Models with Latent Special Covariates," University of Western Ontario, Departmental Research Report Series 20224, University of Western Ontario, Department of Economics.

  8. Liao, Zhipeng, 2013. "Adaptive Gmm Shrinkage Estimation With Consistent Moment Selection," Econometric Theory, Cambridge University Press, vol. 29(5), pages 857-904, October.

    Cited by:

    1. Xun Lu & Su Liangjun, 2015. "Shrinkage Estimation of Dynamic Panel Data Models with Interactive Fixed Effects," Working Papers 02-2015, Singapore Management University, School of Economics.
    2. Hyunseung Kang & Youjin Lee & T. Tony Cai & Dylan S. Small, 2022. "Two robust tools for inference about causal effects with invalid instruments," Biometrics, The International Biometric Society, vol. 78(1), pages 24-34, March.
    3. DiTraglia, Francis J., 2016. "Using invalid instruments on purpose: Focused moment selection and averaging for GMM," Journal of Econometrics, Elsevier, vol. 195(2), pages 187-208.
    4. Yoonseok Lee & Mehmet Caner & Xu Han, 2015. "Adaptive Elastic Net GMM Estimation with Many Invalid Moment Conditions: Simultaneous Model and Moment Selection," Center for Policy Research Working Papers 177, Center for Policy Research, Maxwell School, Syracuse University.
    5. Lewbel, Arthur & Choi, Jin Young & Zhou, Zhuzhu, 2023. "Over-identified Doubly Robust identification and estimation," Journal of Econometrics, Elsevier, vol. 235(1), pages 25-42.
    6. Cheng, Xu & Liao, Zhipeng, 2015. "Select the valid and relevant moments: An information-based LASSO for GMM with many moments," Journal of Econometrics, Elsevier, vol. 186(2), pages 443-464.
    7. Timothy B. Armstrong & Michal Koles'r, 2018. "Sensitivity Analysis using Approximate Moment Condition Models," Cowles Foundation Discussion Papers 2158R, Cowles Foundation for Research in Economics, Yale University, revised Feb 2019.
    8. 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.
    9. Fan, Jianqing & Liao, Yuan, 2012. "Endogeneity in ultrahigh dimension," MPRA Paper 38698, University Library of Munich, Germany.
    10. Jinyuan Chang & Zhentao Shi & Jia Zhang, 2021. "Culling the herd of moments with penalized empirical likelihood," Papers 2108.03382, arXiv.org, revised May 2022.
    11. Phillips, Peter C.B., 2014. "Optimal estimation of cointegrated systems with irrelevant instruments," Journal of Econometrics, Elsevier, vol. 178(P2), pages 210-224.
    12. Shi, Zhentao, 2016. "Econometric estimation with high-dimensional moment equalities," Journal of Econometrics, Elsevier, vol. 195(1), pages 104-119.
    13. Qingliang Fan & Yaqian Wu, 2020. "Endogenous Treatment Effect Estimation with some Invalid and Irrelevant Instruments," Papers 2006.14998, arXiv.org.
    14. Alastair R. Hall, 2015. "Econometricians Have Their Moments: GMM at 32," The Economic Record, The Economic Society of Australia, vol. 91(S1), pages 1-24, June.
    15. Federico A. Bugni & Mehmet Caner & Anders Bredahl Kock & Soumendra Lahiri, 2016. "Inference in partially identified models with many moment inequalities using Lasso," CREATES Research Papers 2016-12, Department of Economics and Business Economics, Aarhus University.
    16. Blasques, Francisco & Duplinskiy, Artem, 2018. "Penalized indirect inference," Journal of Econometrics, Elsevier, vol. 205(1), pages 34-54.
    17. Tae-Hwy Lee & Tao Wang, 2023. "Estimation and Testing of Forecast Rationality with Many Moments," Working Papers 202307, University of California at Riverside, Department of Economics.
    18. Ivan Korolev, 2018. "LM-BIC Model Selection in Semiparametric Models," Papers 1811.10676, arXiv.org.
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