IDEAS home Printed from https://ideas.repec.org/f/c/psu241.html

Liangjun Su

Citations

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

Working papers

  1. Xun Lu & Liangjun Su, 2025. "Two-Way Mean Group Estimators for Heterogeneous Panel Models with Fixed T," Papers 2508.10302, arXiv.org.

    Cited by:

    1. Lu, Xun & Su, Liangjun & Ba, Yinglong, 2026. "On generalized CCE estimation," Journal of Econometrics, Elsevier, vol. 253(C).

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

    Cited by:

    1. Krystian Bua & Giovanni Dosi & Maria Enrica Virgillito, 2025. "The finance-growth nexus over the long-run," LEM Papers Series 2025/24, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    2. Otilia Boldea & Alastair R. Hall, 2025. "Testing for multiple change-points in macroeconometrics: an empirical guide and recent developments," Papers 2507.22204, arXiv.org.
    3. Claudia Pigini & Alessandro Pionati & Francesco Valentini, 2023. "Specification testing with grouped fixed effects," Papers 2310.01950, arXiv.org, revised Sep 2025.
    4. Claudia Pigini & Alessandro Pionati & Francesco Valentini, 2025. "Grouped fixed effects regularization for binary choice models," Papers 2502.06446, arXiv.org, revised Nov 2025.
    5. Katerina Chrysikou & George Kapetanios, 2024. "Heterogeneous Grouping Structures in Panel Data," Papers 2407.19509, arXiv.org.
    6. Bian, Yulin & Su, Liangjun, 2025. "A note on factor models with latent group structures," Economics Letters, Elsevier, vol. 252(C).
    7. Oguzhan Akgun & Ryo Okui, 2025. "Robust Inference Methods for Latent Group Panel Models under Possible Group Non-Separation," Papers 2511.18550, arXiv.org, revised Jul 2026.
    8. 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.

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

    Cited by:

    1. Art=uras Juodis & Martin Weidner, 2026. "Factor-Augmented Panel Regressions and Variance-Weighted Treatment Effects," Papers 2604.18078, arXiv.org.
    2. Yiren Wang & Peter C. B. Phillips & Liangjun Su, 2023. "Panel Data Models with Time-Varying Latent Group Structures," Cowles Foundation Discussion Papers 2364, Cowles Foundation for Research in Economics, Yale University.

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

    Cited by:

    1. Bi, Daning & Chang, Le & Yang, Yanrong, 2025. "Iterative Complement-clustering PCA: Uncovering latent industry structures in stock returns," Economics Letters, Elsevier, vol. 256(C).
    2. Georg Keilbar & Juan M. Rodriguez-Poo & Alexandra Soberon & Weining Wang, 2022. "A projection based approach for interactive fixed effects panel data models," Papers 2201.11482, arXiv.org, revised Feb 2025.
    3. Hou, Li & Jin, Baisuo & Wu, Yuehua, 2024. "Estimation and variable selection for high-dimensional spatial dynamic panel data models," Journal of Econometrics, Elsevier, vol. 238(2).

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

    Cited by:

    1. 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.
    2. Andrei Zeleneev & Weisheng Zhang, 2025. "Tractable Estimation of Nonlinear Panels with Interactive Fixed Effects," Papers 2511.15427, arXiv.org, revised Jun 2026.
    3. Alain Hecq & Luca Margaritella & Stephan Smeekes, 2023. "Inference in Non-stationary High-Dimensional VARs," Papers 2302.01434, arXiv.org, revised Sep 2023.
    4. Chen, Jia & Li, Degui & Li, Yu-Ning & Linton, Oliver, 2025. "Estimating time-varying networks for high-dimensional time series," Journal of Econometrics, Elsevier, vol. 249(PC).
    5. Lin, Ling & Jiang, Yong & Zhou, Zhongbao, 2024. "Asymmetric spillover and network connectedness of policy uncertainty, fossil fuel energy, and global ESG investment," Applied Energy, Elsevier, vol. 368(C).
    6. Zhentao Shi & Jin Xi & Haitian Xie, 2025. "A Synthetic Business Cycle Approach to Counterfactual Analysis with Nonstationary Macroeconomic Data," Papers 2505.22388, arXiv.org.
    7. Christis Katsouris, 2023. "Structural Analysis of Vector Autoregressive Models," Papers 2312.06402, arXiv.org, revised Feb 2024.
    8. Siphat Lim & Edman Flores & Casey Barnett, 2024. "Analyzing the Effectiveness of a System of Equation Model in Comparison to Single Equation Models for Predicting General Price Level in Cambodia," International Journal of Economics and Financial Issues, International Journal of Economics and Financial Issues, vol. 14(5), pages 156-166, September.
    9. Yiren Wang & Peter C. B. Phillips & Liangjun Su, 2023. "Panel Data Models with Time-Varying Latent Group Structures," Cowles Foundation Discussion Papers 2364, Cowles Foundation for Research in Economics, Yale University.
    10. Ando, Tomohiro & Bai, Jushan & Lu, Lina & Vojtech, Cindy M., 2024. "Scenario-based quantile connectedness of the U.S. interbank liquidity risk network," Journal of Econometrics, Elsevier, vol. 244(2).
    11. Lyu, Chenyan & Do, Hung Xuan & Nepal, Rabindra & Jamasb, Tooraj, 2024. "Volatility spillovers and carbon price in the Nordic wholesale electricity markets," Energy Economics, Elsevier, vol. 134(C).
    12. Oelke, Nelly D. & Rai, Ashmita & Hirschkorn, Peter & Mylaine, Breton & Donnelly, Catherine & Montesanti, Stephanie & Isabelle, Gaboury & Maiwald, Karin & Wankah, Paul, 2025. "Developing recommendations and actions for integrated services delivery through primary health care teams in Canada: a deliberative dialogue approach for a national knowledge translation event," Health Policy, Elsevier, vol. 160(C).
    13. Paul Haimerl & Stephan Smeekes & Ines Wilms, 2025. "Estimation of Latent Group Structures in Time-Varying Panel Data Models," Papers 2503.23165, arXiv.org, revised Nov 2025.
    14. Su, Liangjun & Jin, Sainan & Wang, Xia, 2025. "Sieve estimation of state-varying factor models," Journal of Econometrics, Elsevier, vol. 251(C).
    15. Eugene Dettaa & Endong Wang, 2024. "Sparse VARs Do Not Imply Sparse Local Projections: Robust Inference for High-Dimensional Granger Causality," Papers 2410.04330, arXiv.org, revised Feb 2026.
    16. Timothy B. Armstrong & Martin Weidner & Andrei Zeleneev, 2024. "Robust estimation and inference in panels with interactive fixed effects," CeMMAP working papers 28/24, Institute for Fiscal Studies.
    17. Naeem, Muhammad Abubakr & Senthilkumar, Arunachalam & Arfaoui, Nadia & Mohnot, Rajesh, 2024. "Mapping fear in financial markets: Insights from dynamic networks and centrality measures," Pacific-Basin Finance Journal, Elsevier, vol. 85(C).
    18. Wang, Di & Zheng, Yao & Li, Guodong, 2024. "High-dimensional low-rank tensor autoregressive time series modeling," Journal of Econometrics, Elsevier, vol. 238(1).

  6. Wenxin Huang & Sainan Jin & Peter C.B. Phillips & Liangjun Su, 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. Bin Peng & Liangjun Su & Joakim Westerlund & Yanrong Yang, 2021. "Interactive Effects Panel Data Models with General Factors and Regressors," Papers 2111.11506, arXiv.org.
    2. Yanbo Liu & Peter C. B. Phillips & Jun Yu, 2023. "A Panel Clustering Approach To Analyzing Bubble Behavior," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 64(4), pages 1347-1395, November.
    3. 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.
    4. 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.
    5. Jiti Gao & Fei Liu & Bin Peng & Yayi Yan, 2025. "Panel Data Estimation and Inference: Homogeneity versus Heterogeneity," Papers 2502.03019, arXiv.org, revised Jul 2025.
    6. 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.
    7. Saptorshee Kanto Chakraborty & Massimiliano Mazzanti, 2021. "Revisiting the literature on the dynamic Environmental Kuznets Curves using a latent structure approach," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 38(3), pages 923-941, October.
    8. 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.
    9. 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).
    10. Gao, Jiti & Liu, Fei & Peng, Bin & Yan, Yayi, 2023. "Binary response models for heterogeneous panel data with interactive fixed effects," Journal of Econometrics, Elsevier, vol. 235(2), pages 1654-1679.
    11. 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.
    12. Christis Katsouris, 2023. "Optimal Estimation Methodologies for Panel Data Regression Models," Papers 2311.03471, arXiv.org, revised Nov 2023.
    13. 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.

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

    Cited by:

    1. Nabil Bouamara & S'ebastien Laurent & Shuping Shi, 2023. "Sequential Cauchy Combination Test for Multiple Testing Problems with Financial Applications," Papers 2303.13406, arXiv.org, revised Jun 2023.
    2. Qiu, Yue & Qu, Shaoguang & Shi, Zhentao & Xie, Tian, 2025. "Predicting cryptocurrency volatility: The power of model clustering," Economic Modelling, Elsevier, vol. 144(C).

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

    Cited by:

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

  9. Liangjun Su & Xia Wang, 2020. "Corrigendum to “On Time-varying Factor Models: Estimation and Testing” [J. Econometrics 198 (2017) 84-101]," Economics and Statistics Working Papers 8-2020, Singapore Management University, School of Economics.

    Cited by:

    1. Xiyuan Liu & Zongwu Cai & Liangjun Su, 2025. "Time-varying Factor-augmented Forecasting Models with Variable Selection," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202515, University of Kansas, Department of Economics, revised Sep 2025.

  10. Liangjun Su & Ke Miao & Sainan Jin, 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. Duan, Junting & Pelger, Markus & Xiong, Ruoxuan, 2024. "Target PCA: Transfer learning large dimensional panel data," Journal of Econometrics, Elsevier, vol. 244(2).
    2. Ercument Cahan & Jushan Bai & Serena Ng, 2021. "Factor-Based Imputation of Missing Values and Covariances in Panel Data of Large Dimensions," Papers 2103.03045, arXiv.org, revised Feb 2022.
    3. Jean-Baptiste Hasse & Capucine Nobletz, 2024. "Critical Raw Materials Index - CRMI," AMSE Working Papers 2428, Aix-Marseille School of Economics, France.
    4. 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.
    5. 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).
    6. Jin, Sainan & Lu, Xun & Su, Liangjun, 2025. "Three-dimensional heterogeneous panel data models with multi-level interactive fixed effects," Journal of Econometrics, Elsevier, vol. 249(PB).
    7. Artūras Juodis & Simas Kučinskas, 2023. "Quantifying noise in survey expectations," Quantitative Economics, Econometric Society, vol. 14(2), pages 609-650, May.
    8. 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.
    9. 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).
    10. 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).
    11. Yinchu Zhu, 2019. "How well can we learn large factor models without assuming strong factors?," Papers 1910.10382, arXiv.org, revised Nov 2019.
    12. 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.
    13. Jianqing Fan & Kunpeng Li & Yuan Liao, 2020. "Recent Developments on Factor Models and its Applications in Econometric Learning," Papers 2009.10103, arXiv.org.
    14. Serena Ng & Susannah Scanlan, 2023. "Constructing High Frequency Economic Indicators by Imputation," Papers 2303.01863, arXiv.org, revised Oct 2023.
    15. Lu, Xun & Su, Liangjun & Ba, Yinglong, 2026. "On generalized CCE estimation," Journal of Econometrics, Elsevier, vol. 253(C).
    16. Bian, Yulin & Su, Liangjun, 2025. "A note on factor models with latent group structures," Economics Letters, Elsevier, vol. 252(C).
    17. 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.
    18. 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).
    19. 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.
    20. 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).
    21. Xun Lu & Liangjun Su, 2025. "Two-Way Mean Group Estimators for Heterogeneous Panel Models with Fixed T," Papers 2508.10302, arXiv.org.
    22. Victor Chernozhukov & Christian Hansen & Yuan Liao & Yinchu Zhu, 2021. "Inference for Low-Rank Models," Papers 2107.02602, arXiv.org, revised Jan 2023.
    23. Su, Liangjun & Jin, Sainan & Wang, Xia, 2025. "Sieve estimation of state-varying factor models," Journal of Econometrics, Elsevier, vol. 251(C).
    24. Junting Duan & Markus Pelger & Ruoxuan Xiong, 2023. "Target PCA: Transfer Learning Large Dimensional Panel Data," Papers 2308.15627, arXiv.org.
    25. 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.
    26. 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.
    27. Jushan Bai & Serena Ng, 2019. "Matrix Completion, Counterfactuals, and Factor Analysis of Missing Data," Papers 1910.06677, arXiv.org, revised Aug 2021.
    28. Zhongyuan Lyu & Ming Yuan, 2025. "Large-dimensional Factor Analysis with Weighted PCA," Papers 2508.15675, arXiv.org.
    29. Su, Liangjun & Wang, Fa, 2025. "Inference for large dimensional factor models under general missing data patterns," Journal of Econometrics, Elsevier, vol. 250(C).

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

    Cited by:

    1. Juodis, 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.

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

    Cited by:

    1. Gupta, Mahima & Dubey, Amlendu, 2025. "Structural characteristics and non-linear fiscal multipliers," Economic Systems, Elsevier, vol. 49(1).
    2. Leng, Xuan & Chen, Heng & Wang, Wendun, 2023. "Multi-dimensional latent group structures with heterogeneous distributions," Journal of Econometrics, Elsevier, vol. 233(1), pages 1-21.
    3. 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.
    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. Yu, Lu & Gu, Jiaying & Volgushev, Stanislav, 2024. "Spectral clustering with variance information for group structure estimation in panel data," Journal of Econometrics, Elsevier, vol. 241(1).
    6. Huang, Danyang & Hu, Wei & Jing, Bingyi & Zhang, Bo, 2023. "Grouped spatial autoregressive model," Computational Statistics & Data Analysis, Elsevier, vol. 178(C).
    7. Gong, Woosik & Seo, Myung Hwan, 2026. "Bootstraps for dynamic panel threshold models," Journal of Econometrics, Elsevier, vol. 253(C).
    8. Choudhury, Atrayee & Sahu, Sohini, 2025. "The asymmetric impact of fiscal decentralization on ecological footprint-accounting for methodological refinements and globalization facets," The Journal of Economic Asymmetries, Elsevier, vol. 31(C).
    9. Lawal, Adedoyin Isola & Ozturk, Ilhan & Olanipekun, Ifedolapo O. & Asaleye, Abiola John, 2020. "Examining the linkages between electricity consumption and economic growth in African economies," Energy, Elsevier, vol. 208(C).
    10. 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.
    11. 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.
    12. Ali Mehrabani & Shahnaz Parsaeian, 2025. "Shrinkage Estimation and Identification of Latent Group Structures in Panel Data with Interactive Fixed Effects," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202516, University of Kansas, Department of Economics.
    13. Woosik Gong & Myung Hwan Seo, 2022. "Bootstraps for Dynamic Panel Threshold Models," Papers 2211.04027, arXiv.org, revised Nov 2025.
    14. Pionati, Alessandro, 2025. "Latent grouped structures in panel data: a review," MPRA Paper 123954, University Library of Munich, Germany.

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

    Cited by:

    1. Jin, Sainan & Lu, Xun & Su, Liangjun, 2025. "Three-dimensional heterogeneous panel data models with multi-level interactive fixed effects," Journal of Econometrics, Elsevier, vol. 249(PB).
    2. Lu, Xun & Su, Liangjun & Ba, Yinglong, 2026. "On generalized CCE estimation," Journal of Econometrics, Elsevier, vol. 253(C).
    3. Harold D. Chiang & Joel Rodrigue & Yuya Sasaki, 2019. "Post-Selection Inference in Three-Dimensional Panel Data," Papers 1904.00211, arXiv.org, revised Apr 2019.

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

    Cited by:

    1. Yi Li & Xingxing Luo & Mengqi Liao, 2025. "Incorporating Prior Information in Latent Structures Identification for Panel Data Models," Mathematics, MDPI, vol. 13(9), pages 1-26, May.
    2. 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.
    3. Zhonghui Zhang & Chihwa Kao & Jungbin Hwang, 2025. "High-Dimensional Weighted K-Means with Serial Dependence," Working papers 2025-09, University of Connecticut, Department of Economics.
    4. Bian, Yulin & Su, Liangjun, 2025. "A note on factor models with latent group structures," Economics Letters, Elsevier, vol. 252(C).
    5. Yiren Wang & Peter C. B. Phillips & Liangjun Su, 2023. "Panel Data Models with Time-Varying Latent Group Structures," Cowles Foundation Discussion Papers 2364, Cowles Foundation for Research in Economics, Yale University.
    6. Saptorshee Kanto Chakraborty & Massimiliano Mazzanti, 2021. "Revisiting the literature on the dynamic Environmental Kuznets Curves using a latent structure approach," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 38(3), pages 923-941, October.
    7. Dong, Yingjie & Huang, Wenxin & Tse, Yiu-Kuen, 2023. "Price comovement and market segmentation of Chinese A- and H-shares: Evidence from a panel latent-factor model," Journal of International Money and Finance, Elsevier, vol. 131(C).
    8. Oguzhan Akgun & Ryo Okui, 2025. "Robust Inference Methods for Latent Group Panel Models under Possible Group Non-Separation," Papers 2511.18550, arXiv.org, revised Jul 2026.
    9. Christis Katsouris, 2023. "Optimal Estimation Methodologies for Panel Data Regression Models," Papers 2311.03471, arXiv.org, revised Nov 2023.
    10. 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.
    11. Gobillon, Laurent & Magnac, Thierry & Roux, Sébastien, 2022. "Lifecycle Wages and Human Capital Investments: Selection and Missing Data," TSE Working Papers 22-1299, Toulouse School of Economics (TSE).

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

    Cited by:

    1. Miao, Ke & Phillips, Peter C.B. & Su, Liangjun, 2023. "High-dimensional VARs with common factors," Journal of Econometrics, Elsevier, vol. 233(1), pages 155-183.
    2. Gagliardini, Patrick & Ossola, Elisa & Scaillet, Olivier, 2020. "Estimation of large dimensional conditional factor models in finance," Handbook of Econometrics, in: Steven N. Durlauf & Lars Peter Hansen & James J. Heckman & Rosa L. Matzkin (ed.), Handbook of Econometrics, edition 1, volume 7, chapter 0, pages 219-282, Elsevier.
    3. Daniele Massacci & Lucio Sarno & Lorenzo Trapani & Pierluigi Vallarino, 2025. "A general randomized test for Alpha," Papers 2507.17599, arXiv.org, revised May 2026.
    4. Cheng, Tingting & Yan, Cheng & Yan, Yayi, 2021. "Improved inference for fund alphas using high-dimensional cross-sectional tests," Journal of Empirical Finance, Elsevier, vol. 61(C), pages 57-81.
    5. M Hashem Pesaran & Takashi Yamagata, 2024. "Testing for Alpha in Linear Factor Pricing Models with a Large Number of Securities," Journal of Financial Econometrics, Oxford University Press, vol. 22(2), pages 407-460.
    6. Jianqing Fan & Kunpeng Li & Yuan Liao, 2020. "Recent Developments on Factor Models and its Applications in Econometric Learning," Papers 2009.10103, arXiv.org.
    7. 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).
    8. Feng, Long & Lan, Wei & Liu, Binghui & Ma, Yanyuan, 2022. "High-dimensional test for alpha in linear factor pricing models with sparse alternatives," Journal of Econometrics, Elsevier, vol. 229(1), pages 152-175.
    9. Ziyan Zhao & Qingfeng Liu, 2024. "Time-Varying Structural Approximate Dynamic Factor Model," Economic Growth Centre Working Paper Series 2401, Nanyang Technological University, School of Social Sciences, Economic Growth Centre.

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

    Cited by:

    1. Umedjon Ibragimov & Stephanie Beane & Samuel R Friedman & Kelli Komro & Adaora A Adimora & Jessie K Edwards & Leslie D Williams & Barbara Tempalski & Melvin D Livingston & Ronald D Stall & Gina M Wing, 2019. "States with higher minimum wages have lower STI rates among women: Results of an ecological study of 66 US metropolitan areas, 2003-2015," PLOS ONE, Public Library of Science, vol. 14(10), pages 1-18, October.
    2. Andreas Dzemski & Ryo Okui, 2024. "Confidence set for group membership," Quantitative Economics, Econometric Society, vol. 15(2), pages 245-277, May.
    3. Cristian Valeriu Paun & Radu Nechita & Alexandru Patruti & Mihai Vladimir Topan, 2021. "The Impact of the Minimum Wage on Employment: An EU Panel Data Analysis," Sustainability, MDPI, vol. 13(16), pages 1-17, August.
    4. Subir K. Chakrabarti & Srikant Devaraj & Pankaj C. Patel, 2021. "Minimum wage and restaurant hygiene violations: Evidence from Seattle," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 42(1), pages 85-99, January.
    5. Francesco Fallucchi & Andrea Mercatanti & Jan Niederreiter, 2021. "Identifying types in contest experiments," International Journal of Game Theory, Springer;Game Theory Society, vol. 50(1), pages 39-61, March.
    6. Devereux, Kevin & Studnicka, Zuzanna, 2024. "Non-monotonic employment effects by market structure and minimum wage level," CLEF Working Paper Series 66, Canadian Labour Economics Forum (CLEF), University of Waterloo.
    7. Aleksandra Majchrowska & Paweł Strawiński, 2022. "Heterogeneous employment effects of minimum wage policies," Working Papers 2022-18, Faculty of Economic Sciences, University of Warsaw.
    8. Yiren Wang & Liangjun Su & Yichong Zhang, 2022. "Low-rank Panel Quantile Regression: Estimation and Inference," Papers 2210.11062, arXiv.org.
    9. Baek, Jisun & Lee, Changkeun & Park, WooRam, 2021. "The impact of the minimum wage on the characteristics of new establishments: Evidence from South Korea," Labour Economics, Elsevier, vol. 72(C).
    10. Jan Niederreiter, 2023. "Broadening Economics in the Era of Artificial Intelligence and Experimental Evidence," Italian Economic Journal: A Continuation of Rivista Italiana degli Economisti and Giornale degli Economisti, Springer;Società Italiana degli Economisti (Italian Economic Association), vol. 9(1), pages 265-294, March.
    11. Gmeiner, Michael & Gmeiner, Robert, 2023. "Estimating the employment effect of the minimum wage through variation in compliance: evidence from five US states," LSE Research Online Documents on Economics 121277, London School of Economics and Political Science, LSE Library.
    12. Yiren Wang & Peter C. B. Phillips & Liangjun Su, 2023. "Panel Data Models with Time-Varying Latent Group Structures," Cowles Foundation Discussion Papers 2364, Cowles Foundation for Research in Economics, Yale University.
    13. Alessandrini, Diana & Milla, Joniada, 2021. "Minimum Wage Effects on Human Capital Accumulation: Evidence from Canadian Data," IZA Discussion Papers 14178, IZA Network @ LISER.
    14. Loukas Karabarbounis & Jeremy Lise & Anusha Nath, 2022. "Minimum Wages and Labor Markets in the Twin Cities," Working Papers 793, Federal Reserve Bank of Minneapolis.
    15. Luis E. Arango & Sergio A. Rivera, 2020. "“Disemployment” effects of the minimum wage in the Colombian manufacturing sector," Borradores de Economia 1107, Banco de la Republica de Colombia.
    16. Arango, Luis E. & Rivera, Sergio A., 2022. "Moderate wage increases and flexible labour contracts to protect employment in Colombian manufacturing," Journal of Policy Modeling, Elsevier, vol. 44(3), pages 578-598.
    17. McGuinness, Seamus & Redmond, Paul & Delaney, Judith, 2019. "The prevalence and effect on hours worked of the minimum wage in Ireland: A sectoral and regional analysis," Research Series, Economic and Social Research Institute (ESRI), number RS93.
    18. David Neumark & Peter Shirley, 2021. "Myth or Measurement: What Does the New Minimum Wage Research Say about Minimum Wages and Job Loss in the United States?," NBER Working Papers 28388, National Bureau of Economic Research, Inc.
    19. João Dantas, 2025. "Rethinking the Minimum Wage: The U-Shaped Relationship with Unemployment and Who Bears the Burden," De Economist, Springer, vol. 173(4), pages 637-664, December.
    20. Wang, Wuyi & Su, Liangjun, 2021. "Identifying latent group structures in nonlinear panels," Journal of Econometrics, Elsevier, vol. 220(2), pages 272-295.
    21. Sophie-Charlotte Klose, 2020. "Identifying Latent Structures in Maternal Employment: Evidence on the German Parental Benefit Reform," Papers 2011.03541, arXiv.org.
    22. Aleksandra Majchrowska & Paweł Strawiński, 2021. "Minimum wage and local employment: A spatial panel approach," Regional Science Policy & Practice, Wiley Blackwell, vol. 13(5), pages 1581-1602, October.
    23. Hazrul Shahiri & Zulkifly Osman & Mukhriz Izraf Azman Aziz, 2025. "Is a single minimum wage policy viable option? Evidence from the impact of minimum wage on youth employment in Malaysia," Asian-Pacific Economic Literature, The Crawford School, The Australian National University, vol. 39(1), pages 86-101, May.
    24. Nopphol Witvorapong & Chak Hung Jack Cheng, 2024. "Health care policy uncertainty and state-level employment," Empirical Economics, Springer, vol. 66(6), pages 2501-2532, June.
    25. Balázs Égert & Jarmila Botev & David Turner, 2026. "Minimum wages at a turning point?," Comparative Economic Studies, Palgrave Macmillan;Association for Comparative Economic Studies, vol. 68(2), pages 1-35, June.

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

    Cited by:

    1. Lee, Yoonseok & Wang, Yulong, 2023. "Threshold regression with nonparametric sample splitting," Journal of Econometrics, Elsevier, vol. 235(2), pages 816-842.

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

    Cited by:

    1. Sasaki, Yuya & Ura, Takuya, 2023. "Estimation and inference for policy relevant treatment effects," Journal of Econometrics, Elsevier, vol. 234(2), pages 394-450.
    2. Ai, Chunrong & Fang, Yue & Xie, Haitian, 2026. "Data-driven policy learning for continuous treatments," Journal of Econometrics, Elsevier, vol. 253(C).
    3. Ying-Ying Lee & Chu-An Liu, 2024. "Lee Bounds with a Continuous Treatment in Sample Selection," Papers 2411.04312, arXiv.org, revised Oct 2025.
    4. Qingliang Fan & Zijian Guo & Ziwei Mei & Cun-Hui Zhang, 2023. "Inference for Nonlinear Endogenous Treatment Effects Accounting for High-Dimensional Covariate Complexity," Papers 2310.08063, arXiv.org, revised Jun 2024.
    5. Zeqi Wu & Meilin Wang & Wei Huang & Zheng Zhang, 2025. "A New and Efficient Debiased Estimation of General Treatment Models by Balanced Neural Networks Weighting," Papers 2507.04044, arXiv.org.
    6. Yuya Sasaki & Takuya Ura & Yichong Zhang, 2020. "Unconditional Quantile Regression with High Dimensional Data," Papers 2007.13659, arXiv.org, revised Feb 2022.
    7. Alexander Krei{ss} & Christoph Rothe, 2021. "Inference in Regression Discontinuity Designs with High-Dimensional Covariates," Papers 2110.13725, arXiv.org, revised May 2022.
    8. Fernando Campayo-Sanchez & Juan Luis Nicolau, 2025. "Optimizing control variable selection with algorithms: Parsimony and precision in regression analysis," Tourism Economics, , vol. 31(4), pages 803-810, June.
    9. Qingliang Fan & Yu-Chin Hsu & Robert P. Lieli & Yichong Zhang, 2019. "Estimation of Conditional Average Treatment Effects with High-Dimensional Data," Papers 1908.02399, arXiv.org, revised Jul 2021.
    10. Yizhen Xu & AmirEmad Ghassami & Numair Sani & Ilya Shpitser, 2021. "Multiply Robust Causal Mediation Analysis with Continuous Treatments," Papers 2105.09254, arXiv.org, revised Jun 2026.
    11. Alexander Kreiss & Christoph Rothe, 2023. "Inference in regression discontinuity designs with high-dimensional covariates," The Econometrics Journal, Royal Economic Society, vol. 26(2), pages 105-123.
    12. Xie, Haitian, 2024. "Nonlinear and nonseparable structural functions in regression discontinuity designs with a continuous treatment," Journal of Econometrics, Elsevier, vol. 242(1).
    13. Sylvia Klosin, 2021. "Automatic Double Machine Learning for Continuous Treatment Effects," Papers 2104.10334, arXiv.org.
    14. Chunrong Ai & Yue Fang & Haitian Xie, 2024. "Data-Driven Policy Learning for Continuous Treatments," Papers 2402.02535, arXiv.org, revised Dec 2025.
    15. Ta-Wei Huang & Eva Ascarza, 2024. "Doing More with Less: Overcoming Ineffective Long-Term Targeting Using Short-Term Signals," Marketing Science, INFORMS, vol. 43(4), pages 863-884, July.
    16. Yikun Zhang & Yen-Chi Chen, 2025. "Doubly Robust Inference on Causal Derivative Effects for Continuous Treatments," Papers 2501.06969, arXiv.org, revised Apr 2025.
    17. Rahul Singh & Liyuan Xu & Arthur Gretton, 2020. "Kernel Methods for Causal Functions: Dose, Heterogeneous, and Incremental Response Curves," Papers 2010.04855, arXiv.org, revised Oct 2022.
    18. 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.
    19. Lucas Z. Zhang, 2024. "Continuous difference-in-differences with double/debiased machine learning," Papers 2408.10509, arXiv.org, revised Dec 2025.
    20. Cheuk Hang Leung & Yijun Li & Qi Wu, 2025. "Distribution-valued Causal Machine Learning: Implications of Credit on Spending Patterns," Papers 2509.03063, arXiv.org.
    21. Tübbicke Stefan, 2022. "Entropy Balancing for Continuous Treatments," Journal of Econometric Methods, De Gruyter, vol. 11(1), pages 71-89, January.

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

    Cited by:

    1. Xiaorong Yang & Jia Chen & Degui Li & Runze Li, 2023. "Functional-Coefficient Quantile Regression for Panel Data with Latent Group Structure," Papers 2303.13218, arXiv.org.
    2. Yi Li & Xingxing Luo & Mengqi Liao, 2025. "Incorporating Prior Information in Latent Structures Identification for Panel Data Models," Mathematics, MDPI, vol. 13(9), pages 1-26, May.
    3. Andreas Dzemski & Ryo Okui, 2024. "Confidence set for group membership," Quantitative Economics, Econometric Society, vol. 15(2), pages 245-277, May.
    4. Boyuan Zhang, 2022. "Incorporating Prior Knowledge of Latent Group Structure in Panel Data Models," Papers 2211.16714, arXiv.org, revised Oct 2023.
    5. Gupta, Mahima & Dubey, Amlendu, 2025. "Structural characteristics and non-linear fiscal multipliers," Economic Systems, Elsevier, vol. 49(1).
    6. Leng, Xuan & Chen, Heng & Wang, Wendun, 2023. "Multi-dimensional latent group structures with heterogeneous distributions," Journal of Econometrics, Elsevier, vol. 233(1), pages 1-21.
    7. Ryo Okui & Yutao Sun & Wendun Wang, 2025. "Recovering latent linkage structures and spillover effects with structural breaks in panel data models," Papers 2501.09517, arXiv.org.
    8. Zhongjian Lin & Zhentao Shi & Yapeng Zheng, 2026. "Social Interactions Models with Latent Structures," Papers 2602.06435, arXiv.org, revised Jul 2026.
    9. Ando, Tomohiro & Bai, Jushan, 2021. "Large-scale generalized linear longitudinal data models with grouped patterns of unobserved heterogeneity," MPRA Paper 111431, University Library of Munich, Germany.
    10. Zhonghui Zhang & Chihwa Kao & Jungbin Hwang, 2025. "High-Dimensional Weighted K-Means with Serial Dependence," Working papers 2025-09, University of Connecticut, Department of Economics.
    11. Yu, Xiao-Ge & Liang, Han-Ying, 2026. "High-dimensional subgroup functional quantile regression with panel and dependent data," Computational Statistics & Data Analysis, Elsevier, vol. 214(C).
    12. Yiren Wang & Liangjun Su & Yichong Zhang, 2022. "Low-rank Panel Quantile Regression: Estimation and Inference," Papers 2210.11062, arXiv.org.
    13. Yu, Lu & Gu, Jiaying & Volgushev, Stanislav, 2024. "Spectral clustering with variance information for group structure estimation in panel data," Journal of Econometrics, Elsevier, vol. 241(1).
    14. Bian, Yulin & Su, Liangjun, 2025. "A note on factor models with latent group structures," Economics Letters, Elsevier, vol. 252(C).
    15. Yiren Wang & Peter C. B. Phillips & Liangjun Su, 2023. "Panel Data Models with Time-Varying Latent Group Structures," Cowles Foundation Discussion Papers 2364, Cowles Foundation for Research in Economics, Yale University.
    16. Bofei Xiao & Bo Lei & Wei Lan & Bin Guo, 2022. "A blockwise network autoregressive model with application for fraud detection," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 74(6), pages 1043-1065, December.
    17. Giuseppe Feo & Francesco Giordano & Sara Milito & Marcella Niglio & Maria Lucia Parrella, 2025. "Clustering and classification of spatio-temporal data using spatial dynamic panel data models," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 19(2), pages 387-435, June.
    18. Mikihito Nishi, 2025. "K-Means Panel Data Clustering in the Presence of Small Groups," Papers 2508.15408, arXiv.org.
    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. Mugnier, Martin, 2025. "A simple and computationally trivial estimator for grouped fixed effects models," Journal of Econometrics, Elsevier, vol. 250(C).
    21. Oguzhan Akgun & Ryo Okui, 2025. "Robust Inference Methods for Latent Group Panel Models under Possible Group Non-Separation," Papers 2511.18550, arXiv.org, revised Jul 2026.
    22. Li, Donglin & Wang, Wenyue & Ren, Yanyan, 2024. "Quantile estimation of heterogenous panel quantile model with group structure," Economics Letters, Elsevier, vol. 241(C).
    23. Xu Cheng & Frank Schorfheide & Peng Shao, 2025. "Clustering for Multi-Dimensional Heterogeneity with an Application to Production Function Estimation," PIER Working Paper Archive 25-014, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    24. 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.
    25. Chen, Elynn Y. & Fan, Jianqing & Zhu, Xuening, 2023. "Community network auto-regression for high-dimensional time series," Journal of Econometrics, Elsevier, vol. 235(2), pages 1239-1256.
    26. Langevin, R.;, 2024. "Consistent Estimation of Finite Mixtures: An Application to Latent Group Panel Structures," Health, Econometrics and Data Group (HEDG) Working Papers 24/16, HEDG, c/o Department of Economics, University of York.

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

    Cited by:

    1. Andreas Dzemski & Ryo Okui, 2020. "Convergence rate of estimators of clustered panel models with misclassification," Papers 2008.04708, arXiv.org.
    2. Yi Li & Xingxing Luo & Mengqi Liao, 2025. "Incorporating Prior Information in Latent Structures Identification for Panel Data Models," Mathematics, MDPI, vol. 13(9), pages 1-26, May.
    3. Andreas Dzemski & Ryo Okui, 2024. "Confidence set for group membership," Quantitative Economics, Econometric Society, vol. 15(2), pages 245-277, May.
    4. Boyuan Zhang, 2022. "Incorporating Prior Knowledge of Latent Group Structure in Panel Data Models," Papers 2211.16714, arXiv.org, revised Oct 2023.
    5. Tadao Hoshino, 2020. "A Pairwise Strategic Network Formation Model with Group Heterogeneity: With an Application to International Travel," Papers 2012.14886, arXiv.org, revised Feb 2021.
    6. Gupta, Mahima & Dubey, Amlendu, 2025. "Structural characteristics and non-linear fiscal multipliers," Economic Systems, Elsevier, vol. 49(1).
    7. Leng, Xuan & Chen, Heng & Wang, Wendun, 2023. "Multi-dimensional latent group structures with heterogeneous distributions," Journal of Econometrics, Elsevier, vol. 233(1), pages 1-21.
    8. Miao, Ke & Su, Liangjun & Wang, Wendun, 2020. "Panel threshold regressions with latent group structures," Journal of Econometrics, Elsevier, vol. 214(2), pages 451-481.
    9. Mikihito Nishi & Ryo Okui, 2026. "Inference methods for unit-specific coefficients in panel data models with latent group structure," Papers 2606.22035, arXiv.org.
    10. Dante Amengual & Jesús Bueren & Julio A. Crego, 2021. "Endogenous health groups and heterogeneous dynamics of the elderly," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(7), pages 878-897, November.
    11. Denis Chetverikov & Elena Manresa, 2022. "Spectral and post-spectral estimators for grouped panel data models," Papers 2212.13324, arXiv.org, revised Dec 2022.
    12. 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.
    13. Yoshida, Valter T. & Schiozer, Rafael & de Genaro, Alan & dos Santos, Toni R.E., 2025. "A novel credit model risk measure: Do more data lead to lower model risk?," The Quarterly Review of Economics and Finance, Elsevier, vol. 100(C).
    14. Ando, Tomohiro & Bai, Jushan, 2021. "Large-scale generalized linear longitudinal data models with grouped patterns of unobserved heterogeneity," MPRA Paper 111431, University Library of Munich, Germany.
    15. Nibbering, D. & Paap, R., 2019. "Panel Forecasting with Asymmetric Grouping," Econometric Institute Research Papers EI-2019-30, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    16. 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. Okui, Ryo & Wang, Wendun, 2021. "Heterogeneous structural breaks in panel data models," Journal of Econometrics, Elsevier, vol. 220(2), pages 447-473.
    18. Max Cytrynbaum, 2020. "Blocked Clusterwise Regression," Papers 2001.11130, arXiv.org.
    19. Vogt, Michael & Linton, Oliver, 2020. "Multiscale clustering of nonparametric regression curves," Journal of Econometrics, Elsevier, vol. 216(1), pages 305-325.
    20. 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.
    21. Yiren Wang & Liangjun Su & Yichong Zhang, 2022. "Low-rank Panel Quantile Regression: Estimation and Inference," Papers 2210.11062, arXiv.org.
    22. Tim Kutta & Martin Schumann & Holger Dette, 2025. "Inference for Forecasting Accuracy: Pooled versus Individual Estimators in High-dimensional Panel Data," Papers 2512.15592, arXiv.org.
    23. Yu, Lu & Gu, Jiaying & Volgushev, Stanislav, 2024. "Spectral clustering with variance information for group structure estimation in panel data," Journal of Econometrics, Elsevier, vol. 241(1).
    24. Marie-Hélène Felt, 2020. "Losing Contact: The Impact of Contactless Payments on Cash Usage," Staff Working Papers 20-56, Bank of Canada.
    25. Yiren Wang & Peter C. B. Phillips & Liangjun Su, 2023. "Panel Data Models with Time-Varying Latent Group Structures," Cowles Foundation Discussion Papers 2364, Cowles Foundation for Research in Economics, Yale University.
    26. 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).
    27. Kaddoura, Yousef, 2025. "Estimating coefficient-by-coefficient breaks in panel data models," Journal of Econometrics, Elsevier, vol. 249(PB).
    28. Kutta, Tim & Dette, Holger, 2024. "Validating approximate slope homogeneity in large panels," Journal of Econometrics, Elsevier, vol. 246(1).
    29. Paul Haimerl & Stephan Smeekes & Ines Wilms, 2025. "Estimation of Latent Group Structures in Time-Varying Panel Data Models," Papers 2503.23165, arXiv.org, revised Nov 2025.
    30. Mikihito Nishi, 2025. "K-Means Panel Data Clustering in the Presence of Small Groups," Papers 2508.15408, arXiv.org.
    31. Mehrabani, Ali, 2023. "Estimation and identification of latent group structures in panel data," Journal of Econometrics, Elsevier, vol. 235(2), pages 1464-1482.
    32. Wang, Wuyi & Su, Liangjun, 2021. "Identifying latent group structures in nonlinear panels," Journal of Econometrics, Elsevier, vol. 220(2), pages 272-295.
    33. Oguzhan Akgun & Ryo Okui, 2025. "Robust Inference Methods for Latent Group Panel Models under Possible Group Non-Separation," Papers 2511.18550, arXiv.org, revised Jul 2026.
    34. Dzemski, Andreas & Okui, Ryo, 2018. "Confidence Set for Group Membership," Working Papers in Economics 727, University of Gothenburg, Department of Economics.
    35. 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.
    36. 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.
    37. Ali Mehrabani & Shahnaz Parsaeian, 2025. "Shrinkage Estimation and Identification of Latent Group Structures in Panel Data with Interactive Fixed Effects," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202516, University of Kansas, Department of Economics.
    38. 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.
    39. Pionati, Alessandro, 2025. "Latent grouped structures in panel data: a review," MPRA Paper 123954, University Library of Munich, Germany.

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

    Cited by:

    1. Andrii Babii & Jean-Pierre Florens, 2017. "Are Unobservables Separable?," Papers 1705.01654, arXiv.org, revised Apr 2021.
    2. Su, Liangjun & Ura, Takuya & Zhang, Yichong, 2019. "Non-separable models with high-dimensional data," Journal of Econometrics, Elsevier, vol. 212(2), pages 646-677.
    3. Nir Billfeld & Moshe Kim, 2024. "Context-dependent Causality (the Non-Nonotonic Case)," Papers 2404.05021, arXiv.org.
    4. Christoph Breunig, 2019. "Specification Testing in Nonparametric Instrumental Quantile Regression," Papers 1909.10129, arXiv.org.
    5. Tatiana Komarova & Javier Hidalgo, 2019. "Testing nonparametric shape restrictions," Papers 1909.01675, arXiv.org, revised Jun 2020.

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

    Cited by:

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

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

    Cited by:

    1. Barigozzi, Matteo & Cho, Haeran & Fryzlewicz, Piotr, 2018. "Simultaneous multiple change-point and factor analysis for high-dimensional time series," LSE Research Online Documents on Economics 88110, London School of Economics and Political Science, LSE Library.

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

    Cited by:

    1. Ma, Shujie & Su, Liangjun, 2018. "Estimation of large dimensional factor models with an unknown number of breaks," Journal of Econometrics, Elsevier, vol. 207(1), pages 1-29.
    2. 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. Jan Ditzen & Yiannis Karavias & Joakim Westerlund, 2023. "Multiple structural breaks in interactive effects panel data and the impace of quantitative easing on bank lending," Discussion Papers 23-02, Department of Economics, University of Birmingham.
    4. Tingting Cheng & Chaohua Dong & Jiti Gao & Oliver Linton, 2022. "GMM Estimation for High-Dimensional Panel Data Models," Monash Econometrics and Business Statistics Working Papers 11/22, Monash University, Department of Econometrics and Business Statistics.
    5. Freeman, Hugo & Weidner, Martin, 2023. "Linear panel regressions with two-way unobserved heterogeneity," Journal of Econometrics, Elsevier, vol. 237(1).
    6. Ruiqi Liu & Ben Boukai & Zuofeng Shang, 2019. "Statistical Inference on Partially Linear Panel Model under Unobserved Linearity," Papers 1911.08830, arXiv.org.
    7. Su, Liangjun & Wang, Xia, 2017. "On time-varying factor models: Estimation and testing," Journal of Econometrics, Elsevier, vol. 198(1), pages 84-101.
    8. Karsten Schweikert, 2022. "Detecting Multiple Structural Breaks in Systems of Linear Regression Equations with Integrated and Stationary Regressors," Papers 2201.05430, arXiv.org, revised Sep 2024.
    9. Vira Semenova & Matt Goldman & Victor Chernozhukov & Matt Taddy, 2023. "Inference on heterogeneous treatment effects in high‐dimensional dynamic panels under weak dependence," Quantitative Economics, Econometric Society, vol. 14(2), pages 471-510, May.
    10. 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.
    11. Miao, Ke & Phillips, Peter C.B. & Su, Liangjun, 2023. "High-dimensional VARs with common factors," Journal of Econometrics, Elsevier, vol. 233(1), pages 155-183.
    12. Jiang, Peiyun & Kurozumi, Eiji, 2026. "A new test for common breaks in heterogeneous panel data models," Econometrics and Statistics, Elsevier, vol. 37(C), pages 87-125.
    13. Otilia Boldea & Bettina Drepper & Zhuojiong Gan, 2020. "Change point estimation in panel data with time‐varying individual effects," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(6), pages 712-727, September.
    14. 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.
    15. Otilia Boldea & Alastair R. Hall, 2025. "Testing for multiple change-points in macroeconometrics: an empirical guide and recent developments," Papers 2507.22204, arXiv.org.
    16. Lucas D. Konrad & Lukas Vashold & Jesus Crespo Cuaresma, 2026. "Bayesian Indicator-Saturated Regression for Climate Policy Evaluation," Papers 2603.04997, arXiv.org.
    17. Quint Wiersma & Siem Jan Koopman & Julia Schaumburg & Etienne Wijler, 2021. "Regularized estimation for panel time series models with dynamic factors and local cross-sectional dependence," Tinbergen Institute Discussion Papers 21-008/III, Tinbergen Institute, revised 10 Mar 2026.
    18. 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.
    19. 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).
    20. Cheng, Tingting & Gao, Jiti & Yan, Yayi, 2019. "Regime switching panel data models with interactive fixed effects," Economics Letters, Elsevier, vol. 177(C), pages 47-51.
    21. Francesco Giordano & Marcella Niglio & Maria Lucia Parrella, 2024. "Testing Spatial Dynamic Panel Data Models with Heterogeneous Spatial and Regression Coefficients," Journal of Time Series Analysis, Wiley Blackwell, vol. 45(5), pages 771-799, September.
    22. Akbar Zamanzadeh & Tony Cavoli, 2022. "The effect of nonpharmaceutical interventions on COVID-19 infections for lower and middle-income countries: A debiased LASSO approach," PLOS ONE, Public Library of Science, vol. 17(7), pages 1-17, July.
    23. Okui, Ryo & Wang, Wendun, 2021. "Heterogeneous structural breaks in panel data models," Journal of Econometrics, Elsevier, vol. 220(2), pages 447-473.
    24. 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.
    25. 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.
    26. Anil K. Bera & Osman Doğan & Süleyman Taşpınar & Monalisa Sen, 2020. "Specification tests for spatial panel data models," Journal of Spatial Econometrics, Springer, vol. 1(1), pages 1-39, December.
    27. Yufeng Mao & Bin Peng & Mervyn J Silvapulle & Param Silvapulle & Yanrong Yang, 2021. "Decomposition of Bilateral Trade Flows Using a Three-Dimensional Panel Data Model," Monash Econometrics and Business Statistics Working Papers 7/21, Monash University, Department of Econometrics and Business Statistics.
    28. Wang, Luya & Li, Kunpeng, 2025. "Spatial panel data models with structural change," Journal of Econometrics, Elsevier, vol. 251(C).
    29. 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.
    30. Jan Ditzen & Yiannis Karavias & Joakim Westerlund, 2025. "Multiple Structural Breaks in Interactive Effects Panel Data Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 40(1), pages 74-88, January.
    31. Su, Liangjun & Ura, Takuya & Zhang, Yichong, 2019. "Non-separable models with high-dimensional data," Journal of Econometrics, Elsevier, vol. 212(2), pages 646-677.
    32. Wolter, James Lewis, 2016. "Kernel estimation of hazard functions when observations have dependent and common covariates," Journal of Econometrics, Elsevier, vol. 193(1), pages 1-16.
    33. Yufeng Mao & Bin Peng & Mervyn Silvapulle & Param Silvapulle & Yanrong Yang, 2021. "Decomposition of Bilateral Trade Flows Using a Three-Dimensional Panel Data Model," Papers 2101.06805, arXiv.org.
    34. Georg Keilbar & Juan M. Rodriguez-Poo & Alexandra Soberon & Weining Wang, 2022. "A projection based approach for interactive fixed effects panel data models," Papers 2201.11482, arXiv.org, revised Feb 2025.
    35. Agiwal Varun & Kumar Jitendra & Shangodoyin Dahud Kehinde, 2018. "A Bayesian Inference Of Multiple Structural Breaks In Mean And Error Variance In Panelar (1) Model," Statistics in Transition New Series, Statistics Poland, vol. 19(1), pages 7-23, March.
    36. Degui Li & Junhui Qian & Liangjun Su, 2016. "Panel Data Models With Interactive Fixed Effects and Multiple Structural Breaks," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(516), pages 1804-1819, October.
    37. Rogneda Vasilyeva & Anton Skrobotov & Aleksei Tsarev, 2025. "Structural breaks in panel data: COVID-19 pandemic in Russian regions," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 80, pages 117-142.
    38. Vogt, M. & Walsh, C. & Linton, O., 2022. "CCE Estimation of High-Dimensional Panel Data Models with Interactive Fixed Effects," Cambridge Working Papers in Economics 2242, Faculty of Economics, University of Cambridge.
    39. Cheng Hsiao & Yimeng Xie & Qiankun Zhou, 2021. "Factor dimension determination for panel interactive effects models: an orthogonal projection approach," Computational Statistics, Springer, vol. 36(2), pages 1481-1497, June.
    40. Yuki Takara & Shingo Takagi, 2023. "An empirical approach to measure unobserved cultural relations using music trade data," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 47(2), pages 205-245, June.
    41. 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.
    42. Qu, Xi & Lee, Lung-fei & Yu, Jihai, 2017. "QML estimation of spatial dynamic panel data models with endogenous time varying spatial weights matrices," Journal of Econometrics, Elsevier, vol. 197(2), pages 173-201.
    43. Guliyev, Hasraddin, 2025. "Heterogeneous panel data model with sharp and smooth changes: Testing green growth hypothesis in G7 countries," Innovation and Green Development, Elsevier, vol. 4(3).
    44. Maximilian Ruecker & Michael Vogt & Oliver Linton & Christopher Walsh, 2022. "Estimation and Inference in High-Dimensional Panel Data Models with Interactive Fixed Effects," Papers 2206.12152, arXiv.org, revised Aug 2025.
    45. 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.
    46. Costantini, Mauro & Paradiso, Antonio, 2018. "What do panel data say on inequality and GDP? New evidence at US state-level," Economics Letters, Elsevier, vol. 168(C), pages 115-117.
    47. Wang, Xia & Jin, Sainan & Li, Yingxing & Qian, Junhui & Su, Liangjun, 2025. "On time-varying panel data models with time-varying interactive fixed effects," Journal of Econometrics, Elsevier, vol. 249(PB).
    48. 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.
    49. Horváth, Lajos & Rice, Gregory, 2019. "Asymptotics for empirical eigenvalue processes in high-dimensional linear factor models," Journal of Multivariate Analysis, Elsevier, vol. 169(C), pages 138-165.
    50. Tomohiro Ando & Jushan Bai & Kunpeng Li & Yong Song, 2025. "Bayesian inference for dynamic spatial quantile models with interactive effects," Papers 2503.00772, arXiv.org, revised Jun 2025.
    51. Lu, Xun & Su, Liangjun & Ba, Yinglong, 2026. "On generalized CCE estimation," Journal of Econometrics, Elsevier, vol. 253(C).
    52. Bera, Anil K. & Doğan, Osman & Taşpınar, Süleyman, 2018. "Simple tests for endogeneity of spatial weights matrices," Regional Science and Urban Economics, Elsevier, vol. 69(C), pages 130-142.
    53. Bian, Yulin & Su, Liangjun, 2025. "A note on factor models with latent group structures," Economics Letters, Elsevier, vol. 252(C).
    54. Chi-Yang Chu & Chien-Ho Wang & Wan-Jiun Chen, 2025. "Does the Kyoto Protocol have a structural impact on the environmental Kuznets curve? An application of the varying coefficient model," Empirical Economics, Springer, vol. 68(2), pages 729-758, February.
    55. Feng, Xingdong & Li, Wenyu & Zhu, Qianqian, 2024. "Estimation and bootstrapping under spatiotemporal models with unobserved heterogeneity," Journal of Econometrics, Elsevier, vol. 238(1).
    56. Badi H. Baltagi & Georges Bresson & Anoop Chaturvedi & Guy Lacroix, 2023. "Robust dynamic space–time panel data models using $$\varepsilon $$ ε -contamination: an application to crop yields and climate change," Empirical Economics, Springer, vol. 64(6), pages 2475-2509, June.
    57. Yiren Wang & Peter C. B. Phillips & Liangjun Su, 2023. "Panel Data Models with Time-Varying Latent Group Structures," Cowles Foundation Discussion Papers 2364, Cowles Foundation for Research in Economics, Yale University.
    58. Kun Li & Aibing Ji, 2026. "Autoregressive Model for Panel Matrix-Valued Data," Computational Economics, Springer;Society for Computational Economics, vol. 67(2), pages 709-735, February.
    59. Miao, Ke & Li, Kunpeng & Su, Liangjun, 2020. "Panel threshold models with interactive fixed effects," Journal of Econometrics, Elsevier, vol. 219(1), pages 137-170.
    60. Babii, Andrii & Ball, Ryan T. & Ghysels, Eric & Striaukas, Jonas, 2023. "Machine learning panel data regressions with heavy-tailed dependent data: Theory and application," Journal of Econometrics, Elsevier, vol. 237(2).
    61. Yiannis Karavias & Paresh Narayan & Joakim Westerlund, 2021. "Structural Breaks in Interactive Effects Panels and the Stock Market Reaction to COVID-19," Papers 2111.03035, arXiv.org.
    62. Hsiao, Cheng, 2018. "Panel models with interactive effects," Journal of Econometrics, Elsevier, vol. 206(2), pages 645-673.
    63. 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.
    64. Kaddoura, Yousef, 2025. "Estimating coefficient-by-coefficient breaks in panel data models," Journal of Econometrics, Elsevier, vol. 249(PB).
    65. 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.
    66. T. Thomson & S. Hossain, 2018. "Efficient Shrinkage for Generalized Linear Mixed Models Under Linear Restrictions," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 80(2), pages 385-410, August.
    67. Jiang, Peiyun & Kurozumi, Eiji, 2021. "A new test for common breaks in heterogeneous panel data models," Discussion paper series HIAS-E-107, Hitotsubashi Institute for Advanced Study, Hitotsubashi University.
    68. Ayden Higgins & Federico Martellosio, 2019. "Shrinkage Estimation of Network Spillovers with Factor Structured Errors," Papers 1909.02823, arXiv.org, revised Nov 2021.
    69. Jaeho Kim & Le Wang, 2019. "Hidden group patterns in democracy developments: Bayesian inference for grouped heterogeneity," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(6), pages 1016-1028, September.
    70. Miranda, Karen & Martínez Ibáñez, Oscar & Manjón Antolín, Miguel C., 2018. "A correlated random effects spatial Durbin model," Working Papers 2072/313840, Universitat Rovira i Virgili, Department of Economics.
    71. Alessandro Casini & Pierre Perron, 2018. "Structural Breaks in Time Series," Papers 1805.03807, arXiv.org.
    72. 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.
    73. Xun Lu & Liangjun Su, 2025. "Two-Way Mean Group Estimators for Heterogeneous Panel Models with Fixed T," Papers 2508.10302, arXiv.org.
    74. Yang, Kai & Lee, Lung-fei, 2021. "Estimation of dynamic panel spatial vector autoregression: Stability and spatial multivariate cointegration," Journal of Econometrics, Elsevier, vol. 221(2), pages 337-367.
    75. Bai, Jushan & Li, Kunpeng, 2021. "Dynamic spatial panel data models with common shocks," Journal of Econometrics, Elsevier, vol. 224(1), pages 134-160.
    76. Huang, Shiwei & Chen, Yu & Hu, Jie & Zhang, Weiping, 2026. "Dynamic panel data quantile regression with network-linked fixed effects," Journal of Econometrics, Elsevier, vol. 253(C).
    77. Minyoung Jo & Sangyeol Lee, 2021. "On CUSUM test for dynamic panel models," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(2), pages 515-542, June.
    78. Su, Liangjun & Jin, Sainan & Wang, Xia, 2025. "Sieve estimation of state-varying factor models," Journal of Econometrics, Elsevier, vol. 251(C).
    79. Shi, Wei & Lee, Lung-fei, 2017. "Spatial dynamic panel data models with interactive fixed effects," Journal of Econometrics, Elsevier, vol. 197(2), pages 323-347.
    80. 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.
    81. 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.
    82. Feng, Qu, 2020. "Common factors and common breaks in panels: An empirical investigation," Economics Letters, Elsevier, vol. 187(C).
    83. Shi, Wei & Lee, Lung-fei, 2018. "A spatial panel data model with time varying endogenous weights matrices and common factors," Regional Science and Urban Economics, Elsevier, vol. 72(C), pages 6-34.
    84. 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.
    85. 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.
    86. Christis Katsouris, 2023. "Optimal Estimation Methodologies for Panel Data Regression Models," Papers 2311.03471, arXiv.org, revised Nov 2023.
    87. Chen, Likai & Wang, Weining & Wu, Wei Biao, 2020. "Inference of breakpoints in high-dimensional time series," IRTG 1792 Discussion Papers 2020-019, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    88. 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.
    89. Guohua Feng & Jiti Gao & Bin Peng, 2019. "An Integrated Panel Data Approach to Modelling Economic Growth," Papers 1903.07948, arXiv.org.
    90. Hou, Lei & Li, Kunpeng & Li, Qi & Ouyang, Min, 2021. "Revisiting the location of FDI in China: A panel data approach with heterogeneous shocks," Journal of Econometrics, Elsevier, vol. 221(2), pages 483-509.
    91. Higgins, Ayden & Martellosio, Federico, 2023. "Shrinkage estimation of network spillovers with factor structured errors," Journal of Econometrics, Elsevier, vol. 233(1), pages 66-87.
    92. Ali Mehrabani & Shahnaz Parsaeian, 2025. "Shrinkage Estimation and Identification of Latent Group Structures in Panel Data with Interactive Fixed Effects," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202516, University of Kansas, Department of Economics.
    93. Dai, Siqi & Hong, Yongmiao & Li, Haiqi & Zheng, Chaowen, 2025. "Shrinkage estimation of spatial panel data models with multiple structural breaks and a multifactor error structure," Journal of Econometrics, Elsevier, vol. 251(C).
    94. Ando, Tomohiro & Li, Kunpeng & Lu, Lina, 2023. "A spatial panel quantile model with unobserved heterogeneity," Journal of Econometrics, Elsevier, vol. 232(1), pages 191-213.
    95. 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.
    96. Harold D. Chiang & Joel Rodrigue & Yuya Sasaki, 2019. "Post-Selection Inference in Three-Dimensional Panel Data," Papers 1904.00211, arXiv.org, revised Apr 2019.
    97. Yuichi Goto & Kotone Suzuki & Xiaofei Xu & Masanobu Taniguchi, 2023. "Tests for the existence of group effects and interactions for two-way models with dependent errors," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 75(3), pages 511-532, June.
    98. Shobande, Olatunji A., 2023. "Rethinking social change: Does the permanent and transitory effects of electricity and solid fuel use predict health outcome in Africa?," Technological Forecasting and Social Change, Elsevier, vol. 186(PB).

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

    Cited by:

    1. Xiaorong Yang & Jia Chen & Degui Li & Runze Li, 2023. "Functional-Coefficient Quantile Regression for Panel Data with Latent Group Structure," Papers 2303.13218, arXiv.org.
    2. Xu, Xiu & Wang, Weining & Shin, Yongcheol, 2020. "Dynamic Spatial Network Quantile Autoregression," IRTG 1792 Discussion Papers 2020-024, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    3. Tadao Hoshino, 2014. "Quantile regression estimation of partially linear additive models," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 26(3), pages 509-536, September.
    4. Liang Chen, 2019. "Nonparametric Quantile Regressions for Panel Data Models with Large T," Papers 1911.01824, arXiv.org, revised Sep 2020.
    5. Christis Katsouris, 2023. "High Dimensional Time Series Regression Models: Applications to Statistical Learning Methods," Papers 2308.16192, arXiv.org.
    6. Su, Liangjun & Ura, Takuya & Zhang, Yichong, 2019. "Non-separable models with high-dimensional data," Journal of Econometrics, Elsevier, vol. 212(2), pages 646-677.
    7. Galvao, Antonio F. & Gu, Jiaying & Volgushev, Stanislav, 2020. "On the unbiased asymptotic normality of quantile regression with fixed effects," Journal of Econometrics, Elsevier, vol. 218(1), pages 178-215.
    8. Yangbing Tang & Zhongzhan Zhang & Jiang Du, 2024. "Rank-based instrumental variable estimation for semiparametric varying coefficient spatial autoregressive models," Statistical Papers, Springer, vol. 65(3), pages 1805-1839, May.
    9. Tomohiro Ando & Tadao Hoshino, 2025. "Dynamic Network Autoregressive Models for Functional Panel Data," Papers 2502.13431, arXiv.org, revised Jul 2026.
    10. Wang, Xia & Jin, Sainan & Li, Yingxing & Qian, Junhui & Su, Liangjun, 2025. "On time-varying panel data models with time-varying interactive fixed effects," Journal of Econometrics, Elsevier, vol. 249(PB).
    11. Wüthrich, Kaspar, 2020. "A Comparison of Two Quantile Models With Endogeneity," University of California at San Diego, Economics Working Paper Series qt0q43931f, Department of Economics, UC San Diego.
    12. Zhou, Ying & Shen, Long & Ballester, Laura, 2023. "A two-stage credit scoring model based on random forest: Evidence from Chinese small firms," International Review of Financial Analysis, Elsevier, vol. 89(C).
    13. Miao, Ke & Li, Kunpeng & Su, Liangjun, 2020. "Panel threshold models with interactive fixed effects," Journal of Econometrics, Elsevier, vol. 219(1), pages 137-170.
    14. 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.
    15. Tomohiro Ando & Tadao Hoshino & Ruey Tsay, 2026. "Quantile Vector Autoregression without Crossing," Papers 2601.04663, arXiv.org, revised Jul 2026.
    16. Koo, Chao, 2018. "Essays on functional coefficient models," Other publications TiSEM ba87b8a5-3c55-40ec-967d-9, Tilburg University, School of Economics and Management.

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

    Cited by:

    1. 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.
    2. Luo, Feng & Xu, Hongxia & Fan, Guoliang & Zhu, Liping, 2026. "Ultra-high dimensional semiparametric dynamic high-order spatial autoregressive models," Journal of Multivariate Analysis, Elsevier, vol. 211(C).
    3. Yashar Tarverdi, 2018. "Aspects of Governance and $$\hbox {CO}_2$$ CO 2 Emissions: A Non-linear Panel Data Analysis," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 69(1), pages 167-194, January.
    4. 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.

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

    Cited by:

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

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

    Cited by:

    1. Andrii Babii & Jean-Pierre Florens, 2017. "Are Unobservables Separable?," Papers 1705.01654, arXiv.org, revised Apr 2021.
    2. Su, Liangjun & Ura, Takuya & Zhang, Yichong, 2019. "Non-separable models with high-dimensional data," Journal of Econometrics, Elsevier, vol. 212(2), pages 646-677.
    3. Nir Billfeld & Moshe Kim, 2024. "Context-dependent Causality (the Non-Nonotonic Case)," Papers 2404.05021, arXiv.org.
    4. Christoph Breunig, 2019. "Specification Testing in Nonparametric Instrumental Quantile Regression," Papers 1909.10129, arXiv.org.
    5. Tatiana Komarova & Javier Hidalgo, 2019. "Testing nonparametric shape restrictions," Papers 1909.01675, arXiv.org, revised Jun 2020.

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

    Cited by:

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

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

    Cited by:

    1. 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.
    2. Bin Peng & Liangjun Su & Joakim Westerlund & Yanrong Yang, 2021. "Interactive Effects Panel Data Models with General Factors and Regressors," Papers 2111.11506, arXiv.org.
    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. Kock, Anders Bredahl, 2016. "Oracle inequalities, variable selection and uniform inference in high-dimensional correlated random effects panel data models," Journal of Econometrics, Elsevier, vol. 195(1), pages 71-85.
    5. Su, Liangjun & Ura, Takuya & Zhang, Yichong, 2019. "Non-separable models with high-dimensional data," Journal of Econometrics, Elsevier, vol. 212(2), pages 646-677.
    6. Yufeng Mao & Bin Peng & Mervyn Silvapulle & Param Silvapulle & Yanrong Yang, 2021. "Decomposition of Bilateral Trade Flows Using a Three-Dimensional Panel Data Model," Papers 2101.06805, arXiv.org.
    7. 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.
    8. 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.
    9. Christis Katsouris, 2023. "Optimal Estimation Methodologies for Panel Data Regression Models," Papers 2311.03471, arXiv.org, revised Nov 2023.

  31. Ozabaci, Deniz & Henderson, Daniel J. & Su, Liangjun, 2014. "Additive Nonparametric Regression in the Presence of Endogenous Regressors," IZA Discussion Papers 8144, IZA Network @ LISER.

    Cited by:

    1. Teresa D. Harrison & Daniel J. Henderson & Deniz Ozabaci & Christopher A. Laincz, 2023. "Does one size fit all in the non‐profit donation production function?," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 85(2), pages 373-402, April.
    2. Centorrino Samuele & Feve Frederique & Florens Jean-Pierre, 2017. "Additive Nonparametric Instrumental Regressions: A Guide to Implementation," Journal of Econometric Methods, De Gruyter, vol. 6(1), pages 1-25, January.
    3. Regmi, Krishna & J. Henderson, Daniel, 2019. "Labor demand shocks at birth and cognitive achievement during childhood," Economics of Education Review, Elsevier, vol. 73(C).
    4. Qingliang Fan & Zijian Guo & Ziwei Mei & Cun-Hui Zhang, 2023. "Inference for Nonlinear Endogenous Treatment Effects Accounting for High-Dimensional Covariate Complexity," Papers 2310.08063, arXiv.org, revised Jun 2024.
    5. Henderson, Daniel J. & Souto, Anne-Charlotte, 2018. "An Introduction to Nonparametric Regression for Labor Economists," IZA Discussion Papers 11914, IZA Network @ LISER.
    6. Chi‐Yang Chu & Mingming Jiang, 2021. "Financial depth, income inequality, and economic transition," Southern Economic Journal, John Wiley & Sons, vol. 88(1), pages 199-244, July.
    7. Andros Kourtellos & Thanasis Stengos & Yiguo Sun, 2017. "Endogeneity in Semiparametric Threshold Regression," Working Paper series 17-13, Rimini Centre for Economic Analysis.
    8. Xin Geng & Carlos Martins-Filho & Feng Yao, 2018. "Estimation of a Partially Linear Regression in Triangular Systems," Working Papers 18-05, Department of Economics, West Virginia University.
    9. Dong, Hao & Otsu, Taisuke & Taylor, Luke, 2022. "Nonparametric estimation of additive models with errors-in-variables," LSE Research Online Documents on Economics 116007, London School of Economics and Political Science, LSE Library.
    10. Taining Wang & Feng Yao & Subal C. Kumbhakar, 2024. "A flexible stochastic production frontier model with panel data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(4), pages 564-588, June.
    11. Regmi, Krishna & Henderson, Daniel J., 2019. "Labor Demand Shocks at Birth and Cognitive Achievement during Childhood," IZA Discussion Papers 12521, IZA Network @ LISER.
    12. Mustafa Koroglu, 2019. "Growth and Debt: An Endogenous Smooth Coefficient Approach," JRFM, MDPI, vol. 12(1), pages 1-22, February.
    13. Kumbhakar, Subal C. & Li, Mingyang & Lien, Gudbrand, 2023. "Do subsidies matter in productivity and profitability changes?," Economic Modelling, Elsevier, vol. 123(C).

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

    Cited by:

    1. Etienne Farvaque & Jean-Baptiste Gossé & Camille Jehle, 2026. "Income Smoothing Across EU Regions: a Panel Decomposition of Adjustment Channels," Working papers 1037, Banque de France.
    2. Arturas Juodis & Simon Reese, 2018. "The Incidental Parameters Problem in Testing for Remaining Cross-section Correlation," Papers 1810.03715, arXiv.org, revised Feb 2021.
    3. Xiaorong Yang & Jia Chen & Degui Li & Runze Li, 2023. "Functional-Coefficient Quantile Regression for Panel Data with Latent Group Structure," Papers 2303.13218, arXiv.org.
    4. Fei Liu & Jiti Gao & Yanrong Yang, 2020. "Time-Varying Panel Data Models with an Additive Factor Structure," Monash Econometrics and Business Statistics Working Papers 42/20, Monash University, Department of Econometrics and Business Statistics.
    5. Zhu, Xuening & Xu, Ganggang & Fan, Jianqing, 2025. "Simultaneous estimation and group identification for network vector autoregressive model with heterogeneous nodes," Journal of Econometrics, Elsevier, vol. 249(PA).
    6. Lamarche, Carlos & Parker, Thomas, 2023. "Wild bootstrap inference for penalized quantile regression for longitudinal data," Journal of Econometrics, Elsevier, vol. 235(2), pages 1799-1826.
    7. Yi Li & Xingxing Luo & Mengqi Liao, 2025. "Incorporating Prior Information in Latent Structures Identification for Panel Data Models," Mathematics, MDPI, vol. 13(9), pages 1-26, May.
    8. Francesco Vidoli, 2026. "The Geography of Impact: Endogenous Spatial Clustering for Difference-in-Differences Estimation," Working Papers 2601, University of Urbino Carlo Bo, Department of Economics, Society & Politics - Scientific Committee - L. Stefanini & G. Travaglini, revised 2026.
    9. Nicolas Apfel & Helmut Farbmacher & Rebecca Groh & Martin Huber & Henrika Langen, 2022. "Detecting Grouped Local Average Treatment Effects and Selecting True Instruments," Papers 2207.04481, arXiv.org, revised Oct 2023.
    10. Andreas Dzemski & Ryo Okui, 2024. "Confidence set for group membership," Quantitative Economics, Econometric Society, vol. 15(2), pages 245-277, May.
    11. 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.
    12. Boyuan Zhang, 2022. "Incorporating Prior Knowledge of Latent Group Structure in Panel Data Models," Papers 2211.16714, arXiv.org, revised Oct 2023.
    13. Yu Hao & Hiroyuki Kasahara, 2025. "Estimating the Number of Components in Panel Data Finite Mixture Regression Models with an Application to Production Function Heterogeneity," Papers 2506.09666, arXiv.org.
    14. Liu, Ruiqi & Shang, Zuofeng & Zhang, Yonghui & Zhou, Qiankun, 2020. "Identification and estimation in panel models with overspecified number of groups," Journal of Econometrics, Elsevier, vol. 215(2), pages 574-590.
    15. Freeman, Hugo & Weidner, Martin, 2023. "Linear panel regressions with two-way unobserved heterogeneity," Journal of Econometrics, Elsevier, vol. 237(1).
    16. Feng, Guohua & Gao, Jiti & Peng, Bin & Zhang, Xiaohui, 2017. "A varying-coefficient panel data model with fixed effects: Theory and an application to US commercial banks," Journal of Econometrics, Elsevier, vol. 196(1), pages 68-82.
    17. Tadao Hoshino, 2020. "A Pairwise Strategic Network Formation Model with Group Heterogeneity: With an Application to International Travel," Papers 2012.14886, arXiv.org, revised Feb 2021.
    18. Gupta, Mahima & Dubey, Amlendu, 2025. "Structural characteristics and non-linear fiscal multipliers," Economic Systems, Elsevier, vol. 49(1).
    19. Ruiqi Liu & Ben Boukai & Zuofeng Shang, 2019. "Statistical Inference on Partially Linear Panel Model under Unobserved Linearity," Papers 1911.08830, arXiv.org.
    20. Leng, Xuan & Chen, Heng & Wang, Wendun, 2023. "Multi-dimensional latent group structures with heterogeneous distributions," Journal of Econometrics, Elsevier, vol. 233(1), pages 1-21.
    21. Miao, Ke & Su, Liangjun & Wang, Wendun, 2020. "Panel threshold regressions with latent group structures," Journal of Econometrics, Elsevier, vol. 214(2), pages 451-481.
    22. Shujie Ma & Liangjun Su & Yichong Zhang, 2020. "Detecting Latent Communities in Network Formation Models," Papers 2005.03226, arXiv.org, revised Mar 2021.
    23. Falco J. Bargagli-Stoffi & Jan Niederreiter & Massimo Riccaboni, 2020. "Supervised learning for the prediction of firm dynamics," Papers 2009.06413, arXiv.org.
    24. Vira Semenova & Matt Goldman & Victor Chernozhukov & Matt Taddy, 2023. "Inference on heterogeneous treatment effects in high‐dimensional dynamic panels under weak dependence," Quantitative Economics, Econometric Society, vol. 14(2), pages 471-510, May.
    25. Michael Vogt & Oliver Linton, 2015. "Classification of nonparametric regression functions in heterogeneous panels," CeMMAP working papers 06/15, Institute for Fiscal Studies.
    26. Mikihito Nishi & Ryo Okui, 2026. "Inference methods for unit-specific coefficients in panel data models with latent group structure," Papers 2606.22035, arXiv.org.
    27. Lee, Ji Hyung & Shi, Zhentao & Gao, Zhan, 2022. "On LASSO for predictive regression," Journal of Econometrics, Elsevier, vol. 229(2), pages 322-349.
    28. Simon Freyaldenhoven & Christian Hansen & Jorge Perez Perez & Jesse Shapiro, 2021. "Visualization, Identification, and stimation in the Linear Panel Event-Study Design," Working Papers 21-44, Federal Reserve Bank of Philadelphia.
    29. Yannick V. Markhof, 2020. "Divide to Conquer? Latent Preference Types and Country-level Heterogeneity," CSAE Working Paper Series 2020-05, Centre for the Study of African Economies, University of Oxford.
    30. Andrea Orame, 2020. "The role of bank supply in the Italian credit market: evidence from a new regional survey," Temi di discussione (Economic working papers) 1279, Bank of Italy, Economic Research and International Relations Area.
    31. Jiaying Gu & Stanislav Volgushev, 2018. "Panel Data Quantile Regression with Grouped Fixed Effects," Papers 1801.05041, arXiv.org, revised Aug 2018.
    32. Denis Chetverikov & Elena Manresa, 2022. "Spectral and post-spectral estimators for grouped panel data models," Papers 2212.13324, arXiv.org, revised Dec 2022.
    33. Okui, Ryo & Yanagi, Takahide, 2019. "Panel data analysis with heterogeneous dynamics," Journal of Econometrics, Elsevier, vol. 212(2), pages 451-475.
    34. Chang Cai & Sandy Dall’Erba, 2021. "On the evaluation of heterogeneous climate change impacts on US agriculture: does group membership matter?," Climatic Change, Springer, vol. 167(1), pages 1-23, July.
    35. Juan Romero-Padilla, 2018. "A method for clustering panel data based on parameter homogeneity," Journal of Statistical and Econometric Methods, SCIENPRESS Ltd, vol. 7(3), pages 1-3.
    36. Ziwei Mei & Zhentao Shi & Peter C. B. Phillips, 2022. "The boosted HP filter is more general than you might think," Cowles Foundation Discussion Papers 2348, Cowles Foundation for Research in Economics, Yale University.
    37. 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.
    38. Gao, Z. & Pesaran, M. H., 2022. "Identification and Estimation of Categorical Random Coeficient Models," Cambridge Working Papers in Economics 2228, Faculty of Economics, University of Cambridge.
    39. Zhongjian Lin & Zhentao Shi & Yapeng Zheng, 2026. "Social Interactions Models with Latent Structures," Papers 2602.06435, arXiv.org, revised Jul 2026.
    40. 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.
    41. Fei Liu & Jiti Gao & Yanrong Yang, 2019. "Nonparametric Estimation in Panel Data Models with Heterogeneity and Time Varyingness," Monash Econometrics and Business Statistics Working Papers 24/19, Monash University, Department of Econometrics and Business Statistics.
    42. Francesco Fallucchi & Andrea Mercatanti & Jan Niederreiter, 2021. "Identifying types in contest experiments," International Journal of Game Theory, Springer;Game Theory Society, vol. 50(1), pages 39-61, March.
    43. Ando, Tomohiro & Bai, Jushan, 2021. "Large-scale generalized linear longitudinal data models with grouped patterns of unobserved heterogeneity," MPRA Paper 111431, University Library of Munich, Germany.
    44. Mammen, Enno & Wilke, Ralf A. & Zapp, Kristina Maria, 2022. "Estimation of group structures in panel models with individual fixed effects," ZEW Discussion Papers 22-023, ZEW - Leibniz Centre for European Economic Research.
    45. Zhan Gao & Zhentao Shi, 2018. "Implementing Convex Optimization in R: Two Econometric Examples," Papers 1806.10423, arXiv.org, revised Aug 2019.
    46. Jin, Sainan & Lu, Xun & Su, Liangjun, 2025. "Three-dimensional heterogeneous panel data models with multi-level interactive fixed effects," Journal of Econometrics, Elsevier, vol. 249(PB).
    47. Yeonwoo Rho & Yun Liu & Hie Joo Ahn, 2020. "Revealing Cluster Structures Based on Mixed Sampling Frequencies," Papers 2004.09770, arXiv.org, revised Feb 2021.
    48. 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.
    49. Eric Auerbach & Jonathan Auerbach & Sidonia McKenzie, 2026. "Post-Selection Inference for Network Structure," Papers 2607.00312, arXiv.org, revised Jul 2026.
    50. 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.
    51. Ziwei Mei & Zhentao Shi, 2022. "On LASSO for High Dimensional Predictive Regression," Papers 2212.07052, arXiv.org, revised Jan 2024.
    52. Okui, Ryo & Wang, Wendun, 2021. "Heterogeneous structural breaks in panel data models," Journal of Econometrics, Elsevier, vol. 220(2), pages 447-473.
    53. Kong, Jianning & Phillips, Peter C.B. & Sul, Donggyu, 2019. "Weak σ-convergence: Theory and applications," Journal of Econometrics, Elsevier, vol. 209(2), pages 185-207.
    54. Ryo Okui & Takahide Yanagi, 2018. "Kernel Estimation for Panel Data with Heterogeneous Dynamics," Papers 1802.08825, arXiv.org, revised May 2019.
    55. 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.
    56. Claudia Pigini & Alessandro Pionati & Francesco Valentini, 2023. "Specification testing with grouped fixed effects," Papers 2310.01950, arXiv.org, revised Sep 2025.
    57. Max Cytrynbaum, 2020. "Blocked Clusterwise Regression," Papers 2001.11130, arXiv.org.
    58. Marina Khismatullina & Bernhard van der Sluis, 2025. "Multiscale Comparison of Nonparametric Trending Coefficients," Papers 2511.12600, arXiv.org.
    59. Hasraddin Guliyev, 2025. "Using Machine Learning Techniques to Test the Load Capacity Curve Hypothesis: A Classifier-Lasso Application on Global Panel Data," Biophysical Economics and Resource Quality, Springer, vol. 10(1), pages 1-18, June.
    60. Min Wang & Yunbei Ma, 2024. "Spatial Heterogeneity and Clustering of County-Level Carbon Emissions in China," Sustainability, MDPI, vol. 16(23), pages 1-17, November.
    61. Raphael Langevin, 2026. "Policy Learning with Observational Data: The Case of Hepatitis C Treatment for HIV/HCV Co-Infected Patients," Papers 2605.16593, arXiv.org.
    62. Sumon Bhaumik & Subhasish M. Chowdhury & Ralitza Dimova & Hanna Fromell, 2023. "Identity, Communication, and Conflict: An Experiment," Economics Working Papers 2023-02, Department of Economics and Business Economics, Aarhus University.
    63. Hafner, Christian & Walders, Fabian, 2016. "Heterogeneous Liquidity Effects in Corporate Bond Spreads," LIDAM Discussion Papers ISBA 2016050, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    64. Yanqing Yang & Nan Zhang & Jinfeng Ge & Yan Xu, 2025. "Sino-US S and T Frictions and Transnational Knowledge Flows: Evidence from machine learning and cross-national patent data," Papers 2503.21822, arXiv.org.
    65. Zhonghui Zhang & Chihwa Kao & Jungbin Hwang, 2025. "High-Dimensional Weighted K-Means with Serial Dependence," Working papers 2025-09, University of Connecticut, Department of Economics.
    66. Vogt, Michael & Linton, Oliver, 2020. "Multiscale clustering of nonparametric regression curves," Journal of Econometrics, Elsevier, vol. 216(1), pages 305-325.
    67. Wei Chen & Xilu Chen & Chang-Tai Hsieh & Zheng Song, 2019. "A Forensic Examination of China's National Accounts," NBER Working Papers 25754, National Bureau of Economic Research, Inc.
    68. Choi, In & Lin, Rui & Shin, Yongcheol, 2023. "Canonical correlation-based model selection for the multilevel factors," Journal of Econometrics, Elsevier, vol. 233(1), pages 22-44.
    69. Zixuan Han & Tao Li & Jinhong You & Narayanaswamy Balakrishnan, 2025. "Individual Homogeneity Learning in Density Data Response Additive Models," Stats, MDPI, vol. 8(3), pages 1-27, August.
    70. Wang, Wuyi & Phillips, Peter C.B. & Su, Liangjun, 2019. "The heterogeneous effects of the minimum wage on employment across states," Economics Letters, Elsevier, vol. 174(C), pages 179-185.
    71. Custodio João, Igor & Lucas, André & Schaumburg, Julia & Schwaab, Bernd, 2023. "Dynamic clustering of multivariate panel data," Journal of Econometrics, Elsevier, vol. 237(2).
    72. Wang, Wei & Xiao, Zhijie & Ren, Yanyan & Yan, Xiaodong, 2023. "A bi-integrative analysis of two-dimensional heterogeneous panel data models," Economics Letters, Elsevier, vol. 230(C).
    73. Jiangtao Duan & Wei Gao & Hao Qu & Hon Keung Tony, 2019. "Subspace Clustering for Panel Data with Interactive Effects," Papers 1909.09928, arXiv.org, revised Feb 2021.
    74. Ivan Fernandez-Val & Wayne Yuan Gao & Yuan Liao & Francis Vella, 2022. "Dynamic Heterogeneous Distribution Regression Panel Models, with an Application to Labor Income Processes," Papers 2202.04154, arXiv.org, revised Jul 2026.
    75. 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.
    76. Liebl, Dominik & Walders, Fabian, 2019. "Parameter regimes in partial functional panel regression," Econometrics and Statistics, Elsevier, vol. 11(C), pages 105-115.
    77. Claudia Pigini & Alessandro Pionati & Francesco Valentini, 2025. "Grouped fixed effects regularization for binary choice models," Papers 2502.06446, arXiv.org, revised Nov 2025.
    78. Yiren Wang & Liangjun Su & Yichong Zhang, 2022. "Low-rank Panel Quantile Regression: Estimation and Inference," Papers 2210.11062, arXiv.org.
    79. Myungkou Shin, 2022. "Finitely Heterogeneous Treatment Effect in Event-study," Papers 2204.02346, arXiv.org, revised Oct 2024.
    80. Likai Chen & Georg Keilbar & Liangjun Su & Weining Wang, 2023. "High-dimensional inference on jumps in nonparametric time series regression models," Papers 2312.01162, arXiv.org, revised Jul 2026.
    81. Dzemski, Andreas & Okui, Ryo, 2021. "Convergence rate of estimators of clustered panel models with misclassification," Economics Letters, Elsevier, vol. 203(C).
    82. Friedel Bolle & Jonathan H. W. Tan, 2021. "Behavioral types of the dark side: identifying heterogeneous conflict strategies," Journal of the Economic Science Association, Springer;Economic Science Association, vol. 7(1), pages 49-63, September.
    83. Katerina Chrysikou & George Kapetanios, 2024. "Heterogeneous Grouping Structures in Panel Data," Papers 2407.19509, arXiv.org.
    84. 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.
    85. Tim Kutta & Martin Schumann & Holger Dette, 2025. "Inference for Forecasting Accuracy: Pooled versus Individual Estimators in High-dimensional Panel Data," Papers 2512.15592, arXiv.org.
    86. Yu, Lu & Gu, Jiaying & Volgushev, Stanislav, 2024. "Spectral clustering with variance information for group structure estimation in panel data," Journal of Econometrics, Elsevier, vol. 241(1).
    87. Oleg Roshka, 2026. "Global Persistence, Local Residual Structure: Forecasting Heterogeneous Investment Panels," Papers 2604.09821, arXiv.org, revised May 2026.
    88. 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.
    89. Arturas Juodis & Yiannis Karavias, 2019. "Partially heterogeneous tests for Granger non-causality in panel data," Bank of Lithuania Working Paper Series 59, Bank of Lithuania.
    90. Levent Kutlu & Kien C. Tran & Mike G. Tsionas, 2020. "Unknown latent structure and inefficiency in panel stochastic frontier models," Journal of Productivity Analysis, Springer, vol. 54(1), pages 75-86, August.
    91. Jan Niederreiter, 2023. "Broadening Economics in the Era of Artificial Intelligence and Experimental Evidence," Italian Economic Journal: A Continuation of Rivista Italiana degli Economisti and Giornale degli Economisti, Springer;Società Italiana degli Economisti (Italian Economic Association), vol. 9(1), pages 265-294, March.
    92. Bian, Yulin & Su, Liangjun, 2025. "A note on factor models with latent group structures," Economics Letters, Elsevier, vol. 252(C).
    93. Srinivasan, Shweta & Kholod, Nazar & Chaturvedi, Vaibhav & Ghosh, Probal Pratap & Mathur, Ritu & Clarke, Leon & Evans, Meredydd & Hejazi, Mohamad & Kanudia, Amit & Koti, Poonam Nagar & Liu, Bo & Parik, 2018. "Water for electricity in India: A multi-model study of future challenges and linkages to climate change mitigation," Applied Energy, Elsevier, vol. 210(C), pages 673-684.
    94. Boyuan Zhang, 2020. "Forecasting with Bayesian Grouped Random Effects in Panel Data," Papers 2007.02435, arXiv.org, revised Oct 2020.
    95. Yiren Wang & Peter C. B. Phillips & Liangjun Su, 2023. "Panel Data Models with Time-Varying Latent Group Structures," Cowles Foundation Discussion Papers 2364, Cowles Foundation for Research in Economics, Yale University.
    96. Qing Jiang & Meng Li & Xingwei Tong & Qiang Wu & Xun Zhang, 2025. "Random change point model with an application to the potato’s contribution to population," Empirical Economics, Springer, vol. 68(5), pages 2455-2474, May.
    97. Wagner, Martin & Grabarczyk, Peter & Hong, Seung Hyun, 2020. "Fully modified OLS estimation and inference for seemingly unrelated cointegrating polynomial regressions and the environmental Kuznets curve for carbon dioxide emissions," Journal of Econometrics, Elsevier, vol. 214(1), pages 216-255.
    98. Geert Dhaene & Martin Weidner, 2023. "Approximate functional differencing," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 14(3), pages 379-416, December.
    99. Levent Kutlu & Robin C. Sickles & Mike G. Tsionas & Emmanuel Mamatzakis, 2022. "Heterogeneous decision-making and market power: an application to Eurozone banks," Empirical Economics, Springer, vol. 63(6), pages 3061-3092, December.
    100. Paap, Richard & Franses, Philip Hans, 2025. "Shrinkage estimators for periodic autoregressions," Journal of Econometrics, Elsevier, vol. 247(C).
    101. Huang, Danyang & Hu, Wei & Jing, Bingyi & Zhang, Bo, 2023. "Grouped spatial autoregressive model," Computational Statistics & Data Analysis, Elsevier, vol. 178(C).
    102. Jorge A. Rivero, 2023. "Unobserved Grouped Heteroskedasticity and Fixed Effects," Papers 2310.14068, arXiv.org, revised Oct 2023.
    103. Miao, Ke & Li, Kunpeng & Su, Liangjun, 2020. "Panel threshold models with interactive fixed effects," Journal of Econometrics, Elsevier, vol. 219(1), pages 137-170.
    104. Babii, Andrii & Ball, Ryan T. & Ghysels, Eric & Striaukas, Jonas, 2023. "Machine learning panel data regressions with heavy-tailed dependent data: Theory and application," Journal of Econometrics, Elsevier, vol. 237(2).
    105. Yang, Shuquan & Ling, Nengxiang, 2023. "Robust projected principal component analysis for large-dimensional semiparametric factor modeling," Journal of Multivariate Analysis, Elsevier, vol. 195(C).
    106. Oh, Dong Hwan & Patton, Andrew J., 2023. "Dynamic factor copula models with estimated cluster assignments," Journal of Econometrics, Elsevier, vol. 237(2).
    107. 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).
    108. Jiti Gao & Kai Xia, 2017. "Heterogeneous panel data models with cross-sectional dependence," Monash Econometrics and Business Statistics Working Papers 16/17, Monash University, Department of Econometrics and Business Statistics.
    109. Jin Seo Cho & Peter C. B. Phillips & Juwon Seo, 2019. "Parametric Inference on the Mean of Functional Data Applied to Lifetime Income Curves," Working papers 2019rwp-153, Yonsei University, Yonsei Economics Research Institute.
    110. Alonso, Andrés M. & Galeano, Pedro & Peña, Daniel, 2020. "A robust procedure to build dynamic factor models with cluster structure," Journal of Econometrics, Elsevier, vol. 216(1), pages 35-52.
    111. Zhao, Xun & Tang, Lu & Zhang, Weijia & Zhou, Ling, 2025. "Subgroup learning for multiple mixed-type outcomes with block-structured covariates," Computational Statistics & Data Analysis, Elsevier, vol. 204(C).
    112. Weijie Cui & Yong Li, 2023. "Bicluster Analysis of Heterogeneous Panel Data via M-Estimation," Mathematics, MDPI, vol. 11(10), pages 1-19, May.
    113. Kutta, Tim & Dette, Holger, 2024. "Validating approximate slope homogeneity in large panels," Journal of Econometrics, Elsevier, vol. 246(1).
    114. Mei, Ziwei & Shi, Zhentao, 2024. "On LASSO for high dimensional predictive regression," Journal of Econometrics, Elsevier, vol. 242(2).
    115. 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.
    116. Giuseppe Feo & Francesco Giordano & Sara Milito & Marcella Niglio & Maria Lucia Parrella, 2025. "Clustering and classification of spatio-temporal data using spatial dynamic panel data models," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 19(2), pages 387-435, June.
    117. Ayden Higgins & Federico Martellosio, 2019. "Shrinkage Estimation of Network Spillovers with Factor Structured Errors," Papers 1909.02823, arXiv.org, revised Nov 2021.
    118. Gao, Jiti & Xia, Kai & Zhu, Huanjun, 2020. "Heterogeneous panel data models with cross-sectional dependence," Journal of Econometrics, Elsevier, vol. 219(2), pages 329-353.
    119. Paul Haimerl & Stephan Smeekes & Ines Wilms, 2025. "Estimation of Latent Group Structures in Time-Varying Panel Data Models," Papers 2503.23165, arXiv.org, revised Nov 2025.
    120. Zhao, Jiayang & Liu, Jie, 2023. "Homogeneous analysis on network effects in network autoregressive model," Finance Research Letters, Elsevier, vol. 58(PD).
    121. 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).
    122. Ziwei Mei & Peter C. B. Phillips & Zhentao Shi, 2024. "The boosted Hodrick‐Prescott filter is more general than you might think," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(7), pages 1260-1281, November.
    123. Yu Hao & Hiroyuki Kasahara, 2022. "Testing the Number of Components in Finite Mixture Normal Regression Model with Panel Data," Papers 2210.02824, arXiv.org, revised Jun 2023.
    124. Mikihito Nishi, 2025. "K-Means Panel Data Clustering in the Presence of Small Groups," Papers 2508.15408, arXiv.org.
    125. Mehrabani, Ali, 2023. "Estimation and identification of latent group structures in panel data," Journal of Econometrics, Elsevier, vol. 235(2), pages 1464-1482.
    126. Hie Joo Ahn & Yun Liu & Yeonwoo Rho, 2020. "Revealing Cluster Structures Based on Mixed Sampling Frequencies," Finance and Economics Discussion Series 2020-082, Board of Governors of the Federal Reserve System (U.S.).
    127. 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.
    128. Wang, Wuyi & Su, Liangjun, 2021. "Identifying latent group structures in nonlinear panels," Journal of Econometrics, Elsevier, vol. 220(2), pages 272-295.
    129. 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.
    130. Sophie-Charlotte Klose, 2020. "Identifying Latent Structures in Maternal Employment: Evidence on the German Parental Benefit Reform," Papers 2011.03541, arXiv.org.
    131. Kathleen T. Li, 2024. "Frontiers: A Simple Forward Difference-in-Differences Method," Marketing Science, INFORMS, vol. 43(2), pages 267-279, March.
    132. Mugnier, Martin, 2025. "A simple and computationally trivial estimator for grouped fixed effects models," Journal of Econometrics, Elsevier, vol. 250(C).
    133. Antonio Raiola & Nazarii Salish, 2025. "Detection Boundaries for Panel Slope Homogeneity Tests Under Small-Group Heterogeneity," Papers 2510.22841, arXiv.org, revised Apr 2026.
    134. Oguzhan Akgun & Ryo Okui, 2025. "Robust Inference Methods for Latent Group Panel Models under Possible Group Non-Separation," Papers 2511.18550, arXiv.org, revised Jul 2026.
    135. Daniel J. Lewis & Davide Melcangi & Laura Pilossoph & Aidan Toner‐Rodgers, 2023. "Approximating grouped fixed effects estimation via fuzzy clustering regression," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(7), pages 1077-1084, November.
    136. Zhang, Yingying & Wang, Huixia Judy & Zhu, Zhongyi, 2019. "Quantile-regression-based clustering for panel data," Journal of Econometrics, Elsevier, vol. 213(1), pages 54-67.
    137. Chengwang Liao & Zhentao Shi & Yapeng Zheng, 2025. "A Relaxation Approach to Synthetic Control," Papers 2508.01793, arXiv.org, revised May 2026.
    138. Li, Donglin & Wang, Wenyue & Ren, Yanyan, 2024. "Quantile estimation of heterogenous panel quantile model with group structure," Economics Letters, Elsevier, vol. 241(C).
    139. Yoonseok Lee & Donggyu Sul, 2021. "Trimmed Mean Group Estimation," Center for Policy Research Working Papers 237, Center for Policy Research, Maxwell School, Syracuse University.
    140. 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.
    141. Krasnokutskaya, Elena & Song, Kyungchul & Tang, Xun, 2022. "Estimating unobserved individual heterogeneity using pairwise comparisons," Journal of Econometrics, Elsevier, vol. 226(2), pages 477-497.
    142. Christis Katsouris, 2023. "Optimal Estimation Methodologies for Panel Data Regression Models," Papers 2311.03471, arXiv.org, revised Nov 2023.
    143. 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.
    144. Oguzhan Akgun & Alain Pirotte & Giovanni Urga & Zhenlin Yang, 2025. "Testing Clustered Equal Predictive Ability with Unknown Clusters," Papers 2507.14621, arXiv.org, revised Jul 2026.
    145. Bruhin, Adrian & Janizzi, Kelly & Thöni, Christian, 2020. "Uncovering the heterogeneity behind cross-cultural variation in antisocial punishment," Journal of Economic Behavior & Organization, Elsevier, vol. 180(C), pages 291-308.
    146. Sophie Therese Schneider & Konstantin M. Wacker, 2022. "Explaining the global landscape of foreign direct investment: Knowledge capital, gravity, and the role of culture and institutions," The World Economy, Wiley Blackwell, vol. 45(10), pages 3080-3108, October.
    147. Xu Cheng & Frank Schorfheide & Peng Shao, 2025. "Clustering for Multi-Dimensional Heterogeneity with an Application to Production Function Estimation," PIER Working Paper Archive 25-014, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    148. 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.
    149. Ali Mehrabani & Shahnaz Parsaeian, 2025. "Shrinkage Estimation and Identification of Latent Group Structures in Panel Data with Interactive Fixed Effects," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202516, University of Kansas, Department of Economics.
    150. Jia Chen, 2018. "Estimating Latent Group Structure in Time-Varying Coefficient Panel Data Models," Discussion Papers 18/15, Department of Economics, University of York.
    151. 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.
    152. Lu, Xun & Su, Liangjun, 2020. "Determining individual or time effects in panel data models," Journal of Econometrics, Elsevier, vol. 215(1), pages 60-83.
    153. Antonio F. Galvao & Ulrich Hounyo & Jiahao Lin, 2026. "Estimation and Inference for the $\tau$-Quantile of Individual Heterogeneous Coefficient," Papers 2605.01923, arXiv.org, revised Jun 2026.
    154. Kan Yao, 2025. "Low-Rank Estimation of Nonlinear Panel Data Models," Papers 2511.21948, arXiv.org, revised Jul 2026.
    155. Bennedsen, Mikkel & Hillebrand, Eric & Jensen, Sebastian, 2023. "A neural network approach to the environmental Kuznets curve," Energy Economics, Elsevier, vol. 126(C).
    156. Archer Gong Zhang & Jiahua Chen, 2023. "Optimal Estimation under a Semiparametric Density Ratio Model," Papers 2309.09103, arXiv.org.
    157. Changsong Wu & Dequn Zhou & Donglan Zha & Jong Ho Hong, 2025. "Can carbon emission reduction mitigate the PM2.5 air pollution? Evidence of the co-benefits from mitigating climate change," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 27(9), pages 21053-21074, September.
    158. Gu, Jiaying & Volgushev, Stanislav, 2019. "Panel data quantile regression with grouped fixed effects," Journal of Econometrics, Elsevier, vol. 213(1), pages 68-91.
    159. Guðmundsson, Guðmundur Stefán & Brownlees, Christian, 2021. "Detecting groups in large vector autoregressions," Journal of Econometrics, Elsevier, vol. 225(1), pages 2-26.
    160. 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.
    161. Harold D. Chiang & Joel Rodrigue & Yuya Sasaki, 2019. "Post-Selection Inference in Three-Dimensional Panel Data," Papers 1904.00211, arXiv.org, revised Apr 2019.
    162. Michael Vogt & Oliver Linton, 2017. "Classification of non-parametric regression functions in longitudinal data models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 79(1), pages 5-27, January.
    163. Pionati, Alessandro, 2025. "Latent grouped structures in panel data: a review," MPRA Paper 123954, University Library of Munich, Germany.
    164. Jean-Pierre Florens & Anna Simoni, 2025. "Panel data models with randomly generated groups," Papers 2510.24496, arXiv.org.
    165. Li, Kunpeng & Cui, Guowei & Lu, Lina, 2020. "Efficient estimation of heterogeneous coefficients in panel data models with common shocks," Journal of Econometrics, Elsevier, vol. 216(2), pages 327-353.
    166. Thomas Wiemann, 2023. "Optimal Categorical Instrumental Variables," Papers 2311.17021, arXiv.org, revised May 2024.

  33. 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. 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.
    2. Jiti Gao & Oliver Linton & Bin Peng, 2017. "Inference on a Semiparametric Model with Global Power Law and Local Nonparametric Trends," Monash Econometrics and Business Statistics Working Papers 10/17, Monash University, Department of Econometrics and Business Statistics.
    3. 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).
    4. Su, Liangjun & Wang, Xia, 2017. "On time-varying factor models: Estimation and testing," Journal of Econometrics, Elsevier, vol. 198(1), pages 84-101.
    5. 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.
    6. Cesa-Bianchi, Ambrogio & Imbs, Jean & Saleheen, Jumana, 2019. "Finance and synchronization," Journal of International Economics, Elsevier, vol. 116(C), pages 74-87.
    7. Art=uras Juodis & Martin Weidner, 2026. "Factor-Augmented Panel Regressions and Variance-Weighted Treatment Effects," Papers 2604.18078, arXiv.org.
    8. Bai, Jushan, 2024. "Likelihood approach to dynamic panel models with interactive effects," Journal of Econometrics, Elsevier, vol. 240(1).
    9. 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.
    10. Juan M. Rodriguez-Poo & Alexandra Soberon & Stefan Sperlich, 2025. "Inference on panel data models with a generalized factor structure," Papers 2506.10690, arXiv.org.
    11. 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.
    12. 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.
    13. Xuehong Zhu & Yu Dong & Qiong Xu, 2025. "Is There a Solow Productivity Paradox in China’s Manufacturing Industry: Threshold Effect of Factor Expansion Constraint," Growth and Change, Wiley Blackwell, vol. 56(4), December.
    14. 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.
    15. Su, Liangjun & Ura, Takuya & Zhang, Yichong, 2019. "Non-separable models with high-dimensional data," Journal of Econometrics, Elsevier, vol. 212(2), pages 646-677.
    16. 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).
    17. 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.
    18. 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.
    19. Isabel Casas & Jiti Gao & Bin Peng & Shangyu Xie, 2021. "Time‐varying income elasticities of healthcare expenditure for the OECD and Eurozone," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(3), pages 328-345, April.
    20. Su, Liangjun & Zheng, Xin, 2017. "A martingale-difference-divergence-based test for specification," Economics Letters, Elsevier, vol. 156(C), pages 162-167.
    21. 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.
    22. Peng, Bin & Su, Liangjun & Yan, Yayi, 2025. "A robust residual-based test for structural changes in factor models," Journal of Econometrics, Elsevier, vol. 251(C).
    23. 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.
    24. Bai, Jushan & Li, Kunpeng, 2021. "Dynamic spatial panel data models with common shocks," Journal of Econometrics, Elsevier, vol. 224(1), pages 134-160.
    25. 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.
    26. 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.
    27. Feng, Guohua & Peng, Bin & Su, Liangjun & Yang, Thomas Tao, 2019. "Semi-parametric single-index panel data models with interactive fixed effects: Theory and practice," Journal of Econometrics, Elsevier, vol. 212(2), pages 607-622.
    28. Jiti Gao & Bin Peng & Yayi Yan, 2022. "Higher-order Expansions and Inference for Panel Data Models," Papers 2205.00577, arXiv.org, revised Jun 2023.
    29. Christis Katsouris, 2023. "Optimal Estimation Methodologies for Panel Data Regression Models," Papers 2311.03471, arXiv.org, revised Nov 2023.
    30. 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.
    31. Ali Mehrabani & Shahnaz Parsaeian, 2025. "Shrinkage Estimation and Identification of Latent Group Structures in Panel Data with Interactive Fixed Effects," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202516, University of Kansas, Department of Economics.
    32. Jiang, Bin & Yang, Yanrong & Gao, Jiti & Hsiao, Cheng, 2021. "Recursive estimation in large panel data models: Theory and practice," Journal of Econometrics, Elsevier, vol. 224(2), pages 439-465.
    33. 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.
    34. 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.
    35. Baltagi, Badi H. & Feng, Qu & Kao, Chihwa, 2016. "Estimation of heterogeneous panels with structural breaks," Journal of Econometrics, Elsevier, vol. 191(1), pages 176-195.

  34. 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.

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

    Cited by:

    1. 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.
    2. 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.
    3. 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.
    4. Mikihito Nishi, 2024. "Estimating Time-Varying Parameters of Various Smoothness in Linear Models via Kernel Regression," Papers 2406.14046, arXiv.org, revised Jan 2026.

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

    Cited by:

    1. 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. Yoshiyuki Kurachi & Kazuhiro Hiraki & Shinichi Nishioka, 2016. "Does a Higher Frequency of Micro-level Price Changes Matter for Macro Price Stickiness?: Assessing the Impact of Temporary Price Changes," Bank of Japan Working Paper Series 16-E-9, Bank of Japan.
    3. Chudik, Alexander & Pesaran, M. Hashem & Sharifvaghefi, Mahrad, 2024. "Variable selection in high dimensional linear regressions with parameter instability," Journal of Econometrics, Elsevier, vol. 246(1).
    4. Guanyu Su & Junhui Qian, 2021. "Structural Changes in the Renminbi Exchange Rate Mechanism," China & World Economy, Institute of World Economics and Politics, Chinese Academy of Social Sciences, vol. 29(2), pages 1-23, March.
    5. Karsten Schweikert, 2022. "Detecting Multiple Structural Breaks in Systems of Linear Regression Equations with Integrated and Stationary Regressors," Papers 2201.05430, arXiv.org, revised Sep 2024.
    6. Miao, Ke & Phillips, Peter C.B. & Su, Liangjun, 2023. "High-dimensional VARs with common factors," Journal of Econometrics, Elsevier, vol. 233(1), pages 155-183.
    7. Lee Jaeeun & Chen Jie, 2019. "A penalized regression approach for DNA copy number study using the sequencing data," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 18(4), pages 1-14, August.
    8. Steven Parker, 2024. "Assessing progress in decoupling transport CO2 emissions from GDP growth since 1970," Empirical Economics, Springer, vol. 66(1), pages 27-51, January.
    9. Otilia Boldea & Alastair R. Hall, 2025. "Testing for multiple change-points in macroeconometrics: an empirical guide and recent developments," Papers 2507.22204, arXiv.org.
    10. Christis Katsouris, 2023. "High Dimensional Time Series Regression Models: Applications to Statistical Learning Methods," Papers 2308.16192, arXiv.org.
    11. Tu, Yundong & Xie, Xinling, 2023. "Penetrating sporadic return predictability," Journal of Econometrics, Elsevier, vol. 237(1).
    12. Ma, Chenchen & Tu, Yundong, 2025. "When structural break meets threshold effect: Factor analysis under structural instabilities," Journal of Econometrics, Elsevier, vol. 249(PB).
    13. Rogneda Vasilyeva & Anton Skrobotov & Aleksei Tsarev, 2025. "Structural breaks in panel data: COVID-19 pandemic in Russian regions," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 80, pages 117-142.
    14. Gabriela Ciuperca, 2018. "Test by adaptive LASSO quantile method for real-time detection of a change-point," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 81(6), pages 689-720, August.
    15. Karsten Schweikert, 2020. "Oracle Efficient Estimation of Structural Breaks in Cointegrating Regressions," Papers 2001.07949, arXiv.org, revised Apr 2021.
    16. Karsten Schweikert, 2022. "Oracle Efficient Estimation of Structural Breaks in Cointegrating Regressions," Journal of Time Series Analysis, Wiley Blackwell, vol. 43(1), pages 83-104, January.
    17. Tae-Hwy Lee & Shahnaz Parsaeian & Aman Ullah, 2021. "Efficient Combined Estimation under Structural Breaks," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202107, University of Kansas, Department of Economics.
    18. Behrendt, Simon & Schweikert, Karsten, 2021. "A Note on Adaptive Group Lasso for Structural Break Time Series," Econometrics and Statistics, Elsevier, vol. 17(C), pages 156-172.
    19. Artem Prokhorov & Peter Radchenko & Alexander Semenov & Anton Skrobotov, 2024. "Change-Point Detection in Time Series Using Mixed Integer Programming," Papers 2408.05665, arXiv.org, revised May 2025.
    20. Weijie Cui & Yong Li, 2023. "Bicluster Analysis of Heterogeneous Panel Data via M-Estimation," Mathematics, MDPI, vol. 11(10), pages 1-19, May.
    21. Xia, Siyuan & Qian, Junhui, 2025. "Monotonicity in estimating multiple structural breaks," Economics Letters, Elsevier, vol. 257(C).
    22. Paul Haimerl & Stephan Smeekes & Ines Wilms, 2025. "Estimation of Latent Group Structures in Time-Varying Panel Data Models," Papers 2503.23165, arXiv.org, revised Nov 2025.
    23. Gabriela Ciuperca & Matúš Maciak, 2020. "Change‐point detection in a linear model by adaptive fused quantile method," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 47(2), pages 425-463, June.
    24. 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.
    25. Wang, Wuyi & Su, Liangjun, 2021. "Identifying latent group structures in nonlinear panels," Journal of Econometrics, Elsevier, vol. 220(2), pages 272-295.
    26. Berndt Jesenko & Christian Schlögl, 2021. "The effect of web of science subject categories on clustering: the case of data-driven methods in business and economic sciences," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(8), pages 6785-6801, August.
    27. Skrobotov Anton, 2023. "Testing for explosive bubbles: a review," Dependence Modeling, De Gruyter, vol. 11(1), pages 1-26, January.
    28. Qian, Junhui & Su, Liangjun, 2014. "Structural change estimation in time series regressions with endogenous variables," Economics Letters, Elsevier, vol. 125(3), pages 415-421.
    29. Ma, Chenchen & Tu, Yundong, 2023. "Shrinkage estimation of multiple threshold factor models," Journal of Econometrics, Elsevier, vol. 235(2), pages 1876-1892.
    30. Qian, Junhui & Su, Liangjun, 2016. "Shrinkage estimation of common breaks in panel data models via adaptive group fused Lasso," Journal of Econometrics, Elsevier, vol. 191(1), pages 86-109.
    31. Ryo Okui & Wendun Wang, 2018. "Heterogeneous structural breaks in panel data models," Papers 1801.04672, arXiv.org, revised Nov 2018.
    32. Muhammad Jaffri Mohd Nasir & Ramzan Nazim Khan & Gopalan Nair & Darfiana Nur, 2024. "Active-set based block coordinate descent algorithm in group LASSO for self-exciting threshold autoregressive model," Statistical Papers, Springer, vol. 65(5), pages 2973-3006, July.
    33. Dai, Siqi & Hong, Yongmiao & Li, Haiqi & Zheng, Chaowen, 2025. "Shrinkage estimation of spatial panel data models with multiple structural breaks and a multifactor error structure," Journal of Econometrics, Elsevier, vol. 251(C).
    34. 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.

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

    Cited by:

    1. Lu Zhang & Xiaomeng Zhang & Xinyu Zhang, 2024. "Asymptotic Properties of the Distributional Synthetic Controls," Papers 2405.00953, arXiv.org, revised May 2026.
    2. Shangwei Zhao & Jun Liao & Dalei Yu, 2020. "Model averaging estimator in ridge regression and its large sample properties," Statistical Papers, Springer, vol. 61(4), pages 1719-1739, August.
    3. Guozhi Hu & Weihu Cheng & Jie Zeng, 2023. "Optimal Model Averaging for Semiparametric Partially Linear Models with Censored Data," Mathematics, MDPI, vol. 11(3), pages 1-21, February.
    4. Chen, Qitong & Hong, Yongmiao & Li, Haiqi, 2024. "Time-varying forecast combination for factor-augmented regressions with smooth structural changes," Journal of Econometrics, Elsevier, vol. 240(1).
    5. Jonathan Berrisch & Florian Ziel, 2021. "CRPS Learning," Papers 2102.00968, arXiv.org, revised Nov 2021.
    6. Qingfeng Liu & Qingsong Yao & Guoqing Zhao, 2020. "Model averaging estimation for conditional volatility models with an application to stock market volatility forecast," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(5), pages 841-863, August.
    7. Dieqi Gu & Qingfeng Liu & Xinyu Zhang, 2025. "Model Averaging Under Flexible Loss Functions," INFORMS Journal on Computing, INFORMS, vol. 37(6), pages 1605-1623, November.
    8. Aman Ullah & Xinyu Zhang, 2015. "Grouped Model Averaging for Finite Sample Size," Working Papers 201501, University of California at Riverside, Department of Economics.
    9. Jingwen Tu & Hu Yang & Chaohui Guo & Jing Lv, 2021. "Model averaging marginal regression for high dimensional conditional quantile prediction," Statistical Papers, Springer, vol. 62(6), pages 2661-2689, December.
    10. Zhang, Xinyu & Liu, Chu-An, 2023. "Model averaging prediction by K-fold cross-validation," Journal of Econometrics, Elsevier, vol. 235(1), pages 280-301.
    11. Shi, Pengfei & Zhang, Xinyu & Zhong, Wei, 2024. "Estimating conditional average treatment effects with heteroscedasticity by model averaging and matching," Economics Letters, Elsevier, vol. 238(C).
    12. Miaomiao Wang & Xinyu Zhang & Alan T. K. Wan & Kang You & Guohua Zou, 2023. "Jackknife model averaging for high‐dimensional quantile regression," Biometrics, The International Biometric Society, vol. 79(1), pages 178-189, March.
    13. Xianwen Sun & Lixin Zhang, 2024. "Model averaging estimation for nonparametric varying-coefficient models with multiplicative heteroscedasticity," Statistical Papers, Springer, vol. 65(3), pages 1375-1409, May.
    14. 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.
    15. Ruoyao Shi, 2021. "An Averaging Estimator for Two Step M Estimation in Semiparametric Models," Working Papers 202105, University of California at Riverside, Department of Economics.
    16. Cheng, Tingting & Jiang, Shan & Zhao, Albert Bo & Jia, Zhimin, 2023. "Complete subset averaging methods in corporate bond return prediction," Finance Research Letters, Elsevier, vol. 54(C).
    17. Yundong Tu & Siwei Wang, 2023. "Variable Screening and Model Averaging for Expectile Regressions," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 85(3), pages 574-598, June.
    18. Xiaochao Xia & Sijin He & Naiwen Pang, 2025. "Communication-efficient model averaging prediction for massive data with asymptotic optimality," Statistical Papers, Springer, vol. 66(2), pages 1-45, February.
    19. 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.
    20. Peng, Jingfu & Yang, Yuhong, 2022. "On improvability of model selection by model averaging," Journal of Econometrics, Elsevier, vol. 229(2), pages 246-262.
    21. Xianwen Sun & Lixin Zhang, 2024. "Jackknife model averaging for mixed-data kernel-weighted spline quantile regressions," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 87(7), pages 805-842, October.
    22. Aman Ullah & Alan T. K. Wan & Huansha Wang & Xinyu Zhang & Guohua Zou, 2017. "A semiparametric generalized ridge estimator and link with model averaging," Econometric Reviews, Taylor & Francis Journals, vol. 36(1-3), pages 370-384, March.
    23. Jie Zeng & Weihu Cheng & Guozhi Hu, 2023. "Optimal Model Averaging Estimation for the Varying-Coefficient Partially Linear Models with Missing Responses," Mathematics, MDPI, vol. 11(8), pages 1-21, April.
    24. Wenchao Xu & Xinyu Zhang, 2024. "On Asymptotic Optimality of Least Squares Model Averaging When True Model Is Included," Papers 2411.09258, arXiv.org.
    25. Zhang, Xinyu & Ullah, Aman & Zhao, Shangwei, 2016. "On the dominance of Mallows model averaging estimator over ordinary least squares estimator," Economics Letters, Elsevier, vol. 142(C), pages 69-73.
    26. Xiaomeng Zhang & Wendun Wang & Xinyu Zhang, 2022. "Asymptotic Properties of the Synthetic Control Method," Papers 2211.12095, arXiv.org.
    27. Lin, Tzu-Chi & Liu, Chu-An, 2025. "Model averaging prediction for possibly nonstationary autoregressions," Journal of Econometrics, Elsevier, vol. 249(PB).
    28. Zhang, Xiaomeng & Zhang, Xinyu, 2023. "Optimal model averaging based on forward-validation," Journal of Econometrics, Elsevier, vol. 237(2).
    29. Yang Feng & Qingfeng Liu, 2020. "Nested Model Averaging on Solution Path for High-dimensional Linear Regression," Papers 2005.08057, arXiv.org.
    30. 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.
    31. Anthoulla Phella, 2020. "Forecasting With Factor-Augmented Quantile Autoregressions: A Model Averaging Approach," Papers 2010.12263, arXiv.org.
    32. Tu, Yundong & Wang, Siwei, 2025. "Quantile prediction with factor-augmented regression: Structural instability and model uncertainty," Journal of Econometrics, Elsevier, vol. 249(PB).
    33. Xiaochao Xia, 2021. "Model averaging prediction for nonparametric varying-coefficient models with B-spline smoothing," Statistical Papers, Springer, vol. 62(6), pages 2885-2905, December.
    34. Tu, Yundong & Wang, Siwei, 2020. "Jackknife model averaging for expectile regressions in increasing dimension," Economics Letters, Elsevier, vol. 197(C).
    35. Jiawen Luo & Shengjie Fu & Oguzhan Cepni & Rangan Gupta, 2024. "Climate Risks and Forecastability of US Inflation: Evidence from Dynamic Quantile Model Averaging," Working Papers 202420, University of Pretoria, Department of Economics.
    36. Haowen Bao & Zongwu Cai & Yuying Sun & Shouyang Wang, 2023. "Penalized Optimal Forecast Combination for Quantile Regressions," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202514, University of Kansas, Department of Economics, revised May 2025.
    37. Berrisch, Jonathan & Ziel, Florian, 2023. "CRPS learning," Journal of Econometrics, Elsevier, vol. 237(2).
    38. Zishu Zhan & Yang Li & Yuhong Yang & Cunjie Lin, 2023. "Model averaging for semiparametric varying coefficient quantile regression models," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 75(4), pages 649-681, August.
    39. Su, Liangjun & Hoshino, Tadao, 2016. "Sieve instrumental variable quantile regression estimation of functional coefficient models," Journal of Econometrics, Elsevier, vol. 191(1), pages 231-254.
    40. Ji Hyung Lee & Youngki Shin, 2020. "Complete Subset Averaging for Quantile Regressions," Papers 2003.03299, arXiv.org, revised Jul 2021.
    41. Ziwen Gao & Jiahui Zou & Xinyu Zhang & Yanyuan Ma, 2023. "Frequentist model averaging for envelope models," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 50(3), pages 1325-1364, September.
    42. 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.
    43. Yuan, Chaoxia & Fang, Fang & Ni, Lyu, 2022. "Mallows model averaging with effective model size in fragmentary data prediction," Computational Statistics & Data Analysis, Elsevier, vol. 173(C).
    44. Shou-Yung Yin & Chu-An Liu & Chang-Ching Lin, 2016. "Focused Information Criterion and Model Averaging for Large Panels with a Multifactor Error Structure," IEAS Working Paper : academic research 16-A016, Institute of Economics, Academia Sinica, Taipei, Taiwan.
    45. Ruoyao Shi & Zhipeng Liao, 2018. "An Averaging GMM Estimator Robust to Misspecification," Working Papers 201803, University of California at Riverside, Department of Economics.
    46. Iania, Leonardo & Algieri, Bernardina & Leccadito, Arturo, 2022. "Forecasting total energy’s CO2 emissions," LIDAM Discussion Papers LFIN 2022003, Université catholique de Louvain, Louvain Finance (LFIN).
    47. Lu, Xun & Su, Liangjun, 2020. "Determining individual or time effects in panel data models," Journal of Econometrics, Elsevier, vol. 215(1), pages 60-83.
    48. De Luca, Giuseppe & Magnus, Jan R. & Peracchi, Franco, 2018. "Weighted-average least squares estimation of generalized linear models," Journal of Econometrics, Elsevier, vol. 204(1), pages 1-17.
    49. Chu-An Liu & Biing-Shen Kuo & Wen-Jen Tsay, 2017. "Autoregressive Spectral Averaging Estimator," IEAS Working Paper : academic research 17-A013, Institute of Economics, Academia Sinica, Taipei, Taiwan.
    50. 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.

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

    Cited by:

    1. Effraimidis, Georgios, 2016. "Nonparametric Identification of a Time-Varying Frailty Model," DaCHE discussion papers 2016:6, University of Southern Denmark, Dache - Danish Centre for Health Economics.
    2. Hoderlein, Stefan & Su, Liangjun & White, Halbert & Yang, Thomas Tao, 2016. "Testing for monotonicity in unobservables under unconfoundedness," Journal of Econometrics, Elsevier, vol. 193(1), pages 183-202.
    3. 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.
    4. Breunig, Christoph & Hoderlein, Stefan, 2018. "Specification Testing in Random Coefficient Models," Rationality and Competition Discussion Paper Series 77, CRC TRR 190 Rationality and Competition.
    5. Su, Liangjun & Ura, Takuya & Zhang, Yichong, 2019. "Non-separable models with high-dimensional data," Journal of Econometrics, Elsevier, vol. 212(2), pages 646-677.
    6. Huang, Liquan & Khalil, Umair & Yıldız, Neşe, 2019. "Identification and estimation of a triangular model with multiple endogenous variables and insufficiently many instrumental variables," Journal of Econometrics, Elsevier, vol. 208(2), pages 346-366.
    7. Christoph Breunig & Stefan Hoderlein, 2016. "Nonparametric Specification Testing in Random Parameter Models," Boston College Working Papers in Economics 897, Boston College Department of Economics.
    8. Breunig, Christoph, 2016. "Specification testing in nonparametric instrumental quantile regression," SFB 649 Discussion Papers 2016-032, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    9. Babii, Andrii & Florens, Jean-Pierre, 2017. "Are unobservables separable?," TSE Working Papers 17-802, Toulouse School of Economics (TSE).
    10. Chiappori, Pierre-André & Komunjer, Ivana & Kristensen, Dennis, 2015. "Nonparametric identification and estimation of transformation models," Journal of Econometrics, Elsevier, vol. 188(1), pages 22-39.
    11. Khalil, Umair & Yıldız, Neşe, 2022. "A test of the selection on observables assumption using a discontinuously distributed covariate," Journal of Econometrics, Elsevier, vol. 226(2), pages 423-450.
    12. Lin, Yingqian & Tu, Yundong, 2025. "Identification and inference for semiparametric single index transformation models," Journal of Econometrics, Elsevier, vol. 251(C).
    13. Nick Kloodt & Natalie Neumeyer & Ingrid Keilegom, 2021. "Specification testing in semi-parametric transformation models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 30(4), pages 980-1003, December.
    14. Christoph Breunig, 2019. "Specification Testing in Nonparametric Instrumental Quantile Regression," Papers 1909.10129, arXiv.org.
    15. Lin, Yingqian & Tu, Yundong & Yao, Qiwei, 2020. "Estimation for double-nonlinear cointegration," Journal of Econometrics, Elsevier, vol. 216(1), pages 175-191.
    16. 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.

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

    Cited by:

    1. Uddin, Md. Main & Mishra, Vinod & Smyth, Russell, 2020. "Income inequality and CO2 emissions in the G7, 1870–2014: Evidence from non-parametric modelling," Energy Economics, Elsevier, vol. 88(C).
    2. Awaworyi Churchill, Sefa & Inekwe, John & Smyth, Russell & Zhang, Xibin, 2019. "R&D intensity and carbon emissions in the G7: 1870–2014," Energy Economics, Elsevier, vol. 80(C), pages 30-37.
    3. Hidalgo, Javier & Schafgans, Marcia, 2017. "Inference and testing breaks in large dynamic panels with strong cross sectional dependence," Journal of Econometrics, Elsevier, vol. 196(2), pages 259-274.
    4. Ivanovski, Kris & Hailemariam, Abebe, 2022. "Time-varying geopolitical risk and oil prices," International Review of Economics & Finance, Elsevier, vol. 77(C), pages 206-221.
    5. Awaworyi Churchill, Sefa & Inekwe, John & Ivanovski, Kris & Smyth, Russell, 2020. "The Environmental Kuznets Curve across Australian states and territories," Energy Economics, Elsevier, vol. 90(C).
    6. Javier Hidalgo & Jungyoon Lee, 2014. "A Cusum Test of Common Trends in Large Heterogeneous Panels," STICERD - Econometrics Paper Series 576, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    7. Lamia Beldi & Tarek Ghazouani, 2025. "Nonparametric analysis of the relationship between income inequality and energy consumption in African countries," Natural Resources Forum, Blackwell Publishing, vol. 49(2), pages 1401-1423, May.
    8. Khismatullina, Marina & Vogt, Michael, 2023. "Nonparametric comparison of epidemic time trends: The case of COVID-19," Journal of Econometrics, Elsevier, vol. 232(1), pages 87-108.
    9. Awaworyi Churchill, Sefa & Inekwe, John & Ivanovski, Kris, 2021. "R&D expenditure and energy consumption in OECD nations," Energy Economics, Elsevier, vol. 100(C).
    10. Moghaddam, Mohsen Bakhshi & Lloyd-Ellis, Huw, 2022. "Heterogeneous effects of oil price fluctuations: Evidence from a nonparametric panel data model in Canada," Energy Economics, Elsevier, vol. 110(C).
    11. Chen, Bin & Huang, Liquan, 2018. "Nonparametric testing for smooth structural changes in panel data models," Journal of Econometrics, Elsevier, vol. 202(2), pages 245-267.
    12. Xu, Ke-Li, 2016. "Multivariate trend function testing with mixed stationary and integrated disturbances," Journal of Multivariate Analysis, Elsevier, vol. 147(C), pages 38-57.
    13. Jiti Gao & Kai Xia, 2017. "Heterogeneous panel data models with cross-sectional dependence," Monash Econometrics and Business Statistics Working Papers 16/17, Monash University, Department of Econometrics and Business Statistics.
    14. Peng, Bin & Su, Liangjun & Yan, Yayi, 2025. "A robust residual-based test for structural changes in factor models," Journal of Econometrics, Elsevier, vol. 251(C).
    15. Ghazouani, Tarek, 2024. "Investigating the dynamic link between globalization and carbon emissions in BRICS nations: Insights from a non-parametric perspective," International Economics, Elsevier, vol. 180(C).
    16. Chen, Li & Xu, Xiu, 2025. "Testing for common trends and patterns in functional time series data," Economics Letters, Elsevier, vol. 254(C).
    17. Silvapulle, Param & Smyth, Russell & Zhang, Xibin & Fenech, Jean-Pierre, 2017. "Nonparametric panel data model for crude oil and stock market prices in net oil importing countries," Energy Economics, Elsevier, vol. 67(C), pages 255-267.
    18. Gao, Jiti & Xia, Kai & Zhu, Huanjun, 2020. "Heterogeneous panel data models with cross-sectional dependence," Journal of Econometrics, Elsevier, vol. 219(2), pages 329-353.
    19. Bhattacharya, Mita & Inekwe, John & Yan, Eric, 2021. "Dynamics of energy poverty: Evidence from nonparametric estimates across the ASEAN+6 region," Energy Economics, Elsevier, vol. 103(C).
    20. Mohsen Bakhshi Moghaddam & Saeed Moshiri, 2025. "Oil-macroeconomy relationship over time: Does oil still matter?," Empirical Economics, Springer, vol. 69(6), pages 3205-3225, December.
    21. Ghazouani, Tarek, 2022. "Dynamic impact of globalization on renewable energy consumption: Non-parametric modelling evidence," Technological Forecasting and Social Change, Elsevier, vol. 185(C).
    22. Yao, Yao & Ivanovski, Kris & Inekwe, John & Smyth, Russell, 2020. "Human capital and CO2 emissions in the long run," Energy Economics, Elsevier, vol. 91(C).
    23. Chen, Zhihong & Xia, Huizhu, 2020. "Trend instrumental variable regression with an application to the US New Keynesian Phillips Curve," Economic Modelling, Elsevier, vol. 93(C), pages 595-604.
    24. Le, Ha Chi & Bhattacharya, Mita & Smyth, Russell & Zhang, Xibin, 2025. "The impact of R&D on energy consumption: Evidence from nonlinear semi-parametric estimations for selected OECD countries," Energy Economics, Elsevier, vol. 149(C).
    25. Dogan, Ergun & Zhang, Xibin, 2023. "A nonparametric panel data model for examining the contribution of tourism to economic growth," Economic Modelling, Elsevier, vol. 128(C).
    26. Liddle, Brantley & Smyth, Russell & Zhang, Xibin, 2020. "Time-varying income and price elasticities for energy demand: Evidence from a middle-income panel," Energy Economics, Elsevier, vol. 86(C).
    27. Jia Chen, 2018. "Estimating Latent Group Structure in Time-Varying Coefficient Panel Data Models," Discussion Papers 18/15, Department of Economics, University of York.
    28. Maghyereh, Aktham & Abdoh, Hussein, 2021. "The effect of structural oil shocks on bank systemic risk in the GCC countries," Energy Economics, Elsevier, vol. 103(C).
    29. Marina Khismatullina & Michael Vogt, 2022. "Multiscale Comparison of Nonparametric Trend Curves," Papers 2209.10841, arXiv.org.

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

    Cited by:

    1. Yan Li & Liangjun Su & Yuewu Xu, 2015. "A Combined Approach to the Inference of Conditional Factor Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(2), pages 203-220, April.
    2. Tae‐Hwy Lee & Shahnaz Parsaeian & Aman Ullah, 2022. "Forecasting Under Structural Breaks Using Improved Weighted Estimation," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 84(6), pages 1485-1501, December.

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

    Cited by:

    1. Matteo Barigozzi & Christian T. Brownlees & Giampiero M. Gallo & David Veredas, 2010. "Disentangling Systematic and Idiosyncratic Risk for Large Panels of Assets," Econometrics Working Papers Archive wp2010_06, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    2. Serra, Teresa, "undated". "Volatility Spillovers between Food and Energy Markets, A Semiparametric Approach," 2011 International Congress, August 30-September 2, 2011, Zurich, Switzerland 115997, European Association of Agricultural Economists.

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

    Cited by:

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

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

    Cited by:

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

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

    Cited by:

    1. Su, Liangjun, 2012. "Semiparametric GMM estimation of spatial autoregressive models," Journal of Econometrics, Elsevier, vol. 167(2), pages 543-560.
    2. 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.
    3. Danqing Chen & Jianbao Chen & Shuangshuang Li, 2021. "Instrumental Variable Quantile Regression of Spatial Dynamic Durbin Panel Data Model with Fixed Effects," Mathematics, MDPI, vol. 9(24), pages 1-24, December.
    4. He Jiang, 2023. "Robust forecasting in spatial autoregressive model with total variation regularization," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(2), pages 195-211, March.
    5. Philip Kostov & Julie Le Gallo, 2015. "Convergence: A Story of Quantiles and Spillovers," Kyklos, Wiley Blackwell, vol. 68(4), pages 552-576, November.
    6. Philip Kostov, 2009. "A Spatial Quantile Regression Hedonic Model of Agricultural Land Prices," Spatial Economic Analysis, Taylor & Francis Journals, vol. 4(1), pages 53-72.
    7. Yangbing Tang & Zhongzhan Zhang & Jiang Du, 2024. "Rank-based instrumental variable estimation for semiparametric varying coefficient spatial autoregressive models," Statistical Papers, Springer, vol. 65(3), pages 1805-1839, May.
    8. Yunquan Song & Rui Yang & Dongmei He, 2025. "Robust Variable Selection Method with Prior Information for Spatial Quantile Autoregressive Model," Networks and Spatial Economics, Springer, vol. 25(4), pages 985-1011, December.
    9. Stephen Matthews & Daniel M. Parker, 2013. "Progress in Spatial Demography," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 28(10), pages 271-312.
    10. Bernardo Furtado & Frank van Oort, 2011. "Neighborhood weight matrix in a spatial-quantile real estate modeling environment: Evidence from Brazil," ERSA conference papers ersa10p424, European Regional Science Association.
    11. Coro Chasco & Julie Le Gallo, 2015. "Heterogeneity in Perceptions of Noise and Air Pollution: A Spatial Quantile Approach on the City of Madrid," Spatial Economic Analysis, Taylor & Francis Journals, vol. 10(3), pages 317-343, September.
    12. Jiawei Hou & Yunquan Song, 2022. "Interquantile shrinkage in spatial additive autoregressive models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 31(4), pages 1030-1057, December.
    13. Alfredo Cartone & Paolo Postiglione, 2016. "Modelli spaziali di regressione quantilica per l?analisi della convergenza economica regionale," RIVISTA DI ECONOMIA E STATISTICA DEL TERRITORIO, FrancoAngeli Editore, vol. 2016(3), pages 28-48.
    14. Weiguang Wang & Yangyang Wang, 2023. "Regional Differences, Dynamic Evolution and Driving Factors Analysis of PM 2.5 in the Yangtze River Economic Belt," Sustainability, MDPI, vol. 15(4), pages 1-24, February.
    15. Xiuli Wang & Jingchang Shao & Jingjing Wu & Qiang Zhao, 2023. "Robust variable selection with exponential squared loss for partially linear spatial autoregressive models," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 75(6), pages 949-977, December.
    16. Liao, Wen-Chi & Wang, Xizhu, 2012. "Hedonic house prices and spatial quantile regression," Journal of Housing Economics, Elsevier, vol. 21(1), pages 16-27.
    17. Philip Kostov, 2013. "Empirical likelihood estimation of the spatial quantile regression," Journal of Geographical Systems, Springer, vol. 15(1), pages 51-69, January.
    18. Zhu, Huanjun & Zhu, Jialiang & Zhu, Yulin, 2025. "Quantifying change: The impact of digital financial inclusion across income quantiles in China," China Economic Review, Elsevier, vol. 91(C).
    19. Mu Yue & Jingxin Xi, 2025. "Sparse Boosting for Additive Spatial Autoregressive Model with High Dimensionality," Mathematics, MDPI, vol. 13(5), pages 1-16, February.
    20. Marusca De Castris & Daniele Di Gennaro, 2018. "Does agricultural subsidies foster Italian southern farms? A Spatial Quantile Regression Approach," Papers 1803.05659, arXiv.org.

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

    Cited by:

    1. Yu-Chin Hsu & Ta-Cheng Huang & Haiqing Xu, 2018. "Testing for Unobserved Heterogeneous Treatment Effects with Observational Data," Papers 1803.07514, arXiv.org, revised Aug 2021.
    2. Taoufik Bouezmarni & Mohamed Doukali & Abderrahim Taamouti, 2023. "Testing Granger Non-Causality in Expectiles," University of East Anglia School of Economics Working Paper Series 2023-02, School of Economics, University of East Anglia, Norwich, UK..
    3. 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).
    4. Chen, Bin & Hong, Yongmiao, 2011. "Generalized spectral testing for multivariate continuous-time models," Journal of Econometrics, Elsevier, vol. 164(2), pages 268-293, October.
    5. Xueqin Wang & Wenliang Pan & Wenhao Hu & Yuan Tian & Heping Zhang, 2015. "Conditional Distance Correlation," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(512), pages 1726-1734, December.
    6. Lee, Sangyeol & Meintanis, Simos G. & Pretorius, Charl, 2022. "Monitoring procedures for strict stationarity based on the multivariate characteristic function," Journal of Multivariate Analysis, Elsevier, vol. 189(C).
    7. Huang, Meng & Sun, Yixiao & White, Hal, 2013. "A Flexible Nonparametric Test for Conditional Independence," University of California at San Diego, Economics Working Paper Series qt3pt89204, Department of Economics, UC San Diego.
    8. Cheng, Yu-Hsiang & Huang, Tzee-Ming, 2012. "A conditional independence test for dependent data based on maximal conditional correlation," Journal of Multivariate Analysis, Elsevier, vol. 107(C), pages 210-226.
    9. Zhou, Yeqing & Liu, Jingyuan & Zhu, Liping, 2020. "Test for conditional independence with application to conditional screening," Journal of Multivariate Analysis, Elsevier, vol. 175(C).
    10. de Luna Xavier & Johansson Per, 2014. "Testing for the Unconfoundedness Assumption Using an Instrumental Assumption," Journal of Causal Inference, De Gruyter, vol. 2(2), pages 187-199, September.
    11. Taoufik Bouezmarni & Jeroen V.K. Rombouts & Abderrahim Taamouti, 2009. "A Nonparametric Copula Based Test for Conditional Independence with Applications to Granger Causality," Cahiers de recherche 0927, CIRPEE.
    12. Li, Haiqi & Zhong, Wanling & Park, Sung Y., 2016. "Generalized cross-spectral test for nonlinear Granger causality with applications to money–output and price–volume relations," Economic Modelling, Elsevier, vol. 52(PB), pages 661-671.
    13. Fu, Zhonghao & Hong, Yongmiao, 2019. "A model-free consistent test for structural change in regression possibly with endogeneity," Journal of Econometrics, Elsevier, vol. 211(1), pages 206-242.
    14. Chen, Bin & Song, Zhaogang, 2013. "Testing whether the underlying continuous-time process follows a diffusion: An infinitesimal operator-based approach," Journal of Econometrics, Elsevier, vol. 173(1), pages 83-107.
    15. Nianqing Liu & Quang Vuong & Haiqing Xu, 2012. "Rationalization and Identification of Discrete Games with Correlated Types," Department of Economics Working Papers 130915, The University of Texas at Austin, Department of Economics.
    16. Dai, Shengtao & Song, Xiaojun, 2025. "Consistent tests for semiparametric conditional independence," Statistics & Probability Letters, Elsevier, vol. 216(C).
    17. Amaro de Matos, Joao & Fernandes, Marcelo, 2007. "Testing the Markov property with high frequency data," Journal of Econometrics, Elsevier, vol. 141(1), pages 44-64, November.
    18. Amengual, Dante & Carrasco, Marine & Sentana, Enrique, 2020. "Testing distributional assumptions using a continuum of moments," Journal of Econometrics, Elsevier, vol. 218(2), pages 655-689.
    19. Herman J. Bierens & Li Wang, 2017. "Weighted simulated integrated conditional moment tests for parametric conditional distributions of stationary time series processes," Econometric Reviews, Taylor & Francis Journals, vol. 36(1-3), pages 103-135, March.
    20. Maomao Ding & Ruosha Li & Jin Qin & Jing Ning, 2023. "A double‐robust test for high‐dimensional gene coexpression networks conditioning on clinical information," Biometrics, The International Biometric Society, vol. 79(4), pages 3227-3238, December.
    21. Su, Liangjun & Zheng, Xin, 2017. "A martingale-difference-divergence-based test for specification," Economics Letters, Elsevier, vol. 156(C), pages 162-167.
    22. Chen, Bin & Hong, Yongmiao, 2012. "Testing For The Markov Property In Time Series," Econometric Theory, Cambridge University Press, vol. 28(1), pages 130-178, February.
    23. Su, Liangjun & White, Halbert, 2014. "Testing conditional independence via empirical likelihood," Journal of Econometrics, Elsevier, vol. 182(1), pages 27-44.
    24. Chuang, Chia-Chang & Kuan, Chung-Ming & Lin, Hsin-Yi, 2009. "Causality in quantiles and dynamic stock return-volume relations," Journal of Banking & Finance, Elsevier, vol. 33(7), pages 1351-1360, July.
    25. Xu, Kai & Cheng, Qing, 2024. "Test of conditional independence in factor models via Hilbert–Schmidt independence criterion," Journal of Multivariate Analysis, Elsevier, vol. 199(C).
    26. Azadkia, Mona & Chatterjee, Sourav, 2021. "A simple measure of conditional dependence," LSE Research Online Documents on Economics 125584, London School of Economics and Political Science, LSE Library.
    27. Xiaojun Song & Haoyu Wei, 2021. "Nonparametric Tests of Conditional Independence for Time Series," Papers 2110.04847, arXiv.org.
    28. Wang, Li & Zhou, Hongyi & Ma, Weidong & Yang, Ying, 2025. "A conditional distribution function-based measure for independence and K-sample tests in multivariate data," Journal of Multivariate Analysis, Elsevier, vol. 205(C).
    29. Nadarajah, Saralees & Chan, Stephen & Afuecheta, Emmanuel, 2013. "On the characteristic function for asymmetric Student t distributions," Economics Letters, Elsevier, vol. 121(2), pages 271-274.
    30. Shi, Chengchun & Xu, Tianlin & Bergsma, Wicher & Li, Lexin, 2021. "Double generative adversarial networks for conditional independence testing," LSE Research Online Documents on Economics 112550, London School of Economics and Political Science, LSE Library.
    31. Simos G. Meintanis & Joseph Ngatchou-Wandji & James Allison, 2018. "Testing for serial independence in vector autoregressive models," Statistical Papers, Springer, vol. 59(4), pages 1379-1410, December.
    32. Bertrand Candelon & Sessi Tokpavi, 2016. "A Nonparametric Test for Granger Causality in Distribution With Application to Financial Contagion," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(2), pages 240-253, April.
    33. Muhong Gao & Fang Han & Qizhai Li, 2026. "Limit theorems of Azadkia-Chatterjee's conditional graph correlation," Papers 2606.15433, arXiv.org.
    34. Bianchi, Pascal & Elgui, Kevin & Portier, François, 2023. "Conditional independence testing via weighted partial copulas," Journal of Multivariate Analysis, Elsevier, vol. 193(C).
    35. Zhang, Wei & Gao, Wei & Ng, Hon Keung Tony, 2023. "Multivariate tests of independence based on a new class of measures of independence in Reproducing Kernel Hilbert Space," Journal of Multivariate Analysis, Elsevier, vol. 195(C).
    36. Liu, Nianqing & Vuong, Quang & Xu, Haiqing, 2017. "Rationalization and identification of binary games with correlated types," Journal of Econometrics, Elsevier, vol. 201(2), pages 249-268.
    37. Joao Amaro de Matos & Marcelo Fernandes, 2004. "Testing the Markov property with ultra-high frequency financial data," Nova SBE Working Paper Series wp462, Universidade Nova de Lisboa, Nova School of Business and Economics.
    38. Xuehu Zhu & Jun Lu & Jun Zhang & Lixing Zhu, 2021. "Testing for conditional independence: A groupwise dimension reduction‐based adaptive‐to‐model approach," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 48(2), pages 549-576, June.
    39. Fan, Jianqing & Feng, Yang & Xia, Lucy, 2020. "A projection-based conditional dependence measure with applications to high-dimensional undirected graphical models," Journal of Econometrics, Elsevier, vol. 218(1), pages 119-139.
    40. Ai, Chunrong & Sun, Li-Hsien & Zhang, Zheng & Zhu, Liping, 2024. "Testing unconditional and conditional independence via mutual information," Journal of Econometrics, Elsevier, vol. 240(2).
    41. Chen, Feifei & Meintanis, Simos G. & Zhu, Lixing, 2019. "On some characterizations and multidimensional criteria for testing homogeneity, symmetry and independence," Journal of Multivariate Analysis, Elsevier, vol. 173(C), pages 125-144.
    42. Zhang, Xilin & Xu, Hongxia & Fan, Guoliang & Zhu, Liping, 2026. "Conditional independence test in factor models via projection correlation," Computational Statistics & Data Analysis, Elsevier, vol. 218(C).
    43. Jian Yan & Zhuoxi Li & Xianyang Zhang, 2022. "Distance and Kernel-Based Measures for Global and Local Two-Sample Conditional Distribution Testing," Papers 2210.08149, arXiv.org, revised Aug 2025.
    44. Zhang, Yaowu & Zhou, Yeqing & Zhu, Liping, 2024. "A post-screening diagnostic study for ultrahigh dimensional data," Journal of Econometrics, Elsevier, vol. 239(2).
    45. Xiangdong Long & Liangjun Su & Aman Ullah, 2011. "Estimation and Forecasting of Dynamic Conditional Covariance: A Semiparametric Multivariate Model," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 29(1), pages 109-125, January.
    46. Xiangdong Long & Liangjun Su & Aman Ullah, 2009. "Estimation and Forecasting of Dynamic Conditional Covariance: A Semiparametric Multivariate Model Variables with Econometric Applications," Working Papers 200908, University of California at Riverside, Department of Economics, revised Jul 2009.

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

    Cited by:

    1. de Luna, Xavier & Waernbaum, Ingeborg, 2005. "Covariate selection for non-parametric estimation of treatment effects," Working Paper Series 2005:4, IFAU - Institute for Evaluation of Labour Market and Education Policy.
    2. 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).
    3. Huang, Meng & Sun, Yixiao & White, Hal, 2013. "A Flexible Nonparametric Test for Conditional Independence," University of California at San Diego, Economics Working Paper Series qt3pt89204, Department of Economics, UC San Diego.
    4. Hoderlein, Stefan & Su, Liangjun & White, Halbert & Yang, Thomas Tao, 2016. "Testing for monotonicity in unobservables under unconfoundedness," Journal of Econometrics, Elsevier, vol. 193(1), pages 183-202.
    5. Zhou, Yeqing & Liu, Jingyuan & Zhu, Liping, 2020. "Test for conditional independence with application to conditional screening," Journal of Multivariate Analysis, Elsevier, vol. 175(C).
    6. Taoufik Bouezmarni & Jeroen V.K. Rombouts & Abderrahim Taamouti, 2009. "A Nonparametric Copula Based Test for Conditional Independence with Applications to Granger Causality," Cahiers de recherche 0927, CIRPEE.
    7. Yahya Can DURA & Mustafa Kemal BESER & Hakan ACAROGLU, 2017. "Türkiye’nin Ihracata Dayali Buyumesinin Ekonometrik Analizi," Ege Academic Review, Ege University Faculty of Economics and Administrative Sciences, vol. 17(2), pages 295-310.
    8. Li, Haiqi & Zhong, Wanling & Park, Sung Y., 2016. "Generalized cross-spectral test for nonlinear Granger causality with applications to money–output and price–volume relations," Economic Modelling, Elsevier, vol. 52(PB), pages 661-671.
    9. Patrick Gagliardini & Diego Ronchetti, 2020. "Comparing Asset Pricing Models by the Conditional Hansen-Jagannathan Distance," Journal of Financial Econometrics, Oxford University Press, vol. 18(2), pages 333-394.
    10. Dai, Shengtao & Song, Xiaojun, 2025. "Consistent tests for semiparametric conditional independence," Statistics & Probability Letters, Elsevier, vol. 216(C).
    11. Gospodinov, Nikolay & Otsu, Taisuke, 2012. "Local GMM estimation of time series models with conditional moment restrictions," Journal of Econometrics, Elsevier, vol. 170(2), pages 476-490.
    12. Su, Liangjun & Zheng, Xin, 2017. "A martingale-difference-divergence-based test for specification," Economics Letters, Elsevier, vol. 156(C), pages 162-167.
    13. Xu, Kai & Cheng, Qing, 2024. "Test of conditional independence in factor models via Hilbert–Schmidt independence criterion," Journal of Multivariate Analysis, Elsevier, vol. 199(C).
    14. Azadkia, Mona & Chatterjee, Sourav, 2021. "A simple measure of conditional dependence," LSE Research Online Documents on Economics 125584, London School of Economics and Political Science, LSE Library.
    15. Xiaojun Song & Haoyu Wei, 2021. "Nonparametric Tests of Conditional Independence for Time Series," Papers 2110.04847, arXiv.org.
    16. Yoon-Jae Whang, 2004. "Smoothed Empirical Likelihood Methods for Quantile Regression Models," Cowles Foundation Discussion Papers 1453, Cowles Foundation for Research in Economics, Yale University.
    17. Ruiz-Castillo, Javier, 2012. "From the “European Paradox” to a European Drama in citation impact," UC3M Working papers. Economics we1211, Universidad Carlos III de Madrid. Departamento de Economía.
    18. Christophe Dutang, 2012. "The customer, the insurer and the market," Post-Print hal-01616152, HAL.
    19. Bertrand Candelon & Sessi Tokpavi, 2016. "A Nonparametric Test for Granger Causality in Distribution With Application to Financial Contagion," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(2), pages 240-253, April.
    20. Bouezmarni, Taoufik & Taamouti, Abderrahim, 2012. "Nonparametric tests for conditional independence using conditional distributions," UC3M Working papers. Economics we1217, Universidad Carlos III de Madrid. Departamento de Economía.
    21. Ersin Sünbül, 2023. "Linear and Nonlinear Relationship Between Real Exchange Rate, Real Interest Rate and Consumer Price Index: An Empirical Application for Countries with Different Levels of Development," Scientific Annals of Economics and Business (continues Analele Stiintifice), Alexandru Ioan Cuza University, Faculty of Economics and Business Administration, vol. 70(1), pages 57-70, March.
    22. Xuehu Zhu & Jun Lu & Jun Zhang & Lixing Zhu, 2021. "Testing for conditional independence: A groupwise dimension reduction‐based adaptive‐to‐model approach," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 48(2), pages 549-576, June.
    23. Fan, Jianqing & Feng, Yang & Xia, Lucy, 2020. "A projection-based conditional dependence measure with applications to high-dimensional undirected graphical models," Journal of Econometrics, Elsevier, vol. 218(1), pages 119-139.
    24. Ai, Chunrong & Sun, Li-Hsien & Zhang, Zheng & Zhu, Liping, 2024. "Testing unconditional and conditional independence via mutual information," Journal of Econometrics, Elsevier, vol. 240(2).
    25. Zhang, Xilin & Xu, Hongxia & Fan, Guoliang & Zhu, Liping, 2026. "Conditional independence test in factor models via projection correlation," Computational Statistics & Data Analysis, Elsevier, vol. 218(C).
    26. Xiaojun Song & Jichao Yuan, 2026. "A Projection Approach to Nonparametric Significance and Conditional Independence Testing," Papers 2602.15289, arXiv.org.
    27. Omar Vazquez & Sharon X. Xie, 2025. "Robust inverse probability weighted estimators for doubly truncated Cox regression with closed-form standard errors," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 31(2), pages 364-393, April.
    28. Kyungchul Song, 2007. "Testing Conditional Independence via Rosenblatt Transforms," PIER Working Paper Archive 07-026, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    29. Zhang, Yaowu & Zhou, Yeqing & Zhu, Liping, 2024. "A post-screening diagnostic study for ultrahigh dimensional data," Journal of Econometrics, Elsevier, vol. 239(2).

Articles

  1. Lu, Xun & Su, Liangjun & Ba, Yinglong, 2026. "On generalized CCE estimation," Journal of Econometrics, Elsevier, vol. 253(C).

    Cited by:

    1. Art=uras Juodis & Martin Weidner, 2026. "Factor-Augmented Panel Regressions and Variance-Weighted Treatment Effects," Papers 2604.18078, arXiv.org.

  2. Su, Liangjun & Wang, Fa & Wang, Yiren, 2026. "Estimation and inference for unbalanced panel data models with interactive fixed effects," Journal of Econometrics, Elsevier, vol. 255(C).

    Cited by:

    1. Daniel Czarnowske & Amrei Stammann, 2026. "Inference for Fixed Effects Estimators when Panels are Unbalanced," Papers 2607.10246, arXiv.org, revised Jul 2026.

  3. Su, Liangjun & Wang, Fa, 2025. "Inference for large dimensional factor models under general missing data patterns," Journal of Econometrics, Elsevier, vol. 250(C).

    Cited by:

    1. Lu, Xun & Su, Liangjun & Ba, Yinglong, 2026. "On generalized CCE estimation," Journal of Econometrics, Elsevier, vol. 253(C).
    2. Ye Chen & Ke Miao & Liangjun Su, 2026. "High Dimensional Discrete Choice Models With Interactive Fixed Effects Applied to Causal Inference," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 41(1), pages 108-126, January.

  4. Bian, Yulin & Su, Liangjun, 2025. "A note on factor models with latent group structures," Economics Letters, Elsevier, vol. 252(C).

    Cited by:

    1. Zhonghui Zhang & Chihwa Kao & Jungbin Hwang, 2025. "High-Dimensional Weighted K-Means with Serial Dependence," Working papers 2025-09, University of Connecticut, Department of Economics.

  5. Jin, Sainan & Lu, Xun & Su, Liangjun, 2025. "Three-dimensional heterogeneous panel data models with multi-level interactive fixed effects," Journal of Econometrics, Elsevier, vol. 249(PB).

    Cited by:

    1. Daniel Czarnowske & Amrei Stammann, 2025. "(Debiased) Inference for Fixed Effects Estimators with Three-Dimensional Panel and Network Data," Papers 2512.18678, arXiv.org, revised Aug 2026.
    2. Kong, Xinbing & Zhang, Tong, 2026. "Estimation and inference for large-dimensional generalized matrix factor models," Journal of Econometrics, Elsevier, vol. 253(C).
    3. Mutai, Ronald Kipsang & Lu, Jiang & Mukami, Nyambura Lydiah & Chirwa, William Billy & Xiaoguang, Liu & Zhiyou, Yao, 2026. "Beyond the diploma: The untold consequences of short-cycle tertiary education on GDP growth in Sub-Saharan Africa," International Journal of Educational Development, Elsevier, vol. 121(C).

  6. Peng, Bin & Su, Liangjun & Westerlund, Joakim & Yang, Yanrong, 2025. "Interactive Effects Panel Data Models With General Factors And Regressors," Econometric Theory, Cambridge University Press, vol. 41(2), pages 472-488, April.
    See citations under working paper version above.
  7. Wang, Xia & Jin, Sainan & Li, Yingxing & Qian, Junhui & Su, Liangjun, 2025. "On time-varying panel data models with time-varying interactive fixed effects," Journal of Econometrics, Elsevier, vol. 249(PB).

    Cited by:

    1. Krystian Bua & Giovanni Dosi & Maria Enrica Virgillito, 2025. "The finance-growth nexus over the long-run," LEM Papers Series 2025/24, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.

  8. Zhonghao Fu & Liangjun Su & Xia Wang, 2025. "Distinguishing Time-Varying Factor Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 43(3), pages 508-519, July.

    Cited by:

    1. Vishnu Himanshu Ratnam Pandey & Ashutosh Kainthola & Gaurav Kushwaha & C. S. Singh, 2026. "Rock slope failures in Baspa Valley, Himachal Pradesh, India: a multi method numerical assessment and mitigation strategies," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 122(5), pages 1-30, March.

  9. Yiqiu Cao & Sainan Jin & Xun Lu & Liangjun Su, 2024. "Oracle Efficient Estimation of Heterogeneous Dynamic Panel Data Models with Interactive Fixed Effects," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 42(4), pages 1169-1184, October.

    Cited by:

    1. Jin, Sainan & Lu, Xun & Su, Liangjun, 2025. "Three-dimensional heterogeneous panel data models with multi-level interactive fixed effects," Journal of Econometrics, Elsevier, vol. 249(PB).
    2. Juodis, Artūras & Reese, Simon, 2026. "Five lessons for applied researchers from twenty years of common correlated effects estimation," Journal of Econometrics, Elsevier, vol. 253(C).
    3. Lu, Xun & Su, Liangjun & Ba, Yinglong, 2026. "On generalized CCE estimation," Journal of Econometrics, Elsevier, vol. 253(C).
    4. Hong, Han & Ju, Gaosheng & Li, Qi & Yan, Karen X., 2024. "Varying-coefficient spatial dynamic panel data models with fixed effects: Theory and application," Journal of Econometrics, Elsevier, vol. 245(1).
    5. Xun Lu & Liangjun Su, 2025. "Two-Way Mean Group Estimators for Heterogeneous Panel Models with Fixed T," Papers 2508.10302, arXiv.org.
    6. Dai, Siqi & Hong, Yongmiao & Li, Haiqi & Zheng, Chaowen, 2025. "Shrinkage estimation of spatial panel data models with multiple structural breaks and a multifactor error structure," Journal of Econometrics, Elsevier, vol. 251(C).

  10. Fu, Zhonghao & Gao, Shang & Su, Liangjun & Wang, Xia, 2024. "Testing For Strict Stationarity Via The Discrete Fourier Transform," Econometric Theory, Cambridge University Press, vol. 40(3), pages 511-557, June.

    Cited by:

    1. Jin, Sainan & Lu, Xun & Su, Liangjun, 2025. "Three-dimensional heterogeneous panel data models with multi-level interactive fixed effects," Journal of Econometrics, Elsevier, vol. 249(PB).

  11. Zhonghao Fu & Liangjun Su & Xia Wang, 2024. "Estimation and Inference on Time-Varying FAVAR Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 42(2), pages 533-547, April.

    Cited by:

    1. Peng, Bin & Su, Liangjun & Yan, Yayi, 2025. "A robust residual-based test for structural changes in factor models," Journal of Econometrics, Elsevier, vol. 251(C).
    2. Yuying Sun & Shaoxin Hong & Zongwu Cai, 2025. "State-Varying Model Averaging Prediction," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202507, University of Kansas, Department of Economics.

  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).
    See citations under working paper version above.
  13. Lu, Xun & Su, Liangjun, 2023. "Uniform inference in linear panel data models with two-dimensional heterogeneity," Journal of Econometrics, Elsevier, vol. 235(2), pages 694-719.

    Cited by:

    1. Art=uras Juodis & Martin Weidner, 2026. "Factor-Augmented Panel Regressions and Variance-Weighted Treatment Effects," Papers 2604.18078, arXiv.org.
    2. Jin, Sainan & Lu, Xun & Su, Liangjun, 2025. "Three-dimensional heterogeneous panel data models with multi-level interactive fixed effects," Journal of Econometrics, Elsevier, vol. 249(PB).
    3. Wang, Wei & Xiao, Zhijie & Ren, Yanyan & Yan, Xiaodong, 2023. "A bi-integrative analysis of two-dimensional heterogeneous panel data models," Economics Letters, Elsevier, vol. 230(C).
    4. Lu, Xun & Su, Liangjun & Ba, Yinglong, 2026. "On generalized CCE estimation," Journal of Econometrics, Elsevier, vol. 253(C).
    5. Yiren Wang & Peter C. B. Phillips & Liangjun Su, 2023. "Panel Data Models with Time-Varying Latent Group Structures," Cowles Foundation Discussion Papers 2364, Cowles Foundation for Research in Economics, Yale University.
    6. Xun Lu & Liangjun Su, 2025. "Two-Way Mean Group Estimators for Heterogeneous Panel Models with Fixed T," Papers 2508.10302, arXiv.org.
    7. Oguzhan Akgun & Ryo Okui, 2025. "Robust Inference Methods for Latent Group Panel Models under Possible Group Non-Separation," Papers 2511.18550, arXiv.org, revised Jul 2026.

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

    Cited by:

    1. Jan Ditzen & Yiannis Karavias, 2025. "Interactive, Grouped and Non-separable Fixed Effects: A Practitioner's Guide to the New Panel Data Econometrics," Papers 2507.19099, arXiv.org, revised Oct 2025.
    2. Doan Van Dinh & Bui Yen Nhi & Nguyen Hai Dang & Nguyen Huynh My, 2026. "Bank stability and insolvency risk in emerging markets: a dynamic panel approach with PCA‑based Z‑score," Journal of Banking Regulation, Palgrave Macmillan, vol. 27(3), pages 1-20, September.
    3. Cheng, Tingting & Dong, Chaohua & Gao, Jiti & Linton, Oliver, 2024. "GMM estimation for high-dimensional panel data models," Journal of Econometrics, Elsevier, vol. 244(1).
    4. Feifei Li & Ruile Xue & Songying Wang & Mingyue Du, 2024. "Does the Expansion of Local Government Debt Affect the ESG Performance of Enterprises? Evidence From China," SAGE Open, , vol. 14(4), pages 21582440241, October.
    5. Wang, Xia & Jin, Sainan & Li, Yingxing & Qian, Junhui & Su, Liangjun, 2025. "On time-varying panel data models with time-varying interactive fixed effects," Journal of Econometrics, Elsevier, vol. 249(PB).
    6. Yiren Wang & Peter C. B. Phillips & Liangjun Su, 2023. "Panel Data Models with Time-Varying Latent Group Structures," Cowles Foundation Discussion Papers 2364, Cowles Foundation for Research in Economics, Yale University.
    7. Shittu, Ibrahim & Abdul Latiff, Abdul Rais Bin & Baharudin, Siti 'Aisyah, 2024. "Closing the clean cooking gap: Which policies and institutional qualities matter?," Energy Policy, Elsevier, vol. 185(C).
    8. Zhenhao Gong & Min Seong Kim, 2024. "Improved inference for interactive fixed effects model under cross-sectional dependence," Empirical Economics, Springer, vol. 67(2), pages 727-760, August.
    9. Su, Liangjun & Jin, Sainan & Wang, Xia, 2025. "Sieve estimation of state-varying factor models," Journal of Econometrics, Elsevier, vol. 251(C).
    10. Gao, Wenyu & Zhuang, Xudong & Wu, Yu & Xie, Yanxiang & Hu, Yunchao, 2025. "Foreign investors, agency problems and capital allocation efficiency: From the perspective of QFII shareholding," International Review of Financial Analysis, Elsevier, vol. 105(C).
    11. 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.
    12. Bataka, Hodabalo, 2024. "Global value chains participation and gender inequalities in Sub-Saharan Africa: Importance of women education," International Economics, Elsevier, vol. 178(C).
    13. Zhenhao Gong & Min Seong Kim, 2024. "Improved Inference for Interactive Fixed Effects Model under Cross-Sectional Dependence," Working papers 2024-02, University of Connecticut, Department of Economics.
    14. Marchesani, Filippo & Ceci, Giuseppe, 2026. "Taming the white elephant: How smart cities leverage mega events for advancing digital technologies," Technology in Society, Elsevier, vol. 84(C).
    15. Kan Yao, 2025. "Low-Rank Estimation of Nonlinear Panel Data Models," Papers 2511.21948, arXiv.org, revised Jul 2026.

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

    Cited by:

    1. Yi Li & Xingxing Luo & Mengqi Liao, 2025. "Incorporating Prior Information in Latent Structures Identification for Panel Data Models," Mathematics, MDPI, vol. 13(9), pages 1-26, May.
    2. Lu, Yin & Tao, Chunbai & Wang, Di & Uddin, Gazi Salah & Wu, Libo & Zhu, Xuening, 2025. "Robust estimation for dynamic spatial autoregression models with nearly optimal rates," Journal of Econometrics, Elsevier, vol. 251(C).
    3. Zhonghui Zhang & Chihwa Kao & Jungbin Hwang, 2025. "High-Dimensional Weighted K-Means with Serial Dependence," Working papers 2025-09, University of Connecticut, Department of Economics.
    4. Aishan Ye & Jiayi Cai & Zhenjie Yang & Yangyang Deng & Xiaohua Li, 2025. "The Impact of Intelligent Logistics on Logistics Performance Improvement," Sustainability, MDPI, vol. 17(2), pages 1-19, January.
    5. Yiren Wang & Peter C. B. Phillips & Liangjun Su, 2023. "Panel Data Models with Time-Varying Latent Group Structures," Cowles Foundation Discussion Papers 2364, Cowles Foundation for Research in Economics, Yale University.
    6. Hong, Han & Ju, Gaosheng & Li, Qi & Yan, Karen X., 2024. "Varying-coefficient spatial dynamic panel data models with fixed effects: Theory and application," Journal of Econometrics, Elsevier, vol. 245(1).
    7. Giuseppe Feo & Francesco Giordano & Sara Milito & Marcella Niglio & Maria Lucia Parrella, 2025. "Clustering and classification of spatio-temporal data using spatial dynamic panel data models," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 19(2), pages 387-435, June.
    8. Oguzhan Akgun & Ryo Okui, 2025. "Robust Inference Methods for Latent Group Panel Models under Possible Group Non-Separation," Papers 2511.18550, arXiv.org, revised Jul 2026.

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

    Cited by:

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

  18. 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.

    Cited by:

    1. Wang, Xia & Jin, Sainan & Li, Yingxing & Qian, Junhui & Su, Liangjun, 2025. "On time-varying panel data models with time-varying interactive fixed effects," Journal of Econometrics, Elsevier, vol. 249(PB).
    2. Li, Haiqi & Zhou, Jin & Hong, Yongmiao, 2024. "Estimating and testing for smooth structural changes in moment condition models," Journal of Econometrics, Elsevier, vol. 246(1).

  19. 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.
  20. Wang, Wuyi & Su, Liangjun, 2021. "Identifying latent group structures in nonlinear panels," Journal of Econometrics, Elsevier, vol. 220(2), pages 272-295.
    See citations under working paper version above.
  21. Jin, Sainan & Miao, Ke & Su, Liangjun, 2021. "On factor models with random missing: EM estimation, inference, and cross validation," Journal of Econometrics, Elsevier, vol. 222(1), pages 745-777.
    See citations under working paper version above.
  22. Xun Lu & Ke Miao & Liangjun Su, 2021. "Determination of different types of fixed effects in three-dimensional panels," Econometric Reviews, Taylor & Francis Journals, vol. 40(9), pages 867-898, October.
    See citations under working paper version above.
  23. Shujie Ma & Wei Lan & Liangjun Su & Chih-Ling Tsai, 2020. "Testing Alphas in Conditional Time-Varying Factor Models With High-Dimensional Assets," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(1), pages 214-227, January.
    See citations under working paper version above.
  24. Lu, Xun & Su, Liangjun, 2020. "Determining individual or time effects in panel data models," Journal of Econometrics, Elsevier, vol. 215(1), pages 60-83.

    Cited by:

    1. Dardati, Evangelina & Laurent, Thibault & Margaretic, Paula & Paredes, Ean & Thomas-Agnan, Christine, 2026. "Accounting for the full distribution of temperature to predict international migration," TSE Working Papers 26-1728, Toulouse School of Economics (TSE).
    2. Vira Semenova & Matt Goldman & Victor Chernozhukov & Matt Taddy, 2023. "Inference on heterogeneous treatment effects in high‐dimensional dynamic panels under weak dependence," Quantitative Economics, Econometric Society, vol. 14(2), pages 471-510, May.
    3. Steinhauser Dušan & Kittová Zuzana & Khúlová Lucia, 2024. "Relationship Between CO2 Emissions and Trade: The Case of the EU," Intereconomics: Review of European Economic Policy, Paradigm, vol. 59(1), pages 41-47, February.
    4. Stanislav Zabojník & Dusan Steinhauser & Viktoria Pestova, 2023. "EU Decarbonisation: Do EU Electricity Costs Harm Export Competitiveness?," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 25(63), pages 522-522, April.

  25. 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.
  26. Su, Liangjun & Wang, Xia, 2020. "Testing For Structural Changes In Factor Models Via A Nonparametric Regression," Econometric Theory, Cambridge University Press, vol. 36(6), pages 1127-1158, December.

    Cited by:

    1. Chen, Qitong & Hong, Yongmiao & Li, Haiqi, 2024. "Time-varying forecast combination for factor-augmented regressions with smooth structural changes," Journal of Econometrics, Elsevier, vol. 240(1).
    2. Beyhum, Jad & Striaukas, Jonas, 2024. "Testing for sparse idiosyncratic components in factor-augmented regression models," Journal of Econometrics, Elsevier, vol. 244(1).
    3. Bai, Jushan & Duan, Jiangtao & Han, Xu, 2024. "The likelihood ratio test for structural changes in factor models," Journal of Econometrics, Elsevier, vol. 238(2).
    4. Fu, Zhonghao & Hong, Yongmiao & Wang, Xia, 2023. "Testing for structural changes in large dimensional factor models via discrete Fourier transform," Journal of Econometrics, Elsevier, vol. 233(1), pages 302-331.
    5. Wu, Weichi & Zhou, Zhou & Hong, Yongmiao, 2026. "Inference for time-varying factor models under local stationarity," Journal of Econometrics, Elsevier, vol. 253(C).
    6. Yang, Qing & Zhang, Yi, 2022. "Change-point detection for the link function in a single-index model," Statistics & Probability Letters, Elsevier, vol. 186(C).
    7. Wang, Xia & Jin, Sainan & Li, Yingxing & Qian, Junhui & Su, Liangjun, 2025. "On time-varying panel data models with time-varying interactive fixed effects," Journal of Econometrics, Elsevier, vol. 249(PB).
    8. Yiren Wang & Peter C. B. Phillips & Liangjun Su, 2023. "Panel Data Models with Time-Varying Latent Group Structures," Cowles Foundation Discussion Papers 2364, Cowles Foundation for Research in Economics, Yale University.
    9. Peng, Bin & Su, Liangjun & Yan, Yayi, 2025. "A robust residual-based test for structural changes in factor models," Journal of Econometrics, Elsevier, vol. 251(C).
    10. Yuan Liao & Viktor Todorov, 2024. "Changes in the span of systematic risk exposures," Quantitative Economics, Econometric Society, vol. 15(3), pages 817-847, July.
    11. Li, Haiqi & Zhou, Jin & Hong, Yongmiao, 2024. "Estimating and testing for smooth structural changes in moment condition models," Journal of Econometrics, Elsevier, vol. 246(1).
    12. Su, Liangjun & Jin, Sainan & Wang, Xia, 2025. "Sieve estimation of state-varying factor models," Journal of Econometrics, Elsevier, vol. 251(C).
    13. Bai, Jushan & Duan, Jiangtao & Han, Xu, 2024. "Reprint of: The likelihood ratio test for structural changes in factor models," Journal of Econometrics, Elsevier, vol. 244(2).
    14. Wei, Jie & Zhang, Yonghui, 2020. "A time-varying diffusion index forecasting model," Economics Letters, Elsevier, vol. 193(C).

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

    Cited by:

    1. Yi Li & Xingxing Luo & Mengqi Liao, 2025. "Incorporating Prior Information in Latent Structures Identification for Panel Data Models," Mathematics, MDPI, vol. 13(9), pages 1-26, May.
    2. Andrei Zeleneev & Weisheng Zhang, 2025. "Tractable Estimation of Nonlinear Panels with Interactive Fixed Effects," Papers 2511.15427, arXiv.org, revised Jun 2026.
    3. Marta Marson, 2025. "Effects of public expenditure for agriculture on food security in Africa," Empirical Economics, Springer, vol. 68(6), pages 2673-2704, June.
    4. Wang, Xia & Jin, Sainan & Li, Yingxing & Qian, Junhui & Su, Liangjun, 2025. "On time-varying panel data models with time-varying interactive fixed effects," Journal of Econometrics, Elsevier, vol. 249(PB).
    5. Gong, Woosik & Seo, Myung Hwan, 2026. "Bootstraps for dynamic panel threshold models," Journal of Econometrics, Elsevier, vol. 253(C).
    6. Mengnan Xu & Qifa Xu & Cuixia Jiang & Xingxuan Zhuo, 2026. "High-frequency Growth-at-Risk of China: the Role of Macro-financial Environment," Computational Economics, Springer;Society for Computational Economics, vol. 67(3), pages 1533-1570, March.
    7. Jan Ditzen & Yiannis Karavias & Joakim Westerlund, 2026. "Threshold Regression for Fixed-T Panel Data with Interactive Fixed Effects," Papers 2606.12184, arXiv.org.
    8. Piaopeng Song & Yuxiao Gu & Bin Su & Arifa Tanveer & Qiao Peng & Weijun Gao & Shaomin Wu & Shihong Zeng, 2023. "The Impact of Green Technology Research and Development (R&D) Investment on Performance: A Case Study of Listed Energy Companies in Beijing, China," Sustainability, MDPI, vol. 15(16), pages 1-24, August.
    9. Timothy B. Armstrong & Martin Weidner & Andrei Zeleneev, 2024. "Robust estimation and inference in panels with interactive fixed effects," CeMMAP working papers 28/24, Institute for Fiscal Studies.
    10. Paravee Maneejuk & Woraphon Yamaka, 2021. "The Impact of Higher Education on Economic Growth in ASEAN-5 Countries," Sustainability, MDPI, vol. 13(2), pages 1-28, January.
    11. Dimitraki Ourania & Emmanouilidis Kyriakos, 2025. "Nonlinear Dynamics of Militarization and Income Inequality Nexus in Post-Socialist Eastern Europe: A Panel Kink Regression Analysis (1990–2023)," Peace Economics, Peace Science, and Public Policy, De Gruyter, vol. 31(3), pages 323-335.
    12. Emmanuel Mensah & Christopher Boachie, 2024. "The Threshold Effects of National Governance Quality on the Earnings Management – Performance Nexus: Evidence From Dynamic Panel Threshold Regression," SAGE Open, , vol. 14(4), pages 21582440241, December.
    13. Feng Dong & Yujie Zhang & Jianheng Huang & Yajie Liu & Ying Chen, 2025. "Nonlinear impact of the coordination of IFDI and OFDI on green total factor productivity in the context of “Dual Circulation”," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 11(1), pages 1-32, December.

  28. Miao, Ke & Su, Liangjun & Wang, Wendun, 2020. "Panel threshold regressions with latent group structures," Journal of Econometrics, Elsevier, vol. 214(2), pages 451-481.
    See citations under working paper version above.
  29. 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, 2023. "Functional-Coefficient Quantile Regression for Panel Data with Latent Group Structure," Papers 2303.13218, arXiv.org.
    2. 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.
    3. Boyuan Zhang, 2022. "Incorporating Prior Knowledge of Latent Group Structure in Panel Data Models," Papers 2211.16714, arXiv.org, revised Oct 2023.
    4. 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.
    5. Freeman, Hugo & Weidner, Martin, 2023. "Linear panel regressions with two-way unobserved heterogeneity," Journal of Econometrics, Elsevier, vol. 237(1).
    6. Miao, Ke & Su, Liangjun & Wang, Wendun, 2020. "Panel threshold regressions with latent group structures," Journal of Econometrics, Elsevier, vol. 214(2), pages 451-481.
    7. Zhongjian Lin & Zhentao Shi & Yapeng Zheng, 2026. "Social Interactions Models with Latent Structures," Papers 2602.06435, arXiv.org, revised Jul 2026.
    8. Okui, Ryo & Wang, Wendun, 2021. "Heterogeneous structural breaks in panel data models," Journal of Econometrics, Elsevier, vol. 220(2), pages 447-473.
    9. 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.
    10. Cheng, Tingting & Dong, Chaohua & Gao, Jiti & Linton, Oliver, 2024. "GMM estimation for high-dimensional panel data models," Journal of Econometrics, Elsevier, vol. 244(1).
    11. Marina Khismatullina & Bernhard van der Sluis, 2025. "Multiscale Comparison of Nonparametric Trending Coefficients," Papers 2511.12600, arXiv.org.
    12. Vasilios Plakandaras & Rangan Gupta & Qiang Ji, 2025. "Unraveling Financial Fragility of Global Markets Using Machine Learning," Working Papers 202511, University of Pretoria, Department of Economics.
    13. Yiren Wang & Liangjun Su & Yichong Zhang, 2022. "Low-rank Panel Quantile Regression: Estimation and Inference," Papers 2210.11062, arXiv.org.
    14. Katerina Chrysikou & George Kapetanios, 2024. "Heterogeneous Grouping Structures in Panel Data," Papers 2407.19509, arXiv.org.
    15. Wang, Xia & Jin, Sainan & Li, Yingxing & Qian, Junhui & Su, Liangjun, 2025. "On time-varying panel data models with time-varying interactive fixed effects," Journal of Econometrics, Elsevier, vol. 249(PB).
    16. 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.
    17. Bian, Yulin & Su, Liangjun, 2025. "A note on factor models with latent group structures," Economics Letters, Elsevier, vol. 252(C).
    18. 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.
    19. Boyuan Zhang, 2020. "Forecasting with Bayesian Grouped Random Effects in Panel Data," Papers 2007.02435, arXiv.org, revised Oct 2020.
    20. Yiren Wang & Peter C. B. Phillips & Liangjun Su, 2023. "Panel Data Models with Time-Varying Latent Group Structures," Cowles Foundation Discussion Papers 2364, Cowles Foundation for Research in Economics, Yale University.
    21. Huang, Danyang & Hu, Wei & Jing, Bingyi & Zhang, Bo, 2023. "Grouped spatial autoregressive model," Computational Statistics & Data Analysis, Elsevier, vol. 178(C).
    22. Oh, Dong Hwan & Patton, Andrew J., 2023. "Dynamic factor copula models with estimated cluster assignments," Journal of Econometrics, Elsevier, vol. 237(2).
    23. 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).
    24. Kaddoura, Yousef, 2025. "Estimating coefficient-by-coefficient breaks in panel data models," Journal of Econometrics, Elsevier, vol. 249(PB).
    25. 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.
    26. Paul Haimerl & Stephan Smeekes & Ines Wilms, 2025. "Estimation of Latent Group Structures in Time-Varying Panel Data Models," Papers 2503.23165, arXiv.org, revised Nov 2025.
    27. Mehrabani, Ali, 2023. "Estimation and identification of latent group structures in panel data," Journal of Econometrics, Elsevier, vol. 235(2), pages 1464-1482.
    28. 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.
    29. Wang, Wuyi & Su, Liangjun, 2021. "Identifying latent group structures in nonlinear panels," Journal of Econometrics, Elsevier, vol. 220(2), pages 272-295.
    30. 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.
    31. Oguzhan Akgun & Ryo Okui, 2025. "Robust Inference Methods for Latent Group Panel Models under Possible Group Non-Separation," Papers 2511.18550, arXiv.org, revised Jul 2026.
    32. Daniel Czarnowske, 2022. "A Classifier-Lasso Approach for Estimating Production Functions with Latent Group Structures," Papers 2203.02220, arXiv.org.
    33. 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.
    34. Ali Mehrabani & Shahnaz Parsaeian, 2025. "Shrinkage Estimation and Identification of Latent Group Structures in Panel Data with Interactive Fixed Effects," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202516, University of Kansas, Department of Economics.
    35. 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.
    36. 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.
    37. 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.

  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.

    Cited by:

    1. Fei Liu & Jiti Gao & Yanrong Yang, 2019. "Nonparametric Estimation in Panel Data Models with Heterogeneity and Time Varyingness," Monash Econometrics and Business Statistics Working Papers 24/19, Monash University, Department of Econometrics and Business Statistics.
    2. Juodis, Arturas & Sarafidis, Vasilis, 2020. "An Incidental Parameters Free Inference Approach for Panels with Common Shocks," MPRA Paper 104906, University Library of Munich, Germany.
    3. Gao, Jiti & Liu, Fei & Peng, Bin & Yan, Yayi, 2023. "Binary response models for heterogeneous panel data with interactive fixed effects," Journal of Econometrics, Elsevier, vol. 235(2), pages 1654-1679.

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

    Cited by:

    1. Li, Zheng & Zeng, Jingjing & Hensher, David A., 2023. "An efficient approach to structural breaks and the case of automobile gasoline consumption in Australia," Transportation Research Part A: Policy and Practice, Elsevier, vol. 169(C).
    2. Yan Chen & Caiyun Fan & Feipeng Zhang, 2025. "Linear-quadratic quantile regression model with a change point due to a threshold covariate," Computational Statistics, Springer, vol. 40(8), pages 4515-4564, November.
    3. Junho Lee & Ying Sun & Huixia Judy Wang, 2021. "Spatial cluster detection with threshold quantile regression," Environmetrics, John Wiley & Sons, Ltd., vol. 32(8), December.
    4. Hong, Yanran & Li, Pan & Wang, Lu & Zhang, Yaojie, 2023. "New evidence of extreme risk transmission between financial stress and international crude oil markets," Research in International Business and Finance, Elsevier, vol. 64(C).
    5. Martins, Luis F., 2021. "The US debt–growth nexus along the business cycle," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).

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

    Cited by:

    1. 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.
    2. 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.
    3. 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).
    4. Bai, Jushan & Duan, Jiangtao & Han, Xu, 2024. "The likelihood ratio test for structural changes in factor models," Journal of Econometrics, Elsevier, vol. 238(2).
    5. Jiangtao Duan & Jushan Bai & Xu Han, 2025. "Taxonomy and Estimation of Multiple Breakpoints in High-Dimensional Factor Models," Papers 2503.06645, arXiv.org, revised Apr 2026.
    6. Lei Jia & Shouri Hu & Zhaoxing Gao, 2026. "Structural Change Detection in High-Dimensional Transformed Factor Models via Canonical Correlation Analysis," Papers 2606.01553, arXiv.org.
    7. Thomas Despois & Catherine Doz, 2021. "Identifying and interpreting the factors in factor models via sparsity: Different approaches," PSE Working Papers halshs-02235543, HAL.
    8. Ma, Chenchen & Tu, Yundong, 2025. "When structural break meets threshold effect: Factor analysis under structural instabilities," Journal of Econometrics, Elsevier, vol. 249(PB).
    9. Catherine Doz & Peter Fuleky, 2019. "Dynamic Factor Models," Working Papers halshs-02262202, HAL.
    10. 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.
    11. Yiren Wang & Liangjun Su & Yichong Zhang, 2022. "Low-rank Panel Quantile Regression: Estimation and Inference," Papers 2210.11062, arXiv.org.
    12. Xialu Liu & John Guerard & Rong Chen & Ruey Tsay, 2024. "Improving Estimation of Portfolio Risk Using New Statistical Factors," Papers 2409.17182, arXiv.org.
    13. 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.
    14. 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).
    15. 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.
    16. Thomas Despois & Catherine Doz, 2021. "Identifying and interpreting the factors in factor models via sparsity: Different approaches," Working Papers halshs-02235543, HAL.
    17. Li, Degui, 2024. "Estimation of Large Dynamic Covariance Matrices: A Selective Review," Econometrics and Statistics, Elsevier, vol. 29(C), pages 16-30.
    18. Peng, Bin & Su, Liangjun & Yan, Yayi, 2025. "A robust residual-based test for structural changes in factor models," Journal of Econometrics, Elsevier, vol. 251(C).
    19. Wang, Lu & Wu, Jianhong, 2022. "Estimation of high-dimensional factor models with multiple structural changes," Economic Modelling, Elsevier, vol. 108(C).
    20. Urga, Giovanni & Wang, Fa, 2022. "Estimation and inference for high dimensional factor model with regime switching," MPRA Paper 113172, University Library of Munich, Germany.
    21. Wu, Jianhong, 2021. "Estimation of high dimensional factor model with multiple threshold-type regime shifts," Computational Statistics & Data Analysis, Elsevier, vol. 157(C).
    22. Xialu Liu & Elynn Y. Chen, 2022. "Identification and estimation of threshold matrix‐variate factor models," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 49(3), pages 1383-1417, September.
    23. Xialu Liu & John Guerard & Rong Chen & Ruey Tsay, 2025. "Improving estimation of portfolio risk using new statistical factors," Annals of Operations Research, Springer, vol. 346(1), pages 245-261, March.
    24. Su, Liangjun & Jin, Sainan & Wang, Xia, 2025. "Sieve estimation of state-varying factor models," Journal of Econometrics, Elsevier, vol. 251(C).
    25. Bai, Jushan & Duan, Jiangtao & Han, Xu, 2024. "Reprint of: The likelihood ratio test for structural changes in factor models," Journal of Econometrics, Elsevier, vol. 244(2).
    26. Ma, Chenchen & Tu, Yundong, 2023. "Shrinkage estimation of multiple threshold factor models," Journal of Econometrics, Elsevier, vol. 235(2), pages 1876-1892.
    27. 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.
    28. Urga, Giovanni & Wang, Fa, 2024. "Estimation and inference for high dimensional factor model with regime switching," Journal of Econometrics, Elsevier, vol. 241(2).
    29. Ma, Chenchen & Tu, Yundong, 2023. "Group fused Lasso for large factor models with multiple structural breaks," Journal of Econometrics, Elsevier, vol. 233(1), pages 132-154.

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

    Cited by:

    1. Lamarche, Carlos & Parker, Thomas, 2023. "Wild bootstrap inference for penalized quantile regression for longitudinal data," Journal of Econometrics, Elsevier, vol. 235(2), pages 1799-1826.
    2. Yi Li & Xingxing Luo & Mengqi Liao, 2025. "Incorporating Prior Information in Latent Structures Identification for Panel Data Models," Mathematics, MDPI, vol. 13(9), pages 1-26, May.
    3. William W. Chow, 2025. "Inflation cost of strategic goods export restriction: evidence from dynamic spatial panel data model," International Economics and Economic Policy, Springer, vol. 22(4), pages 1-25, October.
    4. Boyuan Zhang, 2022. "Incorporating Prior Knowledge of Latent Group Structure in Panel Data Models," Papers 2211.16714, arXiv.org, revised Oct 2023.
    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. Miao, Ke & Su, Liangjun & Wang, Wendun, 2020. "Panel threshold regressions with latent group structures," Journal of Econometrics, Elsevier, vol. 214(2), pages 451-481.
    7. Denis Chetverikov & Elena Manresa, 2022. "Spectral and post-spectral estimators for grouped panel data models," Papers 2212.13324, arXiv.org, revised Dec 2022.
    8. Zhongjian Lin & Zhentao Shi & Yapeng Zheng, 2026. "Social Interactions Models with Latent Structures," Papers 2602.06435, arXiv.org, revised Jul 2026.
    9. Jin, Sainan & Lu, Xun & Su, Liangjun, 2025. "Three-dimensional heterogeneous panel data models with multi-level interactive fixed effects," Journal of Econometrics, Elsevier, vol. 249(PB).
    10. 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.
    11. Vogt, Michael & Linton, Oliver, 2020. "Multiscale clustering of nonparametric regression curves," Journal of Econometrics, Elsevier, vol. 216(1), pages 305-325.
    12. Wang, Wuyi & Phillips, Peter C.B. & Su, Liangjun, 2019. "The heterogeneous effects of the minimum wage on employment across states," Economics Letters, Elsevier, vol. 174(C), pages 179-185.
    13. Yiren Wang & Liangjun Su & Yichong Zhang, 2022. "Low-rank Panel Quantile Regression: Estimation and Inference," Papers 2210.11062, arXiv.org.
    14. Gobillon, Laurent & Magnac, Thierry & Roux, Sébastien, 2025. "Lifecycle Wages and Human Capital Investments: Selection and Missing Data," IZA Discussion Papers 17838, IZA Network @ LISER.
    15. Likai Chen & Georg Keilbar & Liangjun Su & Weining Wang, 2023. "High-dimensional inference on jumps in nonparametric time series regression models," Papers 2312.01162, arXiv.org, revised Jul 2026.
    16. Katerina Chrysikou & George Kapetanios, 2024. "Heterogeneous Grouping Structures in Panel Data," Papers 2407.19509, arXiv.org.
    17. Zhentao Shi & Liangjun Su & Tian Xie, 2020. "L2-Relaxation: With Applications to Forecast Combination and Portfolio Analysis," Papers 2010.09477, arXiv.org, revised Aug 2022.
    18. Bian, Yulin & Su, Liangjun, 2025. "A note on factor models with latent group structures," Economics Letters, Elsevier, vol. 252(C).
    19. Yiren Wang & Peter C. B. Phillips & Liangjun Su, 2023. "Panel Data Models with Time-Varying Latent Group Structures," Cowles Foundation Discussion Papers 2364, Cowles Foundation for Research in Economics, Yale University.
    20. Jorge A. Rivero, 2023. "Unobserved Grouped Heteroskedasticity and Fixed Effects," Papers 2310.14068, arXiv.org, revised Oct 2023.
    21. Miao, Ke & Li, Kunpeng & Su, Liangjun, 2020. "Panel threshold models with interactive fixed effects," Journal of Econometrics, Elsevier, vol. 219(1), pages 137-170.
    22. Mehrabani, Ali, 2023. "Estimation and identification of latent group structures in panel data," Journal of Econometrics, Elsevier, vol. 235(2), pages 1464-1482.
    23. Wang, Wuyi & Su, Liangjun, 2021. "Identifying latent group structures in nonlinear panels," Journal of Econometrics, Elsevier, vol. 220(2), pages 272-295.
    24. 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.
    25. Oguzhan Akgun & Ryo Okui, 2025. "Robust Inference Methods for Latent Group Panel Models under Possible Group Non-Separation," Papers 2511.18550, arXiv.org, revised Jul 2026.
    26. Daniel J. Lewis & Davide Melcangi & Laura Pilossoph & Aidan Toner‐Rodgers, 2023. "Approximating grouped fixed effects estimation via fuzzy clustering regression," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(7), pages 1077-1084, November.
    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. Ali Mehrabani & Shahnaz Parsaeian, 2025. "Shrinkage Estimation and Identification of Latent Group Structures in Panel Data with Interactive Fixed Effects," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202516, University of Kansas, Department of Economics.
    29. 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.
    30. Marchesani, Filippo & Ceci, Giuseppe, 2026. "Taming the white elephant: How smart cities leverage mega events for advancing digital technologies," Technology in Society, Elsevier, vol. 84(C).
    31. Harold D. Chiang & Joel Rodrigue & Yuya Sasaki, 2019. "Post-Selection Inference in Three-Dimensional Panel Data," Papers 1904.00211, arXiv.org, revised Apr 2019.
    32. Pionati, Alessandro, 2025. "Latent grouped structures in panel data: a review," MPRA Paper 123954, University Library of Munich, Germany.
    33. Li, Kunpeng & Cui, Guowei & Lu, Lina, 2020. "Efficient estimation of heterogeneous coefficients in panel data models with common shocks," Journal of Econometrics, Elsevier, vol. 216(2), pages 327-353.

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

    Cited by:

    1. Gao, Min & Yang, Wenzhi & Wu, Shipeng & Yu, Wei, 2022. "Asymptotic normality of residual density estimator in stationary and explosive autoregressive models," Computational Statistics & Data Analysis, Elsevier, vol. 175(C).
    2. Francesco Giordano & Marcella Niglio & Maria Lucia Parrella, 2024. "Testing Spatial Dynamic Panel Data Models with Heterogeneous Spatial and Regression Coefficients," Journal of Time Series Analysis, Wiley Blackwell, vol. 45(5), pages 771-799, September.
    3. Jungyoon Lee & Peter C.B. Phillips & Francesca Rossi, 2020. "Consistent Misspecification Testing in Spatial Autoregressive Models," Cowles Foundation Discussion Papers 2256, Cowles Foundation for Research in Economics, Yale University.
    4. 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.
    5. Liu, Li & Bu, Ruijun & Pan, Zhiyuan & Xu, Yuhua, 2019. "Are financial returns really predictable out-of-sample?: Evidence from a new bootstrap test," Economic Modelling, Elsevier, vol. 81(C), pages 124-135.
    6. Abhimanyu Gupta & Jungyoon Lee & Francesca Rossi, 2024. "Testing linearity of spatial interaction functions \`a la Ramsey," Papers 2412.14778, arXiv.org, revised Jul 2026.
    7. Lu, Xun & Su, Liangjun, 2020. "Determining individual or time effects in panel data models," Journal of Econometrics, Elsevier, vol. 215(1), pages 60-83.
    8. Abhimanyu Gupta & Xi Qu, 2021. "Consistent specification testing under spatial dependence," Papers 2101.10255, arXiv.org, revised Aug 2022.

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

    Cited by:

    1. Ghazinoory, Sepehr & Aghaei, Parvaneh, 2021. "Differences between policy assessment & policy evaluation; a case study on supportive policies for knowledge-based firms," Technological Forecasting and Social Change, Elsevier, vol. 169(C).
    2. Emmanuel Selorm Tsyawo, 2021. "Feasible IV Regression without Excluded Instruments," Papers 2103.09621, arXiv.org, revised Nov 2022.
    3. Lai, Tingyu & Zhang, Zhongzhan & Wang, Yafei, 2021. "A kernel-based measure for conditional mean dependence," Computational Statistics & Data Analysis, Elsevier, vol. 160(C).
    4. Emmanuel Selorm Tsyawo & Abdul-Nasah Soale, 2021. "A Distance Covariance-based Estimator," Papers 2102.07008, arXiv.org, revised Nov 2025.
    5. Kai Xu & Nan An, 2024. "A tuning-free efficient test for marginal linear effects in high-dimensional quantile regression," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 76(1), pages 93-110, February.

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

    Cited by:

    1. Etienne Farvaque & Jean-Baptiste Gossé & Camille Jehle, 2026. "Income Smoothing Across EU Regions: a Panel Decomposition of Adjustment Channels," Working papers 1037, Banque de France.
    2. Andreas Dzemski & Ryo Okui, 2024. "Confidence set for group membership," Quantitative Economics, Econometric Society, vol. 15(2), pages 245-277, May.
    3. Yu Hao & Hiroyuki Kasahara, 2025. "Estimating the Number of Components in Panel Data Finite Mixture Regression Models with an Application to Production Function Heterogeneity," Papers 2506.09666, arXiv.org.
    4. 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.
    5. Miao, Ke & Su, Liangjun & Wang, Wendun, 2020. "Panel threshold regressions with latent group structures," Journal of Econometrics, Elsevier, vol. 214(2), pages 451-481.
    6. Yao Luo & Hidenori Takahashi, 2022. "Bidding for Contracts under Uncertain Demand: Skewed Bidding and Risk Sharing," Working Papers tecipa-732, University of Toronto, Department of Economics.
    7. Yanbo Liu & Peter C. B. Phillips & Jun Yu, 2023. "A Panel Clustering Approach To Analyzing Bubble Behavior," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 64(4), pages 1347-1395, November.
    8. 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.
    9. Zhongjian Lin & Zhentao Shi & Yapeng Zheng, 2026. "Social Interactions Models with Latent Structures," Papers 2602.06435, arXiv.org, revised Jul 2026.
    10. Francesco Fallucchi & Andrea Mercatanti & Jan Niederreiter, 2021. "Identifying types in contest experiments," International Journal of Game Theory, Springer;Game Theory Society, vol. 50(1), pages 39-61, March.
    11. Zhan Gao & Zhentao Shi, 2018. "Implementing Convex Optimization in R: Two Econometric Examples," Papers 1806.10423, arXiv.org, revised Aug 2019.
    12. Eric Auerbach & Jonathan Auerbach & Sidonia McKenzie, 2026. "Post-Selection Inference for Network Structure," Papers 2607.00312, arXiv.org, revised Jul 2026.
    13. Okui, Ryo & Wang, Wendun, 2021. "Heterogeneous structural breaks in panel data models," Journal of Econometrics, Elsevier, vol. 220(2), pages 447-473.
    14. 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.
    15. Hasraddin Guliyev, 2025. "Using Machine Learning Techniques to Test the Load Capacity Curve Hypothesis: A Classifier-Lasso Application on Global Panel Data," Biophysical Economics and Resource Quality, Springer, vol. 10(1), pages 1-18, June.
    16. Wang, Wuyi & Phillips, Peter C.B. & Su, Liangjun, 2019. "The heterogeneous effects of the minimum wage on employment across states," Economics Letters, Elsevier, vol. 174(C), pages 179-185.
    17. Custodio João, Igor & Lucas, André & Schaumburg, Julia & Schwaab, Bernd, 2023. "Dynamic clustering of multivariate panel data," Journal of Econometrics, Elsevier, vol. 237(2).
    18. Jan Niederreiter, 2023. "Broadening Economics in the Era of Artificial Intelligence and Experimental Evidence," Italian Economic Journal: A Continuation of Rivista Italiana degli Economisti and Giornale degli Economisti, Springer;Società Italiana degli Economisti (Italian Economic Association), vol. 9(1), pages 265-294, March.
    19. Yiren Wang & Peter C. B. Phillips & Liangjun Su, 2023. "Panel Data Models with Time-Varying Latent Group Structures," Cowles Foundation Discussion Papers 2364, Cowles Foundation for Research in Economics, Yale University.
    20. Jorge A. Rivero, 2023. "Unobserved Grouped Heteroskedasticity and Fixed Effects," Papers 2310.14068, arXiv.org, revised Oct 2023.
    21. Bruce E. Hansen & Seojeong Jay Lee, 2018. "Inference for Iterated GMM Under Misspecification and Clustering," Discussion Papers 2018-07, School of Economics, The University of New South Wales.
    22. Bruce E. Hansen & Seojeong Lee, 2021. "Inference for Iterated GMM Under Misspecification," Econometrica, Econometric Society, vol. 89(3), pages 1419-1447, May.
    23. Yu Hao & Hiroyuki Kasahara, 2022. "Testing the Number of Components in Finite Mixture Normal Regression Model with Panel Data," Papers 2210.02824, arXiv.org, revised Jun 2023.
    24. Mikihito Nishi, 2025. "K-Means Panel Data Clustering in the Presence of Small Groups," Papers 2508.15408, arXiv.org.
    25. Mehrabani, Ali, 2023. "Estimation and identification of latent group structures in panel data," Journal of Econometrics, Elsevier, vol. 235(2), pages 1464-1482.
    26. Wang, Wuyi & Su, Liangjun, 2021. "Identifying latent group structures in nonlinear panels," Journal of Econometrics, Elsevier, vol. 220(2), pages 272-295.
    27. Antonio Raiola & Nazarii Salish, 2025. "Detection Boundaries for Panel Slope Homogeneity Tests Under Small-Group Heterogeneity," Papers 2510.22841, arXiv.org, revised Apr 2026.
    28. Oguzhan Akgun & Ryo Okui, 2025. "Robust Inference Methods for Latent Group Panel Models under Possible Group Non-Separation," Papers 2511.18550, arXiv.org, revised Jul 2026.
    29. Dzemski, Andreas & Okui, Ryo, 2018. "Confidence Set for Group Membership," Working Papers in Economics 727, University of Gothenburg, Department of Economics.
    30. 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.
    31. Ali Mehrabani & Shahnaz Parsaeian, 2025. "Shrinkage Estimation and Identification of Latent Group Structures in Panel Data with Interactive Fixed Effects," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202516, University of Kansas, Department of Economics.
    32. Pionati, Alessandro, 2025. "Latent grouped structures in panel data: a review," MPRA Paper 123954, University Library of Munich, Germany.

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

    Cited by:

    1. 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. Fei Liu & Jiti Gao & Yanrong Yang, 2020. "Time-Varying Panel Data Models with an Additive Factor Structure," Monash Econometrics and Business Statistics Working Papers 42/20, Monash University, Department of Econometrics and Business Statistics.
    3. Chen, J. & Li, D. & Li, Y. & Linton, O. B., 2022. "Estimating Time-Varying Networks for High-Dimensional Time Series," Cambridge Working Papers in Economics 2273, Faculty of Economics, University of Cambridge.
    4. Barigozzi, Matteo & Massacci, Daniele, 2025. "Modelling large dimensional datasets with Markov switching factor models," Journal of Econometrics, Elsevier, vol. 247(C).
    5. Chen, Qitong & Hong, Yongmiao & Li, Haiqi, 2024. "Time-varying forecast combination for factor-augmented regressions with smooth structural changes," Journal of Econometrics, Elsevier, vol. 240(1).
    6. Pedro Isaac Chavez-Lopez & Tae-Hwy Lee, 2025. "Quantile-Covariance Three-Pass Regression Filter," Working Papers 202501, University of California at Riverside, Department of Economics.
    7. Cheng, Mingmian & Liao, Yuan & Yang, Xiye, 2023. "Uniform predictive inference for factor models with instrumental and idiosyncratic betas," Journal of Econometrics, Elsevier, vol. 237(2).
    8. Freeman, Hugo & Weidner, Martin, 2023. "Linear panel regressions with two-way unobserved heterogeneity," Journal of Econometrics, Elsevier, vol. 237(1).
    9. Le, Ha Chi & Bhattacharya, Mita & Smyth, Russell & Zhang, Xibin, 2024. "Does economic growth cause energy intensity of well-being in the very long run? Semi-parametric evidence for selected OECD countries," Energy Economics, Elsevier, vol. 139(C).
    10. Beyhum, Jad & Striaukas, Jonas, 2024. "Testing for sparse idiosyncratic components in factor-augmented regression models," Journal of Econometrics, Elsevier, vol. 244(1).
    11. 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.
    12. Duan, Junting & Pelger, Markus & Xiong, Ruoxuan, 2024. "Target PCA: Transfer learning large dimensional panel data," Journal of Econometrics, Elsevier, vol. 244(2).
    13. Miao, Ke & Phillips, Peter C.B. & Su, Liangjun, 2023. "High-dimensional VARs with common factors," Journal of Econometrics, Elsevier, vol. 233(1), pages 155-183.
    14. Cheung, Ying Lun, 2024. "Avoiding jumps in the rotation matrix of time-varying factor models," Finance Research Letters, Elsevier, vol. 67(PB).
    15. Sun, Yuying & Hong, Yongmiao & Wang, Shouyang & Zhang, Xinyu, 2023. "Penalized time-varying model averaging," Journal of Econometrics, Elsevier, vol. 235(2), pages 1355-1377.
    16. Gagliardini, Patrick & Ossola, Elisa & Scaillet, Olivier, 2020. "Estimation of large dimensional conditional factor models in finance," Handbook of Econometrics, in: Steven N. Durlauf & Lars Peter Hansen & James J. Heckman & Rosa L. Matzkin (ed.), Handbook of Econometrics, edition 1, volume 7, chapter 0, pages 219-282, Elsevier.
    17. Koki Kyo & Hideo Noda, 2026. "Analyzing Mechanisms of Business Fluctuations involving Time-Varying Structure in Japan: Methodological Proposition and Empirical Study," Computational Economics, Springer;Society for Computational Economics, vol. 67(4), pages 3123-3182, April.
    18. Jie Wei & Yonghui Zhang, 2023. "Does Principal Component Analysis Preserve the Sparsity in Sparse Weak Factor Models?," Papers 2305.05934, arXiv.org, revised Nov 2024.
    19. 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.
    20. 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.
    21. Dima, Bogdan & Dima, Ştefana Maria & Ioan, Roxana, 2025. "The short-run impact of investor expectations’ past volatility on current predictions: The case of VIX," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 98(C).
    22. Wu, Weichi & Zhou, Zhou & Hong, Yongmiao, 2026. "Inference for time-varying factor models under local stationarity," Journal of Econometrics, Elsevier, vol. 253(C).
    23. Liang Chen & Juan Jose Dolado & Jesus Gonzalo, 2019. "Quantile Factor Models," Papers 1911.02173, arXiv.org, revised Sep 2020.
    24. 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.
    25. Raffaella Giacomini & Jason Lu & Katja Smetanina, 2024. "Perceived shocks and impulse responses," IFS Working Papers WCWP21/24, Institute for Fiscal Studies.
    26. Cheng, Tingting & Dong, Chaohua & Gao, Jiti & Linton, Oliver, 2024. "GMM estimation for high-dimensional panel data models," Journal of Econometrics, Elsevier, vol. 244(1).
    27. Reiß, Markus & Winkelmann, Lars, 2021. "Inference on the maximal rank of time-varying covariance matrices using high-frequency data," Discussion Papers 2021/14, Free University Berlin, School of Business & Economics.
    28. Christian Brownlees & Gu{dh}mundur Stef'an Gu{dh}mundsson & Yaping Wang, 2024. "Performance of Empirical Risk Minimization For Principal Component Regression," Papers 2409.03606, arXiv.org, revised Jul 2026.
    29. Lee, Tae-Hwy & Seregina, Ekaterina, 2026. "Combining forecasts under structural breaks using Graphical LASSO," International Journal of Forecasting, Elsevier, vol. 42(1), pages 126-137.
    30. Catherine Doz & Peter Fuleky, 2019. "Dynamic Factor Models," Working Papers halshs-02262202, HAL.
    31. Ying Lun Cheung, 2024. "Identification of Time-Varying Factor Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 42(1), pages 76-94, January.
    32. Raffaella Giacomini & Jason Lu & Katja Smetanina, 2024. "Perceived shocks and impulse responses," CeMMAP working papers 21/24, Institute for Fiscal Studies.
    33. Xialu Liu & John Guerard & Rong Chen & Ruey Tsay, 2024. "Improving Estimation of Portfolio Risk Using New Statistical Factors," Papers 2409.17182, arXiv.org.
    34. Jianqing Fan & Kunpeng Li & Yuan Liao, 2020. "Recent Developments on Factor Models and its Applications in Econometric Learning," Papers 2009.10103, arXiv.org.
    35. Jaeheon Jung, 2019. "Estimating a Large Covariance Matrix in Time-varying Factor Models," Papers 1910.11965, arXiv.org.
    36. Wang, Xia & Jin, Sainan & Li, Yingxing & Qian, Junhui & Su, Liangjun, 2025. "On time-varying panel data models with time-varying interactive fixed effects," Journal of Econometrics, Elsevier, vol. 249(PB).
    37. Bian, Yulin & Su, Liangjun, 2025. "A note on factor models with latent group structures," Economics Letters, Elsevier, vol. 252(C).
    38. 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.
    39. Wu, Ruike & Yang, Yanrong & Shang, Han Lin & Zhu, Huanjun, 2025. "Making distributionally robust portfolios feasible in high dimension," Journal of Econometrics, Elsevier, vol. 252(PA).
    40. Shikha Gupta & Nand Kumar, 2023. "Time varying dynamics of globalization effect in India," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 22(1), pages 81-97, January.
    41. Tu, Yundong & Wang, Siwei, 2025. "Quantile prediction with factor-augmented regression: Structural instability and model uncertainty," Journal of Econometrics, Elsevier, vol. 249(PB).
    42. Fan, Qingliang & Wu, Ruike & Yang, Yanrong & Zhong, Wei, 2024. "Time-varying minimum variance portfolio," Journal of Econometrics, Elsevier, vol. 239(2).
    43. Sicco Kooiker & Janneke van Brummelen & Julia Schaumburg & Marcin Zamojski, 2026. "Self-driving neural networks for term structure modeling," Tinbergen Institute Discussion Papers 26-007/III, Tinbergen Institute.
    44. Li, Degui, 2024. "Estimation of Large Dynamic Covariance Matrices: A Selective Review," Econometrics and Statistics, Elsevier, vol. 29(C), pages 16-30.
    45. Peng, Bin & Su, Liangjun & Yan, Yayi, 2025. "A robust residual-based test for structural changes in factor models," Journal of Econometrics, Elsevier, vol. 251(C).
    46. Kong, Xin-Bing & Liu, Cheng, 2018. "Testing against constant factor loading matrix with large panel high-frequency data," Journal of Econometrics, Elsevier, vol. 204(2), pages 301-319.
    47. Urga, Giovanni & Wang, Fa, 2022. "Estimation and inference for high dimensional factor model with regime switching," MPRA Paper 113172, University Library of Munich, Germany.
    48. Li, Haiqi & Zhou, Jin & Hong, Yongmiao, 2024. "Estimating and testing for smooth structural changes in moment condition models," Journal of Econometrics, Elsevier, vol. 246(1).
    49. Markus Pelger & Ruoxuan Xiong, 2018. "State-Varying Factor Models of Large Dimensions," Papers 1807.02248, arXiv.org, revised Oct 2020.
    50. Aslanidis, Nektarios & Hartigan, Luke, 2021. "Is the assumption of constant factor loadings too strong in practice?," Economic Modelling, Elsevier, vol. 98(C), pages 100-108.
    51. Yousuf, Kashif & Ng, Serena, 2021. "Boosting high dimensional predictive regressions with time varying parameters," Journal of Econometrics, Elsevier, vol. 224(1), pages 60-87.
    52. Sun, Yucheng & Xu, Wen & Zhang, Chuanhai, 2023. "Identifying latent factors based on high-frequency data," Journal of Econometrics, Elsevier, vol. 233(1), pages 251-270.
    53. Bhattacharya, Rudrani & Chakravarti, Parma & Mundle, Sudipto, 2018. "Forecasting India's Economic Growth: A Time-Varying Parameter Regression Approach," Working Papers 18/238, National Institute of Public Finance and Policy.
    54. Ziyan Zhao & Qingfeng Liu, 2024. "Time-Varying Structural Approximate Dynamic Factor Model," Economic Growth Centre Working Paper Series 2401, Nanyang Technological University, School of Social Sciences, Economic Growth Centre.
    55. Xialu Liu & John Guerard & Rong Chen & Ruey Tsay, 2025. "Improving estimation of portfolio risk using new statistical factors," Annals of Operations Research, Springer, vol. 346(1), pages 245-261, March.
    56. Su, Liangjun & Jin, Sainan & Wang, Xia, 2025. "Sieve estimation of state-varying factor models," Journal of Econometrics, Elsevier, vol. 251(C).
    57. Christian Fieberg & Gerrit Liedtke & Thorsten Poddig, 2025. "Recurrent double-conditional factor model," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 47(1), pages 205-254, March.
    58. Eric Hillebrand & Jakob Mikkelsen & Lars Spreng & Giovanni Urga, 2020. "Exchange Rates and Macroeconomic Fundamentals: Evidence of Instabilities from Time-Varying Factor Loadings," CREATES Research Papers 2020-19, Department of Economics and Business Economics, Aarhus University.
    59. 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.
    60. Esther Ruiz & Pilar Poncela, 2022. "Factor Extraction in Dynamic Factor Models: Kalman Filter Versus Principal Components," Foundations and Trends(R) in Econometrics, now publishers, vol. 12(2), pages 121-231, November.
    61. Zhe Sun & Yundong Tu, 2024. "Factors in Fashion: Factor Analysis towards the Mode," Papers 2409.19287, arXiv.org.
    62. Xiyuan Liu & Zongwu Cai & Liangjun Su, 2025. "Time-varying Factor-augmented Forecasting Models with Variable Selection," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202515, University of Kansas, Department of Economics, revised Sep 2025.
    63. Qingliang Fan & Ruike Wu & Yanrong Yang, 2024. "Shocks-adaptive Robust Minimum Variance Portfolio for a Large Universe of Assets," Papers 2410.01826, arXiv.org.
    64. Matteo Barigozzi & Marc Hallin & Stefano Soccorsi, 2019. "Time-Varying General Dynamic Factor Models and the Measurement of Financial Connectedness," Working Papers ECARES 2019-09, ULB -- Universite Libre de Bruxelles.
    65. Duván Humberto Cataño & Carlos Vladimir Rodríguez-Caballero & Daniel Peña, 2019. "Wavelet Estimation for Dynamic Factor Models with Time-Varying Loadings," CREATES Research Papers 2019-23, Department of Economics and Business Economics, Aarhus University.
    66. Ma, Chenchen & Tu, Yundong, 2023. "Shrinkage estimation of multiple threshold factor models," Journal of Econometrics, Elsevier, vol. 235(2), pages 1876-1892.
    67. 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.
    68. Urga, Giovanni & Wang, Fa, 2024. "Estimation and inference for high dimensional factor model with regime switching," Journal of Econometrics, Elsevier, vol. 241(2).
    69. Tomas Adam & Katerina Arnostova & Oxana Babecka Kucharcukova & Jan Babecky & Sona Benecka & Jan Bruha & Vilma Dingova & Jaromir Gec & Dana Hajkova & Eva Hromadkova & Lubos Komarek & Zlatuse Komarkova , 2019. "Analyses of the Czech Republic's Current Economic Alignment with the Euro Area 2019," Occasional Publications - Edited Volumes, Czech National Bank, Research and Statistics Department, number as19 edited by Katerina Arnostova & Lucie Matejkova.
    70. Su, Liangjun & Wang, Fa, 2025. "Inference for large dimensional factor models under general missing data patterns," Journal of Econometrics, Elsevier, vol. 250(C).
    71. Dai, Siqi & Hong, Yongmiao & Li, Haiqi & Zheng, Chaowen, 2025. "Shrinkage estimation of spatial panel data models with multiple structural breaks and a multifactor error structure," Journal of Econometrics, Elsevier, vol. 251(C).
    72. Maung, Kenwin & Swanson, Norman R., 2025. "A survey of models and methods used for forecasting when investing in financial markets," International Journal of Forecasting, Elsevier, vol. 41(4), pages 1355-1382.
    73. Li, Yu-Ning & Chen, Jia & Linton, Oliver, 2026. "Estimation of common factors for microstructure noise and efficient price in a high-frequency dual factor model," Journal of Econometrics, Elsevier, vol. 254(PA).
    74. Mehmet Balcilar & Riza Demirer & Festus V. Bekun, 2021. "Flexible Time-Varying Betas in a Novel Mixture Innovation Factor Model with Latent Threshold," Mathematics, MDPI, vol. 9(8), pages 1-20, April.
    75. Ma, Chenchen & Tu, Yundong, 2023. "Group fused Lasso for large factor models with multiple structural breaks," Journal of Econometrics, Elsevier, vol. 233(1), pages 132-154.
    76. He, Lingyu & Huang, Fei & Shi, Jianjie & Yang, Yanrong, 2021. "Mortality forecasting using factor models: Time-varying or time-invariant factor loadings?," Insurance: Mathematics and Economics, Elsevier, vol. 98(C), pages 14-34.
    77. Wei, Jie & Zhang, Yonghui, 2020. "A time-varying diffusion index forecasting model," Economics Letters, Elsevier, vol. 193(C).
    78. Yuying Sun & Shaoxin Hong & Zongwu Cai, 2025. "State-Varying Model Averaging Prediction," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202507, University of Kansas, Department of Economics.

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

    Cited by:

    1. Ma, Shujie & Su, Liangjun, 2018. "Estimation of large dimensional factor models with an unknown number of breaks," Journal of Econometrics, Elsevier, vol. 207(1), pages 1-29.
    2. 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. Tochukwu Timothy Okoli, 2025. "Gauging the Impact of Digital Finance on Financial Stability in the Presence of Multiple Unknown Structural Breaks: Evidence from Developing Economies," Economies, MDPI, vol. 13(7), pages 1-20, June.
    4. Jan Ditzen & Yiannis Karavias & Joakim Westerlund, 2023. "Multiple structural breaks in interactive effects panel data and the impace of quantitative easing on bank lending," Discussion Papers 23-02, Department of Economics, University of Birmingham.
    5. Jan Ditzen & Yiannis Karavias, 2025. "Interactive, Grouped and Non-separable Fixed Effects: A Practitioner's Guide to the New Panel Data Econometrics," Papers 2507.19099, arXiv.org, revised Oct 2025.
    6. Ruiqi Liu & Ben Boukai & Zuofeng Shang, 2019. "Statistical Inference on Partially Linear Panel Model under Unobserved Linearity," Papers 1911.08830, arXiv.org.
    7. Ryo Okui & Yutao Sun & Wendun Wang, 2025. "Recovering latent linkage structures and spillover effects with structural breaks in panel data models," Papers 2501.09517, arXiv.org.
    8. 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.
    9. Bin Peng & Liangjun Su & Joakim Westerlund & Yanrong Yang, 2021. "Interactive Effects Panel Data Models with General Factors and Regressors," Papers 2111.11506, arXiv.org.
    10. Wang,Dieter, 2021. "Natural Capital and Sovereign Bonds," Policy Research Working Paper Series 9606, The World Bank.
    11. Jiang, Peiyun & Kurozumi, Eiji, 2026. "A new test for common breaks in heterogeneous panel data models," Econometrics and Statistics, Elsevier, vol. 37(C), pages 87-125.
    12. 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.
    13. Fei Liu & Jiti Gao & Yanrong Yang, 2019. "Nonparametric Estimation in Panel Data Models with Heterogeneity and Time Varyingness," Monash Econometrics and Business Statistics Working Papers 24/19, Monash University, Department of Econometrics and Business Statistics.
    14. Otilia Boldea & Bettina Drepper & Zhuojiong Gan, 2020. "Change point estimation in panel data with time‐varying individual effects," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(6), pages 712-727, September.
    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. Otilia Boldea & Alastair R. Hall, 2025. "Testing for multiple change-points in macroeconometrics: an empirical guide and recent developments," Papers 2507.22204, arXiv.org.
    17. Lucas D. Konrad & Lukas Vashold & Jesus Crespo Cuaresma, 2026. "Bayesian Indicator-Saturated Regression for Climate Policy Evaluation," Papers 2603.04997, arXiv.org.
    18. 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.
    19. Cheng, Tingting & Gao, Jiti & Yan, Yayi, 2019. "Regime switching panel data models with interactive fixed effects," Economics Letters, Elsevier, vol. 177(C), pages 47-51.
    20. Okui, Ryo & Wang, Wendun, 2021. "Heterogeneous structural breaks in panel data models," Journal of Econometrics, Elsevier, vol. 220(2), pages 447-473.
    21. 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.
    22. Yufeng Mao & Bin Peng & Mervyn J Silvapulle & Param Silvapulle & Yanrong Yang, 2021. "Decomposition of Bilateral Trade Flows Using a Three-Dimensional Panel Data Model," Monash Econometrics and Business Statistics Working Papers 7/21, Monash University, Department of Econometrics and Business Statistics.
    23. Wang, Luya & Li, Kunpeng, 2025. "Spatial panel data models with structural change," Journal of Econometrics, Elsevier, vol. 251(C).
    24. Cheng, Tingting & Dong, Chaohua & Gao, Jiti & Linton, Oliver, 2024. "GMM estimation for high-dimensional panel data models," Journal of Econometrics, Elsevier, vol. 244(1).
    25. Jan Ditzen & Yiannis Karavias & Joakim Westerlund, 2025. "Multiple Structural Breaks in Interactive Effects Panel Data Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 40(1), pages 74-88, January.
    26. Yufeng Mao & Bin Peng & Mervyn Silvapulle & Param Silvapulle & Yanrong Yang, 2021. "Decomposition of Bilateral Trade Flows Using a Three-Dimensional Panel Data Model," Papers 2101.06805, arXiv.org.
    27. Georg Keilbar & Juan M. Rodriguez-Poo & Alexandra Soberon & Weining Wang, 2022. "A projection based approach for interactive fixed effects panel data models," Papers 2201.11482, arXiv.org, revised Feb 2025.
    28. 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.
    29. Agiwal Varun & Kumar Jitendra & Shangodoyin Dahud Kehinde, 2018. "A Bayesian Inference Of Multiple Structural Breaks In Mean And Error Variance In Panelar (1) Model," Statistics in Transition New Series, Statistics Poland, vol. 19(1), pages 7-23, March.
    30. Rogneda Vasilyeva & Anton Skrobotov & Aleksei Tsarev, 2025. "Structural breaks in panel data: COVID-19 pandemic in Russian regions," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 80, pages 117-142.
    31. 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.
    32. Xi Chen & Ye Luo & Martin Spindler, 2019. "Adaptive Discrete Smoothing for High-Dimensional and Nonlinear Panel Data," Papers 1912.12867, arXiv.org, revised Jan 2020.
    33. Guliyev, Hasraddin, 2025. "Heterogeneous panel data model with sharp and smooth changes: Testing green growth hypothesis in G7 countries," Innovation and Green Development, Elsevier, vol. 4(3).
    34. Costantini, Mauro & Paradiso, Antonio, 2018. "What do panel data say on inequality and GDP? New evidence at US state-level," Economics Letters, Elsevier, vol. 168(C), pages 115-117.
    35. Wang, Xia & Jin, Sainan & Li, Yingxing & Qian, Junhui & Su, Liangjun, 2025. "On time-varying panel data models with time-varying interactive fixed effects," Journal of Econometrics, Elsevier, vol. 249(PB).
    36. Horváth, Lajos & Rice, Gregory, 2019. "Asymptotics for empirical eigenvalue processes in high-dimensional linear factor models," Journal of Multivariate Analysis, Elsevier, vol. 169(C), pages 138-165.
    37. Lu, Xun & Su, Liangjun & Ba, Yinglong, 2026. "On generalized CCE estimation," Journal of Econometrics, Elsevier, vol. 253(C).
    38. Chi-Yang Chu & Chien-Ho Wang & Wan-Jiun Chen, 2025. "Does the Kyoto Protocol have a structural impact on the environmental Kuznets curve? An application of the varying coefficient model," Empirical Economics, Springer, vol. 68(2), pages 729-758, February.
    39. Yiren Wang & Peter C. B. Phillips & Liangjun Su, 2023. "Panel Data Models with Time-Varying Latent Group Structures," Cowles Foundation Discussion Papers 2364, Cowles Foundation for Research in Economics, Yale University.
    40. Miao, Ke & Li, Kunpeng & Su, Liangjun, 2020. "Panel threshold models with interactive fixed effects," Journal of Econometrics, Elsevier, vol. 219(1), pages 137-170.
    41. Yiannis Karavias & Paresh Narayan & Joakim Westerlund, 2021. "Structural Breaks in Interactive Effects Panels and the Stock Market Reaction to COVID-19," Papers 2111.03035, arXiv.org.
    42. Shahnaz Parsaeian, 2024. "Stein-like Common Correlated Effects Estimation Under Structural Breaks," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202409, University of Kansas, Department of Economics.
    43. Kaddoura, Yousef, 2025. "Estimating coefficient-by-coefficient breaks in panel data models," Journal of Econometrics, Elsevier, vol. 249(PB).
    44. Li, Degui, 2024. "Estimation of Large Dynamic Covariance Matrices: A Selective Review," Econometrics and Statistics, Elsevier, vol. 29(C), pages 16-30.
    45. Jiang, Peiyun & Kurozumi, Eiji, 2021. "A new test for common breaks in heterogeneous panel data models," Discussion paper series HIAS-E-107, Hitotsubashi Institute for Advanced Study, Hitotsubashi University.
    46. Ayden Higgins & Federico Martellosio, 2019. "Shrinkage Estimation of Network Spillovers with Factor Structured Errors," Papers 1909.02823, arXiv.org, revised Nov 2021.
    47. Abhimanyu Gupta & Myung Hwan Seo, 2025. "Optimal break tests for large linear time series models," Papers 2510.12262, arXiv.org.
    48. Bai, Jushan & Li, Kunpeng, 2021. "Dynamic spatial panel data models with common shocks," Journal of Econometrics, Elsevier, vol. 224(1), pages 134-160.
    49. Huang, Shiwei & Chen, Yu & Hu, Jie & Zhang, Weiping, 2026. "Dynamic panel data quantile regression with network-linked fixed effects," Journal of Econometrics, Elsevier, vol. 253(C).
    50. Minyoung Jo & Sangyeol Lee, 2021. "On CUSUM test for dynamic panel models," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(2), pages 515-542, June.
    51. Shahnaz Parsaeian, 2024. "Stein-like Common Correlated Effects Estimation under Structural Breaks," Econometrics, MDPI, vol. 12(2), pages 1-23, April.
    52. Qu Feng, 2019. "Common Factors and Common Breaks in Panels: An Empirical Investigation," Economic Growth Centre Working Paper Series 1905, Nanyang Technological University, School of Social Sciences, Economic Growth Centre.
    53. 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.
    54. 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.
    55. 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.
    56. Chen, Likai & Wang, Weining & Wu, Wei Biao, 2020. "Inference of breakpoints in high-dimensional time series," IRTG 1792 Discussion Papers 2020-019, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    57. 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.
    58. Guohua Feng & Jiti Gao & Bin Peng, 2019. "An Integrated Panel Data Approach to Modelling Economic Growth," Papers 1903.07948, arXiv.org.
    59. Hou, Lei & Li, Kunpeng & Li, Qi & Ouyang, Min, 2021. "Revisiting the location of FDI in China: A panel data approach with heterogeneous shocks," Journal of Econometrics, Elsevier, vol. 221(2), pages 483-509.
    60. Ali Mehrabani & Shahnaz Parsaeian, 2025. "Shrinkage Estimation and Identification of Latent Group Structures in Panel Data with Interactive Fixed Effects," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202516, University of Kansas, Department of Economics.
    61. Dai, Siqi & Hong, Yongmiao & Li, Haiqi & Zheng, Chaowen, 2025. "Shrinkage estimation of spatial panel data models with multiple structural breaks and a multifactor error structure," Journal of Econometrics, Elsevier, vol. 251(C).
    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.
    63. Harold D. Chiang & Joel Rodrigue & Yuya Sasaki, 2019. "Post-Selection Inference in Three-Dimensional Panel Data," Papers 1904.00211, arXiv.org, revised Apr 2019.
    64. Yuichi Goto & Kotone Suzuki & Xiaofei Xu & Masanobu Taniguchi, 2023. "Tests for the existence of group effects and interactions for two-way models with dependent errors," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 75(3), pages 511-532, June.
    65. Shobande, Olatunji A., 2023. "Rethinking social change: Does the permanent and transitory effects of electricity and solid fuel use predict health outcome in Africa?," Technological Forecasting and Social Change, Elsevier, vol. 186(PB).
    66. Li, Kunpeng & Cui, Guowei & Lu, Lina, 2020. "Efficient estimation of heterogeneous coefficients in panel data models with common shocks," Journal of Econometrics, Elsevier, vol. 216(2), pages 327-353.

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

    Cited by:

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

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

    Cited by:

    1. Ma, Shujie & Su, Liangjun, 2018. "Estimation of large dimensional factor models with an unknown number of breaks," Journal of Econometrics, Elsevier, vol. 207(1), pages 1-29.
    2. Jan Ditzen & Yiannis Karavias & Joakim Westerlund, 2023. "Multiple structural breaks in interactive effects panel data and the impace of quantitative easing on bank lending," Discussion Papers 23-02, Department of Economics, University of Birmingham.
    3. 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.
    4. Tatsushi Oka & Pierre Perron, 2016. "Testing for Common Breaks in a Multiple Equations System," Papers 1606.00092, arXiv.org, revised Jan 2018.
    5. Ruiqi Liu & Ben Boukai & Zuofeng Shang, 2019. "Statistical Inference on Partially Linear Panel Model under Unobserved Linearity," Papers 1911.08830, arXiv.org.
    6. Karsten Schweikert, 2022. "Detecting Multiple Structural Breaks in Systems of Linear Regression Equations with Integrated and Stationary Regressors," Papers 2201.05430, arXiv.org, revised Sep 2024.
    7. Ryo Okui & Yutao Sun & Wendun Wang, 2025. "Recovering latent linkage structures and spillover effects with structural breaks in panel data models," Papers 2501.09517, arXiv.org.
    8. 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.
    9. Jiang, Peiyun & Kurozumi, Eiji, 2026. "A new test for common breaks in heterogeneous panel data models," Econometrics and Statistics, Elsevier, vol. 37(C), pages 87-125.
    10. Chen, Yuanxing & Fang, Kuangnan & Lan, Wei & Tsai, Chih-Ling & Zhang, Qingzhao, 2025. "Community influence analysis in social networks," Computational Statistics & Data Analysis, Elsevier, vol. 202(C).
    11. Otilia Boldea & Bettina Drepper & Zhuojiong Gan, 2020. "Change point estimation in panel data with time‐varying individual effects," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(6), pages 712-727, September.
    12. Lucas D. Konrad & Lukas Vashold & Jesus Crespo Cuaresma, 2026. "Bayesian Indicator-Saturated Regression for Climate Policy Evaluation," Papers 2603.04997, arXiv.org.
    13. Martin C. Arnold & Thilo Reinschlussel, 2024. "Bootstrap Adaptive Lasso Solution Path Unit Root Tests," Papers 2409.07859, arXiv.org.
    14. Okui, Ryo & Wang, Wendun, 2021. "Heterogeneous structural breaks in panel data models," Journal of Econometrics, Elsevier, vol. 220(2), pages 447-473.
    15. Kock, Anders Bredahl, 2016. "Oracle inequalities, variable selection and uniform inference in high-dimensional correlated random effects panel data models," Journal of Econometrics, Elsevier, vol. 195(1), pages 71-85.
    16. 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.
    17. Wang, Luya & Li, Kunpeng, 2025. "Spatial panel data models with structural change," Journal of Econometrics, Elsevier, vol. 251(C).
    18. 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.
    19. Jan Ditzen & Yiannis Karavias & Joakim Westerlund, 2025. "Multiple Structural Breaks in Interactive Effects Panel Data Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 40(1), pages 74-88, January.
    20. Oualid Bada & Alois Kneip & Dominik Liebl & Tim Mensinger & James Gualtieri & Robin C. Sickles, 2021. "A Wavelet Method for Panel Models with Jump Discontinuities in the Parameters," Papers 2109.10950, arXiv.org.
    21. Georg Keilbar & Juan M. Rodriguez-Poo & Alexandra Soberon & Weining Wang, 2022. "A projection based approach for interactive fixed effects panel data models," Papers 2201.11482, arXiv.org, revised Feb 2025.
    22. Degui Li & Junhui Qian & Liangjun Su, 2016. "Panel Data Models With Interactive Fixed Effects and Multiple Structural Breaks," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(516), pages 1804-1819, October.
    23. Rogneda Vasilyeva & Anton Skrobotov & Aleksei Tsarev, 2025. "Structural breaks in panel data: COVID-19 pandemic in Russian regions," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 80, pages 117-142.
    24. Wang, Wei & Xiao, Zhijie & Ren, Yanyan & Yan, Xiaodong, 2023. "A bi-integrative analysis of two-dimensional heterogeneous panel data models," Economics Letters, Elsevier, vol. 230(C).
    25. Xi Chen & Ye Luo & Martin Spindler, 2019. "Adaptive Discrete Smoothing for High-Dimensional and Nonlinear Panel Data," Papers 1912.12867, arXiv.org, revised Jan 2020.
    26. Guliyev, Hasraddin, 2025. "Heterogeneous panel data model with sharp and smooth changes: Testing green growth hypothesis in G7 countries," Innovation and Green Development, Elsevier, vol. 4(3).
    27. Maximilian Ruecker & Michael Vogt & Oliver Linton & Christopher Walsh, 2022. "Estimation and Inference in High-Dimensional Panel Data Models with Interactive Fixed Effects," Papers 2206.12152, arXiv.org, revised Aug 2025.
    28. Wang, Xia & Jin, Sainan & Li, Yingxing & Qian, Junhui & Su, Liangjun, 2025. "On time-varying panel data models with time-varying interactive fixed effects," Journal of Econometrics, Elsevier, vol. 249(PB).
    29. Tomohiro Ando & Jushan Bai & Kunpeng Li & Yong Song, 2025. "Bayesian inference for dynamic spatial quantile models with interactive effects," Papers 2503.00772, arXiv.org, revised Jun 2025.
    30. 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.
    31. Yiren Wang & Peter C. B. Phillips & Liangjun Su, 2023. "Panel Data Models with Time-Varying Latent Group Structures," Cowles Foundation Discussion Papers 2364, Cowles Foundation for Research in Economics, Yale University.
    32. Haoran Lu & Dianpeng Wang, 2024. "Grouped Change-Points Detection and Estimation in Panel Data," Mathematics, MDPI, vol. 12(5), pages 1-20, March.
    33. Miao, Ke & Li, Kunpeng & Su, Liangjun, 2020. "Panel threshold models with interactive fixed effects," Journal of Econometrics, Elsevier, vol. 219(1), pages 137-170.
    34. Andrey G. Maksimov & Marina S. Telezhkina, 2024. "Similarity Of Structural Changes: The Case Of University Enrollment Rates," HSE Working papers WP BRP 271/EC/2024, National Research University Higher School of Economics.
    35. Hsiao, Cheng, 2018. "Panel models with interactive effects," Journal of Econometrics, Elsevier, vol. 206(2), pages 645-673.
    36. Kaddoura, Yousef, 2025. "Estimating coefficient-by-coefficient breaks in panel data models," Journal of Econometrics, Elsevier, vol. 249(PB).
    37. Weijie Cui & Yong Li, 2023. "Bicluster Analysis of Heterogeneous Panel Data via M-Estimation," Mathematics, MDPI, vol. 11(10), pages 1-19, May.
    38. Jiang, Peiyun & Kurozumi, Eiji, 2021. "A new test for common breaks in heterogeneous panel data models," Discussion paper series HIAS-E-107, Hitotsubashi Institute for Advanced Study, Hitotsubashi University.
    39. Paul Haimerl & Stephan Smeekes & Ines Wilms, 2025. "Estimation of Latent Group Structures in Time-Varying Panel Data Models," Papers 2503.23165, arXiv.org, revised Nov 2025.
    40. Xun Lu & Liangjun Su, 2025. "Two-Way Mean Group Estimators for Heterogeneous Panel Models with Fixed T," Papers 2508.10302, arXiv.org.
    41. Minyoung Jo & Sangyeol Lee, 2021. "On CUSUM test for dynamic panel models," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(2), pages 515-542, June.
    42. Mehrabani, Ali, 2023. "Estimation and identification of latent group structures in panel data," Journal of Econometrics, Elsevier, vol. 235(2), pages 1464-1482.
    43. Shahnaz Parsaeian, 2024. "Stein-like Common Correlated Effects Estimation under Structural Breaks," Econometrics, MDPI, vol. 12(2), pages 1-23, April.
    44. Su, Liangjun & Jin, Sainan & Wang, Xia, 2025. "Sieve estimation of state-varying factor models," Journal of Econometrics, Elsevier, vol. 251(C).
    45. 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.
    46. Oguzhan Akgun & Ryo Okui, 2025. "Robust Inference Methods for Latent Group Panel Models under Possible Group Non-Separation," Papers 2511.18550, arXiv.org, revised Jul 2026.
    47. Maciak, Matúš, 2021. "Quantile LASSO with changepoints in panel data models applied to option pricing," Econometrics and Statistics, Elsevier, vol. 20(C), pages 166-175.
    48. 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.
    49. Ali Mehrabani & Shahnaz Parsaeian, 2025. "Shrinkage Estimation and Identification of Latent Group Structures in Panel Data with Interactive Fixed Effects," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202516, University of Kansas, Department of Economics.
    50. Dai, Siqi & Hong, Yongmiao & Li, Haiqi & Zheng, Chaowen, 2025. "Shrinkage estimation of spatial panel data models with multiple structural breaks and a multifactor error structure," Journal of Econometrics, Elsevier, vol. 251(C).
    51. 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.
    52. Harold D. Chiang & Joel Rodrigue & Yuya Sasaki, 2019. "Post-Selection Inference in Three-Dimensional Panel Data," Papers 1904.00211, arXiv.org, revised Apr 2019.

  49. 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. Javier Alejo & Antonio F. Galvao & Julian Martinez-Iriarte & Gabriel Montes-Rojas, 2024. "Endogenous Heteroskedasticity in Linear Models," Papers 2412.02767, arXiv.org, revised Dec 2025.
    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.
    3. Linton, Oliver & Xiao, Zhijie, 2019. "Efficient estimation of nonparametric regression in the presence of dynamic heteroskedasticity," Journal of Econometrics, Elsevier, vol. 213(2), pages 608-631.

  50. 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.
  51. 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.
  52. Liangjun Su & Yundong Tu & Aman Ullah, 2015. "Testing Additive Separability of Error Term in Nonparametric Structural Models," Econometric Reviews, Taylor & Francis Journals, vol. 34(6-10), pages 1057-1088, December.

    Cited by:

    1. Yu-Chin Hsu & Ta-Cheng Huang & Haiqing Xu, 2018. "Testing for Unobserved Heterogeneous Treatment Effects with Observational Data," Papers 1803.07514, arXiv.org, revised Aug 2021.
    2. Ghanem, Dalia, 2017. "Testing identifying assumptions in nonseparable panel data models," Journal of Econometrics, Elsevier, vol. 197(2), pages 202-217.
    3. Laura Schmitz, 2022. "Heterogeneous Effects of After-School Care on Child Development," Discussion Papers of DIW Berlin 2006, DIW Berlin, German Institute for Economic Research.
    4. Hoderlein, Stefan & Su, Liangjun & White, Halbert & Yang, Thomas Tao, 2016. "Testing for monotonicity in unobservables under unconfoundedness," Journal of Econometrics, Elsevier, vol. 193(1), pages 183-202.
    5. Andrii Babii & Jean-Pierre Florens, 2017. "Are Unobservables Separable?," Papers 1705.01654, arXiv.org, revised Apr 2021.
    6. Li, Hongjun & Li, Qi & Liu, Ruixuan, 2016. "Consistent model specification tests based on k-nearest-neighbor estimation method," Journal of Econometrics, Elsevier, vol. 194(1), pages 187-202.

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

    Cited by:

    1. Cizek, P. & Jacobs, J. & Ligthart, J.E. & Vrijburg, H., 2015. "GMM Estimation of Fixed Effects Dynamic Panel Data Models with Spatial Lag and Spatial Errors (Revised version of CentER DP 2011-134)," Discussion Paper 2015-003, Tilburg University, Center for Economic Research.
    2. Liqian Cai & Arnab Bhattacharjee & Roger Calantone & Taps Maiti, 2019. "Variable Selection with Spatially Autoregressive Errors: A Generalized Moments LASSO Estimator," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 81(1), pages 146-200, September.
    3. Christopher L. Foote, 2007. "Space and time in macroeconomic panel data: young workers and state-level unemployment revisited," Working Papers 07-10, Federal Reserve Bank of Boston.
    4. Lee, Lung-fei & Yu, Jihai, 2015. "Estimation of fixed effects panel regression models with separable and nonseparable space–time filters," Journal of Econometrics, Elsevier, vol. 184(1), pages 174-192.
    5. Wei Shi & Lung-fei Lee, 2018. "The effects of gun control on crimes: a spatial interactive fixed effects approach," Empirical Economics, Springer, vol. 55(1), pages 233-263, August.
    6. LeSage, James P. & Chih, Yao-Yu & Vance, Colin, 2019. "Markov Chain Monte Carlo estimation of spatial dynamic panel models for large samples," Computational Statistics & Data Analysis, Elsevier, vol. 138(C), pages 107-125.
    7. Liang, Jinwen & Härdle, Wolfgang Karl & Tian, Maozai, 2023. "Imputed quantile tensor regression for near-sited spatial-temporal data," Computational Statistics & Data Analysis, Elsevier, vol. 182(C).
    8. Baltagi, Badi H. & Pirotte, Alain & Yang, Zhenlin, 2020. "Diagnostic Tests for Homoskedasticity in Spatial Cross-Sectional or Panel Models," IZA Discussion Papers 13803, IZA Network @ LISER.
    9. 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.
    10. Al Mamun, Md & Sohag, Kazi & Hassan, M. Kabir, 2017. "Governance, resources and growth," Economic Modelling, Elsevier, vol. 63(C), pages 238-261.
    11. Parent, Olivier & LeSage, James P., 2011. "A space-time filter for panel data models containing random effects," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 475-490, January.
    12. Cizek, P. & Jacobs, J.P.A.M. & Ligthart, J.E. & Vrijburg, H., 2011. "GMM Estimation of Fixed Effects Dynamic Panel Data Models with Spatial Lag and Spatial Errors (Replaced by CentER DP 2015-003)," Discussion Paper 2011-134, Tilburg University, Center for Economic Research.
    13. Danqing Chen & Jianbao Chen & Shuangshuang Li, 2021. "Instrumental Variable Quantile Regression of Spatial Dynamic Durbin Panel Data Model with Fixed Effects," Mathematics, MDPI, vol. 9(24), pages 1-24, December.
    14. Jin, Fei & Lee, Lung-fei & Yu, Jihai, 2020. "First difference estimation of spatial dynamic panel data models with fixed effects," Economics Letters, Elsevier, vol. 189(C).
    15. Jihai Yu & Lung-Fei Lee, 2012. "Convergence: A Spatial Dynamic Panel Data Approach," Global Journal of Economics (GJE), World Scientific Publishing Co. Pte. Ltd., vol. 1(01), pages 1-36.
    16. Francesco Giordano & Marcella Niglio & Maria Lucia Parrella, 2024. "Testing Spatial Dynamic Panel Data Models with Heterogeneous Spatial and Regression Coefficients," Journal of Time Series Analysis, Wiley Blackwell, vol. 45(5), pages 771-799, September.
    17. Parent, Olivier & LeSage, James P., 2012. "Spatial dynamic panel data models with random effects," Regional Science and Urban Economics, Elsevier, vol. 42(4), pages 727-738.
    18. Anil K. Bera & Osman Doğan & Süleyman Taşpınar & Monalisa Sen, 2020. "Specification tests for spatial panel data models," Journal of Spatial Econometrics, Springer, vol. 1(1), pages 1-39, December.
    19. Corinne Autant-Bernard, 2012. "Spatial Econometrics of Innovation: Recent Contributions and Research Perspectives," Spatial Economic Analysis, Taylor & Francis Journals, vol. 7(4), pages 403-419, December.
    20. Giulio Cainelli & Sandro Montresor & Giuseppe Vittucci Marzetti, 2014. "Spatial agglomeration and firm exit: a spatial dynamic analysis for Italian provinces," Small Business Economics, Springer, vol. 43(1), pages 213-228, June.
    21. Li, Liyao & Yang, Zhenlin, 2021. "Spatial dynamic panel data models with correlated random effects," Journal of Econometrics, Elsevier, vol. 221(2), pages 424-454.
    22. Rabovič, Renata & Čížek, Pavel, 2023. "Estimation of spatial sample selection models: A partial maximum likelihood approach," Journal of Econometrics, Elsevier, vol. 232(1), pages 214-243.
    23. Su, Liangjun & Ura, Takuya & Zhang, Yichong, 2019. "Non-separable models with high-dimensional data," Journal of Econometrics, Elsevier, vol. 212(2), pages 646-677.
    24. 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.
    25. Hans Dewachter & Romain Houssa & Priscilla Toffano, 2012. "Spatial propagation of macroeconomic shocks in Europe," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 148(2), pages 377-402, June.
    26. Lung-fei Lee & Jihai Yu, 2012. "QML Estimation of Spatial Dynamic Panel Data Models with Time Varying Spatial Weights Matrices," Spatial Economic Analysis, Taylor & Francis Journals, vol. 7(1), pages 31-74, March.
    27. Lee, Lung-fei & Yu, Jihai, 2014. "Efficient GMM estimation of spatial dynamic panel data models with fixed effects," Journal of Econometrics, Elsevier, vol. 180(2), pages 174-197.
    28. Kazuhiko Hayakawa & Vanessa Smith & M. Hashem Pesaran, 2014. "Transformed Maximum Likelihood Estimation of Short Dynamic Panel Data Models with interactive effects," Cambridge Working Papers in Economics 1412, Faculty of Economics, University of Cambridge.
    29. Qu, Xi & Lee, Lung-fei & Yu, Jihai, 2017. "QML estimation of spatial dynamic panel data models with endogenous time varying spatial weights matrices," Journal of Econometrics, Elsevier, vol. 197(2), pages 173-201.
    30. 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.
    31. Taşpınar, Süleyman & Doğan, Osman & Bera, Anil K., 2017. "GMM gradient tests for spatial dynamic panel data models," Regional Science and Urban Economics, Elsevier, vol. 65(C), pages 65-88.
    32. Bera, Anil K. & Doğan, Osman & Taşpınar, Süleyman, 2018. "Simple tests for endogeneity of spatial weights matrices," Regional Science and Urban Economics, Elsevier, vol. 69(C), pages 130-142.
    33. Olivier Parent, 2012. "A space-time analysis of knowledge production," Journal of Geographical Systems, Springer, vol. 14(1), pages 49-73, January.
    34. Feng, Xingdong & Li, Wenyu & Zhu, Qianqian, 2024. "Estimation and bootstrapping under spatiotemporal models with unobserved heterogeneity," Journal of Econometrics, Elsevier, vol. 238(1).
    35. Badi H. Baltagi & Georges Bresson & Anoop Chaturvedi & Guy Lacroix, 2023. "Robust dynamic space–time panel data models using $$\varepsilon $$ ε -contamination: an application to crop yields and climate change," Empirical Economics, Springer, vol. 64(6), pages 2475-2509, June.
    36. Yang, Zhenlin & Yu, Jihai & Liu, Shew Fan, 2016. "Bias correction and refined inferences for fixed effects spatial panel data models," Regional Science and Urban Economics, Elsevier, vol. 61(C), pages 52-72.
    37. Kelejian, Harry H. & Prucha, Ingmar R., 2010. "Specification and estimation of spatial autoregressive models with autoregressive and heteroskedastic disturbances," Journal of Econometrics, Elsevier, vol. 157(1), pages 53-67, July.
    38. Bera Anil K. & Doğan Osman & Taşpınar Süleyman, 2019. "Testing Spatial Dependence in Spatial Models with Endogenous Weights Matrices," Journal of Econometric Methods, De Gruyter, vol. 8(1), pages 1-33, January.
    39. Kuti Ayomide Oluwafunmisho & Aderogba Taiwo Adebusuyi & Ezenwa Ndubuisi Johnbosco & Quadri Rasheed Adegboyega, 2023. "Catalysts of Economic Welfare in Africa: A Cross-Sectional Autoregressive Distributed Lag Approach," Acta Universitatis Sapientiae, Economics and Business, Paradigm, vol. 11(1), pages 18-41, October.
    40. 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.
    41. Huang, Naqun & Yang, Zhenlin, 2021. "Spatial dynamic models with short panels: Evaluating the impact of purchase restrictions on housing prices," Economic Modelling, Elsevier, vol. 103(C).
    42. Miranda, Karen & Martínez Ibáñez, Oscar & Manjón Antolín, Miguel C., 2018. "A correlated random effects spatial Durbin model," Working Papers 2072/313840, Universitat Rovira i Virgili, Department of Economics.
    43. Ng, Choy Peng & Law, Teik Hua & Jakarni, Fauzan Mohd & Kulanthayan, S., 2018. "Relative improvements in road mobility as compared to improvements in road accessibility and urban growth: A panel data analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 117(C), pages 292-301.
    44. Yang, Kai & Lee, Lung-fei, 2021. "Estimation of dynamic panel spatial vector autoregression: Stability and spatial multivariate cointegration," Journal of Econometrics, Elsevier, vol. 221(2), pages 337-367.
    45. Eduardo A. Souza-Rodrigues, 2016. "Nonparametric Regression with Common Shocks," Econometrics, MDPI, vol. 4(3), pages 1-17, September.
    46. Ana Angulo & F. Trívez, 2010. "The impact of spatial elements on the forecasting of Spanish labour series," Journal of Geographical Systems, Springer, vol. 12(2), pages 155-174, June.
    47. Shi, Wei & Lee, Lung-fei, 2017. "Spatial dynamic panel data models with interactive fixed effects," Journal of Econometrics, Elsevier, vol. 197(2), pages 323-347.
    48. Badi H. Baltagi & Georges Bresson & Anoop Chaturvedi & Guy Lacroix, 2023. "Robust dynamic space-time panel data models using ε-contamination: An application to crop yields and climate change," CIRANO Working Papers 2023s-01, CIRANO.
    49. 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.
    50. Christis Katsouris, 2023. "Optimal Estimation Methodologies for Panel Data Regression Models," Papers 2311.03471, arXiv.org, revised Nov 2023.
    51. Nikodem Szumilo & Edyta Laszkiewicz & Franz Fuerst, 2017. "The spatial impact of employment centres on housing markets," Spatial Economic Analysis, Taylor & Francis Journals, vol. 12(4), pages 472-491, October.
    52. 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.
    53. Parent, Olivier & LeSage, James P., 2010. "A spatial dynamic panel model with random effects applied to commuting times," Transportation Research Part B: Methodological, Elsevier, vol. 44(5), pages 633-645, June.
    54. 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.
    55. Li, Liyao & Yang, Zhenlin, 2020. "Estimation of fixed effects spatial dynamic panel data models with small T and unknown heteroskedasticity," Regional Science and Urban Economics, Elsevier, vol. 81(C).
    56. Kwok, Hon Ho, 2019. "Identification and estimation of linear social interaction models," Journal of Econometrics, Elsevier, vol. 210(2), pages 434-458.
    57. Lee, Lung-fei & Yu, Jihai, 2010. "Some recent developments in spatial panel data models," Regional Science and Urban Economics, Elsevier, vol. 40(5), pages 255-271, September.

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

    Cited by:

    1. Yoshiyuki Kurachi & Kazuhiro Hiraki & Shinichi Nishioka, 2016. "Does a Higher Frequency of Micro-level Price Changes Matter for Macro Price Stickiness?: Assessing the Impact of Temporary Price Changes," Bank of Japan Working Paper Series 16-E-9, Bank of Japan.
    2. Otilia Boldea & Bettina Drepper & Zhuojiong Gan, 2020. "Change point estimation in panel data with time‐varying individual effects," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(6), pages 712-727, September.
    3. Dae‐yub Nam, 2025. "Human Capital and Export Performance in East Asia: Focusing on Gender Inequality," Journal of International Development, John Wiley & Sons, Ltd., vol. 37(7), pages 1490-1502, October.
    4. Laurent Callot & Johannes Tang Kristensen, 2014. "Vector Autoregressions with Parsimoniously Time Varying Parameters and an Application to Monetary Policy," CREATES Research Papers 2014-41, Department of Economics and Business Economics, Aarhus University.
    5. Boldea, Otilia & Cornea-Madeira, Adriana & Hall, Alastair R., 2019. "Bootstrapping structural change tests," Journal of Econometrics, Elsevier, vol. 213(2), pages 359-397.
    6. Maciak, Matúš, 2021. "Quantile LASSO with changepoints in panel data models applied to option pricing," Econometrics and Statistics, Elsevier, vol. 20(C), pages 166-175.
    7. Ma, Chenchen & Tu, Yundong, 2023. "Shrinkage estimation of multiple threshold factor models," Journal of Econometrics, Elsevier, vol. 235(2), pages 1876-1892.
    8. Qian, Junhui & Su, Liangjun, 2016. "Shrinkage estimation of common breaks in panel data models via adaptive group fused Lasso," Journal of Econometrics, Elsevier, vol. 191(1), pages 86-109.

  58. 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. Lenza, Michele & Moutachaker, Inès & Paredes, Joan, 2023. "Density forecasts of inflation: a quantile regression forest approach," Working Paper Series 2830, European Central Bank.
    3. Ribeiro, Pinho J., 2017. "Selecting exchange rate fundamentals by bootstrap," International Journal of Forecasting, Elsevier, vol. 33(4), pages 894-914.
    4. 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.
    5. Hillebrand, Eric & Lukas, Manuel & Wei, Wei, 2021. "Bagging weak predictors," International Journal of Forecasting, Elsevier, vol. 37(1), pages 237-254.
    6. 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.
    7. 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.
    8. Haowen Bao & Zongwu Cai & Yuying Sun & Shouyang Wang, 2023. "Penalized Optimal Forecast Combination for Quantile Regressions," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202514, University of Kansas, Department of Economics, revised May 2025.
    9. 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.
    10. 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.
    11. Giannone, Domenico & Lenza, Michele & Primiceri, Giorgio E., 2021. "Economic predictions with big data: the illusion of sparsity," Working Paper Series 2542, European Central Bank.
    12. Lu, Xun & Su, Liangjun, 2015. "Jackknife model averaging for quantile regressions," Journal of Econometrics, Elsevier, vol. 188(1), pages 40-58.
    13. 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).
    14. 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.
    15. 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.
    16. 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.

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

    Cited by:

    1. 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. Xiaojun Song & Jichao Yuan, 2026. "Testing Heteroskedasticity Under Measurement Error," Papers 2605.20012, arXiv.org.
    3. Xun Lu & Liangjun Su, 2014. "Jackknife Model Averaging for Quantile Regressions," Working Papers 11-2014, Singapore Management University, School of Economics.
    4. 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.
    5. Aman Ullah & Huansha Wang, 2013. "Parametric and Nonparametric Frequentist Model Selection and Model Averaging," Econometrics, MDPI, vol. 1(2), pages 1-23, September.
    6. Liangjun Su & Stefan Hoderlein & Halbert White, 2013. "Testing Monotonicity in Unobservables with Panel Data," Boston College Working Papers in Economics 892, Boston College Department of Economics, revised 01 Feb 2016.
    7. Yan Li & Liangjun Su & Yuewu Xu, 2014. "A Combined Approach to the Inference of Conditional Factor Models," Working Papers 10-2014, Singapore Management University, School of Economics.
    8. Hu, Yue & Li, Haiqi & Tan, Falong, 2024. "Testing the parametric form of the conditional variance in regressions based on distance covariance," Computational Statistics & Data Analysis, Elsevier, vol. 189(C).
    9. Li, Zhaoyuan & Yao, Jianfeng, 2019. "Testing for heteroscedasticity in high-dimensional regressions," Econometrics and Statistics, Elsevier, vol. 9(C), pages 122-139.
    10. 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.

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

    Cited by:

    1. Xun Lu & Su Liangjun, 2015. "Shrinkage Estimation of Dynamic Panel Data Models with Interactive Fixed Effects," Working Papers 02-2015, Singapore Management University, School of Economics.
    2. Baglan, Deniz & Ege Yazgan, M. & Yilmazkuday, Hakan, 2016. "Relative price variability and inflation: New evidence," Journal of Macroeconomics, Elsevier, vol. 48(C), pages 263-282.
    3. Jean-Baptiste Hasse & Quentin Lajaunie, 2020. "Does the Yield Curve Signal Recessions? New Evidence from an International Panel Data Analysis," AMSE Working Papers 2013, Aix-Marseille School of Economics, France.
    4. Kutlu, Levent & Sickles, Robin & Tsionas, Mike G., 2019. "Heterogeneous Decision-Making and Market Power," Working Papers 19-008, Rice University, Department of Economics.
    5. Yi Li & Xingxing Luo & Mengqi Liao, 2025. "Incorporating Prior Information in Latent Structures Identification for Panel Data Models," Mathematics, MDPI, vol. 13(9), pages 1-26, May.
    6. Hidalgo, Javier & Schafgans, Marcia, 2017. "Inference and testing breaks in large dynamic panels with strong cross sectional dependence," Journal of Econometrics, Elsevier, vol. 196(2), pages 259-274.
    7. Hansen, Christian & Liao, Yuan, 2016. "The Factor-Lasso and K-Step Bootstrap Approach for Inference in High-Dimensional Economic Applications," MPRA Paper 75313, University Library of Munich, Germany.
    8. 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.
    9. 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.
    10. Freeman, Hugo & Weidner, Martin, 2023. "Linear panel regressions with two-way unobserved heterogeneity," Journal of Econometrics, Elsevier, vol. 237(1).
    11. Gupta, Mahima & Dubey, Amlendu, 2025. "Structural characteristics and non-linear fiscal multipliers," Economic Systems, Elsevier, vol. 49(1).
    12. Ruiqi Liu & Ben Boukai & Zuofeng Shang, 2019. "Statistical Inference on Partially Linear Panel Model under Unobserved Linearity," Papers 1911.08830, arXiv.org.
    13. Su, Liangjun & Wang, Xia, 2017. "On time-varying factor models: Estimation and testing," Journal of Econometrics, Elsevier, vol. 198(1), pages 84-101.
    14. Miao, Ke & Su, Liangjun & Wang, Wendun, 2020. "Panel threshold regressions with latent group structures," Journal of Econometrics, Elsevier, vol. 214(2), pages 451-481.
    15. Juan Romero-Padilla, 2018. "A method for clustering panel data based on parameter homogeneity," Journal of Statistical and Econometric Methods, SCIENPRESS Ltd, vol. 7(3), pages 1-3.
    16. Zhongjian Lin & Zhentao Shi & Yapeng Zheng, 2026. "Social Interactions Models with Latent Structures," Papers 2602.06435, arXiv.org, revised Jul 2026.
    17. Olatunji A. Shobande & Simplice A. Asongu, 2021. "Financial Development, Human Capital Development and Climate Change in East and Southern Africa," Research Africa Network Working Papers 21/042, Research Africa Network (RAN).
    18. Bai, Jushan, 2024. "Likelihood approach to dynamic panel models with interactive effects," Journal of Econometrics, Elsevier, vol. 240(1).
    19. Kudabayeva Lyazzat & Aktolkin Abubakirova & Omarova Aizhan Igilikovna & Taskinbaikyzy Zhanargul & Saubetova Bibigul Suleimenovna, 2023. "The Relationship between Energy Consumption, Carbon Emissions and Economic Growth in ASEAN-5 Countries," International Journal of Energy Economics and Policy, International Journal of Energy Economics and Policy, vol. 13(2), pages 265-271, March.
    20. Jin, Sainan & Lu, Xun & Su, Liangjun, 2025. "Three-dimensional heterogeneous panel data models with multi-level interactive fixed effects," Journal of Econometrics, Elsevier, vol. 249(PB).
    21. 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.
    22. Okui, Ryo & Wang, Wendun, 2021. "Heterogeneous structural breaks in panel data models," Journal of Econometrics, Elsevier, vol. 220(2), pages 447-473.
    23. Mohitosh Kejriwal & Haiqing Zhao, 2019. "Revisiting the Democracy-Growth Nexus:New Evidence from a Dynamic Common Correlated Effects Approach," Purdue University Economics Working Papers 1317, Purdue University, Department of Economics.
    24. Ali Mehrabani & Aman Ullah, 2020. "Improved Average Estimation in Seemingly Unrelated Regressions," Econometrics, MDPI, vol. 8(2), pages 1-22, April.
    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. 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.
    27. Ando, Tomohiro & Bai, Jushan, 2014. "A simple new test for slope homogeneity in panel data models with interactive effects," MPRA Paper 60795, University Library of Munich, Germany.
    28. Marina Khismatullina & Bernhard van der Sluis, 2025. "Multiscale Comparison of Nonparametric Trending Coefficients," Papers 2511.12600, arXiv.org.
    29. Liangjun Su & Zhentao Shi & Peter C. B. Phillips, 2014. "Identifying Latent Structures in Panel Data," Working Papers 07-2014, Singapore Management University, School of Economics.
    30. Su, Liangjun & Ura, Takuya & Zhang, Yichong, 2019. "Non-separable models with high-dimensional data," Journal of Econometrics, Elsevier, vol. 212(2), pages 646-677.
    31. Mohitosh Kejriwal & Xiaoxiao Li & Evan Totty, 2020. "Multidimensional skills and the returns to schooling: Evidence from an interactive fixed‐effects approach and a linked survey‐administrative data set," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(5), pages 548-566, August.
    32. Ivan Fernandez-Val & Martin Weidner, 2014. "Individual and time effects in nonlinear panel models with large N , T," CeMMAP working papers 32/14, Institute for Fiscal Studies.
    33. Mohitosh Kejriwal & Xiaoxiao Li & Evan Totty, 2019. "Multidemsional Skills and Returns to Schooling: Evidence from an Interactive Fixed Effects Aproach and a Linked Survey-Administrative Dataset," Purdue University Economics Working Papers 1316, Purdue University, Department of Economics.
    34. Yang, Qing & Zhang, Yi, 2022. "Change-point detection for the link function in a single-index model," Statistics & Probability Letters, Elsevier, vol. 186(C).
    35. Yiren Wang & Liangjun Su & Yichong Zhang, 2022. "Low-rank Panel Quantile Regression: Estimation and Inference," Papers 2210.11062, arXiv.org.
    36. Halunga, Andreea G. & Orme, Chris D. & Yamagata, Takashi, 2017. "A heteroskedasticity robust Breusch–Pagan test for Contemporaneous correlation in dynamic panel data models," Journal of Econometrics, Elsevier, vol. 198(2), pages 209-230.
    37. 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.
    38. Likai Chen & Georg Keilbar & Liangjun Su & Weining Wang, 2023. "High-dimensional inference on jumps in nonparametric time series regression models," Papers 2312.01162, arXiv.org, revised Jul 2026.
    39. Hidalgo, Javier & Schafgans, Marcia, 2017. "Inference and testing breaks in large dynamic panels with strong cross sectional dependence," LSE Research Online Documents on Economics 68839, London School of Economics and Political Science, LSE Library.
    40. Wang, Xia & Jin, Sainan & Li, Yingxing & Qian, Junhui & Su, Liangjun, 2025. "On time-varying panel data models with time-varying interactive fixed effects," Journal of Econometrics, Elsevier, vol. 249(PB).
    41. Yunus Emre Ergemen & Carlos Velasco, 2018. "Persistence Heterogeneity Testing in Panels with Interactive Fixed Effects," CREATES Research Papers 2018-11, Department of Economics and Business Economics, Aarhus University.
    42. 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.
    43. Lu, Xun & Su, Liangjun & Ba, Yinglong, 2026. "On generalized CCE estimation," Journal of Econometrics, Elsevier, vol. 253(C).
    44. Yiren Wang & Peter C. B. Phillips & Liangjun Su, 2023. "Panel Data Models with Time-Varying Latent Group Structures," Cowles Foundation Discussion Papers 2364, Cowles Foundation for Research in Economics, Yale University.
    45. Levent Kutlu & Robin C. Sickles & Mike G. Tsionas & Emmanuel Mamatzakis, 2022. "Heterogeneous decision-making and market power: an application to Eurozone banks," Empirical Economics, Springer, vol. 63(6), pages 3061-3092, December.
    46. Miao, Ke & Li, Kunpeng & Su, Liangjun, 2020. "Panel threshold models with interactive fixed effects," Journal of Econometrics, Elsevier, vol. 219(1), pages 137-170.
    47. Feng Xu & Zekai He, 2020. "Testing slope homogeneity in panel data models with a multifactor error structure," Statistical Papers, Springer, vol. 61(1), pages 201-224, February.
    48. Saptorshee Kanto Chakraborty & Massimiliano Mazzanti, 2021. "Revisiting the literature on the dynamic Environmental Kuznets Curves using a latent structure approach," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 38(3), pages 923-941, October.
    49. Xun Lu & Liangjun Su, 2025. "Two-Way Mean Group Estimators for Heterogeneous Panel Models with Fixed T," Papers 2508.10302, arXiv.org.
    50. Mehrabani, Ali, 2023. "Estimation and identification of latent group structures in panel data," Journal of Econometrics, Elsevier, vol. 235(2), pages 1464-1482.
    51. Su, Liangjun & Jin, Sainan & Wang, Xia, 2025. "Sieve estimation of state-varying factor models," Journal of Econometrics, Elsevier, vol. 251(C).
    52. Daniel Borup & Bent Jesper Christensen & Yunus Emre Ergemen, 2019. "Assessing predictive accuracy in panel data models with long-range dependence," CREATES Research Papers 2019-04, Department of Economics and Business Economics, Aarhus University.
    53. 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.
    54. Gao, Jiti & Liu, Fei & Peng, Bin & Yan, Yayi, 2023. "Binary response models for heterogeneous panel data with interactive fixed effects," Journal of Econometrics, Elsevier, vol. 235(2), pages 1654-1679.
    55. Wang, Wuyi & Su, Liangjun, 2021. "Identifying latent group structures in nonlinear panels," Journal of Econometrics, Elsevier, vol. 220(2), pages 272-295.
    56. 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.
    57. 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.
    58. Kazuhiko Hayakawa & Shuichi Nagata & Takashi Yamagata, 2018. "A robust approach to heteroskedasticity, error serial correlation and slope heterogeneity for large linear panel data models with interactive effects," ISER Discussion Paper 1037, Institute of Social and Economic Research, The University of Osaka.
    59. Millimet, Daniel L. & Bellemare, Marc, 2023. "Fixed Effects and Causal Inference," IZA Discussion Papers 16202, IZA Network @ LISER.
    60. Antonio Raiola & Nazarii Salish, 2025. "Detection Boundaries for Panel Slope Homogeneity Tests Under Small-Group Heterogeneity," Papers 2510.22841, arXiv.org, revised Apr 2026.
    61. 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.
    62. Christis Katsouris, 2023. "Optimal Estimation Methodologies for Panel Data Regression Models," Papers 2311.03471, arXiv.org, revised Nov 2023.
    63. 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.
    64. 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.
    65. Ali Mehrabani & Shahnaz Parsaeian, 2025. "Shrinkage Estimation and Identification of Latent Group Structures in Panel Data with Interactive Fixed Effects," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202516, University of Kansas, Department of Economics.

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

    Cited by:

    1. 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. Hoshino, Tadao, 2022. "Sieve IV estimation of cross-sectional interaction models with nonparametric endogenous effect," Journal of Econometrics, Elsevier, vol. 229(2), pages 263-275.
    3. Rodriguez-Poo, Juan M. & Soberón, Alexandra, 2015. "Nonparametric estimation of fixed effects panel data varying coefficient models," Journal of Multivariate Analysis, Elsevier, vol. 133(C), pages 95-122.
    4. Korolev Ivan, 2026. "A Consistent LM-Type Specification Test for Semiparametric Panel Data Models," Journal of Econometric Methods, De Gruyter, vol. 15(1), pages 19-45.
    5. Christopher F. Parmeter & Jeffrey S. Racine, 2018. "Nonparametric Estimation and Inference for Panel Data Models," Department of Economics Working Papers 2018-02, McMaster University.
    6. Li, Cong & Liang, Zhongwen, 2015. "Asymptotics for nonparametric and semiparametric fixed effects panel models," Journal of Econometrics, Elsevier, vol. 185(2), pages 420-434.
    7. Taining Wang & Feng Yao & Jun Cai, 2026. "Nonparametric Estimation of Smooth Coefficients in Fixed-Effect Panel Data Models," Working Papers 26-03, Department of Economics, West Virginia University.
    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.
    9. Green, Carl & Long, Wei & Hsiao, Cheng, 2015. "Testing error serial correlation in fixed effects nonparametric panel data models," Journal of Econometrics, Elsevier, vol. 188(2), pages 466-473.
    10. Juan Rodriguez-Poo & Alexandra Soberón, 2015. "Differencing techniques in semi-parametric panel data varying coefficient models with fixed effects: a Monte Carlo study," Computational Statistics, Springer, vol. 30(3), pages 885-906, September.
    11. Chu, Chi-Yang & Henderson, Daniel J. & Parmeter, Christopher F., 2017. "On discrete Epanechnikov kernel functions," Computational Statistics & Data Analysis, Elsevier, vol. 116(C), pages 79-105.
    12. Wei, Honglei & Zhang, Hongfan & Jiang, Hui & Huang, Lei, 2022. "On the semi-varying coefficient dynamic panel data model with autocorrelated errors," Computational Statistics & Data Analysis, Elsevier, vol. 173(C).
    13. Yashar Tarverdi, 2018. "Aspects of Governance and $$\hbox {CO}_2$$ CO 2 Emissions: A Non-linear Panel Data Analysis," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 69(1), pages 167-194, January.
    14. Christis Katsouris, 2023. "Optimal Estimation Methodologies for Panel Data Regression Models," Papers 2311.03471, arXiv.org, revised Nov 2023.
    15. Li, Hongjun & Li, Qi & Liu, Ruixuan, 2016. "Consistent model specification tests based on k-nearest-neighbor estimation method," Journal of Econometrics, Elsevier, vol. 194(1), pages 187-202.

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

    Cited by:

    1. Spindler, Martin & Winter, Joachim & Hagmayer, Steffen, 2012. "Asymmetric Information in the Market for Automobile Insurance: Evidence from Germany," MEA discussion paper series 201208, Munich Center for the Economics of Aging (MEA) at the Max Planck Institute for Social Law and Social Policy.
    2. Hao Zheng & Yi Yao & Yinglu Deng & Feng Gao, 2022. "Information asymmetry, ex ante moral hazard, and uninsurable risk in liability coverage: Evidence from China's automobile insurance market," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 89(1), pages 131-160, March.
    3. Arnold Polanski & Evarist Stoja, 2015. "Extreme risk interdependence," Bank of England Staff Working Paper series 563, Bank of England.
    4. Xiaoqi Zhang & Yi Chen & Yi Yao, 2021. "Dynamic information asymmetry in micro health insurance: implications for sustainability," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 46(3), pages 468-507, July.
    5. Spindler, Martin, 2013. "“They do know what they are doing... at least most of them.†Asymmetric Information in the (private) Disability Insurance," MEA discussion paper series 201209, Munich Center for the Economics of Aging (MEA) at the Max Planck Institute for Social Law and Social Policy.
    6. David Rowell & Son Nghiem & Luke B Connelly, 2017. "Two Tests for Ex Ante Moral Hazard in a Market for Automobile Insurance," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 84(4), pages 1103-1126, December.
    7. Alois S. Mlambo, 2017. "From an Industrial Powerhouse to a Nation of Vendors: Over Two Decades of Economic Decline and Deindustrialization in Zimbabwe 1990–2015," Journal of Developing Societies, , vol. 33(1), pages 99-125, March.
    8. Polanski, Arnold & Stoja, Evarist, 2017. "Forecasting multidimensional tail risk at short and long horizons," International Journal of Forecasting, Elsevier, vol. 33(4), pages 958-969.
    9. Polanski, Arnold & Stoja, Evarist, 2016. "Extreme risk interdependence," ESRB Working Paper Series 12, European Systemic Risk Board.
    10. Arnold Polanski & Evarist Stoja, 2017. "Forecasting multidimensional tail risk at short and long horizons," Bank of England Staff Working Paper series 660, Bank of England.
    11. Helmi Jedidi & Georges Dionne, 2024. "Nonparametric testing for information asymmetry in the mortgage servicing market," Working Papers 19-1, HEC Montreal, Canada Research Chair in Risk Management.
    12. Karl Ove Aarbu, 2017. "Asymmetric Information in the Home Insurance Market," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 84(1), pages 35-72, March.
    13. Georges Dionne, 2012. "The Empirical Measure of Information Problems with Emphasis on Insurance Fraud and Dynamic Data," Cahiers de recherche 1233, CIRPEE.
    14. Arnold Polanski & Evarist Stoja & Ching-Wai (Jeremy) Chiu, 2019. "Tail risk interdependence," Bank of England Staff Working Paper series 815, Bank of England.
    15. Choi Yun Jeong & Chen Joe & Sawada Yasuyuki, 2015. "Life Insurance and Suicide: Asymmetric Information Revisited," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 15(3), pages 1127-1149, July.
    16. Su, Liangjun & White, Halbert, 2014. "Testing conditional independence via empirical likelihood," Journal of Econometrics, Elsevier, vol. 182(1), pages 27-44.
    17. Georges Dionnne & Pierre-Carl Michaud & Jean Pinquet, 2012. "A Review of Recent Theoretical and Empirical Analyses of Asymmetric Information in Road Safety and Automobile Insurance," Cahiers de recherche 1204, CIRPEE.
    18. Spindler, M., 2014. "“They do know what they are doing ... at least most of them.†Asymmetric Information in the (private) Disability Insurance," Health, Econometrics and Data Group (HEDG) Working Papers 14/16, HEDG, c/o Department of Economics, University of York.
    19. Arnold Polanski & Evarist Stoja & Ching‐Wai (Jeremy) Chiu, 2021. "Tail risk interdependence," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(4), pages 5499-5511, October.
    20. Jian Yan & Zhuoxi Li & Xianyang Zhang, 2022. "Distance and Kernel-Based Measures for Global and Local Two-Sample Conditional Distribution Testing," Papers 2210.08149, arXiv.org, revised Aug 2025.
    21. Feng Gao & Michael R. Powers & Jun Wang, 2017. "Decomposing Asymmetric Information in China's Automobile Insurance Market," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 84(4), pages 1269-1293, December.

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

    Cited by:

    1. Aman Ullah & Tao Wang & Weixin Yao, 2021. "Modal regression for fixed effects panel data," Empirical Economics, Springer, vol. 60(1), pages 261-308, January.
    2. 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.
    3. Artem Prokhorov & Kien C. Tran & Mike G. Tsionas, 2021. "Estimation of semi- and nonparametric stochastic frontier models with endogenous regressors," Empirical Economics, Springer, vol. 60(6), pages 3043-3068, June.
    4. Shujie Ma & Jeffrey S. Racine & Aman Ullah, 2015. "Nonparametric Regression-Spline Random Effects Models," Department of Economics Working Papers 2015-10, McMaster University.
    5. Syed F. Mahmud & Murat Tiniç, 2018. "Herding in Chinese stock markets: a nonparametric approach," Empirical Economics, Springer, vol. 55(2), pages 679-711, September.
    6. Huang, Bai & Lee, Tae-Hwy & Ullah, Aman, 2020. "Combined estimation of semiparametric panel data models," Econometrics and Statistics, Elsevier, vol. 15(C), pages 30-45.

  66. 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. 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.
    4. 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.
    5. 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.
    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. 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.
    10. 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.
    11. 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.

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

    Cited by:

    1. Tae-Hwy Lee & Shahnaz Parsaeian & Aman Ullah, 2022. "Forecasting under Structural Breaks Using Improved Weighted Estimation," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202212, University of Kansas, Department of Economics.
    2. Cai, Zongwu & Fang, Ying & Lin, Ming & Su, Jia, 2018. "Inferences for a Partially Varying Coefficient Model With Endogenous Regressors," IRTG 1792 Discussion Papers 2018-047, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    3. Feng Yao & Junsen Zhang, 2015. "Efficient kernel-based semiparametric IV estimation with an application to resolving a puzzle on the estimates of the return to schooling," Empirical Economics, Springer, vol. 48(1), pages 253-281, February.
    4. Yan Li & Liangjun Su & Yuewu Xu, 2015. "A Combined Approach to the Inference of Conditional Factor Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(2), pages 203-220, April.
    5. Shengjie Hong & Yu-Chin Hsu & Yuanyuan Wan, 2023. "Subvector inference for Varying Coefficient Models with Partial Identification," Working Papers tecipa-756, University of Toronto, Department of Economics.
    6. Ullah, Aman & Wang, Tao & Yao, Weixin, 2023. "Semiparametric partially linear varying coefficient modal regression," Journal of Econometrics, Elsevier, vol. 235(2), pages 1001-1026.
    7. Stefan Sperlich, 2014. "On the choice of regularization parameters in specification testing: a critical discussion," Empirical Economics, Springer, vol. 47(2), pages 427-450, September.
    8. Susan Athey & Julie Tibshirani & Stefan Wager, 2016. "Generalized Random Forests," Papers 1610.01271, arXiv.org, revised Apr 2018.
    9. Xun Lu & Liangjun Su, 2014. "Jackknife Model Averaging for Quantile Regressions," Working Papers 11-2014, Singapore Management University, School of Economics.
    10. Zhang, Hong-Fan, 2021. "Iterative GMM for partially linear single-index models with partly endogenous regressors," Computational Statistics & Data Analysis, Elsevier, vol. 156(C).
    11. S. Centorrino & J. S. Racine, 2016. "Semiparametric Varying Coefficient Models with Endogenous Covariates," Department of Economics Working Papers 2016-02, McMaster University.
    12. Tadao Hoshino, 2018. "Semiparametric Spatial Autoregressive Models With Endogenous Regressors: With an Application to Crime Data," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 36(1), pages 160-172, January.
    13. Su, Liangjun & Hoshino, Tadao, 2016. "Sieve instrumental variable quantile regression estimation of functional coefficient models," Journal of Econometrics, Elsevier, vol. 191(1), pages 231-254.
    14. Pan Zhao & Yifan Cui, 2023. "A Semiparametric Instrumented Difference-in-Differences Approach to Policy Learning," Papers 2310.09545, arXiv.org.
    15. Koo, Chao, 2018. "Essays on functional coefficient models," Other publications TiSEM ba87b8a5-3c55-40ec-967d-9, Tilburg University, School of Economics and Management.
    16. Irina Murtazashvili & Di Liu & Artem Prokhorov, 2015. "Two‐sample nonparametric estimation of intergenerational income mobility in the United States and Sweden," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 48(5), pages 1733-1761, December.
    17. Huang, Bai & Lee, Tae-Hwy & Ullah, Aman, 2020. "Combined estimation of semiparametric panel data models," Econometrics and Statistics, Elsevier, vol. 15(C), pages 30-45.

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

    Cited by:

    1. Jianbao Chen & Suli Cheng, 2021. "GMM Estimation of a Partially Linear Additive Spatial Error Model," Mathematics, MDPI, vol. 9(6), pages 1-28, March.
    2. 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.
    3. Xuan Chen & Yunquan Song, 2025. "Transfer learning for semiparametric varying coefficient spatial autoregressive models," Statistical Papers, Springer, vol. 66(2), pages 1-22, February.
    4. 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.
    5. Luo, Guowang & Wu, Mixia & Pang, Zhen, 2022. "Estimation of spatial autoregressive models with covariate measurement errors," Journal of Multivariate Analysis, Elsevier, vol. 192(C).
    6. Abhimanyu Gupta & Xi Qu & Sorawoot Srisuma & Jiajun Zhang, 2025. "Wald inference on varying coefficients," Papers 2502.03084, arXiv.org, revised Jan 2026.
    7. 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.
    8. Zhang Yuanqing, 2014. "Estimation of Partially Specified Spatial Autoregressive Model," Journal of Systems Science and Information, De Gruyter, vol. 2(3), pages 226-235, June.
    9. Malikov, Emir & Sun, Yiguo, 2017. "Semiparametric Estimation and Testing of Smooth Coefficient Spatial Autoregressive Models," MPRA Paper 77253, University Library of Munich, Germany.
    10. 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.
    11. Kien C. Tran & Mike G. Tsionas, 2023. "Semiparametric estimation of a spatial autoregressive nonparametric stochastic frontier model," Journal of Spatial Econometrics, Springer, vol. 4(1), pages 1-28, December.
    12. Hou, Zhezhi & Zhao, Shunan & Kumbhakar, Subal C., 2023. "The GMM estimation of semiparametric spatial stochastic frontier models," European Journal of Operational Research, Elsevier, vol. 305(3), pages 1450-1464.
    13. 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.
    14. Sun, Yan, 2017. "Estimation of single-index model with spatial interaction," Regional Science and Urban Economics, Elsevier, vol. 62(C), pages 36-45.
    15. Yan-Yong Zhao & Ling-Ling Ge & Yuan Liu, 2025. "Estimation of panel data partially linear time-varying coefficient models with cross-sectional spatial autoregressive errors," Statistical Papers, Springer, vol. 66(1), pages 1-37, January.
    16. Gao, Zhaoxing & Ma, Yingying & Wang, Hansheng & Yao, Qiwei, 2019. "Banded spatio-temporal autoregressions," Journal of Econometrics, Elsevier, vol. 208(1), pages 211-230.
    17. Fang Lu & Guoliang Tian & Jing Yang, 2024. "GMM estimation and variable selection of partially linear additive spatial autoregressive model," Statistical Papers, Springer, vol. 65(4), pages 2253-2288, June.
    18. Mustafa Koroglu & Yiguo Sun, 2016. "Functional-Coefficient Spatial Durbin Models with Nonparametric Spatial Weights: An Application to Economic Growth," Econometrics, MDPI, vol. 4(1), pages 1-16, February.
    19. 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.
    20. DUo Qin & Yimeng Liu, 2013. "Modelling Scale Effect in Crosssection Data:The Case of Hedonic Price Regression," Working Papers 184, Department of Economics, SOAS University of London, UK.
    21. Bing Su & Fukang Zhu & Ke Zhu, 2023. "Statistical inference for the logarithmic spatial heteroskedasticity model with exogenous variables," Papers 2301.06658, arXiv.org.
    22. 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.
    23. 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.
    24. Yangbing Tang & Zhongzhan Zhang & Jiang Du, 2024. "Rank-based instrumental variable estimation for semiparametric varying coefficient spatial autoregressive models," Statistical Papers, Springer, vol. 65(3), pages 1805-1839, May.
    25. Tizheng Li & Yuping Wang, 2024. "Higher-order spatial autoregressive varying coefficient model: estimation and specification test," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 33(4), pages 1258-1299, December.
    26. Li, Shuangshuang & Chen, Jianbao, 2026. "Estimation and testing for fixed effects partially linear nonparametric panel regression model with separable spatially and serially correlated error structure," Journal of Multivariate Analysis, Elsevier, vol. 212(C).
    27. 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.
    28. 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.
    29. Xuan Liang & Jiti Gao & Xiaodong Gong, 2021. "Semiparametric Spatial Autoregressive Panel Data Model with Fixed Effects and Time-Varying Coefficients," Monash Econometrics and Business Statistics Working Papers 5/21, Monash University, Department of Econometrics and Business Statistics.
    30. Alex Hayes & Keith Levin, 2026. "Estimating peer effects in noisy, low-rank networks via network smoothing," Papers 2605.03204, arXiv.org.
    31. 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.
    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. Alberto Gude & Inmaculada Álvarez & Luis Orea, 2018. "Heterogeneous spillovers among Spanish provinces: a generalized spatial stochastic frontier model," Journal of Productivity Analysis, Springer, vol. 50(3), pages 155-173, December.
    34. Hong, Han & Ju, Gaosheng & Li, Qi & Yan, Karen X., 2024. "Varying-coefficient spatial dynamic panel data models with fixed effects: Theory and application," Journal of Econometrics, Elsevier, vol. 245(1).
    35. 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.
    36. 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.
    37. Lu, Fang & Pan, Hao & Yang, Jing, 2025. "GMM estimation and variable selection of semiparametric model with increasing dimension and high-order spatial dependence," Computational Statistics & Data Analysis, Elsevier, vol. 205(C).
    38. 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.
    39. 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.
    40. 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.
    41. 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.
    42. Sun, Yiguo, 2016. "Functional-coefficient spatial autoregressive models with nonparametric spatial weights," Journal of Econometrics, Elsevier, vol. 195(1), pages 134-153.
    43. Huang, Danyang & Wang, Feifei & Zhu, Xuening & Wang, Hansheng, 2020. "Two-mode network autoregressive model for large-scale networks," Journal of Econometrics, Elsevier, vol. 216(1), pages 203-219.
    44. Jing Yang & Yujiang Xiao & Fang Lu, 2025. "Model detection and variable selection for semiparametric additive spatial autoregressive model," Statistical Papers, Springer, vol. 66(4), pages 1-29, June.
    45. Kunming Li & Liting Fang & Tao Lu, 2019. "Bayesian panel smooth transition model with spatial correlation," PLOS ONE, Public Library of Science, vol. 14(3), pages 1-12, March.
    46. 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.
    47. Chen, Jianbao & Li, Fen, 2025. "Penalized quadratic inference functions estimation of fixed effects partially linear varying coefficient spatial error model," Economic Modelling, Elsevier, vol. 146(C).
    48. Mu Yue & Jingxin Xi, 2025. "Sparse Boosting for Additive Spatial Autoregressive Model with High Dimensionality," Mathematics, MDPI, vol. 13(5), pages 1-16, February.
    49. Cheng, Suli & Chen, Jianbao, 2023. "GMM estimation of partially linear additive spatial autoregressive model," Computational Statistics & Data Analysis, Elsevier, vol. 182(C).
    50. Suli Cheng & Jianbao Chen, 2021. "Estimation of partially linear single-index spatial autoregressive model," Statistical Papers, Springer, vol. 62(1), pages 495-531, February.
    51. Tiziano Arduini & Eleonora Patacchini & Edoardo Rainone, 2015. "Parametric and Semiparametric IV Estimation of Network Models with Selectivity," EIEF Working Papers Series 1509, Einaudi Institute for Economics and Finance (EIEF), revised Oct 2015.
    52. 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.
    53. 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).
    54. 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.
    55. 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.
    56. 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.
    57. Kwok, Hon Ho, 2019. "Identification and estimation of linear social interaction models," Journal of Econometrics, Elsevier, vol. 210(2), pages 434-458.

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

    Cited by:

    1. Dong, Chaohua & Linton, Oliver, 2018. "Additive nonparametric models with time variable and both stationary and nonstationary regressors," Journal of Econometrics, Elsevier, vol. 207(1), pages 212-236.
    2. Antonio Musolesi & Giada Andrea Prete & Michel Simioni, 2025. "Is infrastructure capital really productive? Nonparametric modeling and data-driven model selection in a cross-sectionally dependent panel framework," Journal of Productivity Analysis, Springer, vol. 64(3), pages 439-455, December.
    3. 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.
    4. Jia Chen & Jiti Gao & Degui Li, 2011. "Semiparametric Trending Panel Data Models with Cross-Sectional Dependence," Monash Econometrics and Business Statistics Working Papers 15/11, Monash University, Department of Econometrics and Business Statistics.
    5. 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.
    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.
    7. 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.
    8. Jiti Gao & Oliver Linton & Bin Peng, 2017. "Inference on a Semiparametric Model with Global Power Law and Local Nonparametric Trends," Monash Econometrics and Business Statistics Working Papers 10/17, Monash University, Department of Econometrics and Business Statistics.
    9. Ruiqi Liu & Ben Boukai & Zuofeng Shang, 2019. "Statistical Inference on Partially Linear Panel Model under Unobserved Linearity," Papers 1911.08830, arXiv.org.
    10. Miao, Ke & Su, Liangjun & Wang, Wendun, 2020. "Panel threshold regressions with latent group structures," Journal of Econometrics, Elsevier, vol. 214(2), pages 451-481.
    11. 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.
    12. 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.
    13. Chaohua Dong & Jiti Gao & Bin Peng, 2016. "Another Look at Single-Index Models Based on Series Estimation," Monash Econometrics and Business Statistics Working Papers 19/16, Monash University, Department of Econometrics and Business Statistics.
    14. 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.
    15. 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.
    16. 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.
    17. Su, Liangjun & Ju, Gaosheng, 2018. "Identifying latent grouped patterns in panel data models with interactive fixed effects," Journal of Econometrics, Elsevier, vol. 206(2), pages 554-573.
    18. Georgios Gioldasis & Antonio Musolesi & Michel Simioni, 2019. "Nonparametric estimation of R&D international spillovers," Post-Print hal-02789474, HAL.
    19. Christis Katsouris, 2023. "High Dimensional Time Series Regression Models: Applications to Statistical Learning Methods," Papers 2308.16192, arXiv.org.
    20. Guohua Feng & Jiti Gao & Bin Peng, 2019. "An Integrated Panel Data Approach to Modelling Economic Growth," Monash Econometrics and Business Statistics Working Papers 6/19, Monash University, Department of Econometrics and Business Statistics.
    21. Antonio Musolesi & Mario Nosvelli, 2025. "Technology, labour regulation, and nonparametric panel data modelling," Empirical Economics, Springer, vol. 68(4), pages 1799-1828, April.
    22. Dong, Chaohua & Gao, Jiti & Peng, Bin, 2015. "Semiparametric single-index panel data models with cross-sectional dependence," Journal of Econometrics, Elsevier, vol. 188(1), pages 301-312.
    23. Artūras Juodis, 2022. "A regularization approach to common correlated effects estimation," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(4), pages 788-810, June.
    24. Antonio Musolesi & Michel Simioni & Georgios Gioldasis, 2018. "Nonparametric estimation of international R&D spillovers," Working Papers 2018037, University of Ferrara, Department of Economics.
    25. 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.
    26. 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.
    27. 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.
    28. 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.
    29. 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.
    30. Juodis, Artūras & Reese, Simon, 2026. "Five lessons for applied researchers from twenty years of common correlated effects estimation," Journal of Econometrics, Elsevier, vol. 253(C).
    31. Guohua Feng & Jiti Gao & Bin Peng & Xiaohui Zhang, 2015. "A Varying-Coefficient Panel Data Model with Fixed Effects: Theory and an Application to U.S. Commercial Banks," Monash Econometrics and Business Statistics Working Papers 9/15, Monash University, Department of Econometrics and Business Statistics.
    32. 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.
    33. Xiao Huang, 2013. "Nonparametric Estimation in Large Panels with Cross-Sectional Dependence," Econometric Reviews, Taylor & Francis Journals, vol. 32(5-6), pages 754-777, August.
    34. Isabel Casas & Jiti Gao & Bin Peng & Shangyu Xie, 2021. "Time‐varying income elasticities of healthcare expenditure for the OECD and Eurozone," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(3), pages 328-345, April.
    35. Lin, Yingqian & Tu, Yundong, 2024. "Functional coefficient cointegration models with Box–Cox transformation," Economics Letters, Elsevier, vol. 234(C).
    36. 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.
    37. Alexandra Soberon & Antonio Musolesi & Juan M. Rodriguez‐Poo, 2024. "A Semi‐parametric Panel Data Model with Common Factors and Spatial Dependence," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 86(4), pages 905-927, August.
    38. 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.
    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. 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.
    42. De Vos, Ignace & Everaert, Gerdie & Sarafidis, Vasilis, 2021. "A method for evaluating the rank condition for CCE estimators," MPRA Paper 112305, University Library of Munich, Germany, revised 09 Mar 2022.
    43. Yang, Zixin & Song, Xiaojun & Yu, Jihai, 2025. "Estimation of spatial autoregressive panel data models with nonparametric endogenous effect," Journal of Econometrics, Elsevier, vol. 252(PA).
    44. 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.
    45. Soberon, Alexandra & Mazzanti, Massimiliano & Musolesi, Antonio & Rodriguez-Poo, Juan M., 2025. "Efficient estimation of a partially linear panel data model with cross-sectional dependence," Journal of Multivariate Analysis, Elsevier, vol. 206(C).
    46. 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.
    47. 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.
    48. Paul Haimerl & Stephan Smeekes & Ines Wilms, 2025. "Estimation of Latent Group Structures in Time-Varying Panel Data Models," Papers 2503.23165, arXiv.org, revised Nov 2025.
    49. 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.
    50. Zhao Wang & Yuanlu Suo & Taining Wang & Subal C. Kumbhakar, 2025. "Are operationally efficient firms greener?," Empirical Economics, Springer, vol. 69(5), pages 2627-2669, November.
    51. Christina Maschmann & Joakim Westerlund, 2025. "Estimation of Panel Data Models with Nonlinear Factor Structure," Papers 2512.03693, arXiv.org, revised May 2026.
    52. 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.
    53. Eduardo A. Souza-Rodrigues, 2016. "Nonparametric Regression with Common Shocks," Econometrics, MDPI, vol. 4(3), pages 1-17, September.
    54. Zhezhi Hou & Shunan Zhao & Subal C. Kumbhakar, 2025. "Revisiting the Productivity Effects of Public Capital," Empirical Economics, Springer, vol. 68(3), pages 1233-1264, March.
    55. 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.
    56. 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.
    57. Guohua Feng & Jiti Gao & Bin Peng, 2019. "An Integrated Panel Data Approach to Modelling Economic Growth," Papers 1903.07948, arXiv.org.
    58. 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.
    59. 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.
    60. Ali Mehrabani & Shahnaz Parsaeian, 2025. "Shrinkage Estimation and Identification of Latent Group Structures in Panel Data with Interactive Fixed Effects," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202516, University of Kansas, Department of Economics.
    61. Jiang, Bin & Yang, Yanrong & Gao, Jiti & Hsiao, Cheng, 2021. "Recursive estimation in large panel data models: Theory and practice," Journal of Econometrics, Elsevier, vol. 224(2), pages 439-465.
    62. Raffaello Seri & Samuele Centorrino & Michele Bernasconi, 2019. "Nonparametric Estimation and Inference in Economic and Psychological Experiments," Papers 1904.11156, arXiv.org, revised Dec 2019.
    63. 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.
    64. 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.

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

    Cited by:

    1. Aslanidis, Nektarios & Martínez Ibáñez, Óscar, 2012. "Modelling world investment markets using threshold conditional correlation models," Working Papers 2072/203167, Universitat Rovira i Virgili, Department of Economics.
    2. Silvennoinen, Annastiina & Teräsvirta, Timo, 2024. "Consistency and asymptotic normality of maximum likelihood estimators of a multiplicative time-varying smooth transition correlation GARCH model," Econometrics and Statistics, Elsevier, vol. 32(C), pages 57-72.
    3. Abdelradi, Fadi & Serra, Teresa, 2015. "Food–energy nexus in Europe: Price volatility approach," Energy Economics, Elsevier, vol. 48(C), pages 157-167.
    4. Jensen, Mark J. & Maheu, John M., 2013. "Bayesian semiparametric multivariate GARCH modeling," Journal of Econometrics, Elsevier, vol. 176(1), pages 3-17.
    5. Paul Catani & Timo Teräsvirta & Meiqun Yin, 2017. "A Lagrange multiplier test for testing the adequacy of constant conditional correlation GARCH model," Econometric Reviews, Taylor & Francis Journals, vol. 36(6-9), pages 599-621, October.
    6. Zhang, Yongli & Rolling, Craig & Yang, Yuhong, 2021. "Estimating and forecasting dynamic correlation matrices: A nonlinear common factor approach," Journal of Multivariate Analysis, Elsevier, vol. 183(C).
    7. Pick Schen Yip & Robert Brooks & Hung Xuan Do & Duc Khuong Nguyen, 2019. "Dynamic Volatility Spillover Effect between Oil and Agricultural Products," Working Papers 2019-009, Department of Research, Ipag Business School.
    8. Cornelis Gardebroek & Manuel A. Hernandez & Miguel Robles, 2016. "Market interdependence and volatility transmission among major crops," Agricultural Economics, International Association of Agricultural Economists, vol. 47(2), pages 141-155, March.
    9. Yulia Kotlyarova & Marcia Schafgans & Victoria Zinde-Walsh, 2011. "Adapting Kernel Estimation to Uncertain Smoothness," Working Papers daleconwp2011-01, Dalhousie University, Department of Economics.
    10. Yan Li & Liangjun Su & Yuewu Xu, 2015. "A Combined Approach to the Inference of Conditional Factor Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(2), pages 203-220, April.
    11. Teresa Serra & José M. Gil, 2013. "Price volatility in food markets: can stock building mitigate price fluctuations?," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 40(3), pages 507-528, July.
    12. Hernandez, Manuel A. & Gardebroek, Cornelis, "undated". "Do energy prices stimulate food price volatility? Examining volatility transmission between US oil, ethanol and corn markets," 2012 Annual Meeting, August 12-14, 2012, Seattle, Washington 124583, Agricultural and Applied Economics Association.
    13. Barigozzi, Matteo & Brownlees, Christian & Gallo, Giampiero M. & Veredas, David, 2014. "Disentangling systematic and idiosyncratic dynamics in panels of volatility measures," Journal of Econometrics, Elsevier, vol. 182(2), pages 364-384.
    14. Xun Lu & Liangjun Su, 2014. "Jackknife Model Averaging for Quantile Regressions," Working Papers 11-2014, Singapore Management University, School of Economics.
    15. Serra, Teresa & Gil, José M., 2012. "Biodiesel as a motor fuel price stabilization mechanism," Energy Policy, Elsevier, vol. 50(C), pages 689-698.
    16. Serra, Teresa, 2011. "Volatility spillovers between food and energy markets: A semiparametric approach," Energy Economics, Elsevier, vol. 33(6), pages 1155-1164.
    17. Aman Ullah & Mardi Dungey & Xiangdong Long & Yun Wang, 2014. "A Semiparametric Conditional Duration Model," Working Papers 201408, University of California at Riverside, Department of Economics.
    18. Dimitrios Thomakos & Johannes Klepsch & Dimitris N. Politis, 2020. "Model Free Inference on Multivariate Time Series with Conditional Correlations," Stats, MDPI, vol. 3(4), pages 1-26, November.
    19. Kristoufek, Ladislav & Janda, Karel & Zilberman, David, "undated". "Relationship Between Prices of Food, Fuel and Biofuel," 131st Seminar, September 18-19, 2012, Prague, Czech Republic 135793, European Association of Agricultural Economists.
    20. Serra, Teresa, 2012. "Biofuel-related price volatility literature: a review and new approaches," 2012 Conference, August 18-24, 2012, Foz do Iguacu, Brazil 126057, International Association of Agricultural Economists.
    21. Aslanidis, Nektarios & Martinez, Oscar, 2021. "Correlation regimes in international equity and bond returns," Economic Modelling, Elsevier, vol. 97(C), pages 397-410.
    22. López Cabrera, Brenda & Schulz, Franziska, 2013. "Volatility linkages between energy and agricultural commodity prices," SFB 649 Discussion Papers 2013-042, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    23. Fernandez-Diaz, Jose M. & Morley, Bruce, 2019. "Interdependence among agricultural commodity markets, macroeconomic factors, crude oil and commodity index," Research in International Business and Finance, Elsevier, vol. 47(C), pages 174-194.
    24. Tae-Hwy Lee & Millie Yi Mao & Aman Ullah, 2020. "Estimation of High-Dimensional Dynamic Conditional Precision Matrices with an Application to Forecast Combination," Working Papers 202012, University of California at Riverside, Department of Economics.
    25. Kristoufek, Ladislav & Janda, Karel & Zilberman, David, 2012. "Correlations between biofuels and related commodities before and during the food crisis: A taxonomy perspective," Energy Economics, Elsevier, vol. 34(5), pages 1380-1391.
    26. Amer Ait Sidhoum & Teresa Serra, 2016. "Volatility Spillovers in the Spanish Food Marketing Chain: The Case of Tomato," Agribusiness, John Wiley & Sons, Ltd., vol. 32(1), pages 45-63, January.

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

    Cited by:

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

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

    Cited by:

    1. Lu, Xun & White, Halbert, 2014. "Robustness checks and robustness tests in applied economics," Journal of Econometrics, Elsevier, vol. 178(P1), pages 194-206.
    2. Huang, Meng & Sun, Yixiao & White, Hal, 2013. "A Flexible Nonparametric Test for Conditional Independence," University of California at San Diego, Economics Working Paper Series qt3pt89204, Department of Economics, UC San Diego.
    3. Fu, Zhonghao & Hong, Yongmiao, 2019. "A model-free consistent test for structural change in regression possibly with endogeneity," Journal of Econometrics, Elsevier, vol. 211(1), pages 206-242.
    4. Stefan Sperlich, 2014. "On the choice of regularization parameters in specification testing: a critical discussion," Empirical Economics, Springer, vol. 47(2), pages 427-450, September.
    5. Chi-Yang Chu & Chien-Ho Wang & Wan-Jiun Chen, 2025. "Does the Kyoto Protocol have a structural impact on the environmental Kuznets curve? An application of the varying coefficient model," Empirical Economics, Springer, vol. 68(2), pages 729-758, February.
    6. Su, Liangjun & White, Halbert, 2014. "Testing conditional independence via empirical likelihood," Journal of Econometrics, Elsevier, vol. 182(1), pages 27-44.
    7. Liangjun Su & Stefan Hoderlein & Halbert White, 2013. "Testing Monotonicity in Unobservables with Panel Data," Boston College Working Papers in Economics 892, Boston College Department of Economics, revised 01 Feb 2016.
    8. Su, Liangjun & Hoshino, Tadao, 2016. "Sieve instrumental variable quantile regression estimation of functional coefficient models," Journal of Econometrics, Elsevier, vol. 191(1), pages 231-254.
    9. Stefan Sperlich, 2013. "Comments on: An updated review of Goodness-of-Fit tests for regression models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 22(3), pages 419-427, September.
    10. 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.

  74. 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. 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.
    2. Su, Liangjun, 2012. "Semiparametric GMM estimation of spatial autoregressive models," Journal of Econometrics, Elsevier, vol. 167(2), pages 543-560.
    3. Jianbao Chen & Suli Cheng, 2021. "GMM Estimation of a Partially Linear Additive Spatial Error Model," Mathematics, MDPI, vol. 9(6), pages 1-28, March.
    4. 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.
    5. 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.
    6. Luo, Guowang & Wu, Mixia & Pang, Zhen, 2022. "Estimation of spatial autoregressive models with covariate measurement errors," Journal of Multivariate Analysis, Elsevier, vol. 192(C).
    7. Tizheng Li & Ting Liu & Xiangyi Zhang, 2026. "Estimation and inference of high-dimensional partially linear spatial autoregressive models with linear constraints," Computational Statistics, Springer, vol. 41(1), pages 1-37, January.
    8. Abhimanyu Gupta & Xi Qu & Sorawoot Srisuma & Jiajun Zhang, 2025. "Wald inference on varying coefficients," Papers 2502.03084, arXiv.org, revised Jan 2026.
    9. Kunming Li & Liting Fang, 2024. "Bayesian Estimation of the Semiparametric Spatial Lag Model," Mathematics, MDPI, vol. 12(14), pages 1-17, July.
    10. 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.
    11. 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.
    12. Sanying Feng & Tiejun Tong & Sung Nok Chiu, 2023. "Statistical Inference for Partially Linear Varying Coefficient Spatial Autoregressive Panel Data Model," Mathematics, MDPI, vol. 11(22), pages 1-19, November.
    13. Jianbao Chen & Bogui Li & Shuangshuang Li, 2025. "GMM estimation of random effects semiparametric additive SAR panel model with spatiotemporal correlated errors," Statistical Papers, Springer, vol. 66(3), pages 1-40, April.
    14. Malikov, Emir & Sun, Yiguo, 2017. "Semiparametric Estimation and Testing of Smooth Coefficient Spatial Autoregressive Models," MPRA Paper 77253, University Library of Munich, Germany.
    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. 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.
    17. Sun, Yan, 2017. "Estimation of single-index model with spatial interaction," Regional Science and Urban Economics, Elsevier, vol. 62(C), pages 36-45.
    18. 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.
    19. Tizheng Li & Yuping Wang & Ke Fang, 2024. "A semiparametric dynamic higher-order spatial autoregressive model," Statistical Papers, Springer, vol. 65(2), pages 1085-1123, April.
    20. Yu Liu & Yuexin Fang, 2026. "Variable selection of the spatial autoregressive model with covariate data missing at random," Statistical Papers, Springer, vol. 67(2), pages 1-34, April.
    21. 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.
    22. 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.
    23. 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.
    24. 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.
    25. Tizheng Li & Lin Li & Yanhui Li, 2025. "Semiparametric partially linear varying coefficient higher-order spatial autoregressive model," Statistical Papers, Springer, vol. 66(3), pages 1-43, April.
    26. Yangbing Tang & Zhongzhan Zhang & Jiang Du, 2024. "Rank-based instrumental variable estimation for semiparametric varying coefficient spatial autoregressive models," Statistical Papers, Springer, vol. 65(3), pages 1805-1839, May.
    27. 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.
    28. Li, Shuangshuang & Chen, Jianbao, 2026. "Estimation and testing for fixed effects partially linear nonparametric panel regression model with separable spatially and serially correlated error structure," Journal of Multivariate Analysis, Elsevier, vol. 212(C).
    29. 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.
    30. 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.
    31. 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.
    32. Xuan Liang & Jiti Gao & Xiaodong Gong, 2021. "Semiparametric Spatial Autoregressive Panel Data Model with Fixed Effects and Time-Varying Coefficients," Monash Econometrics and Business Statistics Working Papers 5/21, Monash University, Department of Econometrics and Business Statistics.
    33. 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.
    34. 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.
    35. Hong, Han & Ju, Gaosheng & Li, Qi & Yan, Karen X., 2024. "Varying-coefficient spatial dynamic panel data models with fixed effects: Theory and application," Journal of Econometrics, Elsevier, vol. 245(1).
    36. 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.
    37. 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.
    38. Luo, Feng & Xu, Hongxia & Fan, Guoliang & Zhu, Liping, 2026. "Ultra-high dimensional semiparametric dynamic high-order spatial autoregressive models," Journal of Multivariate Analysis, Elsevier, vol. 211(C).
    39. Soberon, Alexandra & Mazzanti, Massimiliano & Musolesi, Antonio & Rodriguez-Poo, Juan M., 2025. "Efficient estimation of a partially linear panel data model with cross-sectional dependence," Journal of Multivariate Analysis, Elsevier, vol. 206(C).
    40. Lu, Fang & Pan, Hao & Yang, Jing, 2025. "GMM estimation and variable selection of semiparametric model with increasing dimension and high-order spatial dependence," Computational Statistics & Data Analysis, Elsevier, vol. 205(C).
    41. 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.
    42. 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.
    43. 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.
    44. 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.
    45. 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.
    46. Xiuli Wang & Jingchang Shao & Jingjing Wu & Qiang Zhao, 2023. "Robust variable selection with exponential squared loss for partially linear spatial autoregressive models," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 75(6), pages 949-977, December.
    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. Konstantinidi, Antri & Kourtellos, Andros & Sun, Yiguo, 2023. "Social threshold regression," Journal of Econometrics, Elsevier, vol. 235(2), pages 2057-2081.
    49. Gupta, A, 2015. "Nonparametric specification testing via the trinity of tests," Economics Discussion Papers 23824, University of Essex, Department of Economics.
    50. Sun, Yiguo, 2016. "Functional-coefficient spatial autoregressive models with nonparametric spatial weights," Journal of Econometrics, Elsevier, vol. 195(1), pages 134-153.
    51. 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.
    52. Ke Wang & Jingwen Huang & Dehui Wang, 2025. "Estimation for single-index varying-coefficient spatial autoregressive model with index covariate measurement errors," Statistical Papers, Springer, vol. 66(6), pages 1-42, October.
    53. Gupta, A, 2015. "Estimation of Spatial Autoregressions with Stochastic Weight Matrices," Economics Discussion Papers 15617, University of Essex, Department of Economics.
    54. Mu Yue & Jingxin Xi, 2025. "Sparse Boosting for Additive Spatial Autoregressive Model with High Dimensionality," Mathematics, MDPI, vol. 13(5), pages 1-16, February.
    55. Cheng, Suli & Chen, Jianbao, 2023. "GMM estimation of partially linear additive spatial autoregressive model," Computational Statistics & Data Analysis, Elsevier, vol. 182(C).
    56. Suli Cheng & Jianbao Chen, 2021. "Estimation of partially linear single-index spatial autoregressive model," Statistical Papers, Springer, vol. 62(1), pages 495-531, February.
    57. 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.
    58. Rui Yang & Yunquan Song, 2025. "Variable Selection for Nonparametric Spatial Expectile Regression Using Deep Neural Networks," Networks and Spatial Economics, Springer, vol. 25(3), pages 847-885, September.
    59. 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.
    60. 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).
    61. 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.
    62. 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.
    63. 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.
    64. Li, Bogui & Chen, Jianbao, 2026. "GMM estimation of fixed effects partially linear additive SAR model with space-time correlated disturbances," Computational Statistics & Data Analysis, Elsevier, vol. 213(C).
    65. 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.
    66. Kwok, Hon Ho, 2019. "Identification and estimation of linear social interaction models," Journal of Econometrics, Elsevier, vol. 210(2), pages 434-458.
    67. Abhimanyu Gupta & Xi Qu, 2021. "Consistent specification testing under spatial dependence," Papers 2101.10255, arXiv.org, revised Aug 2022.

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

    Cited by:

    1. Matthieu Garcin & Clément Goulet, 2017. "Non-parametric news impact curve: a variational approach," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-01244292, HAL.
    2. Cristina Amado & Annastiina Silvennoinen & Timo Teräsvirta, 2018. "Models with Multiplicative Decomposition of Conditional Variances and Correlations," CREATES Research Papers 2018-14, Department of Economics and Business Economics, Aarhus University.
    3. Li, Yan & Yang, Liyan, 2011. "Testing conditional factor models: A nonparametric approach," Journal of Empirical Finance, Elsevier, vol. 18(5), pages 972-992.
    4. Niklas Ahlgren & Alexander Back & Timo Terasvirta, 2024. "A new GARCH model with a deterministic time-varying intercept," Papers 2410.03239, arXiv.org, revised Oct 2024.
    5. Justin Dang & Aman Ullah, 2022. "Machine-Learning-Based Semiparametric Time Series Conditional Variance: Estimation and Forecasting," JRFM, MDPI, vol. 15(1), pages 1-12, January.
    6. Matthieu Garcin & Clément Goulet, 2017. "Non-parametric news impact curve: a variational approach," Post-Print halshs-01244292, HAL.
    7. Yu, Jun, 2012. "A semiparametric stochastic volatility model," Journal of Econometrics, Elsevier, vol. 167(2), pages 473-482.
    8. Yan Li & Liangjun Su & Yuewu Xu, 2015. "A Combined Approach to the Inference of Conditional Factor Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(2), pages 203-220, April.
    9. Amado, Cristina & Teräsvirta, Timo, 2013. "Modelling volatility by variance decomposition," Journal of Econometrics, Elsevier, vol. 175(2), pages 142-153.
    10. Xun Lu & Liangjun Su, 2014. "Jackknife Model Averaging for Quantile Regressions," Working Papers 11-2014, Singapore Management University, School of Economics.
    11. Jaromír Kukal & Tran Van Quang, 2014. "Neparametrický heuristický přístup k odhadu modelu GARCH-M a jeho výhody [Estimating a GARCH-M Model by a Non-Parametric Heuristic Method and Its Advantages]," Politická ekonomie, Prague University of Economics and Business, vol. 2014(1), pages 100-116.
    12. Aman Ullah & Mardi Dungey & Xiangdong Long & Yun Wang, 2014. "A Semiparametric Conditional Duration Model," Working Papers 201408, University of California at Riverside, Department of Economics.
    13. d’Addona, Stefano & Khanom, Najrin, 2022. "Estimating tail-risk using semiparametric conditional variance with an application to meme stocks," International Review of Economics & Finance, Elsevier, vol. 82(C), pages 241-260.
    14. Matthieu Garcin & Clément Goulet, 2015. "A fully non-parametric heteroskedastic model," Documents de travail du Centre d'Economie de la Sorbonne 15086, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    15. Cristina Amado & Timo Teräsvirta, 2017. "Specification and testing of multiplicative time-varying GARCH models with applications," Econometric Reviews, Taylor & Francis Journals, vol. 36(4), pages 421-446, April.
    16. Enno Mammen & Jens Perch Nielsen & Michael Scholz & Stefan Sperlich, 2019. "Conditional Variance Forecasts for Long-Term Stock Returns," Risks, MDPI, vol. 7(4), pages 1-22, November.
    17. Kaiping Wang, 2014. "Modeling Stock Index Returns using Semi-Parametric Approach with Multiplicative Adjustment," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 65-75, December.

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

    Cited by:

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

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

    Cited by:

    1. Ying-Ying Lee, 2018. "Partial Mean Processes with Generated Regressors: Continuous Treatment Effects and Nonseparable Models," Papers 1811.00157, arXiv.org.
    2. Uddin, Md. Main & Mishra, Vinod & Smyth, Russell, 2020. "Income inequality and CO2 emissions in the G7, 1870–2014: Evidence from non-parametric modelling," Energy Economics, Elsevier, vol. 88(C).
    3. Battisti, Michele & Gatto, Massimo Del & Parmeter, Christopher F., 2022. "Skill-biased technical change and labor market inefficiency," Journal of Economic Dynamics and Control, Elsevier, vol. 139(C).
    4. Jingping Gu & Qi Li & Jui-Chung Yang, 2015. "Multivariate Local Polynomial Kernel Estimators: Leading Bias and Asymptotic Distribution," Econometric Reviews, Taylor & Francis Journals, vol. 34(6-10), pages 979-1010, December.
    5. 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.
    6. Henderson, Daniel J. & Souto, Anne-Charlotte, 2018. "An Introduction to Nonparametric Regression for Labor Economists," IZA Discussion Papers 11914, IZA Network @ LISER.
    7. Das, Monica & Basu, Sudip R., 2023. "Inclusive bank based financial development in countries with special needs: A semiparametric analysis," Economic Analysis and Policy, Elsevier, vol. 80(C), pages 740-753.
    8. Peter C.B. Phillips & Degui Li & Jiti Gao, 2013. "Estimating Smooth Structural Change in Cointegration Models," Cowles Foundation Discussion Papers 1910, Cowles Foundation for Research in Economics, Yale University.
    9. Martins-Filho, Carlos & Yao, Feng, 2012. "Kernel-based estimation of semiparametric regression in triangular systems," Economics Letters, Elsevier, vol. 115(1), pages 24-27.
    10. Jiti Gao & Peter C.B. Phillips, 2011. "Semiparametric Estimation in Multivariate Nonstationary Time Series Models," Monash Econometrics and Business Statistics Working Papers 17/11, Monash University, Department of Econometrics and Business Statistics.
    11. Lamia Beldi & Tarek Ghazouani, 2025. "Nonparametric analysis of the relationship between income inequality and energy consumption in African countries," Natural Resources Forum, Blackwell Publishing, vol. 49(2), pages 1401-1423, May.
    12. Manuel Wiesenfarth & Carlos Matías Hisgen & Thomas Kneib & Carmen Cadarso-Suarez, 2014. "Bayesian Nonparametric Instrumental Variables Regression Based on Penalized Splines and Dirichlet Process Mixtures," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 32(3), pages 468-482, July.
    13. Xin Geng & Carlos Martins-Filho & Feng Yao, 2015. "Estimation of a Partially Linear Regression in Triangular Systems," Working Papers 15-46, Department of Economics, West Virginia University.
    14. Kim Kyoo il & Petrin Amil, 2022. "A Generalized Non-Parametric Instrumental Variable-Control Function Approach to Estimation in Nonlinear Settings," Journal of Econometric Methods, De Gruyter, vol. 11(1), pages 91-125, January.
    15. Nicholas Marinucci & Kris Ivanovski, 2023. "Does Inequality Affect Climate Change? A Regional and Sectoral Analysis," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 166(3), pages 705-729, April.
    16. Geng, Xin & Hernandez, Manuel A., 2017. "Aid, Policies and Growth: A Nonlinear Reassessment," IFPRI discussion papers 1699, International Food Policy Research Institute (IFPRI).
    17. Zongwu Cai & Qi Li, 2013. "Some Recent Develop- ments on Nonparametric Econometrics," Working Papers 2013-10-14, Wang Yanan Institute for Studies in Economics (WISE), Xiamen University.
    18. Anjan K. Saha & Vinod Mishra & Russell Smyth, 2021. "Financial development and top income shares in OECD countries," Southern Economic Journal, John Wiley & Sons, vol. 87(3), pages 952-978, January.
    19. Awaworyi Churchill, Sefa & Inekwe, John & Ivanovski, Kris, 2021. "R&D expenditure and energy consumption in OECD nations," Energy Economics, Elsevier, vol. 100(C).
    20. Camarero, Mariam & Peiró-Palomino, Jesús & Tamarit, Cecilio, 2019. "Growth in a time of external imbalances," Economic Modelling, Elsevier, vol. 79(C), pages 262-275.
    21. Jiti Gao & Peter C.B. Phillips, 2013. "Functional Coefficient Nonstationary Regression with Non- and Semi-Parametric Cointegration," Monash Econometrics and Business Statistics Working Papers 16/13, Monash University, Department of Econometrics and Business Statistics.
    22. Artem Prokhorov & Kien C. Tran & Mike G. Tsionas, 2021. "Estimation of semi- and nonparametric stochastic frontier models with endogenous regressors," Empirical Economics, Springer, vol. 60(6), pages 3043-3068, June.
    23. Jesús Peiró-Palomino, 2016. "Social Capital and Economic Growth in Europe: Nonlinear Trends and Heterogeneous Regional Effects," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 78(5), pages 717-751, October.
    24. Francesco Bravo & David Jacho-Chavez, 2011. "Empirical Likelihood for Efficient Semiparametric Average Treatment Effects," Econometric Reviews, Taylor & Francis Journals, vol. 30(1), pages 1-24.
    25. Alyssa Carlson, 2020. "Relaxing Conditional Independence in an Endogenous Binary Response Model," Working Papers 2008, Department of Economics, University of Missouri.
    26. Das, Monica & Basu, Sudip Ranjan, 2022. "Understanding the relationship between income inequality and pollution: A fresh perspective with cross-country evidence," World Development Perspectives, Elsevier, vol. 26(C).
    27. Kim, Namhyun & W. Saart, Patrick, 2021. "Estimation in partially linear semiparametric models with parametric and/or nonparametric endogeneity," Cardiff Economics Working Papers E2021/9, Cardiff University, Cardiff Business School, Economics Section.
    28. Durga P. Gautam, 2014. "Remittances and Governance: Does the Government Free Ride?," Working Papers 14-40, Department of Economics, West Virginia University.
    29. Patrick Saart & Jiti Gao, 2012. "Semiparametric Methods in Nonlinear Time Series Analysis: A Selective Review," Monash Econometrics and Business Statistics Working Papers 21/12, Monash University, Department of Econometrics and Business Statistics.
    30. : Daniel J. Henderson & Chris Papageorgiou & Christopher F. Parmeter, 2012. "Who Benefits from Financial Development? New Methods, New Evidence," Working Papers 2013-07, University of Miami, Department of Economics.
    31. Kai Sun, 2015. "Constrained nonparametric estimation of input distance function," Journal of Productivity Analysis, Springer, vol. 43(1), pages 85-97, February.
    32. Jinjing Tian & Taining Wang & Feng Yao, 2024. "Excessive External Borrowing in China: Evidence from a Nonparametric Threshold Regression Model with Fixed Effects," Mathematics, MDPI, vol. 12(23), pages 1-28, November.
    33. Gao, Jiti & Phillips, Peter C.B., 2013. "Semiparametric estimation in triangular system equations with nonstationarity," Journal of Econometrics, Elsevier, vol. 176(1), pages 59-79.
    34. Ghazouani, Tarek, 2022. "Dynamic impact of globalization on renewable energy consumption: Non-parametric modelling evidence," Technological Forecasting and Social Change, Elsevier, vol. 185(C).
    35. Delgado, Michael S. & Parmeter, Christopher F., 2014. "A simple estimator for partial linear regression with endogenous nonparametric variables," Economics Letters, Elsevier, vol. 124(1), pages 100-103.
    36. Jacho-Chávez, David & Lewbel, Arthur & Linton, Oliver, 2010. "Identification and nonparametric estimation of a transformed additively separable model," Journal of Econometrics, Elsevier, vol. 156(2), pages 392-407, June.
    37. Tarek Ghazouani, 2024. "Is the Relationship Between Clean/Non-clean Energy Consumption and Economic Growth Time-Varying? Non-parametric Evidence for MENA Region," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 15(4), pages 19964-19988, December.
    38. Alemayehu, Fikru K. & Sun, Kai & Kumbhakar, Subal C., 2026. "Productivity dynamics, innovation and endogeneity: A semiparametric stochastic frontiers approach," European Journal of Operational Research, Elsevier, vol. 330(3), pages 1028-1038.
    39. Koo, Chao, 2018. "Essays on functional coefficient models," Other publications TiSEM ba87b8a5-3c55-40ec-967d-9, Tilburg University, School of Economics and Management.
    40. Davide Golinelli & Andrea Musolesi & Alexandra Soberon, 2026. "Continuous Endogenous Variables in Partially Linear Regression Models," SEEDS Working Papers 0926, SEEDS, Sustainability Environmental Economics and Dynamics Studies, revised May 2026.
    41. Lee, Chi-Chuan & Lee, Chien-Chiang & Chiou, Yan-Yu, 2017. "Insurance activities, globalization, and economic growth: New methods, new evidence," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 51(C), pages 155-170.
    42. Sefa Awaworyi Churchill & Bin Peng & Russell Smyth & Quanda Zhang, 2022. "R&D intensity and income inequality in the G7: 1870–2016," Scottish Journal of Political Economy, Scottish Economic Society, vol. 69(3), pages 263-282, July.
    43. Jiti Gao & Peter C.B. Phillips, 2013. "Functional Coefficient Nonstationary Regression," Cowles Foundation Discussion Papers 1911, Cowles Foundation for Research in Economics, Yale University.
    44. Kumbhakar, Subal C. & Li, Mingyang & Lien, Gudbrand, 2023. "Do subsidies matter in productivity and profitability changes?," Economic Modelling, Elsevier, vol. 123(C).
    45. Ying-Ying Lee, 2014. "Partial Mean Processes with Generated Regressors: Continuous Treatment Effects and Nonseparable Models," Economics Series Working Papers 706, University of Oxford, Department of Economics.

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

    Cited by:

    1. Taoufik Bouezmarni & Mohamed Doukali & Abderrahim Taamouti, 2023. "Testing Granger Non-Causality in Expectiles," University of East Anglia School of Economics Working Paper Series 2023-02, School of Economics, University of East Anglia, Norwich, UK..
    2. Tsuyoshi Kunihama & David B. Dunson, 2016. "Nonparametric Bayes inference on conditional independence," Biometrika, Biometrika Trust, vol. 103(1), pages 35-47.
    3. 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).
    4. Semei Coronado & Rebeca Jim'enez-Rodr'iguez & Omar Rojas, 2015. "An empirical analysis of the relationships between crude oil, gold and stock markets," Papers 1510.07599, arXiv.org, revised May 2016.
    5. Huang, Meng & Sun, Yixiao & White, Hal, 2013. "A Flexible Nonparametric Test for Conditional Independence," University of California at San Diego, Economics Working Paper Series qt3pt89204, Department of Economics, UC San Diego.
    6. Joeri Smits & Jeffrey S. Racine, 2013. "Testing Exclusion Restrictions in Nonseparable Triangular Models," Department of Economics Working Papers 2013-02, McMaster University.
    7. Hoderlein, Stefan & Su, Liangjun & White, Halbert & Yang, Thomas Tao, 2016. "Testing for monotonicity in unobservables under unconfoundedness," Journal of Econometrics, Elsevier, vol. 193(1), pages 183-202.
    8. Cheng, Yu-Hsiang & Huang, Tzee-Ming, 2012. "A conditional independence test for dependent data based on maximal conditional correlation," Journal of Multivariate Analysis, Elsevier, vol. 107(C), pages 210-226.
    9. Zhou, Yeqing & Liu, Jingyuan & Zhu, Liping, 2020. "Test for conditional independence with application to conditional screening," Journal of Multivariate Analysis, Elsevier, vol. 175(C).
    10. Hobæk Haff, Ingrid & Segers, Johan, 2015. "Nonparametric estimation of pair-copula constructions with the empirical pair-copula," Computational Statistics & Data Analysis, Elsevier, vol. 84(C), pages 1-13.
    11. Taoufik Bouezmarni & Jeroen V.K. Rombouts & Abderrahim Taamouti, 2009. "A Nonparametric Copula Based Test for Conditional Independence with Applications to Granger Causality," Cahiers de recherche 0927, CIRPEE.
    12. Gaurab Aryal & Isabelle Perrigne & Quang Vuong, 2011. "Identification of Insurance Models with Multidimensional Screening," ANU Working Papers in Economics and Econometrics 2011-538, Australian National University, College of Business and Economics, School of Economics.
    13. Sokbae Lee & Yoon-Jae Whang, 2009. "Nonparametric Tests of Conditional Treatment Effects," Cowles Foundation Discussion Papers 1740, Cowles Foundation for Research in Economics, Yale University.
    14. Li, Haiqi & Zhong, Wanling & Park, Sung Y., 2016. "Generalized cross-spectral test for nonlinear Granger causality with applications to money–output and price–volume relations," Economic Modelling, Elsevier, vol. 52(PB), pages 661-671.
    15. Samuele Centorrino & Jean-Pierre Florens, 2014. "Nonparametric Instrumental Variable Estimation of Binary Response Models," Department of Economics Working Papers 14-07, Stony Brook University, Department of Economics.
    16. Dai, Shengtao & Song, Xiaojun, 2025. "Consistent tests for semiparametric conditional independence," Statistics & Probability Letters, Elsevier, vol. 216(C).
    17. Poirier, Alexandre, 2017. "Efficient estimation in models with independence restrictions," Journal of Econometrics, Elsevier, vol. 196(1), pages 1-22.
    18. Su, Liangjun & Zheng, Xin, 2017. "A martingale-difference-divergence-based test for specification," Economics Letters, Elsevier, vol. 156(C), pages 162-167.
    19. Chen, Bin & Hong, Yongmiao, 2012. "Testing For The Markov Property In Time Series," Econometric Theory, Cambridge University Press, vol. 28(1), pages 130-178, February.
    20. Su, Liangjun & White, Halbert, 2014. "Testing conditional independence via empirical likelihood," Journal of Econometrics, Elsevier, vol. 182(1), pages 27-44.
    21. Xu, Kai & Cheng, Qing, 2024. "Test of conditional independence in factor models via Hilbert–Schmidt independence criterion," Journal of Multivariate Analysis, Elsevier, vol. 199(C).
    22. Azadkia, Mona & Chatterjee, Sourav, 2021. "A simple measure of conditional dependence," LSE Research Online Documents on Economics 125584, London School of Economics and Political Science, LSE Library.
    23. Xiaojun Song & Haoyu Wei, 2021. "Nonparametric Tests of Conditional Independence for Time Series," Papers 2110.04847, arXiv.org.
    24. Sungwon Lee & Joon H. Ro, 2020. "Nonparametric Tests for Conditional Quantile Independence with Duration Outcomes," Working Papers 2013, Nam Duck-Woo Economic Research Institute, Sogang University (Former Research Institute for Market Economy).
    25. Ruiz-Castillo, Javier, 2012. "From the “European Paradox” to a European Drama in citation impact," UC3M Working papers. Economics we1211, Universidad Carlos III de Madrid. Departamento de Economía.
    26. Davide Fiaschi & Paul Johnson, 2025. "(In)stability in the Dynamics of the Cross-Country Distribution of Income Per Capita," Papers 2506.06755, arXiv.org.
    27. Bianchi, Pascal & Elgui, Kevin & Portier, François, 2023. "Conditional independence testing via weighted partial copulas," Journal of Multivariate Analysis, Elsevier, vol. 193(C).
    28. Patra, Rohit K. & Sen, Bodhisattva & Székely, Gábor J., 2016. "On a nonparametric notion of residual and its applications," Statistics & Probability Letters, Elsevier, vol. 109(C), pages 208-213.
    29. Bouezmarni, Taoufik & Taamouti, Abderrahim, 2012. "Nonparametric tests for conditional independence using conditional distributions," UC3M Working papers. Economics we1217, Universidad Carlos III de Madrid. Departamento de Economía.
    30. Ersin Sünbül, 2023. "Linear and Nonlinear Relationship Between Real Exchange Rate, Real Interest Rate and Consumer Price Index: An Empirical Application for Countries with Different Levels of Development," Scientific Annals of Economics and Business (continues Analele Stiintifice), Alexandru Ioan Cuza University, Faculty of Economics and Business Administration, vol. 70(1), pages 57-70, March.
    31. Liu, Nianqing & Vuong, Quang & Xu, Haiqing, 2017. "Rationalization and identification of binary games with correlated types," Journal of Econometrics, Elsevier, vol. 201(2), pages 249-268.
    32. Massa, Ricardo & Rosellón, Juan, 2020. "Linear and nonlinear Granger causality between electricity production and economic performance in Mexico," Energy Policy, Elsevier, vol. 142(C).
    33. Bertrand Caudelon & Sessi Tokpavi, 2014. "A Nonparametric Test for Granger-causality in Distribution with Application to Financial Contagion," EconomiX Working Papers 2014-18, University of Paris Nanterre, EconomiX.
    34. Xuehu Zhu & Jun Lu & Jun Zhang & Lixing Zhu, 2021. "Testing for conditional independence: A groupwise dimension reduction‐based adaptive‐to‐model approach," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 48(2), pages 549-576, June.
    35. Fan, Jianqing & Feng, Yang & Xia, Lucy, 2020. "A projection-based conditional dependence measure with applications to high-dimensional undirected graphical models," Journal of Econometrics, Elsevier, vol. 218(1), pages 119-139.
    36. Ai, Chunrong & Sun, Li-Hsien & Zhang, Zheng & Zhu, Liping, 2024. "Testing unconditional and conditional independence via mutual information," Journal of Econometrics, Elsevier, vol. 240(2).
    37. Györfi, László & Walk, Harro, 2012. "Strongly consistent nonparametric tests of conditional independence," Statistics & Probability Letters, Elsevier, vol. 82(6), pages 1145-1150.
    38. Zhang, Xilin & Xu, Hongxia & Fan, Guoliang & Zhu, Liping, 2026. "Conditional independence test in factor models via projection correlation," Computational Statistics & Data Analysis, Elsevier, vol. 218(C).
    39. Jian Yan & Zhuoxi Li & Xianyang Zhang, 2022. "Distance and Kernel-Based Measures for Global and Local Two-Sample Conditional Distribution Testing," Papers 2210.08149, arXiv.org, revised Aug 2025.
    40. Polanco-Martínez, J.M. & Fernández-Macho, J. & Neumann, M.B. & Faria, S.H., 2018. "A pre-crisis vs. crisis analysis of peripheral EU stock markets by means of wavelet transform and a nonlinear causality test," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 1211-1227.
    41. Zhang, Yaowu & Zhou, Yeqing & Zhu, Liping, 2024. "A post-screening diagnostic study for ultrahigh dimensional data," Journal of Econometrics, Elsevier, vol. 239(2).
    42. Josué M. Polanco-Martínez & Luis M. Abadie, 2016. "Analyzing Crude Oil Spot Price Dynamics versus Long Term Future Prices: A Wavelet Analysis Approach," Energies, MDPI, vol. 9(12), pages 1-19, December.
    43. Hao Dong & Luke Taylor, 2020. "Nonparametric Significance Testing in Measurement Error Models," Departmental Working Papers 2003, Southern Methodist University, Department of Economics.

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

    Cited by:

    1. Galvao Jr., Antonio F., 2009. "Unit root quantile autoregression testing using covariates," Journal of Econometrics, Elsevier, vol. 152(2), pages 165-178, October.
    2. Christis Katsouris, 2023. "Structural Break Detection in Quantile Predictive Regression Models with Persistent Covariates," Papers 2302.05193, arXiv.org.
    3. Tang, Yanlin & Song, Xinyuan & Zhu, Zhongyi, 2015. "Threshold effect test in censored quantile regression," Statistics & Probability Letters, Elsevier, vol. 105(C), pages 149-156.
    4. Tatsushi Oka & Pierre Perron, 2016. "Testing for Common Breaks in a Multiple Equations System," Papers 1606.00092, arXiv.org, revised Jan 2018.
    5. Fuertes, Ana-Maria & Olmo, Jose, 2013. "Optimally harnessing inter-day and intra-day information for daily value-at-risk prediction," International Journal of Forecasting, Elsevier, vol. 29(1), pages 28-42.
    6. Liwen Zhang & Huixia Judy Wang & Zhongyi Zhu, 2017. "Composite change point estimation for bent line quantile regression," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 69(1), pages 145-168, February.
    7. Yan Chen & Caiyun Fan & Feipeng Zhang, 2025. "Linear-quadratic quantile regression model with a change point due to a threshold covariate," Computational Statistics, Springer, vol. 40(8), pages 4515-4564, November.
    8. Yannick Hoga, 2024. "Persistence-Robust Break Detection in Predictive CoVaR Regressions," Papers 2410.05861, arXiv.org, revised Mar 2026.
    9. Oka, Tatsushi & Qu, Zhongjun, 2011. "Estimating structural changes in regression quantiles," Journal of Econometrics, Elsevier, vol. 162(2), pages 248-267, June.
    10. Jin, Hao & Tian, Zheng & Qin, Ruibing, 2009. "Bootstrap tests for structural change with infinite variance observations," Statistics & Probability Letters, Elsevier, vol. 79(19), pages 1985-1995, October.
    11. Antonio Galvao & Kengo Kato & Gabriel Montes-Rojas & Jose Olmo, 2014. "Testing linearity against threshold effects: uniform inference in quantile regression," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 66(2), pages 413-439, April.
    12. Liu, Weiqiang, 2023. "A consistent nonparametric test for the structure change in quantile regression," Economics Letters, Elsevier, vol. 228(C).
    13. Yannick Hoga & Christian Schulz, 2025. "Self-Normalized Inference in (Quantile, Expected Shortfall) Regressions for Time Series," Papers 2502.10065, arXiv.org, revised Jun 2025.
    14. Zhou, Mi & Wang, Huixia Judy & Tang, Yanlin, 2015. "Sequential change point detection in linear quantile regression models," Statistics & Probability Letters, Elsevier, vol. 100(C), pages 98-103.
    15. Alexander Aue & Rex C. Y. Cheung & Thomas C. M. Lee & Ming Zhong, 2014. "Segmented Model Selection in Quantile Regression Using the Minimum Description Length Principle," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(507), pages 1241-1256, September.
    16. Sangyeol Lee & Chang Kyeom Kim, 2024. "Test for conditional quantile change in general conditional heteroscedastic time series models," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 76(2), pages 333-359, April.

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

    Cited by:

    1. Lee, Lung-fei & Yu, Jihai, 2015. "Estimation of fixed effects panel regression models with separable and nonseparable space–time filters," Journal of Econometrics, Elsevier, vol. 184(1), pages 174-192.
    2. 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. Bin Zhou & Qinfeng Xu & Jinhong You, 2011. "Efficient estimation for error component seemingly unrelated nonparametric regression models," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 73(1), pages 121-138, January.
    4. Li, Gaorong & Peng, Heng & Tong, Tiejun, 2013. "Simultaneous confidence band for nonparametric fixed effects panel data models," Economics Letters, Elsevier, vol. 119(3), pages 229-232.
    5. Bang-Qiang He & Xing-Jian Hong & Guo-Liang Fan, 2020. "Penalized empirical likelihood for partially linear errors-in-variables panel data models with fixed effects," Statistical Papers, Springer, vol. 61(6), pages 2351-2381, December.
    6. Tomasz Czekaj & Arne Henningsen, 2013. "Panel Data Specifications in Nonparametric Kernel Regression: An Application to Production Functions," IFRO Working Paper 2013/5, University of Copenhagen, Department of Food and Resource Economics.
    7. Shujie Ma & Jeffrey S. Racine & Aman Ullah, 2015. "Nonparametric Regression-Spline Random Effects Models," Department of Economics Working Papers 2015-10, McMaster University.
    8. Qian, Junhui & Wang, Le, 2012. "Estimating semiparametric panel data models by marginal integration," Journal of Econometrics, Elsevier, vol. 167(2), pages 483-493.
    9. Serfas, D., 2018. "an ex-post econometric analysis of the abolishment of the canadian wheat board," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 277286, International Association of Agricultural Economists.
    10. Bosupeng, Mpho, 2015. "Exports Multiplicity and The Dutch Disease," MPRA Paper 77919, University Library of Munich, Germany, revised 2015.
    11. Gholamreza Hajargasht, 2009. "Nonparametric Panel Data Models, A Penalized Spline Approach," CEPA Working Papers Series WP052009, School of Economics, University of Queensland, Australia.
    12. Liangjun Su & Aman Ullah & Yun Wang, 2013. "Nonparametric regression estimation with general parametric error covariance: a more efficient two-step estimator," Empirical Economics, Springer, vol. 45(2), pages 1009-1024, October.

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

    Cited by:

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

  83. 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. 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.
    2. 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.
    3. Alessio Ciarlone, 2012. "House price cycles in emerging economies," Temi di discussione (Economic working papers) 863, Bank of Italy, Economic Research and International Relations Area.
    4. 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.
    5. 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.
    6. 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.
    7. Mary Riddel, 2011. "Are Housing Bubbles Contagious? A Case Study of Las Vegas and Los Angeles Home Prices," Land Economics, University of Wisconsin Press, vol. 87(1), pages 126-144.

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

    Cited by:

    1. António Afonso & Michael G. Arghyrou & María Dolores Gadea & Alexandros Kontonikas, 2017. ""Whatever it takes" to resolve the European sovereign debt crisis? Bond pricing regime switches and monetary policy effects," Working Papers REM 2017/02, ISEG - Lisbon School of Economics and Management, REM, Universidade de Lisboa.
    2. Su, Liangjun, 2012. "Semiparametric GMM estimation of spatial autoregressive models," Journal of Econometrics, Elsevier, vol. 167(2), pages 543-560.
    3. Baglan, Deniz & Ege Yazgan, M. & Yilmazkuday, Hakan, 2016. "Relative price variability and inflation: New evidence," Journal of Macroeconomics, Elsevier, vol. 48(C), pages 263-282.
    4. Hamadi, Malika & Heinen, Andréas, 2015. "Firm performance when ownership is very concentrated: Evidence from a semiparametric panel," Journal of Empirical Finance, Elsevier, vol. 34(C), pages 172-194.
    5. Benjamin Owusu & Bettina Bökemeier & Alfred Greiner, 2023. "Assessing nonlinearities and heterogeneity in debt sustainability analysis: a panel spline approach," Empirical Economics, Springer, vol. 64(3), pages 1315-1346, March.
    6. Deniz Baglan & Emre Yoldas, 2014. "Non-linearity in the Inflation-Growth Relationship in Developing Economies: Evidence from a Semiparametric Panel Model," Finance and Economics Discussion Series 2014-51, Board of Governors of the Federal Reserve System (U.S.).
    7. Minzhi Wu & Emili Tortosa-Ausina, 2020. "Bank Diversification and Focus in Disruptive Times: China, 2007–2018," Working Papers 2020/21, Economics Department, Universitat Jaume I, Castellón (Spain).
    8. Arghyrou, Michael G & Gadea, Mar a Dolores, 2019. "Private bank deposits and macro/fiscal risk in the euro-area," Cardiff Economics Working Papers E2019/6, Cardiff University, Cardiff Business School, Economics Section.
    9. Geng, Xin & Janssens, Wendy & Kramer, Berber, "undated". "Liquid milk: Cash Constraints and Recurring Savings among Dairy Farmers in Kenya," 2018 Annual Meeting, August 5-7, Washington, D.C. 273823, Agricultural and Applied Economics Association.
    10. Hu, Xuemei, 2017. "Semi-parametric inference for semi-varying coefficient panel data model with individual effects," Journal of Multivariate Analysis, Elsevier, vol. 154(C), pages 262-281.
    11. Mingming Jiang, 2014. "Saving–investment Association and Regional Capital Mobility in China: A Nonparametric Panel Approach," Pacific Economic Review, Wiley Blackwell, vol. 19(2), pages 184-200, May.
    12. Christopher F. Parmeter & Jeffrey S. Racine, 2018. "Nonparametric Estimation and Inference for Panel Data Models," Department of Economics Working Papers 2018-02, McMaster University.
    13. Geng, Xin & Janssens, Wendy & Kramer, Berber, 2023. "Liquid milk: Savings, insurance and side-selling in cooperatives," Journal of Development Economics, Elsevier, vol. 165(C).
    14. G. Arghyrou, Michael & Gadea, Maria-Dolores & Kontonikas, Alexandros, 2024. "Private bank deposits and macro/fiscal risk in the euro-area," Journal of International Money and Finance, Elsevier, vol. 140(C).
    15. Gong, Binlei, 2018. "Agricultural reforms and production in China: Changes in provincial production function and productivity in 1978–2015," Journal of Development Economics, Elsevier, vol. 132(C), pages 18-31.
    16. Yichen Gao & Kunpeng Li, 2013. "Nonparametric estimation of fixed effects panel data models," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 25(3), pages 679-693, September.
    17. Aman Ullah & Tao Wang & Weixin Yao, 2021. "Modal regression for fixed effects panel data," Empirical Economics, Springer, vol. 60(1), pages 261-308, January.
    18. Baglan Deniz & Yoldas Emre, 2016. "Public debt and macroeconomic activity: a predictive analysis for advanced economies," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 20(3), pages 301-324, June.
    19. Masato Nishiwaki & Hyoeg Ug Kwon, 2013. "Are Losers Picked? An Empirical Analysis of Capacity Divestment and Production Reallocation in the Japanese Cement Industry," Journal of Industrial Economics, Wiley Blackwell, vol. 61(2), pages 430-467, June.
    20. Daniel J. Henderson, 2010. "A test for multimodality of regression derivatives with application to nonparametric growth regressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(3), pages 458-480.
    21. Massimiliano Mazzanti & Antonio Musolesi, 2014. "Nonlinearity, heterogeneity and unobserved effects in the carbon dioxide emissions-economic development relation for advanced countries," SEEDS Working Papers 2214, SEEDS, Sustainability Environmental Economics and Dynamics Studies, revised Aug 2014.
    22. Li, Gaorong & Peng, Heng & Tong, Tiejun, 2013. "Simultaneous confidence band for nonparametric fixed effects panel data models," Economics Letters, Elsevier, vol. 119(3), pages 229-232.
    23. Li, Rui & Wan, Alan T.K. & You, Jinhong, 2016. "Semiparametric GMM estimation and variable selection in dynamic panel data models with fixed effects," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 401-423.
    24. Li, Cong & Liang, Zhongwen, 2015. "Asymptotics for nonparametric and semiparametric fixed effects panel models," Journal of Econometrics, Elsevier, vol. 185(2), pages 420-434.
    25. Su, Liangjun & Lu, Xun, 2013. "Nonparametric dynamic panel data models: Kernel estimation and specification testing," Journal of Econometrics, Elsevier, vol. 176(2), pages 112-133.
    26. Bernoth, Kerstin & Erdogan, Burcu, 2012. "Sovereign bond yield spreads: A time-varying coefficient approach," Journal of International Money and Finance, Elsevier, vol. 31(3), pages 639-656.
    27. Malikov, Emir & Kumbhakar, Subal C. & Sun, Yiguo, 2016. "Varying coefficient panel data model in the presence of endogenous selectivity and fixed effects," Journal of Econometrics, Elsevier, vol. 190(2), pages 233-251.
    28. Chen, Jia & Gao, Jiti & Li, Degui, 2012. "Semiparametric trending panel data models with cross-sectional dependence," Journal of Econometrics, Elsevier, vol. 171(1), pages 71-85.
    29. Peter Pütz & Thomas Kneib, 2018. "A penalized spline estimator for fixed effects panel data models," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 102(2), pages 145-166, April.
    30. Ma, Shujie & Liang, Hua & Tsai, Chih-Ling, 2014. "Partially linear single index models for repeated measurements," Journal of Multivariate Analysis, Elsevier, vol. 130(C), pages 354-375.
    31. 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.
    32. Taining Wang & Feng Yao & Jun Cai, 2026. "Nonparametric Estimation of Smooth Coefficients in Fixed-Effect Panel Data Models," Working Papers 26-03, Department of Economics, West Virginia University.
    33. Li, Shuangshuang & Chen, Jianbao, 2026. "Estimation and testing for fixed effects partially linear nonparametric panel regression model with separable spatially and serially correlated error structure," Journal of Multivariate Analysis, Elsevier, vol. 212(C).
    34. Xuan Liang & Jiti Gao & Xiaodong Gong, 2021. "Semiparametric Spatial Autoregressive Panel Data Model with Fixed Effects and Time-Varying Coefficients," Monash Econometrics and Business Statistics Working Papers 5/21, Monash University, Department of Econometrics and Business Statistics.
    35. Taining Wang & Jinjing Tian, 2020. "Recasting the trade impact on labor share: a fixed-effect semiparametric estimation study," Empirical Economics, Springer, vol. 58(5), pages 2465-2511, May.
    36. Zhang, Junhua & Feng, Sanying & Li, Gaorong & Lian, Heng, 2011. "Empirical likelihood inference for partially linear panel data models with fixed effects," Economics Letters, Elsevier, vol. 113(2), pages 165-167.
    37. Zhou, Jianhua & Parmeter, Christopher F. & Kumbhakar, Subal C., 2020. "Nonparametric estimation of the determinants of inefficiency in the presence of firm heterogeneity," European Journal of Operational Research, Elsevier, vol. 286(3), pages 1142-1152.
    38. Elkhan Richard Sadik-Zada & Wilhelm Loewenstein, 2020. "Drivers of CO 2 -Emissions in Fossil Fuel Abundant Settings: (Pooled) Mean Group and Nonparametric Panel Analyses," Energies, MDPI, vol. 13(15), pages 1-24, August.
    39. 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.
    40. Bang-Qiang He & Xing-Jian Hong & Guo-Liang Fan, 2020. "Penalized empirical likelihood for partially linear errors-in-variables panel data models with fixed effects," Statistical Papers, Springer, vol. 61(6), pages 2351-2381, December.
    41. Henderson, Daniel J. & Carroll, Raymond J. & Li, Qi, 2008. "Nonparametric estimation and testing of fixed effects panel data models," Journal of Econometrics, Elsevier, vol. 144(1), pages 257-275, May.
    42. Rui Li & Yuanyuan Zhang, 2021. "Two-stage estimation and simultaneous confidence band in partially nonlinear additive model," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 84(8), pages 1109-1140, November.
    43. Suigen Yang & Xiujuan Yang & Xuefei Wang, 2024. "Estimation and Simultaneous Confidence Bands for Fixed-Effects Panel Data Partially Linear Models," Mathematics, MDPI, vol. 12(23), pages 1-18, November.
    44. Pei, Youquan & Huang, Tao & You, Jinhong, 2018. "Nonparametric fixed effects model for panel data with locally stationary regressors," Journal of Econometrics, Elsevier, vol. 202(2), pages 286-305.
    45. Zhang, Junjie & Wang, Can, 2011. "Co-benefits and additionality of the clean development mechanism: An empirical analysis," Journal of Environmental Economics and Management, Elsevier, vol. 62(2), pages 140-154, September.
    46. 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.
    47. Zhao Wang & Yuanlu Suo & Taining Wang & Subal C. Kumbhakar, 2025. "Are operationally efficient firms greener?," Empirical Economics, Springer, vol. 69(5), pages 2627-2669, November.
    48. Tian, Lingling & Wei, Chuanhua & Sun, Bing & Wu, Mixia, 2026. "Estimation for partially time-varying spatial autoregressive panel data model under linear constraints," Journal of Multivariate Analysis, Elsevier, vol. 212(C).
    49. He, Bang-Qiang & Hong, Xing-Jian & Fan, Guo-Liang, 2017. "Block empirical likelihood for partially linear panel data models with fixed effects," Statistics & Probability Letters, Elsevier, vol. 123(C), pages 128-138.
    50. Hao Xu & Peilin Wang & Kai Ding, 2024. "Transforming Agriculture: Empirical Insights into How the Digital Economy Elevates Agricultural Productivity in China," Sustainability, MDPI, vol. 16(23), pages 1-20, November.
    51. Lee, Yoonseok & Mukherjee, Debasri & Ullah, Aman, 2019. "Nonparametric estimation of the marginal effect in fixed-effect panel data models," Journal of Multivariate Analysis, Elsevier, vol. 171(C), pages 53-67.
    52. Taining Wang & Feng Yao & Subal C. Kumbhakar, 2024. "A flexible stochastic production frontier model with panel data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(4), pages 564-588, June.
    53. Peter Pütz & Thomas Kneib, 2016. "A Penalized Spline Estimator for Fixed Effects Panel Data Models," SOEPpapers on Multidisciplinary Panel Data Research 827, DIW Berlin, The German Socio-Economic Panel (SOEP).
    54. Feng, Sanying & He, Wenqi & Li, Feng, 2020. "Model detection and estimation for varying coefficient panel data models with fixed effects," Computational Statistics & Data Analysis, Elsevier, vol. 152(C).
    55. Qian, Junhui & Wang, Le, 2012. "Estimating semiparametric panel data models by marginal integration," Journal of Econometrics, Elsevier, vol. 167(2), pages 483-493.
    56. Zongwu Cai & Linna Chen & Ying Fang, 2015. "Semiparametric Estimation of Partially Varying-Coefficient Dynamic Panel Data Models," Econometric Reviews, Taylor & Francis Journals, vol. 34(6-10), pages 695-719, December.
    57. Mishra, Sagarika & Narayan, Paresh Kumar, 2015. "A nonparametric model of financial system and economic growth," International Review of Economics & Finance, Elsevier, vol. 39(C), pages 175-191.
    58. Xuemei Hu & Weiming Yang, 2019. "Semi-parametric small area inference in generalized semi-varying coefficient mixed effects models," Statistical Papers, Springer, vol. 60(4), pages 1039-1058, August.
    59. Lai, Peng & Li, Gaorong & Lian, Heng, 2013. "Semiparametric estimation of fixed effects panel data single-index model," Statistics & Probability Letters, Elsevier, vol. 83(6), pages 1595-1602.
    60. Geng, Xin & Janssens, Wendy & Kramer, Berber, 2017. "Liquid milk: Cash constraints and day-to-day intertemporal choice in financial diaries," IFPRI discussion papers 1602, International Food Policy Research Institute (IFPRI).
    61. De Monte Enrico, 2024. "Nonparametric Instrumental Regression with Two-Way Fixed Effects," Journal of Econometric Methods, De Gruyter, vol. 13(1), pages 49-66, January.
    62. Syed F. Mahmud & Murat Tiniç, 2018. "Herding in Chinese stock markets: a nonparametric approach," Empirical Economics, Springer, vol. 55(2), pages 679-711, September.
    63. Huang, Bai & Lee, Tae-Hwy & Ullah, Aman, 2020. "Combined estimation of semiparametric panel data models," Econometrics and Statistics, Elsevier, vol. 15(C), pages 30-45.
    64. Halder, Shaymal C. & Malikov, Emir, 2020. "Smoothed LSDV estimation of functional-coefficient panel data models with two-way fixed effects," Economics Letters, Elsevier, vol. 192(C).
    65. Lin, Zhongjian & Li, Qi & Sun, Yiguo, 2014. "A consistent nonparametric test of parametric regression functional form in fixed effects panel data models," Journal of Econometrics, Elsevier, vol. 178(P1), pages 167-179.

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

    Cited by:

    1. Sebastian Jensen & Siem Jan Koopman, 2026. "Neural networks for nonlinear regression with serially correlated disturbances: Evidence from cloud cover," Papers 2606.22483, arXiv.org, revised Aug 2026.
    2. Ke Yang, 2012. "Multivariate Local Polynomial Regression With Autocorrelated Errors," Economics Bulletin, AccessEcon, vol. 32(4), pages 3298-3305.
    3. Liu, Jun M. & Chen, Rong & Yao, Qiwei, 2010. "Nonparametric transfer function models," Journal of Econometrics, Elsevier, vol. 157(1), pages 151-164, July.
    4. Tanujit Dey & Kun Ho Kim & Chae Young Lim, 2018. "Bayesian time series regression with nonparametric modeling of autocorrelation," Computational Statistics, Springer, vol. 33(4), pages 1715-1731, December.
    5. Su, Liangjun & Lu, Xun, 2013. "Nonparametric dynamic panel data models: Kernel estimation and specification testing," Journal of Econometrics, Elsevier, vol. 176(2), pages 112-133.
    6. Qi Li & Jeffrey Scott Racine, 2006. "Nonparametric Econometrics: Theory and Practice," Economics Books, Princeton University Press, edition 1, volume 1, number 8355, December.
    7. Ioannis Kyriakou & Parastoo Mousavi & Jens Perch Nielsen & Michael Scholz, 2020. "Longer-Term Forecasting of Excess Stock Returns—The Five-Year Case," Mathematics, MDPI, vol. 8(6), pages 1-20, June.
    8. Ioannis Kyriakou & Parastoo Mousavi & Jens Perch Nielsen & Michael Scholz, 2021. "Short-Term Exuberance and Long-Term Stability: A Simultaneous Optimization of Stock Return Predictions for Short and Long Horizons," Mathematics, MDPI, vol. 9(6), pages 1-19, March.
    9. Liangjun Su & Stefan Hoderlein & Halbert White, 2013. "Testing Monotonicity in Unobservables with Panel Data," Boston College Working Papers in Economics 892, Boston College Department of Economics, revised 01 Feb 2016.
    10. Wei, Honglei & Zhang, Hongfan & Jiang, Hui & Huang, Lei, 2022. "On the semi-varying coefficient dynamic panel data model with autocorrelated errors," Computational Statistics & Data Analysis, Elsevier, vol. 173(C).
    11. Martins-Filho, Carlos & Yao, Feng, 2009. "Nonparametric regression estimation with general parametric error covariance," Journal of Multivariate Analysis, Elsevier, vol. 100(3), pages 309-333, March.
    12. Su, Liangjun & Ullah, Aman, 2008. "Local polynomial estimation of nonparametric simultaneous equations models," Journal of Econometrics, Elsevier, vol. 144(1), pages 193-218, May.
    13. Linton, Oliver & Xiao, Zhijie, 2019. "Efficient estimation of nonparametric regression in the presence of dynamic heteroskedasticity," Journal of Econometrics, Elsevier, vol. 213(2), pages 608-631.
    14. Jacho-Chávez, David & Lewbel, Arthur & Linton, Oliver, 2010. "Identification and nonparametric estimation of a transformed additively separable model," Journal of Econometrics, Elsevier, vol. 156(2), pages 392-407, June.
    15. Enno Mammen & Jens Perch Nielsen & Michael Scholz & Stefan Sperlich, 2019. "Conditional Variance Forecasts for Long-Term Stock Returns," Risks, MDPI, vol. 7(4), pages 1-22, November.
    16. Ioannis Kyriakou & Parastoo Mousavi & Jens Perch Nielsen & Michael Scholz, 2019. "Machine Learning for Forecasting Excess Stock Returns The Five-Year-View," Graz Economics Papers 2019-06, University of Graz, Department of Economics.
    17. Ioannis Kyriakou & Parastoo Mousavi & Jens Perch Nielsen & Michael Scholz, 2020. "Short-Term Exuberance and long-term stability: A simultaneous optimization of stock return predictions for short and long horizons," Graz Economics Papers 2020-20, University of Graz, Department of Economics.
    18. Liangjun Su & Aman Ullah & Yun Wang, 2013. "Nonparametric regression estimation with general parametric error covariance: a more efficient two-step estimator," Empirical Economics, Springer, vol. 45(2), pages 1009-1024, October.

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

    Cited by:

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

Chapters

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

    Cited by:

    1. Ruiqi Liu & Ben Boukai & Zuofeng Shang, 2019. "Statistical Inference on Partially Linear Panel Model under Unobserved Linearity," Papers 1911.08830, arXiv.org.
    2. 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.
    3. 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.
    4. Yufeng Mao & Bin Peng & Mervyn J Silvapulle & Param Silvapulle & Yanrong Yang, 2021. "Decomposition of Bilateral Trade Flows Using a Three-Dimensional Panel Data Model," Monash Econometrics and Business Statistics Working Papers 7/21, Monash University, Department of Econometrics and Business Statistics.
    5. Cheng Hsiao & Yimeng Xie & Qiankun Zhou, 2021. "Factor dimension determination for panel interactive effects models: an orthogonal projection approach," Computational Statistics, Springer, vol. 36(2), pages 1481-1497, June.
    6. Yuki Takara & Shingo Takagi, 2023. "An empirical approach to measure unobserved cultural relations using music trade data," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 47(2), pages 205-245, June.
    7. Wang, Xia & Jin, Sainan & Li, Yingxing & Qian, Junhui & Su, Liangjun, 2025. "On time-varying panel data models with time-varying interactive fixed effects," Journal of Econometrics, Elsevier, vol. 249(PB).
    8. Lu, Xun & Su, Liangjun & Ba, Yinglong, 2026. "On generalized CCE estimation," Journal of Econometrics, Elsevier, vol. 253(C).
    9. Bian, Yulin & Su, Liangjun, 2025. "A note on factor models with latent group structures," Economics Letters, Elsevier, vol. 252(C).
    10. Yang, Zixin & Song, Xiaojun & Yu, Jihai, 2025. "Estimation of spatial autoregressive panel data models with nonparametric endogenous effect," Journal of Econometrics, Elsevier, vol. 252(PA).
    11. Hsiao, Cheng, 2018. "Panel models with interactive effects," Journal of Econometrics, Elsevier, vol. 206(2), pages 645-673.
    12. Wei, Honglei & Zhang, Hongfan & Jiang, Hui & Huang, Lei, 2022. "On the semi-varying coefficient dynamic panel data model with autocorrelated errors," Computational Statistics & Data Analysis, Elsevier, vol. 173(C).
    13. 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.
    14. T. Thomson & S. Hossain, 2018. "Efficient Shrinkage for Generalized Linear Mixed Models Under Linear Restrictions," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 80(2), pages 385-410, August.
    15. Ayden Higgins & Federico Martellosio, 2019. "Shrinkage Estimation of Network Spillovers with Factor Structured Errors," Papers 1909.02823, arXiv.org, revised Nov 2021.
    16. Guohua Feng & Jiti Gao & Bin Peng, 2019. "An Integrated Panel Data Approach to Modelling Economic Growth," Papers 1903.07948, arXiv.org.
    17. Harold D. Chiang & Joel Rodrigue & Yuya Sasaki, 2019. "Post-Selection Inference in Three-Dimensional Panel Data," Papers 1904.00211, arXiv.org, revised Apr 2019.

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

    Cited by:

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

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

    Cited by:

    1. Tae‐Hwy Lee & Shahnaz Parsaeian & Aman Ullah, 2022. "Forecasting Under Structural Breaks Using Improved Weighted Estimation," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 84(6), pages 1485-1501, December.

Books

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

    Cited by:

    1. Antonio Musolesi & Giada Andrea Prete & Michel Simioni, 2025. "Is infrastructure capital really productive? Nonparametric modeling and data-driven model selection in a cross-sectionally dependent panel framework," Journal of Productivity Analysis, Springer, vol. 64(3), pages 439-455, December.
    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. Daouia, Abdelaati & Florens, Jean-Pierre & Simar, Léopold, 2020. "Robust frontier estimation from noisy data: A Tikhonov regularization approach," Econometrics and Statistics, Elsevier, vol. 14(C), pages 1-23.
    4. Alexandra Ferreira‐Lopes & Luís Filipe Martins & Ruben Espanhol, 2020. "The relationship between tax rates and tax revenues in eurozone member countries ‐ exploring the Laffer curve," Bulletin of Economic Research, Wiley Blackwell, vol. 72(2), pages 121-145, April.
    5. Pablo Mitnik & Victoria Bryant & David Grusky, 2018. "A Very Uneven Playing Field: Economic Mobility in the United States," Working Papers 2018-097, Human Capital and Economic Opportunity Working Group.
    6. Steven F. Koch & Jeffrey S. Racine, 2016. "Healthcare facility choice and user fee abolition: regression discontinuity in a multinomial choice setting," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 179(4), pages 927-950, October.
    7. Lewbel, Arthur & Yang, Thomas Tao, 2016. "Identifying the average treatment effect in ordered treatment models without unconfoundedness," Journal of Econometrics, Elsevier, vol. 195(1), pages 1-22.
    8. Patrick Saart & Jiti Gao & Nam Hyun Kim, 2014. "Semiparametric methods in nonlinear time series analysis: a selective review," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 26(1), pages 141-169, March.
    9. D’Haultfœuille, Xavier & Maurel, Arnaud & Zhang, Yichong, 2018. "Extremal quantile regressions for selection models and the black–white wage gap," Journal of Econometrics, Elsevier, vol. 203(1), pages 129-142.
    10. Stefan Faridani, 2024. "Testing for Underpowered Literatures," Papers 2406.13122, arXiv.org, revised Jun 2026.
    11. Henderson, Daniel J. & Simar, Léopold & Wang, Le, 2016. "The Three I's of Public Schools: Irrelevant Inputs, Insufficient Resources and Inefficiency," IZA Discussion Papers 10076, IZA Network @ LISER.
    12. Arthur Lewbel & Xun Lu & Liangjun Su, 2012. "Specification Testing for Transformation Models with an Application to Generalized Accelerated Failure-time Models," Boston College Working Papers in Economics 817, Boston College Department of Economics, revised 01 May 2013.
    13. Steven T. Berry & Philip A. Haile, 2020. "Nonparametric Identification of Differentiated Products Demand Using Micro Data," NBER Working Papers 27704, National Bureau of Economic Research, Inc.
    14. Simioni, Michel & Thomas-Agnan, Christine & Trinh, Thi-Huong, 2017. "A Fresh Look at the Nutrition Transition in Vietnam using Semiparametric Modeling," TSE Working Papers 17-842, Toulouse School of Economics (TSE).
    15. Aman Ullah & Huansha Wang, 2013. "Parametric and Nonparametric Frequentist Model Selection and Model Averaging," Econometrics, MDPI, vol. 1(2), pages 1-23, September.
    16. Deniz Ozabaci & Daniel Henderson, 2015. "Additive kernel estimates of returns to schooling," Empirical Economics, Springer, vol. 48(1), pages 227-251, February.
    17. Simioni, Michel & Thomas-Agnan, Christine & Trinh, Thi-Huong, 2017. "Calorie intake and income in China: New evidence using semiparametric modelling with generalized additive models," TSE Working Papers 17-826, Toulouse School of Economics (TSE).
    18. Feeny, Simon & Vuong, Vu, 2017. "Explaining Aid Project and Program Success: Findings from Asian Development Bank Interventions," World Development, Elsevier, vol. 90(C), pages 329-343.
    19. Yixin (Iris) Wang & George Ball & Gopesh Anand & Hyunwoo Park, 2025. "Obligatory Responses to FDA Inspection Outcomes and Future Drug Shortages," Manufacturing & Service Operations Management, INFORMS, vol. 27(3), pages 789-807, May.
    20. Jean-Pierre Florens & Elia Lapenta, 2024. "Partly linear instrumental variables regressions without smoothing on the instruments," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 33(3), pages 897-920, September.
    21. Isabel Proença & Stefan Sperlich & Duygu Savaşcı, 2015. "Semi-mixed effects gravity models for bilateral trade," Empirical Economics, Springer, vol. 48(1), pages 361-387, February.
    22. Lewbel, Arthur & Tang, Xun, 2015. "Identification and estimation of games with incomplete information using excluded regressors," Journal of Econometrics, Elsevier, vol. 189(1), pages 229-244.
    23. Xu, Ke-Li, 2018. "A semi-nonparametric estimator of regression discontinuity design with discrete duration outcomes," Journal of Econometrics, Elsevier, vol. 206(1), pages 258-278.
    24. Lu, Xun & Su, Liangjun, 2015. "Jackknife model averaging for quantile regressions," Journal of Econometrics, Elsevier, vol. 188(1), pages 40-58.
    25. Etayibtalnam Koudjom & Boris O. K. Lokonon & Aklesso Y. G. Egbendewe, 2024. "Climate Change, Malaria Prevalence and Cereal Yields in Sub-Saharan Africa," The European Journal of Development Research, Palgrave Macmillan;European Association of Development Research and Training Institutes (EADI), vol. 36(5), pages 1171-1197, October.
    26. Geraldine Henningsen & Arne Henningsen & Christian Henning, 2015. "Transaction costs and social networks in productivity measurement," Empirical Economics, Springer, vol. 48(1), pages 493-515, February.
    27. Nir Billfeld & Moshe Kim, 2019. "Semiparametric correction for endogenous truncation bias with Vox Populi based participation decision," Papers 1902.06286, arXiv.org.
    28. Michael S. Delgado & Nadine McCloud, 2017. "Foreign direct investment and the domestic capital stock: the good–bad role of higher institutional quality," Empirical Economics, Springer, vol. 53(4), pages 1587-1637, December.
    29. Arthur Lewbel, 2019. "The Identification Zoo: Meanings of Identification in Econometrics," Journal of Economic Literature, American Economic Association, vol. 57(4), pages 835-903, December.
    30. Olesen, O.B. & Ruggiero, J., 2018. "An improved Afriat–Diewert–Parkan nonparametric production function estimator," European Journal of Operational Research, Elsevier, vol. 264(3), pages 1172-1188.

IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.