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Seung C. Ahn

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. Hong-Kyun Kim & Seung C. Ahn & Jihye Kim, 2012. "Vertical and Horizontal Education-Job Mismatches in the Korean Youth Labor Market : A Quantile Regression Approach," Working Papers 1201, Nam Duck-Woo Economic Research Institute, Sogang University (Former Research Institute for Market Economy).

    Cited by:

    1. Manuel, Nick, 2024. "Does the labour market value field of study specific knowledge? An alignment score based approach," Economics of Education Review, Elsevier, vol. 101(C).
    2. Pérez Navarro, Marco Aurelio, 2021. "University graduates’ job-education mismatches in the Spanish labour market," MPRA Paper 109881, University Library of Munich, Germany.
    3. Guillermo Montt, 2017. "Field-of-study mismatch and overqualification: labour market correlates and their wage penalty," IZA Journal of Labor Economics, Springer;Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), vol. 6(1), pages 1-20, December.

  2. Perez, Marcos & Ahn, Seung Chan, 2007. "GMM Estimation of the Number of Latent Factors," MPRA Paper 4862, University Library of Munich, Germany.

    Cited by:

    1. Eichengreen, Barry & Mody, Ashoka & Nedeljkovic, Milan & Sarno, Lucio, 2012. "How the Subprime Crisis went global: Evidence from bank credit default swap spreads," Journal of International Money and Finance, Elsevier, vol. 31(5), pages 1299-1318.
    2. Castagnetti, Carolina & Rossi, Eduardo, 2008. "Estimation methods in panel data models with observed and unobserved components: a Monte Carlo study," MPRA Paper 26196, University Library of Munich, Germany.

  3. Seung C. Ahn & Young H. Lee & Peter Schmidt, 2007. "Panel Data Models with Multiple Time-Varying Individual Effects," Working Papers 0702, University of Crete, Department of Economics.

    Cited by:

    1. van den Oever, Koen & Beerens, Bart, 2021. "Does task-related conflict mediate the board gender diversity–organizational performance relationship?," European Management Journal, Elsevier, vol. 39(4), pages 445-455.
    2. G. Forchini & Bin Jiang & Bin Peng, 2015. "Common Shocks in panels with Endogenous Regressors," Monash Econometrics and Business Statistics Working Papers 8/15, Monash University, Department of Econometrics and Business Statistics.
    3. Bai, Jushan, 2013. "Likelihood approach to dynamic panel models with interactive effects," MPRA Paper 50267, University Library of Munich, Germany.
    4. Chen, Stacey H. & Chen, Jennjou & Chuang, Hongwei & Lin, Tzu-Hsin, 2023. "Physicians Treating Physicians: Relational and Informational Advantages in Treatment and Survival," IZA Discussion Papers 16048, Institute of Labor Economics (IZA).
    5. Ahn, Seung C. & Perez, M. Fabricio, 2010. "GMM estimation of the number of latent factors: With application to international stock markets," Journal of Empirical Finance, Elsevier, vol. 17(4), pages 783-802, September.
    6. 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.
    7. Sarafidis, Vasilis & Wansbeek, Tom, 2010. "Cross-sectional Dependence in Panel Data Analysis," MPRA Paper 20367, University Library of Munich, Germany.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. Hayakawa, Kazuhiko, 2016. "Identification problem of GMM estimators for short panel data models with interactive fixed effects," Economics Letters, Elsevier, vol. 139(C), pages 22-26.
    13. Norkutė, Milda & Sarafidis, Vasilis & Yamagata, Takashi & Cui, Guowei, 2021. "Instrumental variable estimation of dynamic linear panel data models with defactored regressors and a multifactor error structure," Journal of Econometrics, Elsevier, vol. 220(2), pages 416-446.
    14. Bluszcz, Julia & Valente, Marica, 2020. "The Economic Costs of Hybrid Wars: The Case of Ukraine," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, issue Latest Ar, pages 1-25.
    15. Freeman, Hugo & Weidner, Martin, 2023. "Linear panel regressions with two-way unobserved heterogeneity," Journal of Econometrics, Elsevier, vol. 237(1).
    16. Brantly Callaway & Sonia Karami, 2020. "Treatment Effects in Interactive Fixed Effects Models with a Small Number of Time Periods," Papers 2006.15780, arXiv.org, revised Feb 2022.
    17. Hayakawa, Kazuhiko, 2016. "Improved GMM estimation of panel VAR models," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 240-264.
    18. Hyungsik Roger Roger Moon & Martin Weidner, 2013. "Linear regression for panel with unknown number of factors as interactive fixed effects," CeMMAP working papers 49/13, Institute for Fiscal Studies.
    19. Juodis, Artūras & Karabiyik, Hande & Westerlund, Joakim, 2021. "On the robustness of the pooled CCE estimator," Journal of Econometrics, Elsevier, vol. 220(2), pages 325-348.
    20. Bin Peng & Liangjun Su & Joakim Westerlund & Yanrong Yang, 2021. "Interactive Effects Panel Data Models with General Factors and Regressors," Papers 2111.11506, arXiv.org.
    21. Subal C. Kumbhakar & Robin Sickles & Hung-Jen Wang, 2023. "Introduction," Empirical Economics, Springer, vol. 64(6), pages 2467-2474, June.
    22. Denis Chetverikov & Elena Manresa, 2022. "Spectral and post-spectral estimators for grouped panel data models," Papers 2212.13324, arXiv.org, revised Dec 2022.
    23. Shanti Gamper-Rabindran & Shakeeb Khan & Christopher Timmins, 2008. "The Impact of Piped Water Provision on Infant Mortality in Brazil: A Quantile Panel Data Approach," NBER Working Papers 14365, National Bureau of Economic Research, Inc.
    24. Robin C. Sickles & Jiaqi Hao & Chenjun Shang, 2014. "Panel data and productivity measurement: an analysis of Asian productivity trends," Journal of Chinese Economic and Business Studies, Taylor & Francis Journals, vol. 12(3), pages 211-231, August.
    25. Gobillon, Laurent & Magnac, Thierry, 2013. "Regional Policy Evaluation:Interactive Fixed Effects and Synthetic Controls," TSE Working Papers 13-419, Toulouse School of Economics (TSE).
    26. Hyungsik Roger Roger Moon & Martin Weidner, 2014. "Linear regression for panel with unknown number of factors as interactive fixed effects," CeMMAP working papers 35/14, Institute for Fiscal Studies.
    27. G. Forchini & Bin Jiang & Bin Peng, 2015. "Consistent Estimation in Large Heterogeneous Panels with Multifactor Structure Endogeneity," Monash Econometrics and Business Statistics Working Papers 14/15, Monash University, Department of Econometrics and Business Statistics.
    28. Naima Chrid & Sami Saafi & Mohamed Chakroun, 2021. "Export Upgrading and Economic Growth: a Panel Cointegration and Causality Analysis," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 12(2), pages 811-841, June.
    29. Moon, Hyungsik Roger & Shum, Matthew & Weidner, Martin, 2018. "Estimation of random coefficients logit demand models with interactive fixed effects," Journal of Econometrics, Elsevier, vol. 206(2), pages 613-644.
    30. Arturas Juodis & Yiannis Karavias & Vasilis Sarafidis, 2020. "A Homogeneous Approach to Testing for Granger Non-Causality in Heterogeneous Panels," Monash Econometrics and Business Statistics Working Papers 32/20, Monash University, Department of Econometrics and Business Statistics.
    31. Sickles, Robin C. & Hao, Jiaqi & Shang, Chenjun, 2015. "Panel Data and Productivity Measurement," Working Papers 15-018, Rice University, Department of Economics.
    32. 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.
    33. Joakim Westerlund, 2020. "A cross‐section average‐based principal components approach for fixed‐T panels," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(6), pages 776-785, September.
    34. 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.
    35. Weili Ding & Steven F. Lehrer, 2014. "Understanding the Role of Time-Varying Unobserved Ability Heterogeneity in Education Production," NBER Working Papers 19937, National Bureau of Economic Research, Inc.
    36. Williams, Benjamin, 2020. "Nonparametric identification of discrete choice models with lagged dependent variables," Journal of Econometrics, Elsevier, vol. 215(1), pages 286-304.
    37. Shasha Liu & Robin Sickles, 2021. "The agency problem revisited: a structural analysis of managerial productivity and CEO compensation in large US commercial banks," Empirical Economics, Springer, vol. 60(1), pages 391-418, January.
    38. William Horrace & Seth Richards-Shubik, 2013. "Expected Efficiency Ranks From Parametric Stochastic Fronteir Models," Center for Policy Research Working Papers 153, Center for Policy Research, Maxwell School, Syracuse University.
    39. Hugo Freeman & Martin Weidner, 2021. "Linear Panel Regressions with Two-Way Unobserved Heterogeneity," Papers 2109.11911, arXiv.org, revised Aug 2022.
    40. Artūras Juodis & Vasilis Sarafidis, 2018. "Fixed T dynamic panel data estimators with multifactor errors," Econometric Reviews, Taylor & Francis Journals, vol. 37(8), pages 893-929, September.
    41. Piracha, Matloob & Tani, Massimiliano & Tchuente, Guy, 2017. "Immigration Policy and Remittance Behaviour," GLO Discussion Paper Series 94, Global Labor Organization (GLO).
    42. Giovanni Forchini & Bin Jiang & Bin Peng, 2018. "TSLS and LIML Estimators in Panels with Unobserved Shocks," Econometrics, MDPI, vol. 6(2), pages 1-12, April.
    43. 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.
    44. Westerlund, Joakim, 2019. "Testing additive versus interactive effects in fixed-T panels," Economics Letters, Elsevier, vol. 174(C), pages 5-8.
    45. Perez, Marcos & Ahn, Seung Chan, 2007. "GMM Estimation of the Number of Latent Factors," MPRA Paper 4862, University Library of Munich, Germany.
    46. Milda Norkuté & Vasilis Sarafidis & Takashi Yamagata, 2018. "Instrumental Variable Estimation of Dynamic Linear Panel Data Models with Defactored Regressors and a Multifactor Error Structure," ISER Discussion Paper 1019, Institute of Social and Economic Research, The University of Osaka.
    47. Almanidis, Pavlos & Karagiannis, Giannis & Sickles, Robin C., 2015. "Semi-nonparametric Spline Modifications to the Cornwell-Schmidt-Sickles Estimator: An Analysis of U.S. Banking Productivity," Working Papers 15-008, Rice University, Department of Economics.
    48. Wu, Jianhong & Li, Jinchang, 2014. "Testing for individual and time effects in panel data models with interactive effects," Economics Letters, Elsevier, vol. 125(2), pages 306-310.
    49. Duygun, Meryem & Kutlu, Levent & Sickles, Robin C., 2014. "Measuring Productivity and Efficiency: A Kalman," Working Papers 15-010, Rice University, Department of Economics.
    50. Brown Nicholas L., 2024. "Moment-Based Estimation of Linear Panel Data Models with Factor-Augmented Errors," Journal of Econometric Methods, De Gruyter, vol. 13(2), pages 299-317.
    51. 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.
    52. 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.
    53. Hyungsik Roger Moon & Matthew Shum & Martin Weidner, 2017. "Estimation of random coefficients logit demand models with interactive fixed effects," CeMMAP working papers 12/17, Institute for Fiscal Studies.
    54. Li, Si & Perez, M. Fabricio, 2021. "The evolution of pay premiums for managerial attributes," Journal of Corporate Finance, Elsevier, vol. 69(C).
    55. 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.
    56. Meryem Duygun & Levent Kutlu & Robin C. Sickles, 2016. "Measuring productivity and efficiency: a Kalman filter approach," Journal of Productivity Analysis, Springer, vol. 46(2), pages 155-167, December.
    57. Hayakawa, Kazuhiko, 2018. "Corrected standard errors for optimal minimum distance estimator," Economics Letters, Elsevier, vol. 167(C), pages 5-9.
    58. Guohua Feng & Bin Peng & Xiaohui Zhang, 2017. "Productivity and efficiency at bank holding companies in the U.S.: a time-varying heterogeneity approach," Journal of Productivity Analysis, Springer, vol. 48(2), pages 179-192, December.
    59. Ayden Higgins, 2021. "Fixed $T$ Estimation of Linear Panel Data Models with Interactive Fixed Effects," Papers 2110.05579, arXiv.org.
    60. Guido M. Kuersteiner & Ingmar R. Prucha, 2015. "Dynamic Spatial Panel Models: Networks, Common Shocks, and Sequential Exogeneity," CESifo Working Paper Series 5445, CESifo.
    61. Wei Tian, 2023. "Individual Causal Inference Using Panel Data With Multiple Outcomes," Papers 2306.01969, arXiv.org.
    62. Hugo Freeman & Martin Weidner, 2021. "Linear panel regressions with two-way unobserved heterogeneity," CeMMAP working papers CWP39/21, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    63. Artūras Juodis & Vasilis Sarafidis, 2022. "A Linear Estimator for Factor-Augmented Fixed-T Panels With Endogenous Regressors," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(1), pages 1-15, January.
    64. Hyungsik Roger Moon & Martin Weidner, 2013. "Linear regression for panel with unknown number of factors as interactive fixed effects," CeMMAP working papers CWP49/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    65. Robertson, Donald & Sarafidis, Vasilis, 2015. "IV estimation of panels with factor residuals," Journal of Econometrics, Elsevier, vol. 185(2), pages 526-541.
    66. Young Hoon Lee, 2016. "Common Factors in Major League Baseball Game Attendance," Working Papers 1604, Nam Duck-Woo Economic Research Institute, Sogang University (Former Research Institute for Market Economy).
    67. Artūras Juodis, 2018. "Pseudo Panel Data Models With Cohort Interactive Effects," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 36(1), pages 47-61, January.
    68. Kerda Varaku & Robin Sickles, 2023. "Public subsidies and innovation: a doubly robust machine learning approach leveraging deep neural networks," Empirical Economics, Springer, vol. 64(6), pages 3121-3165, June.
    69. 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.
    70. Robin C. Sickles & Wonho Song & Valentin Zelenyuk, 2018. "Econometric Analysis of Productivity: Theory and Implementation in R," CEPA Working Papers Series WP082018, School of Economics, University of Queensland, Australia.
    71. Jinyong Hahn & Ruoyao Shi, 2017. "Synthetic Control and Inference," Econometrics, MDPI, vol. 5(4), pages 1-12, November.
    72. Mohamed Chakroun & Naima Chrid & Sami Saafi, 2021. "Does export upgrading really matter to economic growth? Evidence from panel data for high‐, middle‐ and low‐income countries," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(4), pages 5584-5609, October.
    73. Tsionas, Mike G. & Mamatzakis, Emmanuel, 2019. "Further results on estimating inefficiency effects in stochastic frontier models," European Journal of Operational Research, Elsevier, vol. 275(3), pages 1157-1164.
    74. Greenaway-McGrevy, Ryan & Han, Chirok & Sul, Donggyu, 2012. "Asymptotic distribution of factor augmented estimators for panel regression," Journal of Econometrics, Elsevier, vol. 169(1), pages 48-53.
    75. Yongcheol Shin, 2007. "Comments on: Panel data analysis—advantages and challenges," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 16(1), pages 52-55, May.
    76. Hayakawa, Kazuhiko, 2019. "Alternative over-identifying restriction test in the GMM estimation of panel data models," Econometrics and Statistics, Elsevier, vol. 10(C), pages 71-95.
    77. Yana Petrova & Joakim Westerlund, 2020. "Fixed effects demeaning in the presence of interactive effects in treatment effects regressions and elsewhere," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(7), pages 960-964, November.
    78. Chen, Liang, 2015. "Set identification of panel data models with interactive effects via quantile restrictions," Economics Letters, Elsevier, vol. 137(C), pages 36-40.
    79. Hsiao, Cheng, 2018. "Panel models with interactive effects," Journal of Econometrics, Elsevier, vol. 206(2), pages 645-673.
    80. Yan Sun & Wei Huang, 2022. "Quasi-maximum likelihood estimation of short panel data models with time-varying individual effects," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 85(1), pages 93-114, January.
    81. Nicholas Brown, 2023. "Information Equivalence among Transformations of Semi‐parametric Nonlinear Panel Data Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 85(6), pages 1341-1361, December.
    82. Wu, Jianhong, 2020. "A joint test for serial correlation and heteroscedasticity in fixed-T panel regression models with interactive effects," Economics Letters, Elsevier, vol. 197(C).
    83. Francesco Bartolucci & Federico Belotti & Franco Peracchi, 2013. "Testing for Time-Invariant Unobserved Heterogeneity in Generalized Linear Models for Panel Data," EIEF Working Papers Series 1312, Einaudi Institute for Economics and Finance (EIEF), revised May 2013.
    84. Seung C. Ahn & Young H. Lee, 2014. "Major League Baseball Attendance," Journal of Sports Economics, , vol. 15(5), pages 451-477, October.
    85. Geert Mesters & Victor van der Geest & Catrien Bijleveld, 2014. "Crime, Employment and Social Welfare: an Individual-level Study on Disadvantaged Males," Tinbergen Institute Discussion Papers 14-091/III, Tinbergen Institute.
    86. Castagnetti, Carolina & Rossi, Eduardo, 2008. "Estimation methods in panel data models with observed and unobserved components: a Monte Carlo study," MPRA Paper 26196, University Library of Munich, Germany.
    87. 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.
    88. Ayden Higgins & Federico Martellosio, 2019. "Shrinkage Estimation of Network Spillovers with Factor Structured Errors," Papers 1909.02823, arXiv.org, revised Nov 2021.
    89. KiHoon Jimmy Hong & Bin Peng & Xiaohui Zhang, 2014. "Capturing the Impact of Latent Industry-Wide Shocks with Dynamic Panel Model," Research Paper Series 347, Quantitative Finance Research Centre, University of Technology, Sydney.
    90. De Vos, Ignace & Westerlund, Joakim, 2019. "On CCE estimation of factor-augmented models when regressors are not linear in the factors," Economics Letters, Elsevier, vol. 178(C), pages 5-7.
    91. Giovanni Forchini & Bin Jiang & Bin Peng, 2015. "Consistent Estimation in Large Heterogeneous Panels with Multifactor Structure and Endogeneity," School of Economics Discussion Papers 0315, School of Economics, University of Surrey.
    92. Fedotenkov, Igor & Idrisov, Georgy, 2021. "A supply-demand model of public sector size," Economic Systems, Elsevier, vol. 45(2).
    93. Bai, Jushan & Li, Kunpeng, 2021. "Dynamic spatial panel data models with common shocks," Journal of Econometrics, Elsevier, vol. 224(1), pages 134-160.
    94. Bin Peng & Giovanni Forchini, 2014. "Consistent Estimation of Panel Data Models with a Multifactor Error Structure when the Cross Section Dimension is Large," Working Paper Series 20, Economics Discipline Group, UTS Business School, University of Technology, Sydney.
    95. Laurent Gobillon & François-Charles Wolff, 2015. "Évaluer l’effet des politiques publiques locales avec les contrôles synthétiques et les modèles à facteurs : Une application au marché du poisson français," Working Papers halshs-01183455, HAL.
    96. Juodis, Arturas & Sarafidis, Vasilis, 2020. "Online Supplement to An Incidental Parameters Free Inference Approach for Panels with Common Shocks," MPRA Paper 104908, University Library of Munich, Germany.
    97. Marco Barassi & Yiannis Karavias & Chongxian Zhu, 2023. "Threshold Regression in Heterogeneous Panel Data with Interactive Fixed Effects," Papers 2308.04057, arXiv.org.
    98. Nicholas L. Brown & Peter Schmidt & Jeffrey M. Wooldridge, 2021. "Simple Alternatives to the Common Correlated Effects Model," Papers 2112.01486, arXiv.org.
    99. 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.
    100. Bai, Jushan & Li, Kunpeng, 2013. "Spatial panel data models with common shocks," MPRA Paper 52786, University Library of Munich, Germany, revised 09 Mar 2014.
    101. 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.
    102. Timothy B. Armstrong & Martin Weidner & Andrei Zeleneev, 2022. "Robust Estimation and Inference in Panels with Interactive Fixed Effects," Papers 2210.06639, arXiv.org, revised Dec 2024.
    103. Moyle, Brent D. & Scherrer, Pascal & Weiler, Betty & Wilson, Erica & Caldicott, Rod & Nielsen, Noah, 2017. "Assessing preferences of potential visitors for nature-based experiences in protected areas," Tourism Management, Elsevier, vol. 62(C), pages 29-41.
    104. Nayoung Lee & Hyungsik Roger Moon, 2021. "Heterogeneous Income Profiles Model with Fixed Effects: Incorporating Labour Income Shocks," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 83(6), pages 1377-1407, December.
    105. 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.
    106. Westerlund, Joakim & Norkute, Milda, 2014. "A Factor Analytical Method to Interactive Effects Dynamic Panel Models with or without Unit Root," Working Papers 2014:12, Lund University, Department of Economics.
    107. 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.
    108. Robert F. Phillips & Benjamin D. Williams, 2024. "A Simple Interactive Fixed Effects Estimator for Short Panels," Papers 2410.12709, arXiv.org.
    109. 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.
    110. Ignace De Vos & Gerdie Everaert, 2016. "Bias-Corrected Common Correlated Effects Pooled Estimation In Homogeneous Dynamic Panels," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 16/920, Ghent University, Faculty of Economics and Business Administration.
    111. 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.
    112. Bada, Oualid & Kneip, Alois, 2014. "Parameter cascading for panel models with unknown number of unobserved factors: An application to the credit spread puzzle," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 95-115.
    113. Anthony N. Rezitis, 2015. "Empirical Analysis of Agricultural Commodity Prices, Crude Oil Prices and US Dollar Exchange Rates using Panel Data Econometric Methods," International Journal of Energy Economics and Policy, Econjournals, vol. 5(3), pages 851-868.
    114. Kuersteiner, Guido M. & Prucha, Ingmar R., 2013. "Limit theory for panel data models with cross sectional dependence and sequential exogeneity," Journal of Econometrics, Elsevier, vol. 174(2), pages 107-126.
    115. Lina Lu, 2017. "Simultaneous Spatial Panel Data Models with Common Shocks," Supervisory Research and Analysis Working Papers RPA 17-3, Federal Reserve Bank of Boston.
    116. Matthew Harding & Carlos Lamarche & Chris Muris, 2022. "Estimation of a Factor-Augmented Linear Model with Applications Using Student Achievement Data," Papers 2203.03051, arXiv.org.
    117. Julia Bluszcz & Marica Valente, 2019. "The War in Europe: Economic Costs of the Ukrainian Conflict," Discussion Papers of DIW Berlin 1804, DIW Berlin, German Institute for Economic Research.
    118. Bada, Oualid & Liebl, Dominik, 2014. "phtt: Panel Data Analysis with Heterogeneous Time Trends in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 59(i06).
    119. 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.

  4. Gareth M. Thomas & Seung C. Ahn, 2004. "Likelihood Based Inference for amic Panel Data Models," Econometric Society 2004 Far Eastern Meetings 669, Econometric Society.

    Cited by:

    1. Kruiniger, Hugo, 2018. "A further look at Modified ML estimation of the panel AR(1) model with fixed effects and arbitrary initial conditions," MPRA Paper 88623, University Library of Munich, Germany.

  5. Chan Ahn, S. & Lee, Y.H., 1994. "GMM Estimation of a Panel Data Regression Model with Time-Varying Individual Effects," Papers 9401, Michigan State - Econometrics and Economic Theory.

    Cited by:

    1. Martin Ravallion, 2003. "Externalities in Rural Development: Evidence for China," WIDER Working Paper Series DP2003-54, World Institute for Development Economic Research (UNU-WIDER).
    2. Luis R. Murillo‐Zamorano, 2004. "Economic Efficiency and Frontier Techniques," Journal of Economic Surveys, Wiley Blackwell, vol. 18(1), pages 33-77, February.
    3. Massimiliano Agovino & Agnese Rapposelli, 2015. "Agglomeration externalities and technical efficiency in Italian regions," Quality & Quantity: International Journal of Methodology, Springer, vol. 49(5), pages 1803-1822, September.

  6. Ahn, S.C. & Schmidt, P., 1993. "Efficient Estimation of Dynamic Panel Data Models Under Alternative Sets of Assumptions," Papers 9200, Michigan State - Econometrics and Economic Theory.

    Cited by:

    1. Crepon, Bruno & Kramarz, Francis & Trognon, Alain, 1997. "Parameters of interest, nuisance parameters and orthogonality conditions An application to autoregressive error component models," Journal of Econometrics, Elsevier, vol. 82(1), pages 135-156.

Articles

  1. Ahn, Seung C. & Lee, Young H. & Schmidt, Peter, 2013. "Panel data models with multiple time-varying individual effects," Journal of Econometrics, Elsevier, vol. 174(1), pages 1-14.
    See citations under working paper version above.
  2. Ahn, Seung C. & Perez, M. Fabricio & Gadarowski, Christopher, 2013. "Two-pass estimation of risk premiums with multicollinear and near-invariant betas," Journal of Empirical Finance, Elsevier, vol. 20(C), pages 1-17.

    Cited by:

    1. Annaert, Jan & De Ceuster, Marc & Verstegen, Kurt, 2013. "Are extreme returns priced in the stock market? European evidence," Journal of Banking & Finance, Elsevier, vol. 37(9), pages 3401-3411.
    2. Seung C. Ahn & Alex R. Horenstein, 2017. "Asset Pricing and Excess Returns over the Market Return," Working Papers 2017-12, University of Miami, Department of Economics.
    3. Michael Curran & Adnan Velic, 2018. "The CAPM, National Stock Market Betas, and Macroeconomic Covariates: A Global Analysis," Trinity Economics Papers tep0618, Trinity College Dublin, Department of Economics.

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  4. Seung C. Ahn & Josef C. Brada & Jos� A. M�ndez, 2012. "Effort, Technology and the Efficiency of Agricultural Cooperatives," Journal of Development Studies, Taylor & Francis Journals, vol. 48(11), pages 1601-1616, November.

    Cited by:

    1. Hansen, Rebecca & Hess, Sebastian, 2023. "The Pricing Efficiency of German Wine Cooperatives: A Hedonic Metafrontier Approach," GEWISOLA 63rd Annual Conference, Goettingen, Germany, September 20-22, 2023 344240, GEWISOLA.
    2. Jasper GRASHUIS & Ye SU, 2019. "A Review Of The Empirical Literature On Farmer Cooperatives: Performance, Ownership And Governance, Finance, And Member Attitude," Annals of Public and Cooperative Economics, Wiley Blackwell, vol. 90(1), pages 77-102, March.
    3. Sebhatu, Kifle T. & Gezahegn, Tafesse W. & Berhanu, Tekeste & Maertens, Miet & Passel, Steven Van & D'Haese, Marijke, 2021. "Exploring variability across cooperatives: economic performance of agricultural cooperatives in northern Ethiopia," International Food and Agribusiness Management Review, International Food and Agribusiness Management Association, vol. 24(3), March.
    4. Yang Zou & Qingbin Wang, 2022. "Impacts of farmer cooperative membership on household income and inequality: Evidence from a household survey in China," Agricultural and Food Economics, Springer;Italian Society of Agricultural Economics (SIDEA), vol. 10(1), pages 1-17, December.
    5. Kuhle Prudence Mnisi & Abdul Latif Alhassan, 2021. "Financial structure and cooperative efficiency: A pecking‐order evidence from sugarcane farmers in Eswatini," Annals of Public and Cooperative Economics, Wiley Blackwell, vol. 92(2), pages 261-281, June.
    6. Hironori Yagi & Tsuneo Hayashi, 2021. "Machinery utilization and management organization in Japanese rice farms: Comparison of single‐family, multifamily, and community farms," Agribusiness, John Wiley & Sons, Ltd., vol. 37(2), pages 393-408, April.
    7. Yagi, Hironori & Hayashi, Tsuneo, 2021. "Working conditions and labor flexibility in non-family farms: weather-based labor management by Japanese paddy rice corporations," International Food and Agribusiness Management Review, International Food and Agribusiness Management Association, vol. 24(2), February.

  5. Seung C. Ahn & Christopher Gadarowski & M. Fabricio Perez, 2012. "Robust Two-Pass Cross-Sectional Regressions: A Minimum Distance Approach," Journal of Financial Econometrics, Oxford University Press, vol. 10(4), pages 669-701, September.

    Cited by:

    1. 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.
    2. Hirukawa, Masayuki, 2023. "Robust Covariance Matrix Estimation in Time Series: A Review," Econometrics and Statistics, Elsevier, vol. 27(C), pages 36-61.

  6. Ahn, Seung C. & Perez, M. Fabricio, 2010. "Corrigendum to "GMM estimation of the number of latent factors: With application to international stock markets" [J Empir Financ. 17 (2010) 783-802]," Journal of Empirical Finance, Elsevier, vol. 17(5), pages 1006-1006, December.

    Cited by:

    1. Mu Lin & Zhengdong Huang & Tianhong Zhao & Ying Zhang & Heyi Wei, 2022. "Spatiotemporal Evolution of Travel Pattern Using Smart Card Data," Sustainability, MDPI, vol. 14(15), pages 1-16, August.
    2. Jiang, Pan & Perez, M. Fabricio, 2021. "Follow the leader: Index tracking with factor models," Journal of Empirical Finance, Elsevier, vol. 64(C), pages 337-350.
    3. Perez, M. Fabricio & Shkilko, Andriy & Sokolov, Konstantin, 2015. "Factor models for binary financial data," Journal of Banking & Finance, Elsevier, vol. 61(S2), pages 177-188.

  7. Ahn, Seung C. & Perez, M. Fabricio, 2010. "GMM estimation of the number of latent factors: With application to international stock markets," Journal of Empirical Finance, Elsevier, vol. 17(4), pages 783-802, September.

    Cited by:

    1. Mu Lin & Zhengdong Huang & Tianhong Zhao & Ying Zhang & Heyi Wei, 2022. "Spatiotemporal Evolution of Travel Pattern Using Smart Card Data," Sustainability, MDPI, vol. 14(15), pages 1-16, August.
    2. Jiang, Pan & Perez, M. Fabricio, 2021. "Follow the leader: Index tracking with factor models," Journal of Empirical Finance, Elsevier, vol. 64(C), pages 337-350.
    3. Xiao Fan Liu & Chi K. Tse, 2012. "Dynamics of Network of Global Stock Markets," Accounting and Finance Research, Sciedu Press, vol. 1(2), pages 1-1, November.
    4. Perez, M. Fabricio & Shkilko, Andriy & Sokolov, Konstantin, 2015. "Factor models for binary financial data," Journal of Banking & Finance, Elsevier, vol. 61(S2), pages 177-188.
    5. Seung C. Ahn & Stephan Dieckmann & M. Fabricio Perez, 2018. "Is there a missing factor? A canonical correlation approach to factor models," Review of Financial Economics, John Wiley & Sons, vol. 36(4), pages 321-347, October.

  8. Seung Ahn & Young Lee & Peter Schmidt, 2007. "Stochastic frontier models with multiple time-varying individual effects," Journal of Productivity Analysis, Springer, vol. 27(1), pages 1-12, February.

    Cited by:

    1. Lin, Winston T. & Chen, Yueh H. & Chou, Chia-Ching, 2021. "Assessing the business values of e-commerce and information technology separately and jointly and their impacts upon US firms' performance as measured by productive efficiency," International Journal of Production Economics, Elsevier, vol. 241(C).
    2. Ahn, Seung C. & Perez, M. Fabricio, 2010. "GMM estimation of the number of latent factors: With application to international stock markets," Journal of Empirical Finance, Elsevier, vol. 17(4), pages 783-802, September.
    3. Young Hoon Lee, 2009. "Estimation of Temporal Variations in Fan Loyalty: Application of Multi-Factor Models," Working Papers 0902, Nam Duck-Woo Economic Research Institute, Sogang University (Former Research Institute for Market Economy), revised 2009.
    4. Young H. Lee, 2014. "Stochastic Frontier Models Using GAUSS," Working Papers 1403, Nam Duck-Woo Economic Research Institute, Sogang University (Former Research Institute for Market Economy).
    5. Sickles, Robin C. & Hao, Jiaqi & Shang, Chenjun, 2015. "Panel Data and Productivity Measurement," Working Papers 15-018, Rice University, Department of Economics.
    6. Camilla Mastromarco & Laura Serlenga & Yongcheol Shin, 2023. "Regional Productivity Network in the EU," CESifo Working Paper Series 10404, CESifo.
    7. Antonio Alvarez & Carlos Arias, 2014. "A selection of relevant issues in applied stochastic frontier analysis," Economics and Business Letters, Oviedo University Press, vol. 3(1), pages 3-11.
    8. Young Hoon Lee & Jungsoo Park, 2024. "Middle‐income country trap and total factor productivity growth," Pacific Economic Review, Wiley Blackwell, vol. 29(2), pages 214-229, May.
    9. Camilla Mastromarco & Laura Serlenga & Yongcheol Shin, 2012. "Is Globalization Driving Efficiency? A Threshold Stochastic Frontier Panel Data Modeling Approach," Review of International Economics, Wiley Blackwell, vol. 20(3), pages 563-579, August.
    10. Sakano, Ryoichi & Obeng, Kofi, 2011. "Examining the Inefficiency of Transit Systems Using Latent Class Stochastic Frontier Models," Journal of the Transportation Research Forum, Transportation Research Forum, vol. 50(2).
    11. Perez, Marcos & Ahn, Seung Chan, 2007. "GMM Estimation of the Number of Latent Factors," MPRA Paper 4862, University Library of Munich, Germany.
    12. Almanidis, Pavlos & Karagiannis, Giannis & Sickles, Robin C., 2015. "Semi-nonparametric Spline Modifications to the Cornwell-Schmidt-Sickles Estimator: An Analysis of U.S. Banking Productivity," Working Papers 15-008, Rice University, Department of Economics.
    13. Roman Matkovskyy, 2016. "Arbitrary temporal heterogeneity in time of European countries panel model," Economics Bulletin, AccessEcon, vol. 36(1), pages 576-587.
    14. Ahn, Seung C. & Lee, Young H. & Schmidt, Peter, 2013. "Panel data models with multiple time-varying individual effects," Journal of Econometrics, Elsevier, vol. 174(1), pages 1-14.
    15. Guohua Feng & Bin Peng & Xiaohui Zhang, 2017. "Productivity and efficiency at bank holding companies in the U.S.: a time-varying heterogeneity approach," Journal of Productivity Analysis, Springer, vol. 48(2), pages 179-192, December.
    16. Robin C. Sickles & Wonho Song & Valentin Zelenyuk, 2018. "Econometric Analysis of Productivity: Theory and Implementation in R," CEPA Working Papers Series WP082018, School of Economics, University of Queensland, Australia.
    17. Mastromarco Camilla & Laura Serlenga & Yongcheol Shin, 2013. "Globalisation and technological convergence in the EU," Journal of Productivity Analysis, Springer, vol. 40(1), pages 15-29, August.
    18. Grigorios Emvalomatis, 2012. "Adjustment and unobserved heterogeneity in dynamic stochastic frontier models," Journal of Productivity Analysis, Springer, vol. 37(1), pages 7-16, February.
    19. Young Hoon Lee, 2010. "The Effects of Management Practices on Productivity: Evidence from Baseball Team Production," Working Papers 1005, Nam Duck-Woo Economic Research Institute, Sogang University (Former Research Institute for Market Economy), revised 2010.
    20. Bao Hoang Nguyen & Robin C. Sickles & Valentin Zelenyuk, 2022. "Efficiency Analysis with Stochastic Frontier Models Using Popular Statistical Softwares," Springer Books, in: Duangkamon Chotikapanich & Alicia N. Rambaldi & Nicholas Rohde (ed.), Advances in Economic Measurement, chapter 0, pages 129-171, Springer.
    21. Chen, Yueh H. & Lin, Winston T., 2009. "Analyzing the relationships between information technology, inputs substitution and national characteristics based on CES stochastic frontier production models," International Journal of Production Economics, Elsevier, vol. 120(2), pages 552-569, August.
    22. Roman Matkovskyy, 2016. "A comparison of pre- and post-crisis efficiency of OECD countries: evidence from a model with temporal heterogeneity in time and unobservable individual effect," European Journal of Comparative Economics, Cattaneo University (LIUC), vol. 13(2), pages 135-167, December.
    23. Dang, Viet Anh & Kim, Minjoo & Shin, Yongcheol, 2015. "In search of robust methods for dynamic panel data models in empirical corporate finance," Journal of Banking & Finance, Elsevier, vol. 53(C), pages 84-98.
    24. Bao Hoang Nguyen & Robin C. Sickles & Valentin Zelenyuk, 2021. "What do we know from the vast literature on efficiency and productivity in healthcare? A Systematic Review and Bibliometric Analysis," CEPA Working Papers Series WP092021, School of Economics, University of Queensland, Australia.
    25. Hsu, Chih-Chiang & Lin, Chang-Ching & Yin, Shou-Yung, 2012. "Estimation of a panel stochastic frontier model with unobserved common shocks," MPRA Paper 37313, University Library of Munich, Germany.
    26. Young Hoon Lee, 2009. "Frontier Models and their Application to the Sports Industry," Working Papers 0903, Nam Duck-Woo Economic Research Institute, Sogang University (Former Research Institute for Market Economy), revised 2009.
    27. Bernd Frick & Young Lee, 2011. "Temporal variations in technical efficiency: evidence from German soccer," Journal of Productivity Analysis, Springer, vol. 35(1), pages 15-24, February.

  9. Ahn, Seung C. & Gadarowski, Christopher, 2004. "Small sample properties of the GMM specification test based on the Hansen-Jagannathan distance," Journal of Empirical Finance, Elsevier, vol. 11(1), pages 109-132, January.

    Cited by:

    1. Gospodinov, Nikolay & Kan, Raymond & Robotti, Cesare, 2013. "Chi-squared tests for evaluation and comparison of asset pricing models," Journal of Econometrics, Elsevier, vol. 173(1), pages 108-125.
    2. Paul Gao & Kevin X. D. Huang, 2004. "Aggregate consumption-wealth ratio and the cross-section of stock returns: some international evidence," Research Working Paper RWP 04-07, Federal Reserve Bank of Kansas City.
    3. Gospodinov, Nikolay & Robotti, Cesare, 2021. "Common pricing across asset classes: Empirical evidence revisited," Journal of Financial Economics, Elsevier, vol. 140(1), pages 292-324.
    4. Horim Kim & Jaeyoung Kim & Kyungmyung Jang & Jaemin Han, 2020. "Are the Blockchain-Based Patents Sustainable for Increasing Firm Value?," Sustainability, MDPI, vol. 12(5), pages 1-17, February.
    5. Liguo Zhang & Cuiting Jiang & Xiang Cai & Jun Wu, 2023. "Dynamic linkages between China’s OFDI, transport, and green economic growth: Empirical evidence from the B&R countries," Energy & Environment, , vol. 34(7), pages 2642-2667, November.
    6. Jiayu Liu & Feng Xu & Huan Wang & Xiao Zhang, 2023. "Investigating the Impacts of Built-Up Land Allocation on Carbon Emissions in 88 Cities of the Yangtze River Economic Belt Based on Panel Regressions," Land, MDPI, vol. 12(4), pages 1-15, April.
    7. Zhang, Xiaoyan, 2006. "Specification tests of international asset pricing models," Journal of International Money and Finance, Elsevier, vol. 25(2), pages 275-307, March.
    8. Geert Bekaert & Campbell R. Harvey & Christian Lundblad, 2005. "Liquidity and Expected Returns: Lessons From Emerging Markets," NBER Working Papers 11413, National Bureau of Economic Research, Inc.
    9. Ren, Yu & Shimotsu, Katsumi, 2009. "Improvement in finite sample properties of the Hansen-Jagannathan distance test," Journal of Empirical Finance, Elsevier, vol. 16(3), pages 483-506, June.
    10. Ray, Surajit & Savin, N.E. & Tiwari, Ashish, 2009. "Testing the CAPM revisited," Journal of Empirical Finance, Elsevier, vol. 16(5), pages 721-733, December.
    11. Carlos Enrique Carrasco-Gutierrez & Wagner Piazza Gaglianone, 2012. "Evaluating Asset Pricing Models in a Simulated Multifactor Approach," Brazilian Review of Finance, Brazilian Society of Finance, vol. 10(4), pages 425-460.
    12. Fletcher, Jonathan, 2014. "Benchmark models of expected returns in U.K. portfolio performance: An empirical investigation," International Review of Economics & Finance, Elsevier, vol. 29(C), pages 30-46.
    13. Fletcher, Jonathan & Kihanda, Joseph, 2005. "An examination of alternative CAPM-based models in UK stock returns," Journal of Banking & Finance, Elsevier, vol. 29(12), pages 2995-3014, December.
    14. Massimo Guidolin & Martin Lozano & Juan Arismendi Zambrano, "undated". "Multifactor Empirical Asset Pricing Under Higher-Order Moment Variations," Economics Department Working Paper Series n304-20.pdf, Department of Economics, National University of Ireland - Maynooth.
    15. Yu Hao & Shang Gao & Yunxia Guo & Zhiqiang Gai & Haitao Wu, 2021. "Measuring the nexus between economic development and environmental quality based on environmental Kuznets curve: a comparative study between China and Germany for the period of 2000–2017," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(11), pages 16848-16873, November.
    16. Lingwei Kong, 2023. "Weak (Proxy) Factors Robust Hansen-Jagannathan Distance For Linear Asset Pricing Models," Papers 2307.14499, arXiv.org.
    17. Shi, Qi & Li, Bin, 2019. "Evaluating alternative methods of asset pricing based on the overall magnitude of pricing errors," Finance Research Letters, Elsevier, vol. 29(C), pages 125-128.
    18. Schrimpf, Andreas & Schröder, Michael & Stehle, Richard, 2006. "Evaluating conditional asset pricing models for the German stock market," ZEW Discussion Papers 06-043, ZEW - Leibniz Centre for European Economic Research.
    19. Qiu, Yue & Wang, Zongrun & Xie, Tian & Zhang, Xinyu, 2021. "Forecasting Bitcoin realized volatility by exploiting measurement error under model uncertainty," Journal of Empirical Finance, Elsevier, vol. 62(C), pages 179-201.
    20. Guo, Hui & Savickas, Robert, 2010. "Relation between time-series and cross-sectional effects of idiosyncratic variance on stock returns," Journal of Banking & Finance, Elsevier, vol. 34(7), pages 1637-1649, July.
    21. Iqbal, Javed & Brooks, Robert & Galagedera, Don U.A., 2010. "Testing conditional asset pricing models: An emerging market perspective," Journal of International Money and Finance, Elsevier, vol. 29(5), pages 897-918, September.
    22. Frederik Lundtofte, 2009. "Can An ‘Estimation Factor’ Help Explain Cross‐Sectional Returns?," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 36(5‐6), pages 705-724, June.
    23. Balvers, Ronald J. & Huang, Dayong, 2009. "Evaluation of linear asset pricing models by implied portfolio performance," Journal of Banking & Finance, Elsevier, vol. 33(9), pages 1586-1596, September.

  10. Ahn, Seung Chan & Hoon Lee, Young & Schmidt, Peter, 2001. "GMM estimation of linear panel data models with time-varying individual effects," Journal of Econometrics, Elsevier, vol. 101(2), pages 219-255, April.

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    1. Clemens Possnig & Andreea Rotu{a}rescu & Kyungchul Song, 2022. "Estimating Dynamic Spillover Effects along Multiple Networks in a Linear Panel Model," Papers 2211.08995, arXiv.org.
    2. G. Forchini & Bin Jiang & Bin Peng, 2015. "Common Shocks in panels with Endogenous Regressors," Monash Econometrics and Business Statistics Working Papers 8/15, Monash University, Department of Econometrics and Business Statistics.
    3. Chihwa Kao & Lorenzo Trapani & Giovanni Urga, 2012. "Asymptotics for Panel Models with Common Shocks," Econometric Reviews, Taylor & Francis Journals, vol. 31(4), pages 390-439.
    4. Juodis, Arturas & Sarafidis, Vasilis, 2015. "A Simple Estimator for Short Panels with Common Factors," MPRA Paper 68164, University Library of Munich, Germany.
    5. Bai, Jushan, 2013. "Likelihood approach to dynamic panel models with interactive effects," MPRA Paper 50267, University Library of Munich, Germany.
    6. Kneip, Alois & Sickles, Robin C. & Song, Wonho, 2012. "A New Panel Data Treatment For Heterogeneity In Time Trends," Econometric Theory, Cambridge University Press, vol. 28(3), pages 590-628, June.
    7. Jörg Breitung & Philipp Hansen, 2021. "Alternative estimation approaches for the factor augmented panel data model with small T," Empirical Economics, Springer, vol. 60(1), pages 327-351, January.
    8. Sarafidis, Vasilis & Wansbeek, Tom, 2010. "Cross-sectional Dependence in Panel Data Analysis," MPRA Paper 20367, University Library of Munich, Germany.
    9. 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.
    10. Liangjun Su & Sainan Jin & Yonghui Zhang, 2014. "Specification Test for Panel Data Models with Interactive Fixed Effects," Working Papers 08-2014, Singapore Management University, School of Economics.
    11. Young Hoon Lee, 2009. "Estimation of Temporal Variations in Fan Loyalty: Application of Multi-Factor Models," Working Papers 0902, Nam Duck-Woo Economic Research Institute, Sogang University (Former Research Institute for Market Economy), revised 2009.
    12. M. Hashem Pesaran, 2003. "Estimation and Inference in Large Heterogenous Panels with Cross Section Dependence," CESifo Working Paper Series 869, CESifo.
    13. Hayakawa, Kazuhiko, 2016. "Identification problem of GMM estimators for short panel data models with interactive fixed effects," Economics Letters, Elsevier, vol. 139(C), pages 22-26.
    14. Young Hoon Lee, 2009. "The Impact of Postseason Restructuring on the Competitive Balance and Fan Demand in Major League Baseball," Working Papers 0901, Nam Duck-Woo Economic Research Institute, Sogang University (Former Research Institute for Market Economy), revised 2009.
    15. Freeman, Hugo & Weidner, Martin, 2023. "Linear panel regressions with two-way unobserved heterogeneity," Journal of Econometrics, Elsevier, vol. 237(1).
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    18. Young Hoon Lee & David Berri, 2008. "A Re‐Examination Of Production Functions And Efficiency Estimates For The National Basketball Association," Scottish Journal of Political Economy, Scottish Economic Society, vol. 55(1), pages 51-66, February.
    19. Hyungsik Roger Roger Moon & Martin Weidner, 2013. "Linear regression for panel with unknown number of factors as interactive fixed effects," CeMMAP working papers 49/13, Institute for Fiscal Studies.
    20. Pesaran, M.H., 2004. "‘General Diagnostic Tests for Cross Section Dependence in Panels’," Cambridge Working Papers in Economics 0435, Faculty of Economics, University of Cambridge.
    21. Sam Schulhofer-Wohl, 2011. "Heterogeneity and tests of risk sharing," Staff Report 462, Federal Reserve Bank of Minneapolis.
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    23. Luigi Infante & Stefano Piermattei & Raffaele Santioni & Bianca Sorvillo, 2020. "Diversifying away risks through derivatives: an analysis of the Italian banking system," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 37(2), pages 621-657, July.
    24. Shanti Gamper-Rabindran & Shakeeb Khan & Christopher Timmins, 2008. "The Impact of Piped Water Provision on Infant Mortality in Brazil: A Quantile Panel Data Approach," NBER Working Papers 14365, National Bureau of Economic Research, Inc.
    25. Gobillon, Laurent & Magnac, Thierry, 2013. "Regional Policy Evaluation:Interactive Fixed Effects and Synthetic Controls," TSE Working Papers 13-419, Toulouse School of Economics (TSE).
    26. Hyungsik Roger Roger Moon & Martin Weidner, 2014. "Linear regression for panel with unknown number of factors as interactive fixed effects," CeMMAP working papers 35/14, Institute for Fiscal Studies.
    27. G. Forchini & Bin Jiang & Bin Peng, 2015. "Consistent Estimation in Large Heterogeneous Panels with Multifactor Structure Endogeneity," Monash Econometrics and Business Statistics Working Papers 14/15, Monash University, Department of Econometrics and Business Statistics.
    28. Moon, Hyungsik Roger & Shum, Matthew & Weidner, Martin, 2018. "Estimation of random coefficients logit demand models with interactive fixed effects," Journal of Econometrics, Elsevier, vol. 206(2), pages 613-644.
    29. Sickles, Robin C. & Hao, Jiaqi & Shang, Chenjun, 2015. "Panel Data and Productivity Measurement," Working Papers 15-018, Rice University, Department of Economics.
    30. Hyungsik Roger Moon & Martin Weidner, 2013. "Dynamic linear panel regression models with interactive fixed effects," CeMMAP working papers CWP63/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    31. Federico Belotti & Silvio Daidone & Giuseppe Ilardi & Vincenzo Atella, 2013. "Stochastic frontier analysis using Stata," Stata Journal, StataCorp LLC, vol. 13(4), pages 718-758, December.
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    34. Joakim Westerlund, 2020. "A cross‐section average‐based principal components approach for fixed‐T panels," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(6), pages 776-785, September.
    35. 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.
    36. Han, Chirok & Orea, Luis & Schmidt, Peter, 2005. "Estimation of a panel data model with parametric temporal variation in individual effects," Journal of Econometrics, Elsevier, vol. 126(2), pages 241-267, June.
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    38. Benjamin Williams, 2018. "Identification of the Linear Factor Model," Working Papers 2018-002, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    39. Bai, Jushan & Li, Kunpeng, 2010. "Theory and methods of panel data models with interactive effects," MPRA Paper 43441, University Library of Munich, Germany, revised Dec 2012.
    40. Williams, Benjamin, 2020. "Nonparametric identification of discrete choice models with lagged dependent variables," Journal of Econometrics, Elsevier, vol. 215(1), pages 286-304.
    41. M. Hashem Pesaran, 2004. "Estimation and Inference in Large Heterogeneous Panels with a Multifactor Error Structure," CESifo Working Paper Series 1331, CESifo.
    42. Kim, Yong-seong & Kim, Taebong, 2017. "The Effects of Institutions on the Labour Market Outcomes: Cross-country Analysis," KDI Journal of Economic Policy, Korea Development Institute (KDI), vol. 39(4), pages 69-94.
    43. Hugo Freeman & Martin Weidner, 2021. "Linear Panel Regressions with Two-Way Unobserved Heterogeneity," Papers 2109.11911, arXiv.org, revised Aug 2022.
    44. Artūras Juodis & Vasilis Sarafidis, 2018. "Fixed T dynamic panel data estimators with multifactor errors," Econometric Reviews, Taylor & Francis Journals, vol. 37(8), pages 893-929, September.
    45. Giovanni Forchini & Bin Jiang & Bin Peng, 2018. "TSLS and LIML Estimators in Panels with Unobserved Shocks," Econometrics, MDPI, vol. 6(2), pages 1-12, April.
    46. Jean-Thomas Bernard & Michael Gavin & Lynda Khalaf & Marcel Voia, 2011. "The Environmental Kuznets Curve: Tipping Points, Uncertainty and Weak Identification," Cahiers de recherche CREATE 2011-4, CREATE.
    47. Jianqing Fan & Yuan Liao & Martina Mincheva, 2013. "Large covariance estimation by thresholding principal orthogonal complements," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 75(4), pages 603-680, September.
    48. 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.
    49. Philippe de Vreyer & Javier Herrera & Sandrine Mesplé-Somps, 2009. "Consumption Growth and Spatial Poverty Traps: An Analysis of the Effect of Social Services and Community Infrastructures on Living Standards in Rural Peru," Post-Print hal-01377603, HAL.
    50. Sarafidis, Vasilis & Yamagata, Takashi, 2010. "Instrumental Variable Estimation of Dynamic Linear Panel Data Models with Defactored Regressors under Cross-sectional Dependence," MPRA Paper 25182, University Library of Munich, Germany.
    51. Laura Serlenga & Yongcheol Shin, 2004. "Gravity Models of the Intra-EU Trade: Application of the Hausman-Taylor Estimation in Heterogeneous Panels with Common Time-specific Factors," Edinburgh School of Economics Discussion Paper Series 105, Edinburgh School of Economics, University of Edinburgh.
    52. Peng Shi & Wei Zhang, 2011. "A copula regression model for estimating firm efficiency in the insurance industry," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(10), pages 2271-2287.
    53. Jianqing Fan & Yuan Ke & Yuan Liao, 2016. "Augmented Factor Models with Applications to Validating Market Risk Factors and Forecasting Bond Risk Premia," Papers 1603.07041, arXiv.org, revised Sep 2018.
    54. 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.
    55. 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.
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    58. Jee-Seon Kim & Edward Frees, 2006. "Omitted Variables in Multilevel Models," Psychometrika, Springer;The Psychometric Society, vol. 71(4), pages 659-690, December.
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    60. Lee, Young Hoon, 2006. "A stochastic production frontier model with group-specific temporal variation in technical efficiency," European Journal of Operational Research, Elsevier, vol. 174(3), pages 1616-1630, November.
    61. Hyungsik Roger Roger Moon & Matthew Shum & Martin Weidner, 2012. "Estimation of random coefficients logit demand models with interactive fixed effects," CeMMAP working papers 08/12, Institute for Fiscal Studies.
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    64. Guido M. Kuersteiner & Ingmar R. Prucha, 2015. "Dynamic Spatial Panel Models: Networks, Common Shocks, and Sequential Exogeneity," CESifo Working Paper Series 5445, CESifo.
    65. Hugo Freeman & Martin Weidner, 2021. "Linear panel regressions with two-way unobserved heterogeneity," CeMMAP working papers CWP39/21, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    66. Hyungsik Roger Moon & Martin Weidner, 2013. "Linear regression for panel with unknown number of factors as interactive fixed effects," CeMMAP working papers CWP49/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    67. Moukpè Gniniguè & Essossinam Ali, 2022. "Migrant Remittances and Economic Growth in ECOWAS Countries: Does Digitalization Matter?," The European Journal of Development Research, Palgrave Macmillan;European Association of Development Research and Training Institutes (EADI), vol. 34(5), pages 2517-2542, October.
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    84. Cheng Hsiao & Yan Shen & Wenlong Bian, 2016. "Evaluating the Effectiveness of China's Financial Reform The Efficiency of China's Domestic Banks," Working Papers 2016-02-21, Wang Yanan Institute for Studies in Economics (WISE), Xiamen University.
    85. Francesco Bartolucci & Federico Belotti & Franco Peracchi, 2013. "Testing for Time-Invariant Unobserved Heterogeneity in Generalized Linear Models for Panel Data," EIEF Working Papers Series 1312, Einaudi Institute for Economics and Finance (EIEF), revised May 2013.
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    88. Vuslat Us, 2015. "The Turkish Banking Sector Before and After the Global Crisis:An Ownership Breakdown," CBT Research Notes in Economics 1502, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
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    92. Giovanni Forchini & Bin Peng, 2016. "A Conditional Approach to Panel Data Models with Common Shocks," Econometrics, MDPI, vol. 4(1), pages 1-12, January.
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    96. Hyungsik Roger Roger Moon & Martin Weidner, 2013. "Dynamic linear panel regression models with interactive fixed effects," CeMMAP working papers 63/13, Institute for Fiscal Studies.
    97. Shobande, Olatunji A. & Ogbeifun, Lawrence, 2023. "Pooling cross-sectional and time series data for estimating causality between technological innovation, affluence and carbon dynamics: A comparative evidence from developed and developing countries," Technological Forecasting and Social Change, Elsevier, vol. 187(C).
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    105. Hyungsik Roger Roger Moon & Matthew Shum & Martin Weidner, 2014. "Estimation of random coefficients logit demand models with interactive fixed effects," CeMMAP working papers 20/14, Institute for Fiscal Studies.
    106. Ali M. Kutan & Nahla Samargandi & Kazi Sohag, 2017. "Does Institutional Quality Matter for Financial Development and Growth? Further Evidence from MENA Countries," Australian Economic Papers, Wiley Blackwell, vol. 56(3), pages 228-248, September.
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    112. Hyungsik Roger Roger Moon & Martin Weidner, 2014. "Dynamic linear panel regression models with interactive fixed effects," CeMMAP working papers 47/14, Institute for Fiscal Studies.
    113. Lee, Young Hoon, 2010. "Group-specific stochastic production frontier models with parametric specifications," European Journal of Operational Research, Elsevier, vol. 200(2), pages 508-517, January.
    114. 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.
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    Cited by:

    1. Mastromarco, Camilla & Simar, Leopold, 2014. "Global Dependence and Productivity: A Robust Nonparametric World Frontier Analysis," LIDAM Discussion Papers ISBA 2014049, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    2. Massimo Filippini & William Greene, 2014. "Persistent and Transient Productive Inefficiency: A Maximum Simulated Likelihood Approach," CER-ETH Economics working paper series 14/197, CER-ETH - Center of Economic Research (CER-ETH) at ETH Zurich.
    3. Gardebroek, Cornelis & Oude Lansink, Alfons G.J.M., 2008. "Dynamic Microeconometric Approaches To Analysing Agricultural Policy," 107th Seminar, January 30-February 1, 2008, Sevilla, Spain 6592, European Association of Agricultural Economists.
    4. V.K. Chetty & James J. Heckman, 2022. "Internal Adjustment Costs of Firm-Specific Factors and the Neoclassical Theory of the Firm," NBER Working Papers 30695, National Bureau of Economic Research, Inc.
    5. Levent Kutlu & Shasha Liu & Robin C. Sickles, 2022. "Cost, Revenue, and Profit Function Estimates," Springer Books, in: Subhash C. Ray & Robert G. Chambers & Subal C. Kumbhakar (ed.), Handbook of Production Economics, chapter 16, pages 641-679, Springer.
    6. Belotti, Federico & Ilardi, Giuseppe, 2018. "Consistent inference in fixed-effects stochastic frontier models," Journal of Econometrics, Elsevier, vol. 202(2), pages 161-177.
    7. Lambarraa, Fatima & Stefanou, Spiro E. & Gil, Jose Maria, 2009. "The analysis of irreversibility, uncertainty and dynamic technical inefficiency on the investment decision in Spanish olive sector," 2009 Conference, August 16-22, 2009, Beijing, China 51397, International Association of Agricultural Economists.
    8. Aditi Bhattacharyya, 2012. "Adjustment of inputs and measurement of technical efficiency: A dynamic panel data analysis of the Egyptian manufacturing sectors," Empirical Economics, Springer, vol. 42(3), pages 863-880, June.
    9. Sickles, Robin C. & Hao, Jiaqi & Shang, Chenjun, 2015. "Panel Data and Productivity Measurement," Working Papers 15-018, Rice University, Department of Economics.
    10. Duygun, Meryem & Hao, Jiaqi & Isaksson, Anders & Sickles, Robin C., 2015. "World Productivity Growth: A Model Averaging Approach," Working Papers 15-011, Rice University, Department of Economics.
    11. Tsionas, Mike G. & Malikov, Emir & Kumbhakar, Subal C., 2019. "Endogenous Dynamic Efficiency in the Intertemporal Optimization Models of Firm Behavior," MPRA Paper 97780, University Library of Munich, Germany.
    12. Wang, Mei-Hui & Huang, Tai-Hsin, 2007. "A study on the persistence of Farrell's efficiency measure under a dynamic framework," European Journal of Operational Research, Elsevier, vol. 180(3), pages 1302-1316, August.
    13. Mastromarco, Camilla & Simar, Leopold, 2017. "Cross-Section Dependence and Latent Heterogeneity to Evaluate the Impact of Human Capital on Country Performance," LIDAM Discussion Papers ISBA 2017030, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    14. Mastromarco, Camilla & Simar, Léopold, 2021. "Latent heterogeneity to evaluate the effect of human capital on world technology frontier," LIDAM Reprints ISBA 2021009, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    15. Galán, Jorge E. & Pollitt, Michael G., 2014. "Inefficiency persistence and heterogeneity in Colombian electricity utilities," Energy Economics, Elsevier, vol. 46(C), pages 31-44.
    16. Lai, Hung-pin & Kumbhakar, Subal C., 2018. "Estimation of Dynamic Stochastic Frontier Model using Likelihood-based Approaches," MPRA Paper 87830, University Library of Munich, Germany.
    17. Assaf, A. George & Tsionas, Efthymios G., 2015. "Incorporating destination quality into the measurement of tourism performance: A Bayesian approach," Tourism Management, Elsevier, vol. 49(C), pages 58-71.
    18. Habtamu Alem, 2021. "The Role of Technical Efficiency Achieving Sustainable Development: A Dynamic Analysis of Norwegian Dairy Farms," Sustainability, MDPI, vol. 13(4), pages 1-11, February.
    19. Camilla Mastromarco & Laura Serlenga & Yongcheol Shin, 2012. "Is Globalization Driving Efficiency? A Threshold Stochastic Frontier Panel Data Modeling Approach," Review of International Economics, Wiley Blackwell, vol. 20(3), pages 563-579, August.
    20. Howell, Charles & Grifell-Tatjé, Emili, 2022. "Market heterogeneity and the relationship between competition and price dispersion: Evidence from the U.S. airline market," Transport Policy, Elsevier, vol. 125(C), pages 218-230.
    21. Ang, Frederic & Oude Lansink, Alfons, 2014. "Dynamic Profit Inefficiency: A DEA Application to Belgian Dairy Farms," Working Papers 165693, Katholieke Universiteit Leuven, Centre for Agricultural and Food Economics.
    22. Duygun, Meryem & Kutlu, Levent & Sickles, Robin C., 2014. "Measuring Productivity and Efficiency: A Kalman," Working Papers 15-010, Rice University, Department of Economics.
    23. Camilla Mastromarco & Léopold Simar, 2015. "Effect of FDI and Time on Catching Up: New Insights from a Conditional Nonparametric Frontier Analysis," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(5), pages 826-847, August.
    24. Ioannis Skevas & Grigorios Emvalomatis & Bernhard Brümmer, 2018. "The effect of farm characteristics on the persistence of technical inefficiency: a case study in German dairy farming," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 45(1), pages 3-25.
    25. Meryem Duygun & Levent Kutlu & Robin C. Sickles, 2016. "Measuring productivity and efficiency: a Kalman filter approach," Journal of Productivity Analysis, Springer, vol. 46(2), pages 155-167, December.
    26. Das, Tirthatanmoy & Polachek, Solomon, 2017. "Estimating Labor Force Joiners and Leavers Using a Heterogeneity Augmented Two-Tier Stochastic Frontier," IZA Discussion Papers 10534, Institute of Labor Economics (IZA).
    27. Mastromarco, Camilla & Simar, Léopold, 2018. "Globalization and productivity: A robust nonparametric world frontier analysis," Economic Modelling, Elsevier, vol. 69(C), pages 134-149.
    28. Stefanou, Spiro E., 2009. "A Dynamic Characterization of Efficiency," Agricultural Economics Review, Greek Association of Agricultural Economists, vol. 10(01), pages 1-16.
    29. Orea, Luis & Zofío, José L., 2017. "A primer on the theory and practice of efficiency and productivity analysis," Efficiency Series Papers 2017/05, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).
    30. Massimo Filippini & Elisa Tosetti, 2014. "Stochastic Frontier Models for Long Panel Data Sets: Measurement of the Underlying Energy Efficiency for the OECD Countries," CER-ETH Economics working paper series 14/198, CER-ETH - Center of Economic Research (CER-ETH) at ETH Zurich.
    31. Jean Joseph Minviel & Timo Sipiläinen, 2018. "Dynamic stochastic analysis of the farm subsidy-efficiency link: evidence from France," Journal of Productivity Analysis, Springer, vol. 50(1), pages 41-54, October.
    32. Huang, Tai-Hsin & Chen, Ying-Hsiu, 2009. "A study on long-run inefficiency levels of a panel dynamic cost frontier under the framework of forward-looking rational expectations," Journal of Banking & Finance, Elsevier, vol. 33(5), pages 842-849, May.
    33. Chen, Hong & Wang, Xi & Singh, Baljeet, 2021. "Transient and persistent inefficiency traps in Chinese provinces," Economic Modelling, Elsevier, vol. 97(C), pages 335-347.
    34. Rahmatallah Poudineh & Grigorios Emvalomatis & Tooraj Jamasb, 2014. "Dynamic Efficiency and Incentive Regulation: An Application to Electricity Distribution Networks," Cambridge Working Papers in Economics 1422, Faculty of Economics, University of Cambridge.
    35. Jorge E. Galán & Michael G. Pollitt, 2014. "Inefficiency persistence and heterogeneity in Colombian electricity distribution utilities," Working Papers EPRG 1403, Energy Policy Research Group, Cambridge Judge Business School, University of Cambridge.
    36. Levent Kutlu, 2020. "Greenhouse Gas Emission Efficiencies of World Countries," IJERPH, MDPI, vol. 17(23), pages 1-11, November.
    37. Mastromarco Camilla & Laura Serlenga & Yongcheol Shin, 2013. "Globalisation and technological convergence in the EU," Journal of Productivity Analysis, Springer, vol. 40(1), pages 15-29, August.
    38. Grigorios Emvalomatis, 2012. "Adjustment and unobserved heterogeneity in dynamic stochastic frontier models," Journal of Productivity Analysis, Springer, vol. 37(1), pages 7-16, February.
    39. Deng, Na-Qian & Liu, Li-Qiu & Deng, Ying-Zhi, 2018. "Estimating the effects of restructuring on the technical and service-quality efficiency of electricity companies in China," Utilities Policy, Elsevier, vol. 50(C), pages 91-100.
    40. Cave, Joshua & Chaudhuri, Kausik & Kumbhakar, Subal C., 2023. "Dynamic firm performance and estimator choice: A comparison of dynamic panel data estimators," European Journal of Operational Research, Elsevier, vol. 307(1), pages 447-467.
    41. Valentin Zelenyuk & Zhichao Wang, 2023. "Random vs. Explained Inefficiency in Stochastic Frontier Analysis: The Case of Queensland Hospitals," CEPA Working Papers Series WP052023, School of Economics, University of Queensland, Australia.
    42. Galán, Jorge E. & Veiga, Helena & Wiper, Michael P., 2015. "Dynamic effects in inefficiency: Evidence from the Colombian banking sector," European Journal of Operational Research, Elsevier, vol. 240(2), pages 562-571.
    43. Sickles, Robin C., 2005. "Panel estimators and the identification of firm-specific efficiency levels in parametric, semiparametric and nonparametric settings," Journal of Econometrics, Elsevier, vol. 126(2), pages 305-334, June.
    44. Uehleke, Reinhard & Petrick, Martin & Hüttel, Silke, 2022. "Evaluations of agri-environmental schemes based on observational farm data: The importance of covariate selection," Land Use Policy, Elsevier, vol. 114(C).
    45. Huang, Yu-Fan & Luo, Sui & Wang, Hung-Jen, 2018. "Flexible panel stochastic frontier model with serially correlated errors," Economics Letters, Elsevier, vol. 163(C), pages 55-58.
    46. Jean Joseph Minviel & Timo Sipiläinen, 2021. "A dynamic stochastic frontier approach with persistent and transient inefficiency and unobserved heterogeneity," Agricultural Economics, International Association of Agricultural Economists, vol. 52(4), pages 575-589, July.
    47. Chen, Ying-Hsiu & Lai, Po-Lin, 2019. "Determining the relationship between ownership and technical efficiency by using a dynamic stochastic production frontier approach," Journal of Air Transport Management, Elsevier, vol. 75(C), pages 61-67.
    48. Frederic Ang & Alfons Oude Lansink, 2018. "Decomposing dynamic profit inefficiency of Belgian dairy farms," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 45(1), pages 81-99.
    49. Pavlos Almanidis & Mustafa U. Karakaplan & Levent Kutlu, 2019. "A dynamic stochastic frontier model with threshold effects: U.S. bank size and efficiency," Journal of Productivity Analysis, Springer, vol. 52(1), pages 69-84, December.
    50. Alem, Habtamu, 2020. "Performance of the Norwegian dairy farms: A dynamic stochastic approach," Research in Economics, Elsevier, vol. 74(3), pages 263-271.
    51. Efthymios G. Tsionas, 2006. "Inference in dynamic stochastic frontier models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(5), pages 669-676, July.
    52. Lambarraa, Fatima, 2011. "Dynamic Efficiency Analysis of Spanish Outdoor and Greenhouse Horticulture Sector," 2011 International Congress, August 30-September 2, 2011, Zurich, Switzerland 114408, European Association of Agricultural Economists.
    53. Kutlu, Levent & Sickles, Robin C., 2012. "Estimation of market power in the presence of firm level inefficiencies," Journal of Econometrics, Elsevier, vol. 168(1), pages 141-155.
    54. Barnabé Walheer, 2016. "Multi-Sector Nonparametric Production-Frontier Analysis of the Economic Growth and the Convergence of the European Countries," Pacific Economic Review, Wiley Blackwell, vol. 21(4), pages 498-524, October.
    55. Lambarraa, Fatima, 2012. "The Spanish Horticulture Sector: A dynamic efficiency analysis of Outdoor and Greenhouse farms," 2012 Conference, August 18-24, 2012, Foz do Iguacu, Brazil 126797, International Association of Agricultural Economists.
    56. Antony Andrews & Grigorios Emvalomatis, 2024. "Do adjustment costs constrain public healthcare providers’ technical efficiency? Evidence from the New Zealand Public Healthcare System," Health Care Management Science, Springer, vol. 27(2), pages 268-283, June.
    57. Galán, Jorge & Ramos, Sofía B. & Veiga, Helena, 2015. "An analysis of the dynamics of efficiency of mutual funds," DES - Working Papers. Statistics and Econometrics. WS ws1517, Universidad Carlos III de Madrid. Departamento de Estadística.
    58. Skevas, Ioannis & Emvalomatis, Grigorios & Brümmer, Bernhard, 2018. "Productivity growth measurement and decomposition under a dynamic inefficiency specification: The case of German dairy farms," European Journal of Operational Research, Elsevier, vol. 271(1), pages 250-261.
    59. Kutlu, Levent, 2017. "A constrained state space approach for estimating firm efficiency," Economics Letters, Elsevier, vol. 152(C), pages 54-56.
    60. Assaf, A. George & Tsionas, Mike G., 2019. "A review of research into performance modeling in tourism research - Launching the Annals of Tourism Research curated collection on performance modeling in tourism research," Annals of Tourism Research, Elsevier, vol. 76(C), pages 266-277.
    61. Koutsomanoli-Filippaki, Anastasia & Mamatzakis, Emmanuel C., 2010. "Estimating the speed of adjustment of European banking efficiency under a quadratic loss function," Economic Modelling, Elsevier, vol. 27(1), pages 1-11, January.
    62. Oleg Badunenko & Daniel J. Henderson & Valentin Zelenyuk, 2017. "The Productivity of Nations," CEPA Working Papers Series WP022017, School of Economics, University of Queensland, Australia.

  12. So Im, Kyung & Ahn, Seung C. & Schmidt, Peter & Wooldridge, Jeffrey M., 1999. "Efficient estimation of panel data models with strictly exogenous explanatory variables," Journal of Econometrics, Elsevier, vol. 93(1), pages 177-201, November.

    Cited by:

    1. Amoroso, Sara & Bruno, Randolph Luca & Magazzini, Laura, 2022. "The Identification of Time-Invariant Variables in Panel Data Model: Exploring the Role of Science in Firms’ Productivity," IZA Discussion Papers 15708, Institute of Labor Economics (IZA).
    2. Qian, Hailong & Schmidt, Peter, 2003. "Partial GLS regression," Economics Letters, Elsevier, vol. 79(3), pages 385-392, June.
    3. Baltagi, Badi H. & Bresson, Georges & Pirotte, Alain, 2003. "Fixed effects, random effects or Hausman-Taylor?: A pretest estimator," Economics Letters, Elsevier, vol. 79(3), pages 361-369, June.
    4. Jean-Bernard Chatelain & Kirsten Ralf, 2021. "Inference on time-invariant variables using panel data: a pretest estimator," Working Papers halshs-01719835, HAL.
    5. Eduardo Fé, 2012. "Instrumental variable estimation of heteroskedasticity adaptive error component models," Statistical Papers, Springer, vol. 53(3), pages 577-615, August.
    6. Badi H. Baltagi & Chihwa Kao & Bin Peng, 2014. ""On Testing for Sphericity with Non-normality in a Fixed Effects Panel Data Model," Center for Policy Research Working Papers 176, Center for Policy Research, Maxwell School, Syracuse University.
    7. Baltagi, Badi H. & Feng, Qu & Kao, Chihwa, 2012. "A Lagrange Multiplier test for cross-sectional dependence in a fixed effects panel data model," Journal of Econometrics, Elsevier, vol. 170(1), pages 164-177.
    8. Cheng, Xu & Liao, Zhipeng, 2015. "Select the valid and relevant moments: An information-based LASSO for GMM with many moments," Journal of Econometrics, Elsevier, vol. 186(2), pages 443-464.
    9. Inmaculada Garc�a Mainar & V�ctor M. Montuenga G�mez, 2004. "Returns to education and to experience within the EU: are there differences between wage earners and the self-employed?," Documentos de Trabajo dt2004-08, Facultad de Ciencias Económicas y Empresariales, Universidad de Zaragoza.
    10. Mark A. Klinedinst, 2016. "Bank Decapitalization and Credit Union Capitalization," SAGE Open, , vol. 6(1), pages 21582440166, February.
    11. Park, Byeong U. & Sickles, Robin C. & Simar, Leopold, 2003. "Semiparametric-efficient estimation of AR(1) panel data models," Journal of Econometrics, Elsevier, vol. 117(2), pages 279-309, December.
    12. Timo Mitze, 2010. "Estimating Gravity Models of International Trade with Correlated Time-Fixed Regressors: To IV or not IV?," EERI Research Paper Series EERI_RP_2010_22, Economics and Econometrics Research Institute (EERI), Brussels.
    13. M. Hashem Pesaran & Qiankun Zhou, 2018. "Estimation of time-invariant effects in static panel data models," Econometric Reviews, Taylor & Francis Journals, vol. 37(10), pages 1137-1171, November.
    14. Hafiz M. Muddasar Jamil Shera & Irum Sajjad Dar, 2014. "Addressing Corner Solution Effect for Child Mortality Status Measure: An Application of Tobit Model," International Journal of Academic Research in Business and Social Sciences, Human Resource Management Academic Research Society, International Journal of Academic Research in Business and Social Sciences, vol. 4(12), pages 218-225, December.
    15. Badi H. Baltagi & Chihwa Kao, 2000. "Nonstationary Panels, Cointegration in Panels and Dynamic Panels: A Survey," Center for Policy Research Working Papers 16, Center for Policy Research, Maxwell School, Syracuse University.
    16. Mitze, Timo, 2009. "Endogeneity in Panel Data Models with Time-Varying and Time-Fixed Regressors: To IV or not IV?," Ruhr Economic Papers 83, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    17. Liverpool, Lenis Saweda O. & Winter-Nelson, Alex, 2010. "Asset versus consumption poverty and poverty dynamics in the presence of multiple equilibria in rural Ethiopia," IFPRI discussion papers 971, International Food Policy Research Institute (IFPRI).
    18. Chirok Han & Peter C.B. Phillips, 2007. "GMM Estimation for Dynamic Panels with Fixed Effects and Strong Instruments at Unity," Cowles Foundation Discussion Papers 1599, Cowles Foundation for Research in Economics, Yale University.
    19. Badi H. Baltagi & Long Liu, 2012. "The Hausman-Taylor Panel Data Model with Serial Correlation," Center for Policy Research Working Papers 136, Center for Policy Research, Maxwell School, Syracuse University.
    20. Gian Maria Tomat, 2020. "Present Value Models and the Behaviour of European Financial Markets," Italian Economic Journal: A Continuation of Rivista Italiana degli Economisti and Giornale degli Economisti, Springer;Società Italiana degli Economisti (Italian Economic Association), vol. 6(3), pages 493-520, November.
    21. Nicholas Brown, 2023. "Information Equivalence among Transformations of Semi‐parametric Nonlinear Panel Data Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 85(6), pages 1341-1361, December.
    22. Jee-Seon Kim & Edward Frees, 2007. "Multilevel Modeling with Correlated Effects," Psychometrika, Springer;The Psychometric Society, vol. 72(4), pages 505-533, December.
    23. Badi H. Baltagi, 2013. "Dynamic panel data models," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 10, pages 229-248, Edward Elgar Publishing.
    24. Nguyen, James, 2012. "The relationship between net interest margin and noninterest income using a system estimation approach," Journal of Banking & Finance, Elsevier, vol. 36(9), pages 2429-2437.
    25. Yoichi Matsubayashi & Takao Fujii, 2012. "Substitutability of Savings by Sectors: OECD Experiences," Discussion Papers 1215, Graduate School of Economics, Kobe University.
    26. Helmut Farbmacher & Harald Tauchmann, 2023. "Linear fixed-effects estimation with nonrepeated outcomes," Econometric Reviews, Taylor & Francis Journals, vol. 42(8), pages 635-654, September.
    27. Eduardo Fé Rodríguez, 2009. "Adaptive Instrumental Variable Estimation of Heteroskedastic Error Component Models," Economics Discussion Paper Series 0921, Economics, The University of Manchester.
    28. Inoue, Atsushi, 2008. "Efficient estimation and inference in linear pseudo-panel data models," Journal of Econometrics, Elsevier, vol. 142(1), pages 449-466, January.
    29. Yang, Yimin, 2021. "Efficient estimation of multi-level models with strictly exogenous explanatory variables," Economics Letters, Elsevier, vol. 198(C).
    30. Xu Cheng & Zhipeng Liao, 2012. "Select the Valid and Relevant Moments: A One-Step Procedure for GMM with Many Moments," PIER Working Paper Archive 12-045, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    31. Muhammad Aslam & Wajid Alim & Naeem Khan, 2022. "Nexus between Capital Flows and Economic Growth: An Evidence from South Asian Countries," Journal of Economic Impact, Science Impact Publishers, vol. 4(2), pages 14-21.

  13. Ahn, Seung C, 1997. "Orthogonality Tests in Linear Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 59(1), pages 183-186, February.

    Cited by:

    1. Firmin Doko Tchatoka, 2014. "Specification Tests with Weak and Invalid Instruments," School of Economics and Public Policy Working Papers 2014-05, University of Adelaide, School of Economics and Public Policy.
    2. Doko Tchatoka, Firmin & Dufour, Jean-Marie, 2012. "Identification-robust inference for endogeneity parameters in linear structural models," MPRA Paper 40695, University Library of Munich, Germany.
    3. Agee, Mark D., 2010. "Reducing child malnutrition in Nigeria: Combined effects of income growth and provision of information about mothers' access to health care services," Social Science & Medicine, Elsevier, vol. 71(11), pages 1973-1980, December.
    4. Firmin Doko Tchatoka, 2015. "On bootstrap validity for specification tests with weak instruments," Econometrics Journal, Royal Economic Society, vol. 18(1), pages 137-146, February.
    5. Kiviet, Jan F. & Pleus, Milan, 2017. "The performance of tests on endogeneity of subsets of explanatory variables scanned by simulation," Econometrics and Statistics, Elsevier, vol. 2(C), pages 1-21.
    6. Firmin DOKO TCHATOKA & Jean-Marie DUFOUR, 2016. "Exogeneity Tests, Incomplete Models, Weak Identification and Non-Gaussian Distributions : Invariance and Finite-Sample Distributional Theory," Cahiers de recherche 14-2016, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
    7. Christopher F Baum & Mark E. Schaffer & Steven Stillman, 2007. "Enhanced routines for instrumental variables/generalized method of moments estimation and testing," Stata Journal, StataCorp LLC, vol. 7(4), pages 465-506, December.
    8. Christopher F Baum & Mark E. Schaffer & Steven Stillman, 2007. "Enhanced routines for instrumental variables/GMM estimation and testing," Boston College Working Papers in Economics 667, Boston College Department of Economics, revised 05 Sep 2007.

  14. Ahn, Seung C. & Schmidt, Peter, 1997. "Efficient estimation of dynamic panel data models: Alternative assumptions and simplified estimation," Journal of Econometrics, Elsevier, vol. 76(1-2), pages 309-321.

    Cited by:

    1. Binder, M. & Hsaio, C. & Pesaran, M.H., 2000. "Estimation and Inference in Short Panel Vector Autoregressions with Unit Roots and Cointegration," Cambridge Working Papers in Economics 0003, Faculty of Economics, University of Cambridge.
    2. De Wachter, Stefan & Tzavalis, Elias, 2012. "Detection of structural breaks in linear dynamic panel data models," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3020-3034.
    3. d’Agostino, Giorgio & Dunne, J. Paul & Pieroni, Luca, 2016. "Government Spending, Corruption and Economic Growth," World Development, Elsevier, vol. 84(C), pages 190-205.
    4. Kruiniger, Hugo, 2013. "Quasi ML estimation of the panel AR(1) model with arbitrary initial conditions," Journal of Econometrics, Elsevier, vol. 173(2), pages 175-188.
    5. Seung C. Ahn & Gareth M. Thomas, 2023. "Likelihood-based inference for dynamic panel data models," Empirical Economics, Springer, vol. 64(6), pages 2859-2909, June.
    6. Kyuho Jin, 2022. "Can Business Groups Survive Institutional Advancements? Examining the Role of Internal Market for Non-Tradable, Intangible Assets," Sustainability, MDPI, vol. 14(17), pages 1-17, September.
    7. Wang, Mei-Hui & Huang, Tai-Hsin, 2007. "A study on the persistence of Farrell's efficiency measure under a dynamic framework," European Journal of Operational Research, Elsevier, vol. 180(3), pages 1302-1316, August.
    8. Kruiniger, Hugo, 2009. "Gmm Estimation And Inference In Dynamic Panel Data Models With Persistent Data," Econometric Theory, Cambridge University Press, vol. 25(5), pages 1348-1391, October.
    9. Badri Narayanan G, 2005. "Effects of trade liberalisation, environmental and labour regulations on employment in India's organised textile sector," Indira Gandhi Institute of Development Research, Mumbai Working Papers 2005-005, Indira Gandhi Institute of Development Research, Mumbai, India.
    10. Chien, Chih-Chung & Chen, Shikuan & Chang, Ming-Jen, 2023. "Financial constraints on credit ratings and cash-flow sensitivity," International Review of Financial Analysis, Elsevier, vol. 88(C).
    11. Gareth M. Thomas & Seung C. Ahn, 2004. "Likelihood Based Inference for amic Panel Data Models," Econometric Society 2004 Far Eastern Meetings 669, Econometric Society.
    12. Rym Ben Ayed Mouelhi & Mohamed Goaied, 2002. "Efficiency Measure from Dynamic Stochastic Production Frontier: Application to Tunisian Textile, Clothing and Leather Industries," Working Papers 0235, Economic Research Forum, revised 31 Nov 2002.
    13. Jinyong Hahn & Jerry Hausman & Guido Kuersteiner, 2005. "Bias Corrected Instrumental Variables Estimation for Dynamic Panel Models with Fixed E¤ects," Boston University - Department of Economics - Working Papers Series WP2005-024, Boston University - Department of Economics.
    14. Chirok Han & Hyoungjong Kim, 2023. "Dynamic panel GMM estimators with improved finite sample properties using parametric restrictions for dimension reduction," Empirical Economics, Springer, vol. 64(6), pages 2589-2610, June.
    15. Peter Phillips & Hyungsik Moon, 2000. "Nonstationary panel data analysis: an overview of some recent developments," Econometric Reviews, Taylor & Francis Journals, vol. 19(3), pages 263-286.
    16. Hakan Yetkiner & Gamze Öztürk & Bahar Taş, 2024. "Consumption convergence: theory and evidence," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 51(3), pages 619-643, August.
    17. César Calderón & Alberto Chong, 2004. "Volume and Quality of Infrastructure and the Distribution of Income: An Empirical Investigation," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 50(1), pages 87-106, March.
    18. Chen, Yanjing, 2009. "Agglomeration and location of foreign direct investment: The case of China," China Economic Review, Elsevier, vol. 20(3), pages 549-557, September.
    19. Hahn, Jinyong & Hausman, Jerry & Kuersteiner, Guido, 2007. "Long difference instrumental variables estimation for dynamic panel models with fixed effects," Journal of Econometrics, Elsevier, vol. 140(2), pages 574-617, October.
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    Cited by:

    1. Taye Mengistae, 1998. "Wage rates and job queues: does the public sector overpay in Ethiopia?," CSAE Working Paper Series 1998-20, Centre for the Study of African Economies, University of Oxford.
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  18. Schmidt, Peter & Ahn, Seung C & Wyhowski, Donald, 1992. "On the Estimation of Panel-Data Models with Serial Correlation When Instruments Are Not Strictly Exogenous: Comment," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(1), pages 10-14, January.

    Cited by:

    1. Hahn, Jinyong, 1997. "Efficient estimation of panel data models with sequential moment restrictions," Journal of Econometrics, Elsevier, vol. 79(1), pages 1-21, July.

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