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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. Juodis, Arturas & Sarafidis, Vasilis, 2014. "Fixed T Dynamic Panel Data Estimators with Multi-Factor Errors," MPRA Paper 57659, University Library of Munich, Germany.
    2. William Horrace & Seth Richards-Shubik & Ian Wright, 2015. "Expected efficiency ranks from parametric stochastic frontier models," Empirical Economics, Springer, vol. 48(2), pages 829-848, March.
    3. Zhan Gao & M. Hashem Pesaran, 2023. "Identification and estimation of categorical random coefficient models," Empirical Economics, Springer, vol. 64(6), pages 2543-2588, June.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. Bai, Jushan, 2013. "Likelihood approach to dynamic panel models with interactive effects," MPRA Paper 50267, University Library of Munich, Germany.
    10. 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).
    11. Liu, Shasha & Sickles, Robin, 2020. "The Agency Problem Revisited: A Structural Analysis of Managerial Productivity and CEO Compensation in Large U.S. Commercial Banks," Working Papers 20-001, Rice University, Department of Economics.
    12. 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.
    13. Chen, Liang, 2015. "Set identification of panel data models with interactive effects via quantile restrictions," Economics Letters, Elsevier, vol. 137(C), pages 36-40.
    14. 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.
    15. 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.
    16. Sarafidis, Vasilis & Wansbeek, Tom, 2010. "Cross-sectional Dependence in Panel Data Analysis," MPRA Paper 20367, University Library of Munich, Germany.
    17. 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.
    18. Hsiao, Cheng, 2018. "Panel models with interactive effects," Journal of Econometrics, Elsevier, vol. 206(2), pages 645-673.
    19. Laurent Gobillon & Thierry Magnac, 2014. "Regional Policy Evaluation: Interactive Fixed Effects and Synthetic Control," CESifo Working Paper Series 5077, CESifo.
    20. 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.
    21. 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.
    22. Piracha, Matloob & Tani, Massimiliano & Tchuente, Guy, 2017. "Immigration Policy and Remittance Behaviour," IZA Discussion Papers 10927, Institute of Labor Economics (IZA).
    23. 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.
    24. 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.
    25. 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.
    26. 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.
    27. Young H. Lee, 2018. "Common Factors in Major League Baseball Game Attendance," Journal of Sports Economics, , vol. 19(4), pages 583-598, May.
    28. Freeman, Hugo & Weidner, Martin, 2023. "Linear panel regressions with two-way unobserved heterogeneity," Journal of Econometrics, Elsevier, vol. 237(1).
    29. 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.
    30. 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.
    31. Hayakawa, Kazuhiko, 2016. "Improved GMM estimation of panel VAR models," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 240-264.
    32. Hyungsik Roger Moon & Martin Weidner, 2015. "Linear Regression for Panel With Unknown Number of Factors as Interactive Fixed Effects," Econometrica, Econometric Society, vol. 83(4), pages 1543-1579, July.
    33. 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.
    34. Bin Peng & Liangjun Su & Joakim Westerlund & Yanrong Yang, 2021. "Interactive Effects Panel Data Models with General Factors and Regressors," Monash Econometrics and Business Statistics Working Papers 23/21, Monash University, Department of Econometrics and Business Statistics.
    35. 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.
    36. 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).
    37. 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.
    38. Seung C. Ahn & Young H. Lee, 2014. "Major League Baseball Attendance," Journal of Sports Economics, , vol. 15(5), pages 451-477, October.
    39. Subal C. Kumbhakar & Robin Sickles & Hung-Jen Wang, 2023. "Introduction," Empirical Economics, Springer, vol. 64(6), pages 2467-2474, June.
    40. Denis Chetverikov & Elena Manresa, 2022. "Spectral and post-spectral estimators for grouped panel data models," Papers 2212.13324, arXiv.org, revised Dec 2022.
    41. 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.
    42. 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.
    43. 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.
    44. 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.
    45. 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.
    46. 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.
    47. 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.
    48. 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.
    49. 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.
    50. Juodis, Arturas & Sarafidis, Vasilis, 2020. "An Incidental Parameters Free Inference Approach for Panels with Common Shocks," MPRA Paper 104906, University Library of Munich, Germany.
    51. Sickles, Robin C. & Hao, Jiaqi & Shang, Chenjun, 2015. "Panel Data and Productivity Measurement," Working Papers 15-018, Rice University, Department of Economics.
    52. 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.
    53. Ayden Higgins & Federico Martellosio, 2019. "Shrinkage Estimation of Network Spillovers with Factor Structured Errors," Papers 1909.02823, arXiv.org, revised Nov 2021.
    54. 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.
    55. 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.
    56. 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.
    57. 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.
    58. 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.
    59. Donald Robertson & Vasilis Sarafidis, 2013. "IV Estimation of Panels with Factor Residuals," Cambridge Working Papers in Economics 1321, Faculty of Economics, University of Cambridge.
    60. 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.
    61. Fedotenkov, Igor & Idrisov, Georgy, 2021. "A supply-demand model of public sector size," Economic Systems, Elsevier, vol. 45(2).
    62. Kazuhiko Hayakawa & M. Hashem Pesaran & L. Vanessa Smith, 2014. "Transformed Maximum Likelihood Estimation of Short Dynamic Panel Data Models with Interactive Effects," CESifo Working Paper Series 4822, CESifo.
    63. Bai, Jushan & Li, Kunpeng, 2021. "Dynamic spatial panel data models with common shocks," Journal of Econometrics, Elsevier, vol. 224(1), pages 134-160.
    64. 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.
    65. Williams, Benjamin, 2020. "Nonparametric identification of discrete choice models with lagged dependent variables," Journal of Econometrics, Elsevier, vol. 215(1), pages 286-304.
    66. 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.
    67. 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.
    68. Marco Barassi & Yiannis Karavias & Chongxian Zhu, 2023. "Threshold Regression in Heterogeneous Panel Data with Interactive Fixed Effects," Papers 2308.04057, arXiv.org.
    69. Nicholas L. Brown & Peter Schmidt & Jeffrey M. Wooldridge, 2021. "Simple Alternatives to the Common Correlated Effects Model," Papers 2112.01486, arXiv.org.
    70. Hugo Freeman & Martin Weidner, 2021. "Linear Panel Regressions with Two-Way Unobserved Heterogeneity," Papers 2109.11911, arXiv.org, revised Aug 2022.
    71. 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.
    72. 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.
    73. Bai, Jushan & Li, Kunpeng, 2013. "Spatial panel data models with common shocks," MPRA Paper 52786, University Library of Munich, Germany, revised 09 Mar 2014.
    74. 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.
    75. Westerlund, Joakim, 2019. "Testing additive versus interactive effects in fixed-T panels," Economics Letters, Elsevier, vol. 174(C), pages 5-8.
    76. Guido M. Kuersteiner & Ingmar R. Prucha, 2020. "Dynamic Spatial Panel Models: Networks, Common Shocks, and Sequential Exogeneity," Econometrica, Econometric Society, vol. 88(5), pages 2109-2146, September.
    77. Perez, Marcos & Ahn, Seung Chan, 2007. "GMM Estimation of the Number of Latent Factors," MPRA Paper 4862, University Library of Munich, Germany.
    78. 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.
    79. 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.
    80. 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.
    81. 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.
    82. Duygun, Meryem & Kutlu, Levent & Sickles, Robin C., 2014. "Measuring Productivity and Efficiency: A Kalman," Working Papers 15-010, Rice University, Department of Economics.
    83. 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.
    84. Sickles, Robin C. & Song, Wonho & Zelenyuk, Valentin, 2018. "Econometric Analysis of Productivity: Theory and Implementation in R," Working Papers 18-008, Rice University, Department of Economics.
    85. 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.
    86. Georg Keilbar & Juan M. Rodriguez-Poo & Alexandra Soberon & Weining Wang, 2022. "A semiparametric approach for interactive fixed effects panel data models," Papers 2201.11482, arXiv.org, revised Mar 2023.
    87. 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.
    88. 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.
    89. Li, Si & Perez, M. Fabricio, 2021. "The evolution of pay premiums for managerial attributes," Journal of Corporate Finance, Elsevier, vol. 69(C).
    90. 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.
    91. 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.
    92. Hayakawa, Kazuhiko, 2018. "Corrected standard errors for optimal minimum distance estimator," Economics Letters, Elsevier, vol. 167(C), pages 5-9.
    93. 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.
    94. 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.
    95. 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.
    96. Ayden Higgins, 2021. "Fixed $T$ Estimation of Linear Panel Data Models with Interactive Fixed Effects," Papers 2110.05579, arXiv.org.
    97. Wei Tian, 2023. "Individual Causal Inference Using Panel Data With Multiple Outcomes," Papers 2306.01969, arXiv.org.
    98. 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.
    99. 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.
    100. 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.
    101. 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.
    102. 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.
    103. 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.
    104. 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.
    105. 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.
    106. 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.
    107. 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.
    108. 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.
    109. 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.
    110. 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.
    111. Ruoyao Shi & Jinyong Hahn, 2016. "Synthetic Control and Inference," Working Papers 201802, University of California at Riverside, Department of Economics, revised Nov 2017.
    112. 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.
    113. 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).
    114. 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.
    115. 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.

  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. 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.
    2. Ravallion, Martin, 2002. "Externalities in rural development - evidence for China," Policy Research Working Paper Series 2879, The World Bank.
    3. Luis R. Murillo‐Zamorano, 2004. "Economic Efficiency and Frontier Techniques," Journal of Economic Surveys, Wiley Blackwell, vol. 18(1), pages 33-77, February.

  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. & 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.

  2. 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.
  3. Seung C. Ahn & Alex R. Horenstein, 2013. "Eigenvalue Ratio Test for the Number of Factors," Econometrica, Econometric Society, vol. 81(3), pages 1203-1227, May.

    Cited by:

    1. Masahiko Shibamoto & Shoka Hayaki & Yoshitaka Ogisu, 2021. "COVID-19 Infection Spread and Human Mobility," Discussion Paper Series DP2021-16, Research Institute for Economics & Business Administration, Kobe University, revised Feb 2022.
    2. Woon Gyu Choi & Taesu Kang & Geun-Young Kim & Byongju Lee, 2014. "Global Liquidity Transmission to Emerging Market Economies, and Their Policy Responses," Working Papers 2014-38, Economic Research Institute, Bank of Korea.
    3. Bajraj, Gent & Lorca, Jorge & Wlasiuk, Juan M., 2023. "On foreign drivers of emerging markets fluctuations," Economic Modelling, Elsevier, vol. 129(C).
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    337. Francisco Corona & Nelson Muriel & Jesús López-Pérez, 2023. "Who is the greatest team in Liga MX? A dynamic analysis/¿Cuál es el equipo más grande de la Liga MX? Un análisis dinámico," Estudios Económicos, El Colegio de México, Centro de Estudios Económicos, vol. 38(2), pages 225–260-2.
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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. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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. 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, 2014. "Nonparametric Testing for Anomaly Effects in Empirical Asset Pricing Models," Working Papers 09-2014, Singapore Management University, School of Economics.
    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. 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.
    3. 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.

  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. 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.
    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.
    4. 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.
    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. 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.
    3. Grigorios Emvalomatis, 2012. "Adjustment and unobserved heterogeneity in dynamic stochastic frontier models," Journal of Productivity Analysis, Springer, vol. 37(1), pages 7-16, February.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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).
    11. Sickles, Robin C. & Hao, Jiaqi & Shang, Chenjun, 2015. "Panel Data and Productivity Measurement," Working Papers 15-018, Rice University, Department of Economics.
    12. 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.
    13. Camilla Mastromarco & Laura Serlenga & Yongcheol Shin, 2023. "Regional Productivity Network in the EU," CESifo Working Paper Series 10404, CESifo.
    14. 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.
    15. 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.
    16. 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.
    17. 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.
    18. 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.
    19. 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).
    20. Perez, Marcos & Ahn, Seung Chan, 2007. "GMM Estimation of the Number of Latent Factors," MPRA Paper 4862, University Library of Munich, Germany.
    21. 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.
    22. 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.
    23. Roman Matkovskyy, 2016. "Arbitrary temporal heterogeneity in time of European countries panel model," Economics Bulletin, AccessEcon, vol. 36(1), pages 576-587.
    24. Sickles, Robin C. & Song, Wonho & Zelenyuk, Valentin, 2018. "Econometric Analysis of Productivity: Theory and Implementation in R," Working Papers 18-008, Rice University, Department of Economics.
    25. 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.
    26. 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.
    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. Geert Bekaert & Campbell R. Harvey & Christian Lundblad, 2007. "Liquidity and Expected Returns: Lessons from Emerging Markets," The Review of Financial Studies, Society for Financial Studies, vol. 20(6), pages 1783-1831, November.
    4. Gospodinov, Nikolay & Robotti, Cesare, 2021. "Common pricing across asset classes: Empirical evidence revisited," Journal of Financial Economics, Elsevier, vol. 140(1), pages 292-324.
    5. 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.
    6. Lingwei Kong, 2023. "Weak (Proxy) Factors Robust Hansen-Jagannathan Distance For Linear Asset Pricing Models," Papers 2307.14499, arXiv.org.
    7. 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.
    8. 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.
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    1. Juodis, Arturas & Sarafidis, Vasilis, 2014. "Fixed T Dynamic Panel Data Estimators with Multi-Factor Errors," MPRA Paper 57659, University Library of Munich, Germany.
    2. Zhan Gao & M. Hashem Pesaran, 2023. "Identification and estimation of categorical random coefficient models," Empirical Economics, Springer, vol. 64(6), pages 2543-2588, June.
    3. 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.
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    5. 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.
    6. 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.
    7. Feng, Qu & Horrace, William C., 2007. "Fixed-effect estimation of technical efficiency with time-invariant dummies," Economics Letters, Elsevier, vol. 95(2), pages 247-252, May.
    8. Juodis, Arturas & Sarafidis, Vasilis, 2015. "A Simple Estimator for Short Panels with Common Factors," MPRA Paper 68164, University Library of Munich, Germany.
    9. Bai, Jushan, 2013. "Likelihood approach to dynamic panel models with interactive effects," MPRA Paper 50267, University Library of Munich, Germany.
    10. Chen, Liang, 2015. "Set identification of panel data models with interactive effects via quantile restrictions," Economics Letters, Elsevier, vol. 137(C), pages 36-40.
    11. 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.
    12. 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.
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    14. Hsiao, C. & Pesaran, M.H., 2004. "‘Random Coefficient Panel Data Models’," Cambridge Working Papers in Economics 0434, Faculty of Economics, University of Cambridge.
    15. Sarafidis, Vasilis & Wansbeek, Tom, 2010. "Cross-sectional Dependence in Panel Data Analysis," MPRA Paper 20367, University Library of Munich, Germany.
    16. 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.
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    18. Hsiao, Cheng, 2018. "Panel models with interactive effects," Journal of Econometrics, Elsevier, vol. 206(2), pages 645-673.
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    93. 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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    95. 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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    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. Mastromarco, Camilla & Simar, Leopold, 2018. "Globalization and productivity: A robust nonparametric world frontier analysis," LIDAM Reprints ISBA 2018008, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    4. 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.
    5. 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.
    6. Mastromarco, Camilla & Simar, Leopold, 2013. "Effect of FDI and Time on Catching-up: New Insights from a Conditional Nonparametric Frontier Analysis," LIDAM Discussion Papers ISBA 2013015, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    7. Kutlu, Levent & Liu, Shasha & Sickles, Robin C., 2018. "Cost, Revenue, and Profit Function Estimates," Working Papers 18-006, Rice University, Department of Economics.
    8. 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.
    9. Levent Kutlu, 2020. "Greenhouse Gas Emission Efficiencies of World Countries," IJERPH, MDPI, vol. 17(23), pages 1-11, November.
    10. 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.
    11. 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.
    12. Grigorios Emvalomatis, 2012. "Adjustment and unobserved heterogeneity in dynamic stochastic frontier models," Journal of Productivity Analysis, Springer, vol. 37(1), pages 7-16, February.
    13. 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.
    14. Meryem Duygun & Jiaqi Hao & Anders Isaksson & Robin C. Sickles, 2017. "World Productivity Growth: A Model Averaging Approach," Pacific Economic Review, Wiley Blackwell, vol. 22(4), pages 587-619, October.
    15. Belotti, Federico & Ilardi, Giuseppe, 2018. "Consistent inference in fixed-effects stochastic frontier models," Journal of Econometrics, Elsevier, vol. 202(2), pages 161-177.
    16. 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.
    17. 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.
    18. Ang, Frederic & Oude Lansink, Alfons, 2014. "Dynamic profit inefficiency: a DEA application to Belgian dairy farms," 2014 International Congress, August 26-29, 2014, Ljubljana, Slovenia 182649, European Association of Agricultural Economists.
    19. 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.
    20. 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.
    21. 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.
    22. Camilla Mastromarco & Léopold Simar, 2021. "Latent heterogeneity to evaluate the effect of human capital on world technology frontier," Journal of Productivity Analysis, Springer, vol. 55(2), pages 71-89, April.
    23. 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.
    24. 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).
    25. 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.
    26. Sickles, Robin C. & Hao, Jiaqi & Shang, Chenjun, 2015. "Panel Data and Productivity Measurement," Working Papers 15-018, Rice University, Department of Economics.
    27. 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.
    28. 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.
    29. 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.
    30. 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.
    31. 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.
    32. Alem, Habtamu, 2020. "Performance of the Norwegian dairy farms: A dynamic stochastic approach," Research in Economics, Elsevier, vol. 74(3), pages 263-271.
    33. 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.
    34. 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).
    35. Galán, Jorge E. & Pollitt, Michael G., 2014. "Inefficiency persistence and heterogeneity in Colombian electricity utilities," Energy Economics, Elsevier, vol. 46(C), pages 31-44.
    36. 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.
    37. 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.
    38. 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.
    39. 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.
    40. 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.
    41. 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.
    42. Duygun, Meryem & Kutlu, Levent & Sickles, Robin C., 2014. "Measuring Productivity and Efficiency: A Kalman," Working Papers 15-010, Rice University, Department of Economics.
    43. Spyro Stefanou, "undated". "A Dynamic Characterization of Efficiency," Working Papers 0712, University of Crete, Department of Economics, revised 00 Oct 2006.
    44. 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.
    45. 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.
    46. 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.
    47. 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.
    48. 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.
    49. 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.
    50. 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.
    51. 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.
    52. Das, Tirthatanmoy & Polachek, Solomon W., 2017. "Estimating labor force joiners and leavers using a heterogeneity augmented two-tier stochastic frontier," Journal of Econometrics, Elsevier, vol. 199(2), pages 156-172.
    53. 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.
    54. 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).
    55. Kutlu, Levent, 2017. "A constrained state space approach for estimating firm efficiency," Economics Letters, Elsevier, vol. 152(C), pages 54-56.
    56. 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.
    57. 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.
    58. 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.
    59. 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.
    60. 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.
    61. Chen, Hong & Wang, Xi & Singh, Baljeet, 2021. "Transient and persistent inefficiency traps in Chinese provinces," Economic Modelling, Elsevier, vol. 97(C), pages 335-347.
    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. 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.
    3. Qian, Hailong & Schmidt, Peter, 2003. "Partial GLS regression," Economics Letters, Elsevier, vol. 79(3), pages 385-392, June.
    4. 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.
    5. 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.
    6. 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.
    7. Jean-Bernard Chatelain & Kirsten Ralf, 2021. "Inference on time-invariant variables using panel data: a pretest estimator," Working Papers halshs-01719835, HAL.
    8. Eduardo Fé, 2012. "Instrumental variable estimation of heteroskedasticity adaptive error component models," Statistical Papers, Springer, vol. 53(3), pages 577-615, August.
    9. 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.
    10. 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.
    11. 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.
    12. Jee-Seon Kim & Edward Frees, 2007. "Multilevel Modeling with Correlated Effects," Psychometrika, Springer;The Psychometric Society, vol. 72(4), pages 505-533, December.
    13. 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.
    14. 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.
    15. 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.
    16. Mark A. Klinedinst, 2016. "Bank Decapitalization and Credit Union Capitalization," SAGE Open, , vol. 6(1), pages 21582440166, February.
    17. 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.
    18. 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.
    19. Yoichi Matsubayashi & Takao Fujii, 2012. "Substitutability of Savings by Sectors: OECD Experiences," Discussion Papers 1215, Graduate School of Economics, Kobe University.
    20. Helmut Farbmacher & Harald Tauchmann, 2023. "Linear fixed-effects estimation with nonrepeated outcomes," Econometric Reviews, Taylor & Francis Journals, vol. 42(8), pages 635-654, September.
    21. Eduardo Fé Rodríguez, 2009. "Adaptive Instrumental Variable Estimation of Heteroskedastic Error Component Models," Economics Discussion Paper Series 0921, Economics, The University of Manchester.
    22. M. Hashem Pesaran & Qiankun Zhou, 2014. "Estimation of Time-invariant Effects in Static Panel Data Models," CESifo Working Paper Series 4983, CESifo.
    23. Mitze, Timo, 2010. "Estimating Gravity Models of International Trade with Correlated Time-Fixed Regressors: To IV or not IV?," MPRA Paper 23540, University Library of Munich, Germany.
    24. 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.
    25. 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.
    26. Inoue, Atsushi, 2008. "Efficient estimation and inference in linear pseudo-panel data models," Journal of Econometrics, Elsevier, vol. 142(1), pages 449-466, January.
    27. Yang, Yimin, 2021. "Efficient estimation of multi-level models with strictly exogenous explanatory variables," Economics Letters, Elsevier, vol. 198(C).
    28. 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.
    29. 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.
    30. 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).
    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. Christopher F Baum & Mark E. Schaffer & Steven Stillman, 2007. "Enhanced routines for instrumental variables/generalized method of moments estimation and testing," Stata Journal, StataCorp LP, vol. 7(4), pages 465-506, December.
    2. 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.
    3. 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.
    4. Doko Tchatoka, Firmin, 2013. "On bootstrap validity for specification tests with weak instruments," MPRA Paper 47485, University Library of Munich, Germany.
    5. 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.
    6. 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.
    7. Jan F. KIVIET & Milan PLEUS, 2012. "The performance of tests on endogeneity of subsets of explanatory variables scanned by simulation," Economic Growth Centre Working Paper Series 1208, Nanyang Technological University, School of Social Sciences, Economic Growth Centre.
    8. Firmin Doko Tchatoka & Jean-Marie Dufour, 2016. "Exogeneity tests, incomplete models, weak identification and non-Gaussian distributions: invariance and finite-sample distributional theory," CIRANO Working Papers 2016s-62, CIRANO.

  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. Céline Nauges & Alban Thomas, 2003. "Long-run Study of Residential Water Consumption," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 26(1), pages 25-43, September.
    2. EKINCI, Ramazan & TUZUN,Osman & CEYLAN, Fatih, 2020. "The Relationship Between Inflation And Economic Growth: Experiences Of Some Inflation Targeting Countries," Studii Financiare (Financial Studies), Centre of Financial and Monetary Research "Victor Slavescu", vol. 24(1), pages 6-20, March.
    3. Jan F. Kiviet, 2005. "Judging Contending Estimators by Simulation: Tournaments in Dynamic Panel Data Models," Tinbergen Institute Discussion Papers 05-112/4, Tinbergen Institute.
    4. 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.
    5. 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.
    6. d’Agostino, Giorgio & Dunne, J. Paul & Pieroni, Luca, 2016. "Government Spending, Corruption and Economic Growth," World Development, Elsevier, vol. 84(C), pages 190-205.
    7. 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.
    8. Tue Gørgens & Christopher L. Skeels & Allan H. Würtz, 2009. "Efficient Estimation of Non-Linear Dynamic Panel Data Models with Application to Smooth Transition Models," CREATES Research Papers 2009-51, Department of Economics and Business Economics, Aarhus University.
    9. Montes-Rojas Gabriel & Sosa-Escudero Walter & Zincenko Federico, 2020. "Level-Based Estimation of Dynamic Panel Models," Journal of Econometric Methods, De Gruyter, vol. 9(1), pages 1-23, January.
    10. Calderón, César & Chong, Alberto E., 2001. "Volume and Quality of Infrastructure and the Distribution of Income: An Empirical Investigation," IDB Publications (Working Papers) 6087, Inter-American Development Bank.
    11. Elhorst, J. Paul, 2003. "Unconditional maximum likelihood estimation of dynamic models for spatial panels," Research Report 03C27, University of Groningen, Research Institute SOM (Systems, Organisations and Management).
    12. Pua, Andrew Adrian Yu & Fritsch, Markus & Schnurbus, Joachim, 2019. "Large sample properties of an IV estimator based on the Ahn and Schmidt moment conditions," Passauer Diskussionspapiere, Betriebswirtschaftliche Reihe B-37-19, University of Passau, Faculty of Business and Economics.
    13. 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.
    14. Pua, Andrew Adrian Yu & Fritsch, Markus & Schnurbus, Joachim, 2019. "Practical aspects of using quadratic moment conditions in linear dynamic panel data models," Passauer Diskussionspapiere, Betriebswirtschaftliche Reihe B-38-19, University of Passau, Faculty of Business and Economics.
    15. Hugo Kruiniger, 2006. "GMM Estimation and Inference in Dynamic Panel Data Models with Persistent Data," Working Papers 560, Queen Mary University of London, School of Economics and Finance.
    16. 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.
    17. 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.
    18. 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.
    19. 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).
    20. Gareth M. Thomas & Seung C. Ahn, 2004. "Likelihood Based Inference for amic Panel Data Models," Econometric Society 2004 Far Eastern Meetings 669, Econometric Society.
    21. 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.
    22. 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.
    23. 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.
    24. 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.
    25. De Blander, Rembert, 2020. "Iterative estimation correcting for error auto-correlation in short panels, applied to lagged dependent variable models," Econometrics and Statistics, Elsevier, vol. 15(C), pages 3-29.
    26. Chen, Chien-Ming & van Dalen, Jan, 2010. "Measuring dynamic efficiency: Theories and an integrated methodology," European Journal of Operational Research, Elsevier, vol. 203(3), pages 749-760, June.
    27. César Calderón & Alberto Chong & Norman Loayza, 1999. "Determinants of Current Account Deficits in Developing Countries," Working Papers Central Bank of Chile 51, Central Bank of Chile.
    28. 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.
    29. 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.
    30. Mouelhi, Rim Ben Ayed, 2007. "Impact of trade liberalization on firm's labour demand by skill: The case of Tunisian manufacturing," Labour Economics, Elsevier, vol. 14(3), pages 539-563, June.
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    1. Badi H. Baltagi, 1999. "Specification Tests in Panel Data Models Using Artificial Regressions," Annals of Economics and Statistics, GENES, issue 55-56, pages 277-297.
    2. Rocha, Roberto & Morales, Marco & Thorburn, Craig, 2008. "An empirical analysis of the annuity rate in Chile," Journal of Pension Economics and Finance, Cambridge University Press, vol. 7(1), pages 95-119, March.
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    4. Yushi Yoshida & Hiro Ito, 2004. "How do the Asian Economies Compete with Japan in the US Market, China Exceptional? A Triangular Trade Approach," Discussion Papers 18, Kyushu Sangyo University, Faculty of Economics.
    5. Rüttenauer, Tobias & Ludwig, Volker, 2019. "Fixed Effects Individual Slopes: Accounting and Testing for Heterogeneous Effects in Panel Data or Other Multilevel Models," SocArXiv k4rnu, Center for Open Science.
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    8. El Aynaoui, Karim & Ibourk, Aomar, 2014. "Les déterminants des exportations du Maroc : une investigation empirique sur données de panel [The determinants of Morocco's exports: An empirical investigation using panel data]," MPRA Paper 63021, University Library of Munich, Germany, revised 2014.
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    Cited by:

    1. Mengistae, Taye, 1999. "Wage rates and job queues - does the public sector overpay in Ethiopia?," Policy Research Working Paper Series 2105, The World Bank.
    2. Benoît Rapoport & Céline Bourdais, 2008. "Parental time and working schedules," Journal of Population Economics, Springer;European Society for Population Economics, vol. 21(4), pages 903-932, October.
    3. G Johnes, 2000. "Wage differentials and the responsiveness of labor supply: an international comparison," Working Papers 539615, Lancaster University Management School, Economics Department.

  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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