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Stochastic frontier models with multiple time-varying individual effects

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Cited by:

  1. Young Hoon Lee, 2013. "Estimation of temporal variations in fan loyalty: application of multi-factor models," Chapters, in: Plácido Rodríguez & Stefan Késenne & Jaume García (ed.), The Econometrics of Sport, chapter 8, pages 135-153, Edward Elgar Publishing.
  2. 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).
  3. Sickles, Robin C. & Hao, Jiaqi & Shang, Chenjun, 2015. "Panel Data and Productivity Measurement," Working Papers 15-018, Rice University, Department of Economics.
  4. Camilla Mastromarco & Laura Serlenga & Yongcheol Shin, 2023. "Regional Productivity Network in the EU," CESifo Working Paper Series 10404, CESifo.
  5. 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.
  6. 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.
  7. 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.
  8. 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.
  9. 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.
  10. 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.
  11. 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.
  12. 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.
  13. 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.
  14. 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.
  15. 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).
  16. 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.
  17. 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).
  18. Perez, Marcos & Ahn, Seung Chan, 2007. "GMM Estimation of the Number of Latent Factors," MPRA Paper 4862, University Library of Munich, Germany.
  19. Pavlos Almanidis & Giannis Karagiannis & Robin Sickles, 2015. "Semi-nonparametric spline modifications to the Cornwell–Schmidt–Sickles estimator: an analysis of US banking productivity," Empirical Economics, Springer, vol. 48(1), pages 169-191, February.
  20. Roman Matkovskyy, 2016. "Arbitrary temporal heterogeneity in time of European countries panel model," Economics Bulletin, AccessEcon, vol. 36(1), pages 576-587.
  21. 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.
  22. Grigorios Emvalomatis, 2012. "Adjustment and unobserved heterogeneity in dynamic stochastic frontier models," Journal of Productivity Analysis, Springer, vol. 37(1), pages 7-16, February.
  23. 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.
  24. 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.
  25. 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.
  26. 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.
  27. Kok Fong See & Shawna Grosskopf & Vivian Valdmanis & 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 WP072021, School of Economics, University of Queensland, Australia.
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