Using Copulas to Model Time Dependence in Stochastic Frontier Models

REFERENCES

• Aigner , D. , Lovell , C. A. K. , Schmidt , P. ( 1977 ). Formulation and estimation of stochastic frontier production function models . Journal of Econometrics 6 ( 1 ): 21 – 37 .
   Google Scholar
• Alvarez , A. , Amsler , C. , Orea , L. , Schmidt , P. ( 2006 ). Interpreting and testing the scaling property in models where inefficiency depends on firm characteristics . Journal of Productivity Analysis 25 ( 3 ): 201 – 212 .
   Web of Science ®Google Scholar
• Battese , G. E. , Coelli , T. J. ( 1992 ). Frontier production functions, technical efficiency and panel data: With application to paddy farmers in india. Journal of Productivity Analysis 3(1–2): 153–169 .
   Google Scholar
• Battese , G. E. , Coelli , T. J. ( 1995 ). A model for technical inefficiency effects in a stochastic frontier production function for panel data . Empirical Economics 20 : 325 – 332 .
   Google Scholar
• Bee , M. ( 2010 ). Adaptive importance sampling for simulating copula-based distributions . Insurance: Mathematics and Economics 48 ( 2 ): 237 – 245 .
   Web of Science ®Google Scholar
• Caudill , S. B. , Ford , J. M. , Gropper , D. M. ( 1995 ). Frontier estimation and firm-specific inefficiency measures in the presence of heteroscedasticity . Journal of Business and Economic Statistics 13 ( 1 ): 105 – 111 .
   Web of Science ®Google Scholar
• Cherubini , U. , Luciano , E. , Vecchiato , W. ( 2004 ). Copula Methods in Finance. Wiley Finance Series. John Wiley and Sons Ltd .
   Google Scholar
• Devroye , L. ( 1986 ). Non-Uniform Random Variate Generation . New York : Springer .
   Google Scholar
• Erwidodo ( 1990 ). Panel Data Analysis on Farm-Level Efficiency, Input Demand and Output Supply of Rice Farming in West Java, Indonesia. Unpublished dissertation, Department of Agricultural Economics, Michigan State University, East Lansing, MI .
   Google Scholar
• Fang , H.-B. , Fang , K.-T. , Kotz , S. ( 2002 ). The meta-elliptical distributions with given marginals . Journal of Multivariate Analysis 82 ( 1 ): 1 – 16 .
   Web of Science ®Google Scholar
• Genest , C. , Rémillard , B. , Beaudoin , D. ( 2009 ). Goodness-of-fit tests for copulas: A review and a power study . Insurance: Mathematics and Economics 44 ( 2 ): 199 – 213 .
   Web of Science ®Google Scholar
• Gill , J. ( 2008 ). Bayesian Methods: A Social and Behavioral Sciences Approach . London : Chapman and Hall/CRC .
   Google Scholar
• Gouriéroux , C. , Monfort , A. ( 1991 ). Simulation based inference in models with heterogeneity . Annales d’Économie et de Statistique ( 20/21 ): 69 – 107 .
   Google Scholar
• Greene , W. H. ( 2003 ). Econometric Analysis. , 5th ed. Upper Saddle River , NJ : Prentice Hall .
   Google Scholar
• Greene , W. H. ( 2005 ). Reconsidering heterogeneity in panel data estimators of the stochastic frontier model . Journal of Econometrics 126 ( 2 ): 269 – 303 .
   Web of Science ®Google Scholar
• Hadri , K. ( 1999 ). Estimation of a doubly heteroscedastic stochastic frontier cost function . Journal of Business and Economic Statistics 17 ( 3 ): 359 – 363 .
   Web of Science ®Google Scholar
• Hansen , L. P. ( 1982 ). Large sample properties of generalized method of moments estimators . Econometrica 50 ( 4 ): 1029 – 1054 .
   Web of Science ®Google Scholar
• Hayashi , F. ( 2000 ). Econometrics . Princeton : Princeton University Press .
   Google Scholar
• Horrace , W. C. , Schmidt , P. ( 1996 ). Confidence statements for efficiency estimates from stochastic frontier models . Journal of Productivity Analysis 7 ( 2 ): 257 – 282 .
   Web of Science ®Google Scholar
• Horrace , W. C. , Schmidt , P. ( 2000 ). Multiple comparisons with the best, with economic applications . Journal of Applied Econometrics 15 ( 1 ): 1 – 26 .
   Web of Science ®Google Scholar
• Horrace , W. C. ( 2005 ). Some results on the multivariate truncated normal distribution . Journal of Multivariate Analysis 94 ( 1 ): 209 – 221 .
   Web of Science ®Google Scholar
• Jondrow , J. , Lovell , C. A. K. , Materov , I. S. , Schmidt , P. ( 1982 ). On the estimation of technical inefficiency in the stochastic frontier production function model . Journal of Econometrics 19 ( 2–3 ): 233 – 238 .
   Web of Science ®Google Scholar
• Kojadinovic , I. , Yan , J. ( 2010 ). Modeling multivariate distributions with continuous margins using the copula r package. Journal of Statistical Software 34(9) .
   Google Scholar
• Kumbhakar , S. C. ( 1990 ). Production frontiers, panel data, and time-varying technical inefficiency . Journal of Econometrics 46 ( 1–2 ): 201 – 211 .
   Web of Science ®Google Scholar
• Lee , Y. H. , Schmidt , P. ( 1993 ). A production frontier model with flexible temporal variation in technical inefficiency . In: Fried , H. , Lovell , C. , Schmidt , P. , eds. Measurement of Productive Efficiency: Techniques and Applications . New York : Oxford University Press .
   Google Scholar
• Li , H. , Scarsini , M. , Shaked , M. (1996). Linkages: A tool for the construction of multivariate distributions with given nonoverlapping multivariate marginals. Journal of Multivariate Analysis 56(1):20–41.
   Web of Science ®Google Scholar
• McFadden , D. , Ruud , P. A. ( 1994 ). Estimation by simulation . The Review of Economics and Statistics 76 ( 4 ): 591 – 608 .
   Web of Science ®Google Scholar
• McFadden , D. ( 1989 ). A method of simulated moments for estimation of discrete response models without numerical integration . Econometrica 57 ( 5 ): 995 – 1026 .
   Web of Science ®Google Scholar
• Meeusen , W. , van den Broeck , J. ( 1977 ). Efficiency estimation from cobb-douglas production functions with composed error . International Economic Review 18 ( 2 ): 435 – 444 .
   Web of Science ®Google Scholar
• Nelsen , R. B. ( 2006 ). An Introduction to Copulas, Vol. 139 of Springer Series in Statistics. 2nd ed. New York: Springer .
   Google Scholar
• Pitt , M. M. , Lee , L.-F. ( 1981 ). The measurement and sources of technical inefficiency in the indonesian weaving industry . Journal of Development Economics 9 ( 1 ): 43 – 64 .
   Web of Science ®Google Scholar
• Prokhorov , A. , Schmidt , P. ( 2009 ). Likelihood-based estimation in a panel setting: robustness, redundancy and validity of copulas . Journal of Econometrics 153 ( 1 ): 93 – 104 .
   Web of Science ®Google Scholar
• Robert , C. , Casella , G. ( 2004 ). Monte Carlo Statistical Methods . New York : Springer .
   Google Scholar
• Sklar , A. ( 1959 ). Fonctions de répartition à n dimensions et leurs marges . Publications de l'Institut de Statistique de l'Université de Paris 8 : 229 – 231 .
   Google Scholar
• Tsay , W.-J. , Huang , C. J. , Fu , T.-T. , Ho , I. L. A. ( 2009 ). Maximum likelihood estimation of censored stochastic frontier models: An application to the three-stage dea method. IEAS Working Paper: Academia Sinica .
   Google Scholar
• Wang , H.-J. ( 2002 ). Heteroscedasticity and non-monotonic efficiency effects of a stochastic frontier model . Journal of Productivity Analysis 18 ( 3 ): 241 – 253 .
   Web of Science ®Google Scholar
• Wang , W. S. , Amsler , C. , Schmidt , P. ( 2011 ). Goodness of fit tests in stochastic frontier models . Journal of Productivity Analysis 35 : 95 – 118 .
   Web of Science ®Google Scholar