Stochastic frontier models with multiple time-varying individual effects

Journal of Productivity Analysis

Volumn 27, Issue 1, 2007, Pages 1-12

  Ahn, Seung C ^a   Lee, Young H ^b   Schmidt, Peter ^c  

^a ARIZONA STATE UNIVERSITY   (United States)

^b Hansung University   (South Korea)

^c MICHIGAN STATE UNIVERSITY   (United States)

Author keywords

Panel data; Stochastic frontiers; Time varying technical efficiency

Indexed keywords

EID: 33847083573     PISSN: 0895562X     EISSN: 15730441     Source Type: Journal    
DOI: 10.1007/s11123-006-0020-8     Document Type: Article

References (22)

1. Ahn SC, Lee YH, Schmidt P (2001) GMM estimation of linear panel data models with time-varying individual effects. J Econometrics 101:219-255
2. Amemiya T (1978) The estimation of a simultaneous equation generalized probit model. Econometrica 46:1193-1205
3. Bai J (2003) Inferential theory for factor models of large dimensions. Econometrica 71:135-171
4. Bai J, Ng S (2002) Determining the number of factors in approximate factor models. Econometrica 70:191-221
5. Battese GE, Coelli TJ (1992) Frontier production functions, technical efficiency and panel data with application to paddy farmers in India. J Prod Anal 3:153-169
6. Chamberlain G (1984) Panel data. In: Griliches Z, Intriligator M, (eds) Handbook of econometrics II. North-Holland
7. Cornwell C, Schmidt P, Sickles R (1990) Production frontiers with cross-sectional and time-series variation in efficiency levels. J Econometrics 46:185-200
8. Cuesta RA (2000) A production model with firm-specific temporal variation in technical inefficiency: with application to spanish dairy farms. J Prod Anal 13:139-149
9. Druska V, Horrace WC (2004) Generalized moments estimation for spatial panel data: indenesian rice farms. Am J Agric Econ 86 (1):185-198
10. Erwidodo (1990) Panel data analysis on farm-level efficiency, input demand and output supply of rice farming in west Java, Indonesia, Unpublished Ph.D. Dissertation, Department of Agricultural Economics, Michigan State University, East Lansing
11. Han C, Orea L, Schmidt P (2005) Estimation of a panel data model with parametric temporal variation in individual effects. J Econometrics 126 (1):241-267
12. Hansen PL (1982) Large sample properties of generalized method of moments estimators. Econometrica 50:1029-1054
13. Jöreskog KG (1967) Some contributions to maximum likelihood factor analysis. Psychometrika 34:183-202
14. Kim SH, Lee YH (2006) The productivity debate of east asia revisited: a stochastic frontier approach. Appl Econ 38(14/10):1697-1706
15. Kumbhakar SC (1990) Production frontiers, panel data, and time-varying technical inefficiency. J Econometrics 46:201-211
16. Ledermann W (1937) On the rank of the reduced correlation matrix in multiple-factor analysis. Psychometrika 2:85-93
17. Lee YH (2006) A stochastic production frontier model with group-specific temporal variation in technical efficiency. Eur J Oper Res 174:1616-1630
18. Lee YH, Schmidt P (1993) A production frontier model with flexible temporal variation in technical inefficiency. In: Fried H, Lovell CAK, Schmidt S (eds) The measurement of productive efficiency: techniques and applications. Oxford University Press, Oxford
19. Newey WK (1987) Efficient estimation of limited dependent variable models with endogenous explanatory variables. J Econometrics 36:231-250
20. Pitt M, Lee L-F (1981) The measurement and sources of technical inefficiency in the Indonesian Weaving Industry. J Dev Econ 9:43-64
21. Schmidt P, Sickles RC (1984) Production frontiers and panel data. J Business Econ Stat 2:367-374
22. Wansbeek T, Meijer E (2000) Measurement error and latent variables in econometrics. Amsterdam, Elsevier