Understanding prediction intervals for firm specific inefficiency scores from parametric stochastic frontier models

Journal of Productivity Analysis

Volumn 42, Issue 1, 2014, Pages 55-65

  Wheat, Phill ^a   Greene, William ^b   Smith, Andrew ^a  

^a UNIVERSITY OF LEEDS   (United Kingdom)

^b NEW YORK UNIVERSITY   (United States)

Author keywords

Efficiency; Prediction intervals; Stochastic frontier

Indexed keywords

EID: 84919658471     PISSN: 0895562X     EISSN: 15730441     Source Type: Journal    
DOI: 10.1007/s11123-013-0346-y     Document Type: Article

References (28)

1. Aigner DJ, Lovell CAK, Schmidt P (1977) Formulation and estimation of stochastic frontier production function models. J Econom 6(1):21–37
2. Alvarez A, Amsler C, Orea L, Schmidt P (2006) Interpreting and testing the scaling property in models where inefficiency depends on firm characteristics. J Prod Anal 25:201–212
3. Amsler C, Leonard M, Schmidt P (2010) Estimation and inference in parametric deterministic frontier models, working paper
4. Battese GE, Coelli TJ (1992) Frontier production functions and the efficiencies of Indian Farms Using Panel data from ICRISAT’s village level studies. J Quant Econ 5:327–348
5. Bera AK, Sharma SC (1999) Estimating production uncertainty in stochastic frontier production frontier models. J Prod Anal 12:187–210
6. Coelli T, Rao DSP, O’Donnell CJ, Battese GE (2005) An introduction to efficiency and productivity analysis, 2nd edn. New York, Springer
7. Cuesta RA (2000) A production model with firm-specific temporal variation in technical inefficiency: with application to Spanish dairy farms. J Prod Anal 13(2):139–152
8. Econometric Software Inc. (2010) LIMDEP, user’s manual. http://www.limdep.com, Plainview, NY
9. Farrell MJ (1957) The measurement of productive efficiency. J R Stat Soc Ser A Gen 120(3):253–290
10. Flores-Lagunes A, Horrace WC, Schnier KE (2007) Identifying technically efficient fishing vessels: a non-empty, minimal subset approach. J Appl Econom 22:729–745
11. Greene WH (2008) The econometric approach to efficiency analysis. In: Fried HO, Lovell CAK, Schmidt SS (eds) The measurement of productive efficiency growth, 2nd edn. Oxford University Press, New York
12. Greene WH (2011) Econometric analysis, 7th edn. Prentice Hall, New York
13. Hjalmarsson L, Kumbhakar SC, Heshmati A (1996) DEA, DFA and SFA: a comparison. J Prod Anal 7:303–327
14. Horrace WC (2005) On ranking and selection from independent truncated normal distributions. J Econom 126:335–354
15. Horrace WC, Schmidt P (1996) Confidence statements for efficiency estimates from stochastic frontier models. J Prod Anal 7(2/3):257–282
16. Horrace WC, Schmidt P (2000) Multiple comparisons with the best, with economic applications. J Appl Econom 15:1–26
17. Jondrow J, Lovell CAK, Materov IS, Schmidt P (1982) On estimation of technical inefficiency in the stochastic frontier production function model. J Econom 19:233–238
18. Kim Y, Schmidt P (2008) Marginal comparisons with the best and the efficiency measurement problem. J Bus Econ Stat 26(2):253–260
19. Krinsky I, Robb A (1986) On approximating the statistical properties of elasticities. Rev Econ Stat 68(4):715–719
20. Kumbhakar SC, Löthgren M (1998) A Monte Carlo analysis of technical inefficiency predictors. Working paper series in economics and finance, no. 229, Stockholm School of Economics
21. Meeusen W, van Den Broeck J (1977) Efficiency estimation from Cobb-Douglas production functions with composed error. Intern Econ Rev 18(2):435–444
22. Pitt M, Lee L (1981) The measurement and sources of technical inefficiency in Indonesian weaving industry. J Dev Econ 9:43–64
23. R Development Core Team (2010) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. ISBN 3-900051-07-0. http://www.R-project.org
24. Simar L, Wilson PW (2010) Inferences from cross-sectional, stochastic frontier models. Econom Rev 29(1):62–98
25. Smith A, Wheat P (2012) Evaluating alternative policy responses to franchise failure: Evidence from the passenger rail sector in Britain. J Transp Econ Policy 46(1):25–43
26. Taube R (1988) Möglichkeiten der Effizienzmess ung von öffentlichen Verwaltungen. Duncker & Humbolt GmbH, Berlin
27. Train KE (2009) Discrete choice methods with simulation, 2nd edn. Cambridge University Press, New York
28. Waldman DM (1984) Properties of technical efficiency estimators in the stochastic frontier model. J Econom 25:353–364