Computing confidence intervals for output-oriented DEA models: An application to agricultural research in Brazil

Journal of the Operational Research Society

Volumn 62, Issue 10, 2011, Pages 1844-1850

  Souza, G ^a   Souza, M ^a   Gomes, E ^a  

^a EMBRAPA CERRADOS   (Brazil)

Author keywords

agricultural research; bootstrap; confidence intervals; data envelopment analysis

Indexed keywords

AGRICULTURE; DATA ENVELOPMENT ANALYSIS; DECISION MAKING; EFFICIENCY; NORMAL DISTRIBUTION; RANDOM ERRORS;

AGRICULTURAL RESEARCH; BOOTSTRAP; CONFIDENCE INTERVAL; EFFICIENCY MEASUREMENT; RESEARCH PRODUCTIONS; STATISTICAL PROPERTIES; THEORETICAL FRAMEWORK; TRUNCATED NORMAL DISTRIBUTIONS;

STATISTICAL METHODS;

EID: 80051874835     PISSN: 01605682     EISSN: 14769360     Source Type: Journal    
DOI: 10.1057/jors.2010.137     Document Type: Article

References (25)

1. ArellanoMand Bond S (1991). Some tests of specification for panel data: Monte Carlo evidence and an application to employment equations. Rev Econ Stud 58: 277-297.
2. Arellano M and Bover O (1995). Another look at the instrumental variable estimation of error-components models. J Econometrics 68: 29-51.
3. Banker RD (1993). Maximum likelihood, consistency and DEA: A statistical foundation. Mngt Sci 39: 1265-1273.
4. Banker RD, Charnes A and Cooper WW (1984). Some models for estimating technical scale inefficiencies in data envelopment analysis. Mngt Sci 30: 1078-1092. (Pubitemid 14651320)
5. Banker RD and Natarajan R (2004). Statistical tests based on DEA efficiency scores. In: Cooper WW, Seiford LM and J Zhu (eds). Handbook on Data Envelopment Analysis. Kluwer International Series: Boston, pp 299-321.
6. Banker RD and Natarajan R (2008). Evaluating contextual variables affecting productivity using data envelopment analysis. Opns Res 56: 48-58. (Pubitemid 351463108)
7. Blundell R and Bond S (1998). Initial conditions and moment restrictions in dynamic panel data models. J Econometrics 87: 115-143. (Pubitemid 128415761)
8. Charnes A, Cooper WW and Rhodes E (1978). Measuring the efficiency of decision making units. Eur J Opl Res 2: 429-444. (Pubitemid 9402758)
9. Coelli TJ, Prasada Rao DS, O'Donnell CJ and Battese GE (2005). An Introduction to Efficiency and Productivity Analysis. 2nd edn. Springer: New York.
10. ConoverWJ (1998). Practical Nonparametric Statistics. Wiley: New York.
11. Daraio C and Simar L (2007). Advanced Robust and Nonparametric Methods in Efficiency Analysis. Springer: New York.
12. Deprins D, Simar L and Tulkens H (1984). Measuring labor inefficiency in post offices. In: Marchand M, Pestieau P and Tulkens H (eds). The Performance of Public Enterprises: Concepts and Measurements. North-Holland: Amsterdam, pp 243-267.
13. Efron B and Tibshirani R (1986). Bootstrap methods for standard errors, confidence intervals and other measures of statistical accuracy. Stat Sci 1: 54-77.
14. Efron B and Tibshirani R (1993). An Introduction to the Bootstrap. Chapman & Hall: New York.
15. Emrouznejad A and Amin GR (2009). DEA models for ratio data: Convexity consideration. Appl Math Model 33(1): 486-498.
16. Gomes EG and Souza GS (2008). Percepçoes psicométricas sobre a importância de atividades de pesquisa. Anais do XL Simpósio Brasileiro de Pesquisa Operacional (Proceedings of the Brazilian Operational Research Symposium). Sociedade Brasileira de Pesquisa Operacional, Rio de Janeiro, Brazil, p 2758.
17. Hollingsworth B and Smith P (2003). Use of ratios in data envelopment analysis. Appl Econ Lett 10: 733-735. (Pubitemid 37458459)
18. Kumbhakar S and Lovell CAK (2000). Stochastic Frontier Analysis. Cambridge University Press: New York.
19. Löthgren M and Tambour M (1999). Bootstrapping the data envelopment analysis Malmquist productivity index. Appl Econ 31: 417-423.
20. Saaty TL (1994). The Fundamentals of DecisionMaking and Priority Theory with the Analytic Hierarchy Process. RWS Publication: Pittsburgh.
21. Simar L and Wilson PW (2004). Performance of the bootstrap for DEA estimators and iterating the principle. In: Cooper WW, Seiford LM and Zhu J (eds). Handbook on Data Envelopment Analysis. Kluwer International Series: Boston, pp 265-298.
22. Simar L and Wilson PW (2007). Estimation and inference in two-stage, semi-parametric models of production processes. J Econometrics 136(1): 31-64. (Pubitemid 44380324)
23. Souza GS and Staub RB (2007). Two-stage inference using data envelopment analysis efficiency measurements in univariate production models. Int Trans Opl Res 14: 245-258.
24. Souza GS, Gomes EG and Staub RB (2010). Probabilistic measures of efficiency and the influence of contextual variables in nonparametric production models: An application to agricultural research in Brazil. Int Trans Opl Res 17: 351-363.
25. Torgerson WS (1958). Theory and Methods of Scaling. Wiley: New York.