Probabilistic measures of efficiency and the influence of contextual variables in nonparametric production models: An application to agricultural research in Brazil

International Transactions in Operational Research

Volumn 17, Issue 3, 2010, Pages 351-363

  Da Silva e Souza, Geraldo ^a   Gomes, Eliane Gonçalves ^a   Staub, Roberta Blass ^b  

^a EMBRAPA CERRADOS   (Brazil)

^b BANCO CENTRAL DO BRASIL   (Brazil)

Author keywords

Agricultural research; Contextual variables; Free disposal hull (FDH); Two stage inference

Indexed keywords

EID: 80051892954     PISSN: 09696016     EISSN: 14753995     Source Type: Journal    
DOI: 10.1111/j.1475-3995.2009.00734.x     Document Type: Article

References (23)

1. Arellano, M., Bond, S., 1991. Some tests of specification for panel data: Monte Carlo evidence and an application to employment equations. Review of Economic Studies 58, 2, 277–297.
2. Arellano, M., Bover, O., 1995. Another look at the instrumental variable estimation of the error-components models. Journal of Econometrics 68, 29–51.
3. Blundell, R., Bond, S., 1998. Initial conditions and moment restrictions in dynamic panel-data models. Journal of Econometrics 87, 115–143.
4. Conover, W.J., 1998. Practical Nonparametric Statistics. Wiley, New York.
5. Cooper, W.W., Seiford, L.M., Tone, K., 2000. Data Envelopment Analysis: A Comprehensive Text with Models, Applications, References and DEA-Solver Software. Kluwer Academic Publishers, Boston, MA.
6. Daraio, C., Simar, L., 2007. Advanced Robust and Nonparametric Methods in Efficiency Analysis. Springer, New York.
7. Deprins, D., Simar, L., Tulkens, H., 1984. Measuring labor inefficiency in post offices. In Marchand, M., Pestieau, P., Tulkens, H. (eds) The Performance of Public Enterprises: Concepts and Measurements. North-Holland, Amsterdam, pp. 243–267.
8. Embrapa. 2006. Manual dos indicadores de avaliação de desempenho das unidades descentralizadas da Embrapa: Metas quantitativas – Versão para ano base 2007. Superintendência de Pesquisa e Desenvolvimento, Brasília.
9. Greene, W.H., 2007. Econometric Analysis. Prentice Hall, Englewood Cliffs, NJ.
10. Kerstens, K., Eeckaut, P.V., 1999. Estimating returns to scale using non-parametric deterministic technologies: a new method based on goodness-of-fit. European Journal of Operational Research 113, 206–214.
11. Kotz, N., Johnson, L., 1989. Thurstone's theory of comparative judgment. Encyclopedia of Statistical Sciences 9, 237–239.
12. Podinovski, V.V., 2004. On the linearisation of reference technologies for testing returns to scale in FDH models. European Journal of Operational Research 152, 800–802.
13. Saaty, T.L., 1994. The Fundamentals of Decision Making and Priority Theory with the Analytic Hierarchy Process. RWS Publication, Pittsburgh, PA.
14. Seiford, L.M., Thrall, R.M., 1990. Recent developments in DEA, the mathematical programming approach to frontier analysis. Journal of Econometrics 46, 7–38.
15. Silverman, B.W., 1986. Density Estimation for Statistics and Data Analysis. Chapman and Hall, London.
16. Simar, L., Wilson, P.W., 2007. Estimation and inference in two-stage, semi-parametric models of production processes. Journal of Econometrics 136, 1, 31–64.
17. Soleimani-damaneh, M., Jahanshahloo, G.R., Reshadi, M., 2006. On the estimation of returns-to-scale in FDH models. European Journal of Operational Research 174, 1055–1059.
18. Soleimani-damaneh, M., Mostafaee, A., 2009. Stability of the classification of returns to scale in FDH models. European Journal of Operational Research 196, 1223–1228.
19. Souza, G.S., 2006. Significância de efeitos técnicos na eficiência de produção da pesquisa agropecuária brasileira. Revista Brasileira de Economia 60, 1, 91–117.
20. Souza, G.S., Alves, E., Avila, A.F.D., 1999. Technical efficiency in agricultural research. Scientometrics 46, 141–160.
21. Souza, G.S., Gomes, E.G., Magalhães, M.C., Avila, A.F.D., 2007. Economic efficiency of Embrapa's research centers and the influence of contextual variables. Pesquisa Operacional 27, 15–26.
22. Torgerson, W.S., 1958. Theory and Methods of Scaling. Wiley, New York.
23. Wilson, P.W., 2008. FEAR: a software package for frontier efficiency analysis with R. Socio-Economic Planning Sciences 42, 247–254.