Testing independence in models of productive efficiency

Journal of Productivity Analysis

Volumn 20, Issue 3, 2003, Pages 361-390

  Wilson, Paul W ^a  

^a UNIVERSITY OF TEXAS AT AUSTIN   (United States)

Author keywords

Data envelopment analysis; Dependence; Productive efficiency

Indexed keywords

EID: 3843131876     PISSN: 0895562X     EISSN: None     Source Type: Journal    
DOI: 10.1023/A:1027355917855     Document Type: Conference Paper

References (43)

1. Ahmad, I. A. and Q. Li. (1997). "Testing Independence by Nonparametric Kernel Method." Statistics and Probability Letters 34, 201-210.
2. Aly, H. Y., R. G. Grabowski, C. Pasurka and N. Rangan. (1990). "Technical, Scale, and Allocative Efficiencies in U.S. Banking: An Empirical Investigation." Review of Economics and Statistics 72, 211-218.
3. Bellman, R. J. (1961). Adaptive Control Processes. Princeton, NJ: Princeton University Press.
4. Blum, J. R., J. Kiefer and M. Rosenblatt. (1961). "Distribution Free Tests of Independence Based on the Sample Distribution Function." Annals of Mathematical Statistics 32, 485-498.
5. Brock, W., D. Hsieh and B. LeBaron. (1991). Nonlinear Dynamics, Chaos, and Instability: Statistical Theory and Economic Evidence. Cambridge, MA: MIT Press.
6. Charnes, A., W. W. Cooper and E. Rhodes. (1981). "Evaluating Program and Managerial Efficiency: An Application of Data Envelopment Analysis to Program Follow Through." Management Science 27, 668-697.
7. Dette, H. and N. Neumeyer. (2000). "A Note on a Specification Test of Independence." Metrika 51, 133-144.
8. Fan, J. and I. Gijbels. (1996). Local Polynomial Modelling and Its Applications. London: Chapman & Hall.
9. Färe, R., S. Grosskopf and C. A. K. Lovell. (1985). The Measurement of Efficiency of Production. Boston: Kluwer-Nijhoff Publishing.
10. Farrell, M. J. (1957). "The Measurement of Productive Efficiency." Journal of the Royal Statistical Society, Series A 120, 253-281.
11. Fisher, N. I. and P. Switzer. (1985). "Chi-plots for Assessing Dependence." Biometrika 72, 253-265.
12. Gijbels, I., E. Mammen, B. U. Park and L. Simar. (1999). "On Estimation of Monotone and Concave Frontier Functions." Journal of the American Statistical Association 94, 220-228.
13. Härdle, W. and E. Mammen. (1926-1947). "Comparing Nonparametric versus Parametric Regression Fits." Annals of Statistics 21.
14. Hall, P., J. S. Marron and B. U. Park. (1992). "Smoothed Cross Validation." Probability Theory and Related Fields 92, 1-20.
15. Hall, P., S. J. Sheather, M. C. Jones and J. S. Marron. (1991). "On Optimal Data-based Bandwidth Selection in Kernel Density Estimation." Biometrika 78, 263-269.
16. Hjort, N. L. (1999). "Towards Semiparametric Bandwidth Selectors for Kernel Density Estimators." Unpublished working paper. Department of Mathematics, Oslo, Norway: Universitetet i Oslo.
17. Hjort, N. L. and M. C. Jones. (1996). "Better Rules of Thumb for Choosing Bandwidth in Density Estimation." Unpublished working paper. Department of Mathematics, Oslo, Norway: Universitetet i Oslo.
18. Hoeffding, W. (1948). "A Non-Parametric Test of Independence." Annals of Mathematical Statistics 58, 546-557.
19. Johnson, D. and R. McClelland. (1997). "Nonparametric Tests for the Independence of Regressors and Disturbances as Specification Tests." Review of Economics and Statistics 79, 335-340.
20. Johnson, D. and R. McClelland. (1998). "A General Dependence Test and Applications." Journal of Applied Econometrics 13, 627-644.
21. Jones, M. C., J. S. Marron and S. J. Sheather. (1996). "Progress in Data-based Bandwidth Selection for Kernel Density Estimation." Computational Statistics 11, 337-381.
22. Kallenberg, W. C. M. and T. Ledwina. (1999). "Data-driven Rank Tests for Independence." Journal of the American Statistical Association 94, 285-301.
23. Kim, W. C., B. U. Park and J. S. Marron. (1994). "Asymptotically Best Bandwidth Selectors in Kernel Density Estimation." Statistics and Probability Letters 19, 119-127.
24. Kneip, A., B. U. Park and L. Simar. (1998). "A Note on the Convergence of Nonparametric DEA Estimators for Production Efficiency Scores." Econometric Theory 14, 783-793.
25. Kruskal, W. H. (1958). "Ordinal Measures of Association." Journal of the American Statistical Association 53, 814-861.
26. Lehman, E. L. (1966). "Some Concepts of Dependence." Annals of Mathematical Statistics 37, 1137-1153.
27. Robinson, P. M. (1991). "Consistent Nonparametric Entropy-Based Testing." Review of Economic Studies 58, 437-453.
28. Scott, D. W. (1992). Multivariate Density Estimation: Theory, Practice, and Visualization. New York: John Wiley and Sons, Inc.
29. Schwarz, G. (1978). "Estimating the Dimension of a Model." Annals of Statistics 6, 461-464.
30. Sheather, S. J. and M. C. Jones. (1991). "A Reliable Data-based Bandwidth Selection Method for Kernel Density Estimation." Journal of the Royal Statistical Society, Series B 53, 683-690.
31. Shephard, R. W. (1970). Theory of Cost and Production Function. Princeton: Princeton University Press.
32. Silverman, B. W. (1986). Density Estimation for Statistics and Data Analysis. London: Chapman and Hall.
33. Simar, L. and P. W. Wilson. (1998). "Sensitivity Analysis of Efficiency Scores: How to Bootstrap in Nonparametric Frontier Models." Management Science 44(11), 49-61.
34. Simar, L. and P. W. Wilson. (2000a). "A General Methodology for Bootstrapping in Nonparametric Frontier Models." Journal of Applied Statistics 27, 779-802.
35. Simar, L. and P. W. Wilson. (2000b). "Statistical Inference in Nonparametric Frontier Models: The State of the Art." Journal of Productivity Analysis 13, 49-78.
36. Simar, L. and P. W. Wilson. (2001). "Aplicación del 'Bootstrap' Para Estimadores D.E.A." In A. Alvarez La Medición de la Eficiencia y la Productividad. Madrid: Pirámide. Translation of "Performance of the Bootstrap for DEA Estimators and Iterating the Principle." Discussion Paper No. 0002. Institut de Statistique, Louvain-la-Neuve, Belgium: Université Catholique de Louvain.
37. Simar, L. and P. W. Wilson. (2002a). "Estimation and Inference in Two-Stage, Semi-Parametric Models of Production Processes." discussion paper no. 0307, Institut de Statistique, Université Catholique de Louvain, Louvain-la-Neuve, Belgium.
38. Simar, L. and P. W. Wilson. (2002b). "Nonparametric Tests of Returns to Scale." European Journal of Operational Research 139, 115-132.
39. Skaug, H. J. and D. Tjøstheim. (1993). "A Nonparametric Test of Serial Independence based on the Empirical Distribution Function." Biometrika 80, 591-602.
40. 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.
41. Staniswalis, J. (1989). "Local Bandwidth Selection for Kernel Estimates." Journal of the American Statistical Association 84, 284-288.
42. Szegö, G. (1959). Orthogonal Polynomials. New York: American Mathematical Society.
43. Zheng, J. X. (1997). "A Consistent Specification Test of Independence." Nonparametric Statistics 7, 297-306.