Evaluating Contextual Variables Affecting Productivity Using Data Envelopment Analysis

Published Online:https://doi.org/10.1287/opre.1070.0460

References

  • Aigner D. J., Chu S. F. On estimating the industry production function. Amer. Econom. Rev. (1968) 58(4):826–839Google Scholar
  • Aigner D. J., Lovell C. A. K., Schmidt P. Formulation and estimation of stochastic frontier production function models. J. Econometrics (1977) 6:21–37CrossrefGoogle Scholar
  • Banker R. D. Maximum likelihood, consistency and data envelopment analysis: A statistical foundation. Management Sci. (1993) 39(10):1265–1273LinkGoogle Scholar
  • Banker R. D., Chang H., Cooper W. W. A simulation study of DEA and parametric frontier models in the presence of heteroscedasticity. Eur. J. Oper. Res. (2004) 153:624–640CrossrefGoogle Scholar
  • Banker R. D., Charnes A., Cooper W. W. Models for the estimation of technical and scale inefficiencies in data envelopment analysis. Management Sci. (1984) 30:1078–1092LinkGoogle Scholar
  • Banker R. D., Gadh V. M., Gorr W. L. A Monte Carlo comparison of two production frontier estimation methods: Corrected ordinary least square and data envelopment analysis. Eur. J. Oper. Res. (1993) 67:332–343CrossrefGoogle Scholar
  • Banker R. D., Janakiraman S., Natarajan R. Evaluating the adequacy of parametric functional forms in estimating monotone and concave production functions. J. Productivity Anal. (2002) 17:111–132CrossrefGoogle Scholar
  • Farrell M. J. The measurement of productive efficiency. J. Roy. Statist. Soc. (A, general) (1957) 120(part 3):253–281CrossrefGoogle Scholar
  • Forsund F. R. The evolution of DEA—The economics perspective. (1999) . Working paper, University of Oslo, Oslo, NorwayGoogle Scholar
  • Greene W. H. Maximum likelihood estimation of econometric frontier production functions. J. Econometrics (1980) 13:27–56CrossrefGoogle Scholar
  • Grosskopf S. Statistical inference and nonparametric efficiency: A selective survey. J. Productivity Anal. (1996) 7:161–176CrossrefGoogle Scholar
  • Gstach D. Another approach to data envelopment analysis in noisy environments: DEA+. J. Productivity Anal. (1998) 9:161–176CrossrefGoogle Scholar
  • Jondrow J., Lovell C. A. K., Materov I. S., Schmidt P. On the estimation of technical inefficiency in the stochastic frontier production function model. J. Econometrics (1982) 19:233–238CrossrefGoogle Scholar
  • Kalirajan K. P. On measuring the contribution of human capital to agricultural production. Indian Econom. Rev. (1989) 24:247–261Google Scholar
  • Meeusen W., van den Broeck J. Efficiency estimation from Cobb-Douglas production functions with composed error. Internat. Econom. Rev. (1977) 18(2):435–444CrossrefGoogle Scholar
  • Olson J. A., Schmidt P., Waldman D. M. A Monte Carlo study of stochastic frontier production functions. J. Econometrics (1980) 13:67–82CrossrefGoogle Scholar
  • Ondrich J., Ruggiero J. Efficiency measurement in the stochastic frontier model. Eur. J. Oper. Res. (2001) 129:434–442CrossrefGoogle Scholar
  • Pitt M. M., Lee L. F. Measurement and sources of technical inefficiency in the Indonesian weaving industry. J. Development Econom. (1981) 9:43–64CrossrefGoogle Scholar
  • Ray S. Resource-use efficiency in public schools: A study of Connecticut data. Management Sci. (1991) 37(12):1620–1628LinkGoogle Scholar
  • Schmidt P. On the statistical estimation of parametric frontier production functions. Rev. Econom. Statist. (1976) 58(2):238–239CrossrefGoogle Scholar
  • Schmidt P. Frontier production functions. Econometric Rev. (1985) 4:289–328CrossrefGoogle Scholar
  • Simar L., Wilson P. Estimation and inference in two-stage, semi-parametric models of production processes. J. Econometrics (2007) 136:31–64CrossrefGoogle Scholar
  • Wang H., Schmidt P. One-step and two-step estimation of the effects of exogenous variables on technical efficiency levels. J. Productivity Anal. (2002) 18:129–144CrossrefGoogle Scholar
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