Skip to main content
Log in

Variable selection for dynamic measures of efficiency in the computer industry

  • Articles
  • Published:
International Advances in Economic Research Aims and scope Submit manuscript

Abstract

Data Envelopment Analysis (DEA) measures of efficiency are very sensitive to the choice of variables for two reasons: the number of efficient firms is directly related to the number (n) of variables and the selection of the n variables greatly affects the measure of efficiency. A methodology is proposed which identifies the optimal number of variables, and which identifies the contribution of each variable to the measure of efficiency. The computer industry is used as an example to illustrate the method.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • Banker, R.; Charnes, A.; Cooper, W. “Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis,”Management Science, 30 (9), 1984, pp. 1078–92.

    Google Scholar 

  • Bardhan, I.; Cooper, W.; Kumbhakar, S. “A Simulation Study of Joint Uses of Data Envelopment Analysis and Statistical Regressions for Production Function Estimation and Efficiency Evaluation,”Journal of Productivity Analysis, 9 (3), May, 1998, pp. 249–78.

    Article  Google Scholar 

  • Bresnahan, T.; Greenstein, S. “Technological Competition and the Structure of the Computer Industry,”Journal of Industrial Economics, 47 (1), March, 1999, pp. 1–40.

    Google Scholar 

  • Bridges, E.; Yim, YC.; Briesch, R. “A High-Tech Product Market Share Model with Customer Expectations,”Marketing Science, 14 (1), 1995, pp. 61–81.

    Google Scholar 

  • Charnes, A.; Cooper, A.; Rhodes, E. “Measuring the Efficiency of Decision Making Units,”European Journal of Operations Research, 2, 1978, pp. 429–44.

    Article  Google Scholar 

  • Farrell, M. J. “The Measurement of Productive Efficiency,”Journal of the Royal Statistical Society, Series A 120(III), 1957, pp. 253–61.

    Google Scholar 

  • Forbes; King; Morgan. “A Small Sample Variable Selection Procedure,” Monash University, Department of Econometrics Working Paper: 15/95, 1995.

  • Forsund, Finn R.; Sarafoglou, Nikias. “On The Origins of Data Envelopment Analysis,”Journal of Productivity Analysis, 17, January, 2002, pp. 23–40.

    Google Scholar 

  • Golan, A. “A Simultaneous Estimation and Variable Selection Rule,”Journal of Econometrics, 101 (1), March, 2001, pp. 165–93.

    Article  Google Scholar 

  • Grosskopf, S. “Statistical Inference and Nonparametric Efficiency: A Selective Survey,”Journal of Productivity Analysis, 7 (2–3), July, 1996, pp. 161–76.

    Google Scholar 

  • Mitchell, M. “The Scale of Production in Technological Revolutions,” Federal Reserve Bank of Minneapolis Staff Report: 269, April, 2000, p. 27.

    Google Scholar 

  • Norsworthy, J. R.; Jang, S. L. “Empirical Measurement and Analysis of Productivity and Technological Change-Applications in Hi-Technology and Service Industries Contributions to Economic Analysis series, North Holland (1992).

  • Sengupta, J. K. “Dynamic and Stochastic Efficiency Analysis,” World Scientific, 2000.

  • Thore; Kozmetsky; Phillips. “DEA of Financial Statements Data: The U.S. Computer Industry,”Journal of Productivity Analysis, 5 (3), October, 1994, pp. 229–48.

    Article  Google Scholar 

  • Zheng, X.; Loh, W. “Consistent Variable Selection in Linear Models,”Journal of the American Statistical Association, 90, N429, March, 1995, pp. 151–56.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

About this article

Cite this article

Fanchon, P. Variable selection for dynamic measures of efficiency in the computer industry. International Advances in Economic Research 9, 175–188 (2003). https://doi.org/10.1007/BF02295441

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF02295441

Keywords

Navigation