Data Envelopment Analysis Estimates Research Articles

Measuring product market efficiency: A new methodology

This paper proposes a new methodology to measure product market efficiency. Our approach is based on the economic theory of product market equilibrium where consumers have incomplete information, and it allows quality to be multidimensional. We illustrate the methodology and compare it with other methodologies including the data envelopment analysis (DEA)-based procedure of Kamakura, Ratchford, and Agrawal (1988). The empirical results show that our model is robust to the precise distributional form of the disturbance term. In addition, our efficiency estimates are always equal to or lower than the DEA estimates of efficiency.

Maximum Likelihood, Consistency and Data Envelopment Analysis: A Statistical Foundation

This paper provides a formal statistical basis for the efficiency evaluation techniques of data envelopment analysis (DEA). DEA estimators of the best practice monotone increasing and concave production function are shown to be also maximum likelihood estimators if the deviation of actual output from the efficient output is regarded as a stochastic variable with a monotone decreasing probability density function. While the best practice frontier estimator is biased below the theoretical frontier for a finite sample size, the bias approaches zero for large samples. The DEA estimators exhibit the desirable asymptotic property of consistency, and the asymptotic distribution of the DEA estimators of inefficiency deviations is identical to the true distribution of these deviations. This result is then employed to suggest possible statistical tests of hypotheses based on asymptotic distributions.

A Comparative Application of Data Envelopment Analysis and Translog Methods: An Illustrative Study of Hospital Production

This paper compares inferences about hospital cost and production correspondences from two different estimation models: (1) the econometric modeling of the translog cost function, and (2) the application of Data Envelopment Analysis (DEA). While there are numerous examples of the application of each approach to empirical data, this paper provides insights into the relative strengths of the estimation methods by applying both models to the same data. The translog results suggest that constant reruns are operant, whereas the DEA results suggest that both increasing and decreasing returns to scale may be observed in different segments of the production correspondence, in turn suggesting that the translog model may be ‘averaging’ diametrically opposite behavior. On the other hand, by examining the rate of output transformation, both models agree that patient days devoted to care of children are more resource intensive than those devoted to adults or to the elderly. In addition, we compare estimates of technical efficiencies of individual hospitals obtained from the two methods. The DEA estimates are found to be highly related to the capacity utilization, but no such relationship was found for the translog estimates. This comparative application of different estimation models to the same data to obtain inferences about the nature of underlying cost and production correspondences sheds interesting light on the strengths of each approach, and suggests the need for additional research comparing estimation models using real as well as simulated data.