Maximum Likelihood, Consistency and Data Envelopment Analysis: A Statistical Foundation
2002/09/10
研討會日期 : 2002-09-10
時間 : 15:00
主講人 : Prof. Rajiv D. Banker
地點 : B棟110室
演講者簡介 : Prof. Rajiv D. Banker為Ph.D. in Business Administration，Harvard University(1980)。
現為Ashbel Smith Chair in Accounting and Information Management；Director of Accounting and Information
Management Programs，School of Management，The University of Texas at Dallas。
其主要研究領域為Planning、Accounting及 Control Systems。
演講摘要 : his 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 sto astic 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 istribution 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.
