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Maximum Likelihood Estimation of Censored Stochastic Frontier Models: An Application to the Three-Stage DEA Method

Wen-Jen Tsay (), Cliff J. Huang (), Tsu-Tan Fu () and I-Lin Ho ()
Additional contact information
Cliff J. Huang: Department of Economics Vanderbilt University
Tsu-Tan Fu: Institute of Economics, Academia Sinica, Taipei, Taiwan, http://www.econ.sinica.edu.tw/index.php?foreLang=en
I-Lin Ho: The Institute of Physics Academia Sinica Taipei, Taiwan, http://www.phys.sinica.edu.tw/?eng=T

No 09-A003, IEAS Working Paper : academic research from Institute of Economics, Academia Sinica, Taipei, Taiwan

Abstract: This paper takes issues with the appropriateness of applying the stochastic frontier analysis (SFA) technique to account for environmental effects and statistical noise in the popular three-stage data envelopment analysis (DEA). A correctly specified SFA model with a censored dependent variable and the associated maximum likelihood estimation (MLE) are proposed. The simulations show that the finite sample performance of the proposed MLE of the censored SFA model is very promising. An empirical example of farmers’ credit unions in Taiwan illustrates the comparison between the censored and standard SFA in accounting for environmental effects and statistical noise.

Keywords: Three-stage data envelopment analysis; stochastic frontier analysis; censored stochastic frontier model (search for similar items in EconPapers)
Pages: 27 pages
Date: 2009-03
New Economics Papers: this item is included in nep-ecm and nep-eff
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