A Monte Carlo Study of Efficiency Estimates from Frontier Models
AbstractParametric stochastic frontier models yield firm-level conditional distributions of inefficiency that are truncated normal. Given these distributions, how should one assess and rank firm-level efficiency? This study compares the techniques of estimated (a) the conditional means of inefficiency and (b) probabilities that firms are most or least efficient. Monte Carlo experiments suggest that the efficiency probabilities are more reliable in terms of mean absolute percent error when inefficiency has large variation across firms. Along the way we tackle some interesting problems associated with simulating and assessing estimator performance inthe stochastic frontier environment.
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Bibliographic InfoPaper provided by Center for Policy Research, Maxwell School, Syracuse University in its series Center for Policy Research Working Papers with number 97.
Length: 34 pages
Date of creation: Aug 2007
Date of revision:
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Truncated normal; stochastic frontier; efficiency; multivariate probabilities.;
Find related papers by JEL classification:
- C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
- C16 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Econometric and Statistical Methods; Specific Distributions
- C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory
- D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
This paper has been announced in the following NEP Reports:
- NEP-ALL-2007-09-02 (All new papers)
- NEP-ECM-2007-09-02 (Econometrics)
- NEP-EFF-2007-09-02 (Efficiency & Productivity)
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