Stochastic Frontier Production Function With Errors-In-Variables
AbstractThis paper develops a procedure for estimating parameters of a cross-sectional stochastic frontier production function when the factors of production suffer from measurement errors. Specifically, we use Fuller's (1987) reliability ratio concept to develop an estimator for the model in Aigner et al (1977). Our Monte-Carlo simulation exercise illustrates the direction and the severity of bias in the estimates of the elasticity parameters and the returns to scale feature of the production function when using the traditional maximum-likelihood estimator (MLE) in presence of measurement errors. In contrast the reliability ratio based estimator consistently estimates these parameters even under extreme degree of measurement errors. Additionally, estimates of firm level technical efficiency are severely biased for traditional MLE compared to reliability ratio estimator, rendering inter-firm efficiency comparisons infeasible. The seriousness of measurement errors in a practical setting is demonstrated by using data for a cross-section of publicly traded U.S. corporations.
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Bibliographic InfoPaper provided by Lund University, Department of Economics in its series Working Papers with number 1999:007.
Length: 33 pages
Date of creation: 29 Sep 1999
Date of revision:
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Postal: Department of Economics, School of Economics and Management, Lund University, Box 7082, S-220 07 Lund,Sweden
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Fax: +46 +46 2224613
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More information through EDIRC
Errors-In-Variables; Stochastic Frontier; Technical Efficiency; Reliability Ratio;
Find related papers by JEL classification:
- C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
- C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
- 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-2000-01-24 (All new papers)
- NEP-ECM-2000-01-24 (Econometrics)
- NEP-IND-2000-01-24 (Industrial Organization)
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