Endogeneity corrected stochastic production frontier and technical efficiency
Shee, Apurba ORCID: 0000-0002-1836-9637 and Stefanou, Spiro E. (2014) Endogeneity corrected stochastic production frontier and technical efficiency. American Journal of Agricultural Economics, 97 (3). pp. 939-952. ISSN 0002-9092 (Print), 1467-8276 (Online) (doi:https://doi.org/10.1093/ajae/aau083)
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Abstract
A major econometric issue in estimating production parameters and technical efficiency is the possibility that some forces influencing production are only observed by the firm and not by the econometrician. Not only can this misspecification lead to a biased inference on the output elasticity of inputs, but it also provides a faulty measure of technical efficiency. We extend the Levinsohn and Petrin (2003) approach and provide an estimation algorithm to overcome the problem of endogenous input choice in stochastic production frontier estimation by generating consistent estimates of production parameters and technical efficiency. We apply the proposed method to a plant-level panel dataset from the Colombian food manufacturing sector for the period 1982–1998. This dataset provides the value of output and prices charged for each product, expenditures, and prices paid for each material used, energy consumption in kilowatt per hour and energy prices, number of workers and payroll, and book values of capital stock. Empirical results find that the traditional stochastic production frontier tends to underestimate the output elasticity of capital and firm-level technical efficiency. The evidence in this research suggests that addressing the endogeneity issue matters in stochastic production frontier analysis.
Item Type: | Article |
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Uncontrolled Keywords: | Keywords: Colombian food industry, Endogeneity of input choice, Maximum likelihood, Semiparametric estimation, Stochastic production frontier, Technical efficiency |
Subjects: | S Agriculture > S Agriculture (General) |
Faculty / School / Research Centre / Research Group: | Faculty of Engineering & Science Faculty of Engineering & Science > Natural Resources Institute Faculty of Engineering & Science > Natural Resources Institute > Development Studies Research Group Faculty of Engineering & Science > Natural Resources Institute > Food & Markets Department |
Last Modified: | 26 Apr 2020 16:36 |
URI: | http://gala.gre.ac.uk/id/eprint/17857 |
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