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A Panel Data Approach to the Measurement of Technical Efficiency and its Determinants: Some Evidence from the Tunisian Agro-Food Industry

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  • Lachaal, Lassaad
  • Chebil, Ali
  • Dhehibi, Boubaker

Abstract

This study investigates firm level technical efficiency of production and its determinants in the Tunisian agro-food industry. To this end, a stochastic production frontier model, in which technical efficiency effects are assumed to be a function of firm-specific variables and time, is estimated using panel data on 46 agro-food firms observed over a period of 14 years. Results indicate that technical efficiency in the sample of firms investigated ranges from a minimum of 45% to a maximum of 90% with an average technical efficiency estimate of 67%. Further, investigation of the sources of technical inefficiency in the sample reveals that the age of capital stock and firm size are negatively associated with efficiency, the share of skilled labour is positively associated with efficiency and, on average, technical efficiency tendes to decline during the period of investigation.

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Bibliographic Info

Article provided by Greek Association of Agricultural Economists in its journal Agricultural Economics Review.

Volume (Year): 05 (2004)
Issue (Month): 1 (January)
Pages:

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Handle: RePEc:ags:aergaa:26450

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Web page: http://www.etagro.gr/
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Keywords: Research and Development/Tech Change/Emerging Technologies;

References

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  1. K. Kalirajan, 1981. "An Econometric Analysis of Yield Variability in Paddy Production," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 29(3), pages 283-294, November.
  2. Lachaal, Lassaad, 1994. "Subsidies, Endogenous Technical Efficiency And The Measurement Of Productivity Growth," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, Southern Agricultural Economics Association, vol. 26(01), July.
  3. Forsund, Finn R. & Lovell, C. A. Knox & Schmidt, Peter, 1980. "A survey of frontier production functions and of their relationship to efficiency measurement," Journal of Econometrics, Elsevier, Elsevier, vol. 13(1), pages 5-25, May.
  4. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, Elsevier, vol. 6(1), pages 21-37, July.
  5. Pitt, Mark M. & Lee, Lung-Fei, 1981. "The measurement and sources of technical inefficiency in the Indonesian weaving industry," Journal of Development Economics, Elsevier, vol. 9(1), pages 43-64, August.
  6. Bauer, Paul W., 1990. "Recent developments in the econometric estimation of frontiers," Journal of Econometrics, Elsevier, Elsevier, vol. 46(1-2), pages 39-56.
  7. Battese, G E & Coelli, T J, 1995. "A Model for Technical Inefficiency Effects in a Stochastic Frontier Production Function for Panel Data," Empirical Economics, Springer, Springer, vol. 20(2), pages 325-32.
  8. Kumbhakar, Subal C & Ghosh, Soumendra & McGuckin, J Thomas, 1991. "A Generalized Production Frontier Approach for Estimating Determinants of Inefficiency in U.S. Dairy Farms," Journal of Business & Economic Statistics, American Statistical Association, American Statistical Association, vol. 9(3), pages 279-86, July.
  9. Jondrow, James & Knox Lovell, C. A. & Materov, Ivan S. & Schmidt, Peter, 1982. "On the estimation of technical inefficiency in the stochastic frontier production function model," Journal of Econometrics, Elsevier, Elsevier, vol. 19(2-3), pages 233-238, August.
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Cited by:
  1. Masood, Tariq & Ahmad, Mohd. Izhar, 2010. "Technical Efficiency of Microfinance Institutions in India- A Stochastic Frontier Approach," MPRA Paper 25454, University Library of Munich, Germany.

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