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Estimating technical efficiency under technological heterogeneity in Hungarian crop sector

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  • Barath, Lajos
  • Ferto, Imre

Abstract

Technological heterogeneity is an important issue in studies of agricultural production. We assume that this is much more serious in transition countries, since the agricultural sector in these countries is characterized by the presence of even more different technologies and structures. Previous studies address the issue of production heterogeneity in developed countries; however, there is a clear lack in the literature concerning the effect of different technologies in transition countries. There are two common approaches to estimate different technologies: the most common one is to split the sample into groups based on some a priori information; an alternative method is the latent class models. In the present paper both approaches are used to identify different technologies and to estimate technical efficiency. It seems to be that the LCM model identified better technological differences and separated better the effect of heterogeneity and technical efficiency.

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Bibliographic Info

Paper provided by Agricultural Economics Society in its series 86th Annual Conference, April 16-18, 2012, Warwick University, Coventry, UK with number 134961.

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Date of creation: Apr 2012
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Handle: RePEc:ags:aesc12:134961

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Keywords: Technical efficiency; Heterogeneity; Latent class model; Hungarian agriculture; Crop Production/Industries; Research and Development/Tech Change/Emerging Technologies; Q12;

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  1. Antonio Alvarez & Julio del Corral, 2010. "Identifying different technologies using a latent class model: extensive versus intensive dairy farms," European Review of Agricultural Economics, Foundation for the European Review of Agricultural Economics, vol. 37(2), pages 231-250, June.
  2. Lajos Zoltan Bakucs & Laure Latruffe & Imre Fertő & Jozsef Fogarasi, 2010. "The impact of EU accession on farms' technical efficiency in Hungary," Post-Communist Economies, Taylor & Francis Journals, vol. 22(2), pages 165-175.
  3. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
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