A Bayesian stochastic frontier: an application to agricultural productivity growth in European countries
AbstractThis paper measures and compares total factor productivity (TFP) growth in agriculture for the European Union (EU) countries and candidate countries (CC), in order to distinguish and investigate cross-country differences in agricultural productivity growth rates from 1993 to 2006. A stochastic production frontier model is estimated using a Bayesian approach capturing country-specific time-invariant heterogeneity and country-specific time-varying inefficiency. Agricultural productivity growth is found to be mostly driven by technological change. The TFP growth rates of the EU-12 countries and CC are about twice the EU-15 growth rate. Catch-up in productivity levels is observed between EU-15 and EU-12 as well as between EU-15 and CC. The results are compared for a situation in which country-specific time-invariant heterogeneity is not taken into account. Copyright The Author(s) 2012
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Bibliographic InfoArticle provided by Springer in its journal Economic Change and Restructuring.
Volume (Year): 45 (2012)
Issue (Month): 4 (November)
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Web page: http://www.springerlink.com/link.asp?id=113294
Bayesian inference; Stochastic production frontier; Time-varying technical inefficiency; Total factor productivity growth; European agriculture; C15; D24; O47;
Find related papers by JEL classification:
- C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
- D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
- O47 - Economic Development, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Measurement of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence
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