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A Bayesian stochastic frontier: an application to agricultural productivity growth in European countries

Axel Tonini

Economic Change and Restructuring, 2012, vol. 45, issue 4, 247-269

Abstract: This 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

Keywords: Bayesian inference; Stochastic production frontier; Time-varying technical inefficiency; Total factor productivity growth; European agriculture; C15; D24; O47 (search for similar items in EconPapers)
Date: 2012
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DOI: 10.1007/s10644-011-9117-9

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