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

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  • A. Tonini

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

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  • A. Tonini, 2012. "A Bayesian stochastic frontier: an application to agricultural productivity growth in European countries," Economic Change and Restructuring, Springer, vol. 45(4), pages 247-269, November.
    • Handle: RePEc:kap:ecopln:v:45:y:2012:i:4:p:247-269
    DOI: 10.1007/s10644-011-9117-9
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    Cited by:

    1. Makieła, Kamil & Marzec, Jerzy & Pisulewski, Andrzej, 2016. "Productivity Change Analysis of Polish Dairy Farms After Poland’s Accession to the EU – An Output Growth Decomposition Approach," MPRA Paper 80295, University Library of Munich, Germany.
    2. Annageldy Arazmuradov, 2016. "Economic prospect on carbon emissions in Commonwealth of Independent States," Economic Change and Restructuring, Springer, vol. 49(4), pages 395-427, November.
    3. Jitea, Ionel-Mugurel & Pocol, Cristina Bianca, 2014. "The Common Agricultural Policy and productivity gains in Romanian agriculture: is there any evidence of convergence to the Western European realities?," Studies in Agricultural Economics, Research Institute for Agricultural Economics, vol. 116(3), pages 1-3, December.
    4. Marzec, Jerzy & Pisulewski, Andrzej, 2019. "The Measurement of Time Varying Technical Efficiency and Productivity Change in Polish Crop Farms," German Journal of Agricultural Economics, Humboldt-Universitaet zu Berlin, Department for Agricultural Economics, vol. 68(1), March.
    5. Alessandro Magrini, 2021. "A Stochastic Frontier Model to Assess Agricultural Eco-efficiency of European Countries in 1990–2019," International Journal of Statistics and Probability, Canadian Center of Science and Education, vol. 10(4), pages 138-138, July.

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    More about this item

    Keywords

    Bayesian inference; Stochastic production frontier; Time-varying technical inefficiency; Total factor productivity growth; European agriculture; C15; D24; O47;
    All these keywords.

    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, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Empirical Studies of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence

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