Makieła, Kamil and Marzec, Jerzy and Pisulewski, Andrzej (2016): Productivity Change Analysis of Polish Dairy Farms After Poland’s Accession to the EU – An Output Growth Decomposition Approach.
Preview |
PDF
MPRA_paper_80295.pdf Download (875kB) | Preview |
Abstract
The aim of this study is to assess changes in productivity of Polish dairy farms after Poland’s accession to the EU. In order to do so a new decomposition of output growth is proposed in a stochastic frontier framework. We show how changes in economies of scale can be isolated, which leads to redefined components of output growth and a better measure of productivity growth. The productivity component is now disaggregated to its three generic sources: total scale change, real technical change and efficiency change. The analysis of 1,191 Polish dairy farms between 2004-2011 has revealed that production growth (3.91%) is mostly due to inputs accumulation (3.4%) rather than productivity growth (0.51%.) Further decomposition indicates that productivity component is driven by real technical growth (1%) and changes in scale elasticity, which have had a negative effect on productivity (-0.81%). Technical efficiency growth (0.36%) played a rather minor role.
Item Type: | MPRA Paper |
---|---|
Original Title: | Productivity Change Analysis of Polish Dairy Farms After Poland’s Accession to the EU – An Output Growth Decomposition Approach |
English Title: | Productivity Change Analysis of Polish Dairy Farms After Poland’s Accession to the EU – An Output Growth Decomposition Approach |
Language: | English |
Keywords: | productivity analysis, Polish dairy farms, output growth decomposition, stochastic frontier analysis, FADN |
Subjects: | C - Mathematical and Quantitative Methods > C0 - General > C01 - Econometrics C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C11 - Bayesian Analysis: General D - Microeconomics > D2 - Production and Organizations > D24 - Production ; Cost ; Capital ; Capital, Total Factor, and Multifactor Productivity ; Capacity Q - Agricultural and Natural Resource Economics ; Environmental and Ecological Economics > Q1 - Agriculture > Q12 - Micro Analysis of Farm Firms, Farm Households, and Farm Input Markets |
Item ID: | 80295 |
Depositing User: | Kamil Makieła |
Date Deposited: | 27 Jul 2017 07:40 |
Last Modified: | 02 Oct 2019 11:05 |
References: | Aigner, D., Lovell, C., and Schmidt, P. (1977), “Formulation and estimation of stochastic frontier production function models”, Journal of Econometrics, Vol. 6, pp. 21–37. Bertazzoli, A., Ghelfi, R., Guzmán, I. and Rivaroli, R., (2014), “A dual approach to evaluating the agricultural productivity of fruit farms in Emilia-Romagna”, Outlook on Agriculture, Vol. 43 (1), pp. 31–38. van den Broeck, J., Koop, G., Osiewalski, J., and Steel, M. (1994), “Stochastic Frontier Models; A Bayesian Perspective”, Journal of Econometrics, Vol. 61 (2), pp. 273–303. Brümmer, B., Glauben, T., and Thijssen, G. (2002), “Decomposition of Productivity Growth using Distance Functions: The Case of Dairy Farms in Three European Countries”, American Journal of Agricultural Economics, Vol. 84 (3), pp. 628–644. Cuesta, R, (2000), “A production model with firm-specific temporal variation in technical inefficiency: with application to Spanish dairy farms”, Journal of Productivity Analysis, Vol. 13(2), pp: 139–158. Emvalomatis G, Stefanou, S., and Lansink, A (2011), “A reduced-form model for dynamic efficiency measurement: Application to dairy farms in Germany and the Netherlands”, American Journal of Agricultural Economics, Vol. 93, pp. 161–174. Färe, R., Grosskopf, S., Norris, M., and Zhang, Z., (1994), “Productivity Growth, Technical Progress, and Efficiency Change in Industrialized Countries”, The American Economic Review, Vol. 84 (1), pp: 66–83. Fuentes, H., Grifell-Tatjé, E., and Pereleman, S., (2001), “A Parametric Distance Function Approach for Malmquist Productivity Index Estimation”, Journal of Productivity Analysis, Vol. 15, pp. 79–94. Koop, G., Osiewalski, J., and Steel, M., (1999), “Bayesian efficiency analysis through individual effects: Hospital cost frontiers”, Journal of Econometrics, Vol. 76, pp. 77–105. Koop, G., Osiewalski, J., and Steel, M., (1999), “The Components of Output Growth: A Stochastic Frontier Analysis”, Oxford Bulletin of Economics and Statistics, Vol. 61 (4), pp. 455–487. Latruffe, L., Davidova, S., and Balcombe, K., (2008), “Productivity Change in Poland Agriculture: an Illustration of a bootstrapping procedure Applied to Malmquist indices”, Post – Communist Economies, Vol. 20 (4), pp. 449–460. Makieła, K. (2009), “Economic Growth Decomposition. An Empirical Analysis Using Bayesian Frontier Approach”, Central European Journal of Economic Modelling and Econometrics, Vol. 1 (4), pp. 333–369. Makieła, K., (2014), “Bayesian Stochastic Frontier Analysis of Economic Growth and Productivity Change in the EU, USA, Japan and Switzerland”, Central European Journal of Economic Modelling and Econometrics, Vol. 6, pp. 193–216. Meeusen, W, and van den Broeck, J, (1997), “Efficiency estimation from Cobb-Douglas production functions with composed error”, International Economic Review, Vol. 8, pp. 435–444. Osiewalski, J., and Steel, M., (1998), „Numerical tools for the Bayesian analysis of stochastic frontier models”, Journal of Productivity Analysis, Vol. 10, pp: 103–117. Orea, L., (2002), “Parametric decomposition of a generalized Malmquist productivity index”, Journal of Productivity Analysis, Vol. 18, pp. 5–22. Reinhard, S., Lovell, C., and Thijssen, G., (1999), “Estimation of technical and environmental efficiency: An application to Dutch dairy farms”, American Journal of Agricultural Economics, Vol. 81, pp: 44–60. Theodoridis, A., Hasanov, S. and Abruev, A., (2014), “Efficiency and productivity change analysis of cotton production in Uzbekistan”, Outlook on Agriculture, Vol. 43 (4), pp. 259–263. Tonini, A., (2012), “A Bayesian stochastic frontier: An Application to agricultural productivity growth in European countries”, Economic Change Restructuring, Vol. 45, pp. 247–269. |
URI: | https://mpra.ub.uni-muenchen.de/id/eprint/80295 |