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The distribution of dairy farm size in Poland: a markov approach based on information theory

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  • Axel Tonini
  • Roel Jongeneel

Abstract

This article sets out to analyse the evolution of the dairy farm structure of Poland during the post-socialist period. After focusing on how the farm structure has changed over time, an instrumental variable generalized cross entropy estimator is used to develop and estimate a Markov model in order to explore how farm structure will probably develop in the coming decade. The estimator exploits both sample data and prior information, including general and plausible information on farm mobility and structural adjustments based on independent literature. Next, several statistical indicators are computed for farm mobility and for which farms are likely to survive. Finally, milk projections are made and related to policy scenarios. The projections show that the number of dairy farms will continue to decline, but the number of medium and large farms will increase. In the coming decade, subsistence dairy farms are expected to leave the sector slowly. Milk projections show that under the status quo, milk quotas will be binding and overrun, whereas under the 'soft landing' scenario they appear to be only binding after 2010.

Suggested Citation

  • Axel Tonini & Roel Jongeneel, 2009. "The distribution of dairy farm size in Poland: a markov approach based on information theory," Applied Economics, Taylor & Francis Journals, vol. 41(1), pages 55-69.
    • Handle: RePEc:taf:applec:v:41:y:2009:i:1:p:55-69
    DOI: 10.1080/00036840701704394
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    References listed on IDEAS

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    1. Petrick, Martin & Weingarten, Peter (ed.), 2004. "The role of agriculture in Central and Eastern European rural development: engine of change or social buffer?," Studies on the Agricultural and Food Sector in Transition Economies, Leibniz Institute of Agricultural Development in Transition Economies (IAMO), volume 25, number 93023.
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    Cited by:

    1. Mikkel Bojesen & Hans Skov-Petersen & Morten Gylling, 2013. "Forecasting the potential of Danish biogas production: spatial representation of Markov chains," IFRO Working Paper 2013/16, University of Copenhagen, Department of Food and Resource Economics.
    2. Huettel, Silke & Jongeneel, Roelof A., 2009. "Impact of the EU Milk Quota on Structural Change in the Dairy Sectors of Germany and The Netherlands," 2009 Conference, August 16-22, 2009, Beijing, China 50943, International Association of Agricultural Economists.
    3. Nancy McCarthy & Heath Henderson, 2014. "The Role of Renewable Energy Laws in Expanding Energy from Non-Traditional Renewables," IDB Publications (Working Papers) 86813, Inter-American Development Bank.
    4. Zheng, Yanan & Goddard, Ellen W. & Qiu, Feng, 2018. "Exploring the Effect of Disease Outbreaks on Farm Structure Change: A Dynamic Analysis for Canadian Pig Industry," 2018 Annual Meeting, August 5-7, Washington, D.C. 273801, Agricultural and Applied Economics Association.
    5. Viaggi, Davide & Raggi, Meri & Gomez y Paloma, Sergio, 2011. "Farm-household investment behaviour and the CAP decoupling: Methodological issues in assessing policy impacts," Journal of Policy Modeling, Elsevier, vol. 33(1), pages 127-145, January.
    6. Zimmermann, Andrea & Heckelei, Thomas, 2012. "Differences of farm structural change across European regions," Discussion Papers 162879, University of Bonn, Institute for Food and Resource Economics.
    7. Oudendag, Diti & Hoogendoorn, Mark & Jongeneel, Roel, 2014. "Agent-Based Modeling of Farming Behavior: A Dutch Case Study on Milk Quota Abolishment and Sustainable Dairying," 2014 International Congress, August 26-29, 2014, Ljubljana, Slovenia 182700, European Association of Agricultural Economists.
    8. Huettel, Silke & Jongeneel, Roelof A., 2008. "Structural Change in the Dairy Sectors of Germany and The Netherlands - A Markov Chain Analysis," 2008 International Congress, August 26-29, 2008, Ghent, Belgium 43659, European Association of Agricultural Economists.
    9. Piet, Laurent, 2011. "Assessing structural change in agriculture with a parametric Markov chain model. Illustrative applications to EU-15 and the USA," 2011 International Congress, August 30-September 2, 2011, Zurich, Switzerland 114668, European Association of Agricultural Economists.
    10. Yuval Dolev & Ayal Kimhi, 2010. "Do family farms really converge to a uniform size? The role of unobserved farm efficiency ," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 54(1), pages 119-136, January.
    11. Alexander Gocht & Norbert Röder & Sebastian Neuenfeldt & Hugo Storm & Thomas Heckelei, 2012. "Modelling farm structural change: A feasibility study for ex-post modelling utilizing FADN and FSS data in Germany and developing an ex-ante forecast module for the CAPRI farm type layer baseline," JRC Working Papers JRC75524, Joint Research Centre (Seville site).
    12. Nancy McCarthy & Heath Henderson, 2014. "The Role of Renewable Energy Laws in Expanding Energy from Non-Traditional Renewables," IDB Publications (Working Papers) 6677, Inter-American Development Bank.
    13. Jan Kubacki & Andrzej Młodak, 2010. "A Typology of Polish Farms Using Probabilistic d–clustering," Statistics in Transition new series, Główny Urząd Statystyczny (Polska), vol. 11(3), pages 615-638, December.
    14. Heath Henderson, 2014. "Structural transformation and smallholder agriculture: an information-theoretic analysis of the Nicaraguan case," Agricultural Economics, International Association of Agricultural Economists, vol. 45(4), pages 443-458, July.
    15. Jongeneel, Roelof A. & Tonini, Axel, 2008. "Dairy Quota and Farm Structural Change: A Case Study on the Netherlands," 107th Seminar, January 30-February 1, 2008, Sevilla, Spain 6692, European Association of Agricultural Economists.
    16. repec:psc:journl:v:9:y:2017:i:3:p:243-273 is not listed on IDEAS

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