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Movers and Stayers in the Farming Sector: Accounting for Unobserved Heterogeneity in Structural Change

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  • Saint-Cyr, Legrand D.F.
  • Piet, Laurent

Abstract

The Markov chain model (MCM) has become a popular tool in the agricultural economics literature to describe how farms experience structural change and to study the impact of various drivers of this process, including public support. Even though some studies have accounted for heterogeneity across farms by letting transition probabilities depend on co- variates depicting farms and/or farmers' characteristics, only observed heterogeneity has been considered so far. Assuming that structural change may also relate to unobserved farms and/or farmers' characteristics, we present how to implement the mover-stayer model (MSM) which considers a mixture of two types of farms, the `stayers' who always remain in their initial size category and the `movers' who follow a first-order Markovian process, and how to estimate it thanks to the expectation-maximization (EM) algorithm. This modeling framework relaxes the assumption of homogeneity in the transition process which grounds the usual MCM. An empirical application to a panel of French farms over 2000-2013 shows that the MSM outperforms the MCM in recovering the underlying year-to-year transition process as well as in deriving the long-run transition matrix and forecasting future farm size distributions.

Suggested Citation

  • Saint-Cyr, Legrand D.F. & Piet, Laurent, 2015. "Movers and Stayers in the Farming Sector: Accounting for Unobserved Heterogeneity in Structural Change," 89th Annual Conference, April 13-15, 2015, Warwick University, Coventry, UK 204234, Agricultural Economics Society.
    • Handle: RePEc:ags:aesc15:204234
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    References listed on IDEAS

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    1. Shorrocks, A F, 1976. "Income Mobility and the Markov Assumption," Economic Journal, Royal Economic Society, vol. 86(343), pages 566-578, September.
    2. Denis Fougère & Thierry Kamionka, 2003. "Bayesian inference for the mover-stayer model in continuous time with an application to labour market transition data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(6), pages 697-723.
    3. Andrea Zimmermann & Thomas Heckelei, 2012. "Structural Change of European Dairy Farms – A Cross-Regional Analysis," Journal of Agricultural Economics, Wiley Blackwell, vol. 63(3), pages 576-603, September.
    4. Stokes, Jeffrey R., 2006. "Entry, Exit, and Structural Change in Pennsylvania's Dairy Sector," Agricultural and Resource Economics Review, Cambridge University Press, vol. 35(02), pages 357-373, October.
    5. Hugo Storm & Thomas Heckelei & Ron C. Mittelhammer, 2016. "Bayesian estimation of non-stationary Markov models combining micro and macro data," European Review of Agricultural Economics, Foundation for the European Review of Agricultural Economics, vol. 43(2), pages 303-329.
    6. repec:ags:nareaj:159470 is not listed on IDEAS
    7. MacRae, Elizabeth Chase, 1977. "Estimation of Time-Varying Markov Processes with Aggregate Data," Econometrica, Econometric Society, vol. 45(1), pages 183-198, January.
    8. Frydman, Halina & Schuermann, Til, 2008. "Credit rating dynamics and Markov mixture models," Journal of Banking & Finance, Elsevier, vol. 32(6), pages 1062-1075, June.
    9. Jafry, Yusuf & Schuermann, Til, 2004. "Measurement, estimation and comparison of credit migration matrices," Journal of Banking & Finance, Elsevier, vol. 28(11), pages 2603-2639, November.
    10. Karantininis, Kostas, 2002. "Information-based estimators for the non-stationary transition probability matrix: an application to the Danish pork industry," Journal of Econometrics, Elsevier, vol. 107(1-2), pages 275-290, March.
    11. Stavins, R. N. & Stanton, B. F., 1980. "Alternative Procedures For Estimating The Size Distribution Of Farms," Northeastern Journal of Agricultural and Resource Economics, Northeastern Agricultural and Resource Economics Association, vol. 0(Number 2), pages 1-6, October.
    12. M. C. Hallberg, 1969. "Projecting the Size Distribution of Agricultural Firms—An Application of a Markov Process with Non-Stationary Transition Probabilities," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 51(2), pages 289-302.
    13. Christoph R. Weiss, 1999. "Farm Growth and Survival: Econometric Evidence for Individual Farms in Upper Austria," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 81(1), pages 103-116.
    14. Frydman, Halina, 2005. "Estimation in the Mixture of Markov Chains Moving With Different Speeds," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 1046-1053, September.
    15. Jayasri Dutta & J. A. Sefton & M. R. WEALE, 2001. "Income distribution and income dynamics in the United Kingdom," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(5), pages 599-617.
    16. Silke Huettel & Roel Jongeneel, 2011. "How has the EU milk quota affected patterns of herd-size change?," European Review of Agricultural Economics, Foundation for the European Review of Agricultural Economics, vol. 38(4), pages 497-527, October.
    17. 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.
    18. Lydia Zepeda, 1995. "Asymmetry and Nonstationarity in the Farm Size Distribution of Wisconsin Milk Producers: An Aggregate Analysis," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 77(4), pages 837-852.
    19. Jean-Pierre Butault & Nathalie Delame, 2005. "Concentration de la production agricole et croissance des exploitations," Économie et Statistique, Programme National Persée, vol. 390(1), pages 47-64.
    20. Halina Frydman & Jarl G. Kallberg & Duen-Li Kao, 1985. "Testing the Adequacy of Markov Chain and Mover-Stayer Models as Representations of Credit Behavior," Operations Research, INFORMS, vol. 33(6), pages 1203-1214, December.
    21. T. C. Lee & G. G. Judge & T. Takayama, 1965. "On Estimating the Transition Probabilities of a Markov Process," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 47(3), pages 742-762.
    22. Bickenbach, Frank & Bode, Eckhardt, 2001. "Markov or not Markov - this should be a question," Kiel Working Papers 1086, Kiel Institute for the World Economy (IfW).
    23. Timothy M. Morgan & Carol S. Aneshensel & Virginia A. Clark, 1983. "Parameter Estimation for Mover-Stayer Models," Sociological Methods & Research, , vol. 11(3), pages 345-366, February.
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    Cited by:

    1. Tamirat, Aderajew AS & Trujillo-Barrera, Andres A. & Pennings, Joost M. E., 2018. "Farm Level Risk Balancing Behavior and the Role of Latent Heterogeneity," 2018 Annual Meeting, August 5-7, Washington, D.C. 274467, Agricultural and Applied Economics Association.
    2. Legrand D. F, Saint-Cyr, 2017. "Farm heterogeneity and agricultural policy impacts on size dynamics: evidence from France," Working Papers SMART - LERECO 17-04, INRA UMR SMART-LERECO.
    3. Laurent, Piet & Legrand D.F. Saint-Cyr, 2016. "Projection de la population des exploitations agricoles françaises à l’horizon 2025," Working Papers SMART - LERECO 16-11, INRA UMR SMART-LERECO.

    More about this item

    Keywords

    Agribusiness; Farm Management;

    JEL classification:

    • Q12 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Micro Analysis of Farm Firms, Farm Households, and Farm Input Markets
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • D92 - Microeconomics - - Micro-Based Behavioral Economics - - - Intertemporal Firm Choice, Investment, Capacity, and Financing

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