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Bayesian estimation of non-stationary Markov models combining micro and macro data

Author

Listed:
  • Hugo Storm
  • Thomas Heckelei
  • Ron C. Mittelhammer

Abstract

We develop a Bayesian framework for estimating non-stationary Markov models in situations where macro population data are available only on the proportion of individuals residing in each state, but micro-level sample data are available on observed transitions between states. Posterior distributions on non-stationary transition probabilities (TPs) are derived combining micro and macrodata using potentially asynchronous data observations, providing a new method for inferring TPs that merges previously disparate approaches. Monte Carlo simulations demonstrate how observed micro transitions can improve the precision of posterior information. We provide an empirical illustration in the context of farm structural change.

Suggested Citation

  • 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, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 43(2), pages 303-329.
    • Handle: RePEc:oup:erevae:v:43:y:2016:i:2:p:303-329.
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    File URL: http://hdl.handle.net/10.1093/erae/jbv018
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    Cited by:

    1. Zorn, Alexander & Zimmert, Franziska, 2020. "Structural adjustment of Swiss dairy farms - farm exit and farm type change," 60th Annual Conference, Halle/ Saale, Germany, September 23-25, 2020 305605, German Association of Agricultural Economists (GEWISOLA).
    2. Storm, Hugo & Heckelei, Thomas, 2012. "Predicting agricultural structural change using census and sample data," 2012 Annual Meeting, August 12-14, 2012, Seattle, Washington 125185, Agricultural and Applied Economics Association.
    3. Alexander Zorn & Franziska Zimmert, 2022. "Structural change in the dairy sector: exit from farming and farm type change," Agricultural and Food Economics, Springer;Italian Society of Agricultural Economics (SIDEA), vol. 10(1), pages 1-31, December.
    4. Storm, Hugo & Heckelei, Thomas & Espinosa, María & Gomez y Paloma, Sergio, . "Short Term Prediction of Agricultural Structural Change using Farm Accountancy Data Network and Farm Structure Survey Data," German Journal of Agricultural Economics, Humboldt-Universitaet zu Berlin, Department for Agricultural Economics, vol. 64(03).
    5. 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 Research Reports JRC75524, Joint Research Centre.
    6. Legrand D. F. Saint-Cyr & Laurent Piet, 2017. "Movers and stayers in the farming sector: accounting for unobserved heterogeneity in structural change," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 66(4), pages 777-795, August.
    7. Zorn, Alexander & Zimmert, Franziska, "undated". "Structural adjustment of Swiss dairy farms - farm exit and farm type change," 60th Annual Conference, Halle/ Saale, Germany, September 23-25, 2020 305605, German Association of Agricultural Economists (GEWISOLA).
    8. Unay-Gailhard, İlkay & Bojnec, Štefan, 2016. "Sustainable participation behaviour in agri-environmental measures," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 138, pages 47-58.
    9. Zimmermann, Andrea & Heckelei, Thomas, "undated". "Differences of farm structural change across European regions," Discussion Papers 162879, University of Bonn, Institute for Food and Resource Economics.
    10. Piet, Laurent & Saint-Cyr, Legrand D.F., 2016. "Projection de la population des exploitations agricoles françaises à l’horizon 2025," Working Papers 250208, Institut National de la recherche Agronomique (INRA), Departement Sciences Sociales, Agriculture et Alimentation, Espace et Environnement (SAE2).
    11. Saint-Cyr, Legrand D. F. & Piet, Laurent, 2014. "Movers and Stayers in the Farming Sector: Another Look at Heterogeneity in Structural Change," 2014 International Congress, August 26-29, 2014, Ljubljana, Slovenia 183068, European Association of Agricultural Economists.
    12. 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.
    13. Neuenfeldt, S. & Rieger, J. & Heckelei, T. & Gocht, A. & Ciaian, P. & Tetteh, G., 2018. "A multiplicative competitive interaction model to explain structural change along farm specialisation, size and exit/entry using Norwegian farm census data," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 277090, International Association of Agricultural Economists.

    More about this item

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access

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