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

Author

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  • Storm, Hugo
  • Heckelei, Thomas

Abstract

In this poster a Bayesian estimation framework for a non-stationary Markov model is developed for situations where sample data with observed transition between classes (micro data) and aggregate population shares (macro data) are available. Posterior distributions on transition probabilities are derived based on a micro based prior and a macro based Likelihood function thereby consistently combining previously separated approaches. Monte Carlo simulations for ordered and unordered Markov states show how observed micro transitions improve precision of posterior knowledge as the sample size increases.

Suggested Citation

  • Storm, Hugo & Heckelei, Thomas, "undated". "Bayesian estimation of non-stationary Markov models combining micro and macro data," 2011 Annual Meeting, July 24-26, 2011, Pittsburgh, Pennsylvania 103645, Agricultural and Applied Economics Association.
    • Handle: RePEc:ags:aaea11:103645
    DOI: 10.22004/ag.econ.103645
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    Cited by:

    1. 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).
    2. 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.
    3. 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).
    4. 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.
    5. 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).
    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. 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.
    8. 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.
    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. 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).
    11. 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.
    12. 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.
    13. 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.

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    Keywords

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    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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