IDEAS home Printed from https://ideas.repec.org/a/ags/gjagec/270178.html
   My bibliography  Save this article

Short Term Prediction of Agricultural Structural Change using Farm Accountancy Data Network and Farm Structure Survey Data

Author

Listed:
  • Storm, Hugo
  • Heckelei, Thomas
  • Espinosa, María
  • Gomez y Paloma, Sergio

Abstract

The prediction of farm structural change is of large interest at EU policy level, but available methods are limited regarding the joint and consistent use of available data sources. This paper develops a Bayesian Markov framework for short-term prediction of farm numbers that allows combining two asynchronous data sources in a single estimation. Specifically, the approach allows combining aggregated Farm Structure Survey (FSS) macro data, available every two to three years, with individual farm level Farm Accountancy Data Network (FADN) micro data, available on a yearly basis. A Bayesian predictive distribution is derived from which point predictions such as mean and other moments are obtained. The proposed approach is evaluated in an out-of-sample prediction exercise of farm numbers in German regions and compared to linear and geometric prediction as well as a “no-change” prediction of farm numbers. Results show that the proposed approach outperforms the geometric prediction but does not significantly improve upon the linear prediction and a prediction of no change in this context. Die Vorhersage des landwirtschaftlichen Strukturwandels ist von großem Interesse für die EU-Agrarpolitik, aber gegenwärtige Methoden können die verfügbaren Datenquellen nicht vollständig und in konsistenter Weise verwenden. Zur kurzfristigen Vorhersage des Agrarstrukturwandels wird ein Bayes’scher Markov-Ansatz entwickelt, der die Kombination von zwei asynchronen Datenquellen in einer einzigen Schätzung erlaubt. Im konkreten Fall werden dabei in konsistenter Weise aggregierte Daten des Farm Structure Survey (FSS), die alle zwei bis drei Jahre erhoben werden, mit jährlich verfügbaren Stichprobendaten des einzelbetrieblichen Farm Accountancy Data Network (FADN) kombiniert. Eine geschätzte Bayes’sche Vorhersageverteilung erlaubt die Ermittlung von Punktvorhersagen in Form des arithmetischen Mittels und die Ableitung anderer Momente. Evaluiert wird der Ansatz in einer „out-of-sample“-Vorhersage für die Anzahl landwirtschaftlicher Betriebe in verschiedenen Klassen und Bundesländern in Deutschland. Verglichen werden die Ergebnisse mit einer linearen und geometrischen Vorhersage sowie einer „konstanten“ Vorhersage, die keine Veränderungen zum letzten Beobachtungsjahr unterstellt. Im Vergleich zur geometrischen Vorhersage liefert der Ansatz bessere Ergebnisse, wobei lineare und konstante Vorhersage ähnliche Ergebnisse in diesem Kontext liefern.

Suggested Citation

  • Storm, Hugo & Heckelei, Thomas & Espinosa, María & Gomez y Paloma, Sergio, 2015. "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), September.
    • Handle: RePEc:ags:gjagec:270178
    DOI: 10.22004/ag.econ.270178
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/270178/files/3_Storm.pdf
    Download Restriction: no
    File URL: https://ageconsearch.umn.edu/record/270178/files/3_Storm.pdf?subformat=pdfa
    Download Restriction: no
    File URL: https://libkey.io/10.22004/ag.econ.270178?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. Laurent Piet & Laure Latruffe & Chantal Le Mouël & Yann Desjeux, 2012. "How do agricultural policies influence farm size inequality? The example of France," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 39(1), pages 5-28, February.
    3. Moro, Daniele & Sckokai, Paolo, 2013. "The impact of decoupled payments on farm choices: Conceptual and methodological challenges," Food Policy, Elsevier, vol. 41(C), pages 28-38.
    4. Gunnar Breustedt & Thomas Glauben, 2007. "Driving Forces behind Exiting from Farming in Western Europe," Journal of Agricultural Economics, Wiley Blackwell, vol. 58(1), pages 115-127, February.
    5. 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.
    6. Hyndman, Rob J. & Koehler, Anne B., 2006. "Another look at measures of forecast accuracy," International Journal of Forecasting, Elsevier, vol. 22(4), pages 679-688.
    7. Laurent Piet & Laure Latruffe & Chantal Le Mouël & Yann Desjeux, 2012. "How do agricultural policies influence farm size inequality? The example of France," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 39(1), pages 5-28, February.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Marie Dervillé & Gilles Allaire & Élise Maigné & Éric Cahuzac, 2017. "Internal and contextual drivers of dairy restructuring: evidence from French mountainous areas and post†quota prospects," Agricultural Economics, International Association of Agricultural Economists, vol. 48(1), pages 91-103, January.
    2. Stefan Mann, 2021. "Synthesizing Knowledge about Structural Change in Agriculture: The Integration of Disciplines and Aggregation Levels," Agriculture, MDPI, vol. 11(7), pages 1-14, June.
    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. Legrand D. F. Saint‐Cyr, 2022. "Heterogeneous farm‐size dynamics and impacts of subsidies from agricultural policy: Evidence from France," Journal of Agricultural Economics, Wiley Blackwell, vol. 73(3), pages 893-923, September.
    5. Zier, Patrick, 2013. "Econometric impact assessment of the Common Agricultural Policy in East German agriculture," Studies on the Agricultural and Food Sector in Transition Economies, Leibniz Institute of Agricultural Development in Transition Economies (IAMO), volume 71, number 71.
    6. Boere, Esther & Peerlings, Jack & Reinhard, Stijn & Heijman, Wim, 2014. "The dynamics of dairy land use change with respect to the milk quota regime," 2014 International Congress, August 26-29, 2014, Ljubljana, Slovenia 182710, European Association of Agricultural Economists.
    7. Legrand D. F, Saint-Cyr, 2017. "Farm heterogeneity and agricultural policy impacts on size dynamics: evidence from France," Working Papers SMART 17-04, INRAE UMR SMART.
    8. Chiara Landi & Gianluca Stefani & Benedetto Rocchi & Ginevra Virginia Lombardi & Sabina Giampaolo, 2016. "Regional Differentiation and Farm Exit: A Hierarchical Model for Tuscany," Journal of Agricultural Economics, Wiley Blackwell, vol. 67(1), pages 208-230, February.
    9. Fałkowski, Jan, 2017. "Promoting change or preserving the status quo? The consequences of dominating local politics by agricultural interests," Land Use Policy, Elsevier, vol. 68(C), pages 448-459.
    10. He, Xi, 2018. "Bigger Farms and Bigger Food Firms-The Agricultural Origin of Industrial Concentration in the Food Sector," 2018 Annual Meeting, August 5-7, Washington, D.C. 274206, Agricultural and Applied Economics Association.
    11. Ostapchuk, Igor & Gagalyuk, Taras & Curtiss, Jarmila, 2021. "Post-acquisition integration and growth of farms: the case of Ukrainian agroholdings," International Food and Agribusiness Management Review, International Food and Agribusiness Management Association, vol. 24(4), April.
    12. Matthews, Alan & Salvatici, Luca & Scoppola, Margherita, 2017. "Trade Impacts of Agricultural Support in the EU," Commissioned Papers 252767, International Agricultural Trade Research Consortium.
    13. Qun Zhang & Cifang Wu, 2022. "Optimization Model of Permanent Basic Farmland Indicators Distribution from the Perspective of Equity: A Case from W County, China," Land, MDPI, vol. 11(8), pages 1-13, August.
    14. Kersting, Stefan & Hüttel, Silke & Odening, Martin, 2015. "Structural change in agriculture under capacity constraints: An equilibrium approach," Thuenen-Series of Applied Economic Theory 140, University of Rostock, Institute of Economics.
    15. 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.
    16. Barbottin, Aude & Bouty, Clémence & Martin, Philippe, 2018. "Using the French LPIS database to highlight farm area dynamics: The case study of the Niort Plain," Land Use Policy, Elsevier, vol. 73(C), pages 281-289.
    17. Robert Finger & Nadja El Benni, 2021. "Farm income in European agriculture: new perspectives on measurement and implications for policy evaluation," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 48(2), pages 253-265.
    18. Landi, Chiara & Bartolini, Fabio & Rovai, Massimo, 2014. "A spatial analysis of the farm structural change: the case study of Tuscany region," 2014 International Congress, August 26-29, 2014, Ljubljana, Slovenia 182938, European Association of Agricultural Economists.
    19. Piet, Laurent, 2017. "Concentration of the agricultural production in the EU: the two sides of a coin," 2017 International Congress, August 28-September 1, 2017, Parma, Italy 261439, European Association of Agricultural Economists.
    20. Bina Agarwal & Bruno Dorin, 2019. "Group farming in France: Why do some regions have more cooperative ventures than others?," Environment and Planning A, , vol. 51(3), pages 781-804, May.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ags:gjagec:270178. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: AgEcon Search (email available below). General contact details of provider: https://edirc.repec.org/data/iahubde.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.