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The Use of Maximum Entropy to Estimate Input‐Output Coefficients From Regional Farm Accounting Data

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  • Yves Léony
  • Ludo Peeters
  • Maurice Quinqu
  • Yves Surry

Abstract

This paper proposes the use of the Generalised Maximum Entropy (GME) method to estimate input‐output coefficients, which reflect the unobserved allocation of farm input accounting costs to the various outputs produced. The GME method uses Shannon's information criterion as a basis for estimation. The performance of the GME method is compared with three other estimation techniques: Ordinary Least Squares (OLS), Bayesian estimation, and Linear Programming (LP). The various methods are applied to accounting data from a sample of beef‐dairy farms in Brittany, France. The analysis shows that the GME method offers an interesting alternative to “traditional” estimation methods. In contrast with the latter, though, the GME method is suitable to handle easily the problems of singularity, constrained estimation, and zero‐observations. Moreover, due to its flexibility, transparency and relative ease of implementation, the GME method is of great value to practitioners. However, the sensitivity of the GME estimates with respect to the design of the prior information set needs to be investigated further.

Suggested Citation

  • Yves Léony & Ludo Peeters & Maurice Quinqu & Yves Surry, 1999. "The Use of Maximum Entropy to Estimate Input‐Output Coefficients From Regional Farm Accounting Data," Journal of Agricultural Economics, Wiley Blackwell, vol. 50(3), pages 425-439, September.
    • Handle: RePEc:bla:jageco:v:50:y:1999:i:3:p:425-439
    DOI: 10.1111/j.1477-9552.1999.tb00891.x
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    Cited by:

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    2. Tiberti, M., 2013. "Production costs of Soft Wheat in Italy," 2013 Second Congress, June 6-7, 2013, Parma, Italy 149898, Italian Association of Agricultural and Applied Economics (AIEAA).
    3. Lindberg, Gunnar & Midmore, Peter & Surry, Yves R., 2011. "Agriculture’s inter-industry linkages, aggregation bias and rural policy reforms," 122nd Seminar, February 17-18, 2011, Ancona, Italy 99358, European Association of Agricultural Economists.
    4. Bahta, Sirak Teclemariam & Berner, Anja & Offermann, Frank, 2011. "Estimation of Commodity Specific Production Costs Using German Farm Accountancy Data," 2011 International Congress, August 30-September 2, 2011, Zurich, Switzerland 114233, European Association of Agricultural Economists.
    5. Louhichi, Kamel & Jacquet, Florence & Butault, Jean Pierre, 2012. "Estimating input allocation from heterogeneous data sources: A comparison of alternative estimation approaches," Agricultural Economics Review, Greek Association of Agricultural Economists, vol. 13(2), pages 1-20.
    6. Heckelei, Thomas & Britz, Wolfgang, 2000. "Positive Mathematical Programming with Multiple Data Points: A Cross-Sectional Estimation Procedure," Cahiers d'Economie et de Sociologie Rurales (CESR), Institut National de la Recherche Agronomique (INRA), vol. 57.
    7. Gocht, Alexander, 2008. "Estimating input allocation for farm supply models," 107th Seminar, January 30-February 1, 2008, Sevilla, Spain 6469, European Association of Agricultural Economists.
    8. Lugovoy, Oleg & Polbin, Andrey & Potashnikov, Vladimir, 2015. "Bayesian Updating of Input-Output Tables," Conference papers 332664, Purdue University, Center for Global Trade Analysis, Global Trade Analysis Project.
    9. Heckelei, Thomas & Wolff, Hendrik, 2002. "A Methodological Note on the Estimation of Programming Models," 2002 International Congress, August 28-31, 2002, Zaragoza, Spain 24896, European Association of Agricultural Economists.
    10. Hansen, Heiko & Surry, Yves R., 2006. "Die Schatzung Verfahrensspezifischer Faktoreinsatzmengen Fur Die Landwirtschaft In Deutschland," 46th Annual Conference, Giessen, Germany, October 4-6, 2006 14959, German Association of Agricultural Economists (GEWISOLA).
    11. G. Lindberg & P. Midmore & Y. Surry, 2012. "Agriculture’s Inter-industry Linkages, Aggregation Bias and Rural Policy Reforms," Journal of Agricultural Economics, Wiley Blackwell, vol. 63(3), pages 552-575, September.
    12. Lips, Markus, 2009. "Full Product Costs on Base of Farm Accountancy Data by Means of Maximum Entropy," 2009 Conference, August 16-22, 2009, Beijing, China 51088, International Association of Agricultural Economists.
    13. Lips, Markus, 2014. "Disproportionate joint cost allocation at individual-farm level using maximum entropy," 2014 International Congress, August 26-29, 2014, Ljubljana, Slovenia 182851, European Association of Agricultural Economists.
    14. Petsakos, Athanasios & Rozakis, Stelios, 2015. "Calibration of agricultural risk programming models," European Journal of Operational Research, Elsevier, vol. 242(2), pages 536-545.
    15. Alexandre Gohin, 2020. "Prospective sur l'évolution des systèmes agricoles sur les territoires bretons en lien avec la reconquête de la qualité de l'eau-Etude des impacts de ces évolutions sur les revenus, les emplois direct," Working Papers hal-03331840, HAL.
    16. Caputo, Michael R. & Paris, Quirino, 2008. "Comparative statics of the generalized maximum entropy estimator of the general linear model," European Journal of Operational Research, Elsevier, vol. 185(1), pages 195-203, February.
    17. Hansen, H. & Surry, Y., 2007. "Die Schätzung verfahrensspezifischer Faktoreneinsatzmengen für die Landwirtschaft in Deutschland," Proceedings “Schriften der Gesellschaft für Wirtschafts- und Sozialwissenschaften des Landbaues e.V.”, German Association of Agricultural Economists (GEWISOLA), vol. 42, March.
    18. Arfini, Filippo & Donati, Michele & Paris, Quirino, 2008. "Innovation in Estimation of Revenue and Cost Functions in PMP Using FADN Information at Regional Level," 2008 International Congress, August 26-29, 2008, Ghent, Belgium 44008, European Association of Agricultural Economists.
    19. Anthony T. Flegg & Guiseppe R. Lamonica & Francesco M. Chelli & Maria C. Recchioni & Timo Tohmo, 2021. "A new approach to modelling the input–output structure of regional economies using non-survey methods," Journal of Economic Structures, Springer;Pan-Pacific Association of Input-Output Studies (PAPAIOS), vol. 10(1), pages 1-31, December.
    20. Kamel Elouhichi & Maria Espinosa Goded & Pavel Ciaian & Angel Perni Llorente & Bouda Vosough Ahmadi & Liesbeth Colen & Sergio Gomez Y Paloma, 2018. "The EU-Wide Individual Farm Model for Common Agricultural Policy Analysis (IFM-CAP v.1): Economic Impacts of CAP Greening," JRC Research Reports JRC108693, Joint Research Centre.
    21. Arfini, Filippo & Donati, Michele & Grossi, L. & Paris, Quirino, 2008. "Revenue and Cost Functions in PMP: a Methodological Integration for a Territorial Analysis of CAP," 107th Seminar, January 30-February 1, 2008, Sevilla, Spain 6636, European Association of Agricultural Economists.

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