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Estimation of Multi-Output Production Functions with Incomplete Data: A Generalized Maximum Entropy Approach

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  • Miller, Douglas
  • Lence, Sergio H.

Abstract

One problem commonly encountered when analysing multiproduct-multifactor firms is the lack of activity-specific input data. The present study contributes to the empirical literature on production functions by presenting an information theoretic approach to estimating production functions in the absence of activity-specific input allocations. The procedure relies solely on production data, so that behavioural hypotheses (e.g., profit maximisation) are not required and estimation can proceed in the absence of price data. In addition, the method can be applied to ill-posed problems. The proposed procedure is demonstrated with simulated production data and exhibits favourable statistical properties. Copyright 1998 by Oxford University Press.
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Suggested Citation

  • Miller, Douglas & Lence, Sergio H., 1998. "Estimation of Multi-Output Production Functions with Incomplete Data: A Generalized Maximum Entropy Approach," Staff General Research Papers Archive 1219, Iowa State University, Department of Economics.
  • Handle: RePEc:isu:genres:1219
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    Cited by:

    1. 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), INRA (French National Institute for Agricultural Research), vol. 57.
    2. 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.
    3. Msangi, Siwa & Howitt, Richard E., 2006. "Estimating Disaggregate Production Functions: An Application to Northern Mexico," 2006 Annual meeting, July 23-26, Long Beach, CA 21080, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    4. Raja Chakir, 2009. "Spatial Downscaling of Agricultural Land-Use Data: An Econometric Approach Using Cross Entropy," Land Economics, University of Wisconsin Press, vol. 85(2), pages 238-251.
    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), June.
    6. 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.
    7. Letort, Elodie & Carpentier, Alain, 2009. "Endogeneity of acreage choices in input allocation equations: implied problems and a solution," 2009 Annual Meeting, July 26-28, 2009, Milwaukee, Wisconsin 49217, Agricultural and Applied Economics Association.
    8. Anderson, Weston & You, Liangzhi & Wood, Stanley & Wood-Sichra, Ulrike & Wu, Wenbin, 2014. "A comparative analysis of global cropping systems models and maps:," IFPRI discussion papers 1327, International Food Policy Research Institute (IFPRI).
    9. Heckelei, T. & Wolff, H., 2002. "Ansätze zur (Auf-)Lösung eines alten Methodenstreits: Ökonometrische Spezifikation von Programmierungsmodellen zur Agrarangebotsanalyse," Proceedings "Schriften der Gesellschaft für Wirtschafts- und Sozialwissenschaften des Landbaues e.V.", German Association of Agricultural Economists (GEWISOLA), vol. 37.
    10. You, Liangzhi & Wood, Stanley & Wood-Sichra, Ulrike, 2004. "Generating Plausible Crop Distribution Maps For Sub-Sahara Africa Using Spatial Allocation Model," 2004 Annual meeting, August 1-4, Denver, CO 19965, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    11. Howitt, Richard E. & Msangi, Siwa, 2002. "Reconstructing Disaggregate Production Functions," 2002 Annual meeting, July 28-31, Long Beach, CA 19585, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    12. Arfini, Filippo & Donati, Michele & Marongiu, Sonia & Cesaro, Luca, 2012. "Farm production costs estimation trough PMP Models: an application in three Italian Regions," Congress Papers 124117, Italian Association of Agricultural and Applied Economics (AIEAA).
    13. Mueller, Marc, 2004. "Where Has All The Water Gone? Estimation Of A Production Function For The Agricultural Sector In The Region Khorezm, Uzbekistan," 2004 Annual meeting, August 1-4, Denver, CO 20106, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    14. Steven Sexton & David Zilberman, 2011. "Land for Food and Fuel Production: The Role of Agricultural Biotechnology," NBER Chapters,in: The Intended and Unintended Effects of U.S. Agricultural and Biotechnology Policies, pages 269-288 National Bureau of Economic Research, Inc.
    15. Steven Sexton & David Zilberman, 2011. "How Agricultural Biotechnology Boosts Food Supply and Accomodates Biofuels," NBER Working Papers 16699, National Bureau of Economic Research, Inc.
    16. Letort, Elodie & Carpentier, Alain, 2010. "Variable Input Allocation: Why Heterogeneity Matters?," 120th Seminar, September 2-4, 2010, Chania, Crete 109387, European Association of Agricultural Economists.
    17. You, Liangzhi & Wood, Stanley & Wood-Sichra, Ulrike, 2009. "Generating plausible crop distribution maps for Sub-Saharan Africa using a spatially disaggregated data fusion and optimization approach," Agricultural Systems, Elsevier, pages 126-140.
    18. 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.
    19. Groeneveld, Rolf & van Ierland, E. C. & Hejiman, W. J. M., 1999. "A comparison of approaches to spatially explicit modelling of land use/cover change," ERSA conference papers ersa99pa431, European Regional Science Association.

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