Recovering Output-Specific Inputs from Aggregate Input Data: A Generalized Cross Entropy Approach
AbstractFor multiproduct firms, data on aggregate input usage are typically available but data on activity-specific inputs are not. The present study proposes a generalized cross-entropy approach to estimate activity-specific input allocations that are consistent with the aggregate information. The proposed method does not require behavioral assumptions (e.g., profit maximization) but does accommodate behavioral restrictions as well as nonsample information about the plausible factor shares across enterprises. Monte Carlo experiments using simulated data for multifactor-multiproduct firms are used to evaluate the performance of the proposed method.
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Bibliographic InfoPaper provided by Iowa State University, Department of Economics in its series Staff General Research Papers with number 1305.
Date of creation: 01 Nov 1998
Date of revision:
Publication status: Published in American Journal of Agricultural Economics, November 1998, vol. 80 no. 4, pp. 852-867
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Postal: Iowa State University, Dept. of Economics, 260 Heady Hall, Ames, IA 50011-1070
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Web page: http://www.econ.iastate.edu
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- Sergio H. Lence & Douglas J. Miller, 1998. "Recovering Output-Specific Inputs from Aggregate Input Data: A Generalized Cross-Entropy Approach," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 80(4), pages 852-867.
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