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Recovering Output‐Specific Inputs from Aggregate Input Data: A Generalized Cross‐Entropy Approach
Author(s) -
Lence Sergio H.,
Miller Douglas J.
Publication year - 1998
Publication title -
american journal of agricultural economics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.949
H-Index - 111
eISSN - 1467-8276
pISSN - 0002-9092
DOI - 10.2307/1244069
Subject(s) - monte carlo method , aggregate (composite) , maximization , entropy (arrow of time) , computer science , econometrics , profit maximization , profit (economics) , aggregate data , mathematical optimization , economics , microeconomics , mathematics , statistics , materials science , physics , quantum mechanics , composite material
For 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.