Abstract
A new information-based approach for estimating systems of many equations with nonnegativity constraints is presented. This approach, called generalized maximum entropy (GME), is more practical and efficient than traditional maximum-likelihood methods. The GME method is used to estimate an almost ideal demand system for five types of meat using cross-sectional data from Mexico, where most households did not buy at least one type of meat during the survey week. The system of demands is shown to vary across demographic groups.
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© 2001 President and Fellows of Harvard College and the Massachusetts Institute of Technology
2001
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