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A BAYESIAN APPROACH TO DISCRIMINATION AMONG ECONOMIC MODELS *
Author(s) -
Wiginton John C.
Publication year - 1974
Publication title -
decision sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.238
H-Index - 108
eISSN - 1540-5915
pISSN - 0011-7315
DOI - 10.1111/j.1540-5915.1974.tb00606.x
Subject(s) - bayesian probability , econometrics , aggregate (composite) , computer science , representation (politics) , process (computing) , mathematical economics , mathematics , artificial intelligence , materials science , politics , political science , law , composite material , operating system
Frequently, alternative theories are proposed as relevant models for an economic process. Which alternative is a relatively better representation is a question of fact, but empirical methods of resolving the issue have not been compelling. This study developes a technique for discrimination from Bayesian statistical theory. This technique can analyze an arbitrary number of alternatives simultaneously, and each alternative can be characterized by distribution theory appropriate to its structure. An example, the aggregate consumption function, is considered, and each alternative is characterized by the Normal regression process. The results may only be regarded as suggestive, as the parameterization of the structure may be incomplete on that assumption.