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Misspecification Testing: A Comprehensive Approach
Author(s) -
McGuirk Anya M.,
Driscoll Paul,
Alwang Jeffrey
Publication year - 1993
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 - 10.2307/1243992
Subject(s) - econometrics , monte carlo method , computer science , set (abstract data type) , regression , joint (building) , statistics , mathematics , engineering , architectural engineering , programming language
Misspecification tests of individual assumptions underlying regression models often lead to erroneous conclusions regarding source of misspecification. Monte Carlo experiments demonstrate that a comprehensive set of individual and joint tests reduces the likelihood of such conclusions. A practical testing strategy is proposed and suggestions made regarding its implementation.