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Testing for Misspecification in Binary Response Models with Competing Distributions *
Author(s) -
Chen YiTing
Publication year - 2007
Publication title -
oxford bulletin of economics and statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.131
H-Index - 73
eISSN - 1468-0084
pISSN - 0305-9049
DOI - 10.1111/j.1468-0084.2007.00474.x
Subject(s) - econometrics , probit , logit , monte carlo method , probit model , class (philosophy) , binary number , moment (physics) , econometric model , computer science , statistics , mathematics , artificial intelligence , physics , arithmetic , classical mechanics
In empirical studies, the probit and logit models are often used without checks for their competing distributional specifications. It is also rare for econometric tests to be focused on this issue. Santos Silva [ Journal of Applied Econometrics (2001), Vol. 16, pp. 577–597] is an important recent exception. By using the conditional moment test principle, we discuss a wide class of non‐nested tests that can easily be applied to detect the competing distributions for the binary response models. This class of tests includes the test of Santos Silva (2001) for the same task as a particular example and provides other useful alternatives. We also compare the performance of these tests by a Monte Carlo simulation.