Testing normality in bivariate probit models : a simple artificial regression based LM test

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Title: Testing normality in bivariate probit models : a simple artificial regression based LM test
Authors: Murphy, Anthony
Permanent link: http://hdl.handle.net/10197/1768
Date: Dec-1994
Abstract: A simple and convenient LM test of normality in the bivariate probit model is derived. The alternative hypothesis is based on a form of truncated Gram Charlier Type series. The LM test may be calculated as an artificial regression. However, the proposed artificial regression does not use the outer product gradient form. Thus it is likely to perform reasonably well in small samples.
Type of material: Working Paper
Publisher: University College Dublin. School of Economics
Series/Report no.: UCD Centre for Economic Research Working Paper Series; WP94/27
Keywords: Bivariate probitNormalityTruncated Gram Charlier seriesLM testArtificial regression
Subject LCSH: Econometrics--Mathematical models
Regression analysis
Language: en
Status of Item: Not peer reviewed
Appears in Collections:Economics Working Papers & Policy Papers

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