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Artificial regression based mis-specification tests for discrete choice models
Author(s)
Date Issued
1994-07
Date Available
2010-01-13T17:08:13Z
Abstract
LM tests for omitted variables, neglected heteroscedasticity and other mis-specifications in general discrete choice models may be simply and conveniently calculated using an artificial regression. This artificial regression approach is likely to have better small sample properties than the more common outer product gradient (OPG) form of LM test.
External Notes
A hard copy is available in UCD Library at GEN 330.08 IR/UNI
Type of Material
Working Paper
Publisher
University College Dublin. School of Economics
Series
UCD Centre for Economic Research Working Paper Series
WP94/16
Classification
C35
Subject – LCSH
Regression analysis
Econometrics--Mathematical models
Language
English
Status of Item
Not peer reviewed
This item is made available under a Creative Commons License
File(s)
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Name
wp94_16.pdf
Size
235.49 KB
Format
Adobe PDF
Checksum (MD5)
a002dbfd4444cf552c7f05741bd897a0
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