Artificial regression based mis-specification tests for discrete choice models
|Title:||Artificial regression based mis-specification tests for discrete choice models||Authors:||Murphy, Anthony||Permanent link:||http://hdl.handle.net/10197/1760||Date:||Jul-1994||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.||Type of material:||Working Paper||Publisher:||University College Dublin. School of Economics||Series/Report no.:||UCD Centre for Economic Research Working Paper Series; WP94/16||Keywords:||Discrete choice; LM mis-specification tests; Artificial regressions||Subject LCSH:||Regression analysis
|Language:||en||Status of Item:||Not peer reviewed|
|Appears in Collections:||Economics Working Papers & Policy Papers|
Show full item record
This item is available under the Attribution-NonCommercial-NoDerivs 3.0 Ireland. No item may be reproduced for commercial purposes. For other possible restrictions on use please refer to the publisher's URL where this is made available, or to notes contained in the item itself. Other terms may apply.