Testing for omitted variables

Jeroen Weesie ()
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Jeroen Weesie: Utrecht University

No 2.2, North American Stata Users' Group Meetings 2001 from Stata Users Group

Abstract: Testing for omitted variables should play an important part in specification analyses of statistical "linear form" models. Such omissions may comprise terms in variables that were included themselves (e.g., a quadratic term, or a categorical specification instead of a metric one), interactions between variables in the model, and variables that were left out to begin with. Re-estimating models with additional variables and performing (for example) likelihood ratio tests is time-consuming. Score tests provide an attractive alternative, since the tests can be computed using only results from the model already estimated. We present a Stata command for performing score testing after most Stata estimation commands (e.g., logit, heckman, streg etc.). This command supports multiple-equation models, clustered observations, and adjusted p-values for simultaneous testing.

Date: 2001-01-15
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http://fmwww.bc.edu/RePEc/nasug2001/Boston_testomit.pdf (application/pdf)

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Persistent link: https://EconPapers.repec.org/RePEc:boc:asug01:2.2

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