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Testing for omitted variables

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  • Jeroen Weesie

    (Utrecht University)

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.

Suggested Citation

  • Jeroen Weesie, 2001. "Testing for omitted variables," North American Stata Users' Group Meetings 2001 2.2, Stata Users Group.
  • Handle: RePEc:boc:asug01:2.2
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    File URL: http://fmwww.bc.edu/RePEc/nasug2001/Boston_testomit.pdf
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