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lgrgtest: Lagrange multiplier test after constrained maximum-likelihood estimation using Stata

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  • Harald Tauchmann

    (FAU Erlangen-Nürnberg)

Abstract

Besides the Wald and the likelihood-ratio test, the Lagrange multiplier test (Rao 1948; Aitchison and Silvey 1958; Silvey, 1959)—also known as the score test—is the third canonical approach to testing hypotheses after maximum likelihood estimation. While the Stata commands test and lrtest implement the former two, real Stata does not have a general command for implementing the latter. This presentation introduces the new community-contributed Stata postestimation command lgrgtest that allows for straightforwardly using Lagrange multiplier test after constrained maximum-likelihood estimation. lgrgtest is intended to be compatible with all Stata estimation commands that use maximum likelihood and allow for the options constraints(), iterate(), and from() and obey Stata's standards for the syntax of estimation commands. lgrgtest can also be used after cnsreg. lgrgtest draws on Stata’s constraint command and the accompanying option constraints(), which only allows for imposing linear restrictions on a model. This results in the limitation of lgrgtest being confined to testing linear constraints only. A (partial) replication of Egger et al. (2011) illustrates the use of lgrgtest in applied empirical work.

Suggested Citation

  • Harald Tauchmann, 2023. "lgrgtest: Lagrange multiplier test after constrained maximum-likelihood estimation using Stata," German Stata Conference 2023 09, Stata Users Group.
    • Handle: RePEc:boc:dsug23:09
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