Influence functions for linear regression (with an application to regression adjustment)

Ben Jann

No 32, University of Bern Social Sciences Working Papers from University of Bern, Department of Social Sciences

Abstract: Influence functions are useful, for example, because they provide an easy and flexible way to estimate standard errors. This paper contains a brief overview of influence functions in the context of linear regression and illustrates how their empirical counterparts can be computed in Stata, both for unweighted data and for weighted data. Influence functions for regression-adjustment estimators of average treatment effects are also covered.

Keywords: influence function; sampling variance; sampling weights; standard error; linear regression; mean difference; regression adjustment; average treatment effect; causal inference (search for similar items in EconPapers)
JEL-codes: C12 C13 (search for similar items in EconPapers)
Pages: 26 pages
Date: 2019-03-27, Revised 2019-03-30
New Economics Papers: this item is included in nep-ecm
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Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:bss:wpaper:32

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