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Influence functions at work

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  • Philippe Van Kerm

    (Luxembourg Institute of Socio-Economic Research (LISER), Luxembourg)

Abstract

This presentation illustrates three practical uses of influence functions (IF) in Stata. First (and most obviously), inspection of IFs helps detecting influential sample observations. I show how this can be done in practice and how similar this is to examining jackknife replicates. Second, IFs make it easy to calculate (asymptotic) standard errors and confidence intervals for a wide range of statistics. I illustrate how this can be done in Stata with the total command so as to account for complex survey design easily. Third and finally, application of ‘recentered influence function (RIF) regression’ has recently been advocated to approximate the impact of covariates on (unconditional) distribution statistics. I demonstrate this use of IFs in Stata and discuss interpretation of RIF regression model coefficients. Empirical applications are to income distribution analysis. Several user-written utilities and commands are illustrated along the way.

Suggested Citation

  • Philippe Van Kerm, 2015. "Influence functions at work," United Kingdom Stata Users' Group Meetings 2015 11, Stata Users Group.
    • Handle: RePEc:boc:usug15:11
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    File URL: http://repec.org/usug2015/vankerm_uksug15.pdf
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    Cited by:

    1. Stefan Schneck, 2018. "The Effect of Self-Employment on Income Inequality," SOEPpapers on Multidisciplinary Panel Data Research 999, DIW Berlin, The German Socio-Economic Panel (SOEP).
    2. Stefan Schneck, 2020. "Self-employment as a source of income inequality," Eurasian Business Review, Springer;Eurasia Business and Economics Society, vol. 10(1), pages 45-64, March.

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