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Relative distribution analysis in Stata

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  • Ben Jann

Abstract

In this paper I discuss the method of relative distribution analysis and present Stata software implementing various elements of the methodology. The relative distribution is the distribution of the relative ranks that the outcomes from one distribution take on in another distribution. The methodology can be used, for example, to compare the distribution of wages between men and women. Another example would be the analysis of changes in the distribution of earnings over time. Of interest are the relative cumulative distribution (relative CDF), the relative density (relative PDF), as well as summary measures such as the median relative polarization (MRP). The presented software can be used to estimate these quantities and also provides functionality such as location-and-shape decompositions or covariate balancing. Statistical inference is implemented in terms of influence functions and supports estimation for complex samples.

Suggested Citation

  • Ben Jann, 2020. "Relative distribution analysis in Stata," University of Bern Social Sciences Working Papers 37, University of Bern, Department of Social Sciences, revised 21 Jun 2021.
  • Handle: RePEc:bss:wpaper:37
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    References listed on IDEAS

    as
    1. DiNardo, John & Fortin, Nicole M & Lemieux, Thomas, 1996. "Labor Market Institutions and the Distribution of Wages, 1973-1992: A Semiparametric Approach," Econometrica, Econometric Society, vol. 64(5), pages 1001-1044, September.
    2. Sergio Firpo & Nicole M. Fortin & Thomas Lemieux, 2009. "Unconditional Quantile Regressions," Econometrica, Econometric Society, vol. 77(3), pages 953-973, May.
    3. Fernando Rios-Avila, 2020. "Recentered influence functions (RIFs) in Stata: RIF regression and RIF decomposition," Stata Journal, StataCorp LP, vol. 20(1), pages 51-94, March.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    relative distribution; relative density; median relative polarization; divergence; reweighting; influence functions;
    All these keywords.

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C46 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Specific Distributions
    • C87 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Econometric Software

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