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kmr: A Command to Correct Survey Weights for Unit Nonresponse using Groups’ Response Rates

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This article describes kmr, a Stata command to estimate a micro compliance function using group’s nonresponse rates (2007, Journal of Econometrics 136: 213-235), which can be used to correct survey weights for unit nonresponse. We illustrate the use of kmr with an empirical example using the Current Population Survey and state-level nonresponse rates.

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  • Ercio Munõz & Salvatore Morelli, 2020. "kmr: A Command to Correct Survey Weights for Unit Nonresponse using Groups’ Response Rates," CSEF Working Papers 589, Centre for Studies in Economics and Finance (CSEF), University of Naples, Italy.
    • Handle: RePEc:sef:csefwp:589
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    1. Vladimir Hlasny & Paolo Verme, 2018. "Top Incomes and the Measurement of Inequality in Egypt," The World Bank Economic Review, World Bank, vol. 32(2), pages 428-455.
    2. Bruce D. Meyer & Wallace K. C. Mok & James X. Sullivan, 2015. "Household Surveys in Crisis," Journal of Economic Perspectives, American Economic Association, vol. 29(4), pages 199-226, Fall.
    3. Vladimir Hlasny, 2020. "Nonresponse Bias in Inequality Measurement: Cross‐Country Analysis Using Luxembourg Income Study Surveys," Social Science Quarterly, Southwestern Social Science Association, vol. 101(2), pages 712-731, March.
    4. Korinek, Anton & Mistiaen, Johan A. & Ravallion, Martin, 2007. "An econometric method of correcting for unit nonresponse bias in surveys," Journal of Econometrics, Elsevier, vol. 136(1), pages 213-235, January.
    5. Christopher R. Bollinger & Barry T. Hirsch & Charles M. Hokayem & James P. Ziliak, 2019. "Trouble in the Tails? What We Know about Earnings Nonresponse 30 Years after Lillard, Smith, and Welch," Journal of Political Economy, University of Chicago Press, vol. 127(5), pages 2143-2185.
    6. Anton Korinek & Johan Mistiaen & Martin Ravallion, 2006. "Survey nonresponse and the distribution of income," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 4(1), pages 33-55, April.
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    2. Paolo Brunori & Pedro Salas-Rojo & Paolo Verme, 2022. "Estimating Inequality with Missing Incomes," Working Papers 616, ECINEQ, Society for the Study of Economic Inequality.
    3. Paolo Brunori & Francisco H.G. Ferreira & Pedro Salas-Rojo, "undated". "Inherited inequality: a general framework and an application to South Africa," Working Papers 658, ECINEQ, Society for the Study of Economic Inequality.
    4. Rafael Carranza & Marc Morgan & Brian Nolan, 2023. "Top Income Adjustments and Inequality: An Investigation of the EU‐SILC," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 69(3), pages 725-754, September.
    5. Martin Ravallion, 2022. "Missing Top Income Recipients," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 20(1), pages 205-222, March.
    6. Brunori, Paolo & Ferreira, Francisco H. G. & Salas-Rojo, Pedro, 2024. "Inherited Inequality: A General Framework and a 'Beyond-Averages' Application to South Africa," IZA Discussion Papers 17203, Institute of Labor Economics (IZA).

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