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A Simple Method for Predicting Distributions by Means of Covariates with Examples from Poverty and Health Economics

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  • Jing Dai
  • Stefan Sperlich
  • Walter Zucchini

Abstract

We present an integration based procedure for predicting the distribution f of an indicator of interest in situations where, in addition to the sample data, one has access to covariates that are available for the entire population. The proposed method, based on similar ideas that have been used in the literature on policy evaluation, provides an alternative to existing simulation and imputation methods. It is very simple to apply, flexible, requires no additional assumptions, and does not involve the inclusion of artificial random terms. It therefore yields reproducible estimates and allows for valid inference. It also provides a tool for future predictions, scenarios and ex-ante impact evaluation. We illustrate our procedure by predicting income distributions in a case with sample selection, and both current and future doctor visits. We find our approach outperforms other commonly used procedures substantially.

Suggested Citation

  • Jing Dai & Stefan Sperlich & Walter Zucchini, 2016. "A Simple Method for Predicting Distributions by Means of Covariates with Examples from Poverty and Health Economics," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 152(I), pages 49-80, March.
  • Handle: RePEc:ses:arsjes:2016-i-3
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    Cited by:

    1. Inés Barbeito & Ricardo Cao & Stefan Sperlich, 2023. "Bandwidth selection for statistical matching and prediction," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 32(1), pages 418-446, March.
    2. José María Sarabia & Faustino Prieto & Vanesa Jordá & Stefan Sperlich, 2020. "A Note on Combining Machine Learning with Statistical Modeling for Financial Data Analysis," Risks, MDPI, vol. 8(2), pages 1-14, April.

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    More about this item

    Keywords

    predicting distributions; missing values; household expenditures; income distribution; health economics; impact evaluation;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics
    • I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty
    • I15 - Health, Education, and Welfare - - Health - - - Health and Economic Development

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