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Recovering Income Distribution in the Presence of Interval-Censored Data

Author

Listed:
  • Canavire Bacarreza, Gustavo J.

    (World Bank)

  • Rios-Avila, Fernando

    (Levy Economics Institute)

  • Sacco-Capurro, Flavia

    (World Bank)

Abstract

This paper proposes a method to analyze interval-censored data, using multiple imputation based on a heteroskedastic interval regression approach. The proposed model aims to obtain a synthetic data set that can be used for standard analysis, including standard linear regression, quantile regression, or poverty and inequality estimation. The paper presents two applications to show the performance of the method. First, it runs a Monte Carlo simulation to show the method's performance under the assumption of multiplicative heteroskedasticity, with and without conditional normality. Second, it uses the proposed methodology to analyze labor income data in Grenada for 2013–20, where the salary data are interval-censored according to the salary intervals prespecified in the survey questionnaire. The results obtained are consistent across both exercises.

Suggested Citation

  • Canavire Bacarreza, Gustavo J. & Rios-Avila, Fernando & Sacco-Capurro, Flavia, 2023. "Recovering Income Distribution in the Presence of Interval-Censored Data," IZA Discussion Papers 15921, Institute of Labor Economics (IZA).
    • Handle: RePEc:iza:izadps:dp15921
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    More about this item

    Keywords

    heteroskedastic interval regression; Monte Carlo simulation; interval-censored data; wages;
    All these keywords.

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C34 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Truncated and Censored Models; Switching Regression Models
    • J3 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs

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