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Measurement error and its impact on estimates of income dynamics

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  • Nayoung Lee

    (University of Cincinnati)

Abstract

This paper examines whether reported income generates biases for studies on economic mobility and poverty dynamics. Using a linear measurement error model capturing mean-reverting measurement error, this study finds that substantial classical measurement error exists in reported data, leading to a bias toward zero in the estimate of income dynamics. Time-invariant non-classical measurement error and unobserved heterogeneity offset the effect of classical measurement error. This study also identifies the standard deviation of the measurement error, which is estimated to be about 70% of that of the equation error in the income model, suggesting that random measurement error is substantial.

Suggested Citation

  • Nayoung Lee, 2022. "Measurement error and its impact on estimates of income dynamics," Empirical Economics, Springer, vol. 63(5), pages 2539-2550, November.
    • Handle: RePEc:spr:empeco:v:63:y:2022:i:5:d:10.1007_s00181-022-02218-4
    DOI: 10.1007/s00181-022-02218-4
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    More about this item

    Keywords

    Measurement error; Non-classical measurement error; Economic mobility; Income dynamics;
    All these keywords.

    JEL classification:

    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty
    • O15 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Economic Development: Human Resources; Human Development; Income Distribution; Migration

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