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Partial Identification of Economic Mobility: With an Application to the United States

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  • Daniel L. Millimet
  • Hao Li
  • Punarjit Roychowdhury

Abstract

The economic mobility of individuals and households is of fundamental interest. While many measures of economic mobility exist, reliance on transition matrices remains pervasive due to simplicity and ease of interpretation. However, estimation of transition matrices is complicated by the well-acknowledged problem of measurement error in self-reported and even administrative data. Existing methods of addressing measurement error are complex, rely on numerous strong assumptions, and often require data from more than two periods. In this article, we investigate what can be learned about economic mobility as measured via transition matrices while formally accounting for measurement error in a reasonably transparent manner. To do so, we develop a nonparametric partial identification approach to bound transition probabilities under various assumptions on the measurement error and mobility processes. This approach is applied to panel data from the United States to explore short-run mobility before and after the Great Recession.

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  • Daniel L. Millimet & Hao Li & Punarjit Roychowdhury, 2020. "Partial Identification of Economic Mobility: With an Application to the United States," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(4), pages 732-753, October.
    • Handle: RePEc:taf:jnlbes:v:38:y:2020:i:4:p:732-753
    DOI: 10.1080/07350015.2019.1569527
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    Cited by:

    1. Li, Hao & Millimet, Daniel L. & Roychowdhury, Punarjit, 2019. "Measuring Economic Mobility in India Using Noisy Data: A Partial Identification Approach," IZA Discussion Papers 12505, Institute of Labor Economics (IZA).
    2. Ding Liu & Daniel L. Millimet, 2021. "Bounding the joint distribution of disability and employment with misclassification," Health Economics, John Wiley & Sons, Ltd., vol. 30(7), pages 1628-1647, July.
    3. Brantly Callaway & Tong Li & Irina Murtazashvili, 2021. "Nonlinear Approaches to Intergenerational Income Mobility allowing for Measurement Error," Papers 2107.09235, arXiv.org, revised Dec 2021.

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    More about this item

    JEL classification:

    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
    • D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution
    • I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty

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