An Analysis of U.S. Domestic Migration via Subset-stable Measures of Administrative Data

74 Pages Posted: 30 Jun 2020 Last revised: 22 Sep 2020

See all articles by Ben Klemens

Ben Klemens

U.S. Department of the Treasury, Office of Tax Analysis (OTA)

Date Written: June 3, 2020

Abstract

How does the likelihood of moving across U.S. regions vary with changes in household characteristics, and how does the risk of a change in status vary given a move? Statistics aimed at these questions are calculated for households who earned formal market income in the U.S., 2001-2015, totaling about 1.7 billion observations with 82.7 million long-distance moves, and covering statuses such as income, education and employment status, local and federal tax payments, housing tenure, number of children, retirement or marital status. The key theoretical result of this article shows that the Cochran-Mantel-Haenszel statistic is the unique aggregate risk ratio within a broad class that has the "subset stability" property: If a statistic has value s₁ for one subset and s₂ for another, then the statistic for the union of the two sets is between s₁ and s₂. A sequence of pseudo-experiments generate a wealth of descriptive statistics for the relationship between moving and a broad range of household characteristics, for the full population and salient subsets, with some focus on the characteristics of the 44.2% of movers who see negative income returns relative to the counterfactual of staying.

Keywords: migration, administrative records, demographic analysis, taxrevenue, risk ratios, returns to education, retirement, tax policy

JEL Classification: J61, C14, H24, D19

Suggested Citation

Klemens, Ben, An Analysis of U.S. Domestic Migration via Subset-stable Measures of Administrative Data (June 3, 2020). Available at SSRN: https://ssrn.com/abstract=3197362 or http://dx.doi.org/10.2139/ssrn.3197362

Ben Klemens (Contact Author)

U.S. Department of the Treasury, Office of Tax Analysis (OTA) ( email )

1500 Pennsylvania Ave., N.W.
Washington, DC 22203
United States

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