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Constructing and validating a best-fit economic well-being index for urban U.S. counties: a Tiebout model approach

Author

Listed:
  • Justin Ehrlich

    (Syracuse University)

  • Simon Medcalfe

    (Augusta University)

  • Shane Sanders

    (Syracuse University)

Abstract

This study builds on the history of economic well-being (EWB) index construction to develop such an index for urban U.S. counties (population > 62,437). Unlike previous studies, we rely on external validation of economic well-being to construct a best-fit index, where our external validation approach follows the Tiebout Hypothesis. We estimate a best-fit, linear regression-based index, in which lagged features of economic well-being are weighted based on ability to explain subsequent county population change. Compared to an arbitrarily equally-weighted model using a composite index a model using lagged weighted EWB individual variables provide greater transparency while also explaining substantially more variation in population change across urban counties (19.9% vs. 15.7%).

Suggested Citation

  • Justin Ehrlich & Simon Medcalfe & Shane Sanders, 2024. "Constructing and validating a best-fit economic well-being index for urban U.S. counties: a Tiebout model approach," Public Choice, Springer, vol. 199(1), pages 45-63, April.
    • Handle: RePEc:kap:pubcho:v:199:y:2024:i:1:d:10.1007_s11127-023-01055-y
    DOI: 10.1007/s11127-023-01055-y
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