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Estimating Equilibrium Models of Local Jurisdictions
Abstract
Research over the past several years has led to the development of models characterizing equilibrium in a system of local jurisdictions. An important insight from these models is that plausible single‐crossing assumptions about preferences generate strong predictions about the equilibrium distribution of households across communities. To date, these predictions have not subjected to formal empirical tests. The purpose of this paper is to provide an integrated approach for testing predictions from this class of models. We first test conditions for locational equilibrium implied by these models. In particular, we test predictions about the distribution of households by income across communities. We then test the models' predictions about the relationships among loclational equilibrium conditions, housing markets, and housing prices. By drawing inferences from a structural general equilibrium model, the paper offers a unified treatment of theory and empirical testing.
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Citations
Cited by
Identification and estimation of hedonic models
Ekeland, I., Heckman, J. J., & Nesheim, L. (2004) · Journal of Political Economy · doi:10.1086/379947 · Cited by 380
Estimating Housing Demand With an Application to Explaining Racial Segregation in Cities
Bajari, P., & Kahn, M. E. (2005) · Journal of Business & Economic Statistics · doi:10.1198/073500104000000334 · Cited by 301
Ferreira, F. (2010) · Journal of Public Economics · doi:10.1016/j.jpubeco.2010.04.003 · Cited by 148
Metadata
- Authors
- Epple, D., & Sieg, H.
- Venue
- Journal of Political Economy
- Publisher
- University of Chicago Press
- Published
- 1999-08
- Volume
- 107
- Issue
- 4
- Pages
- 645-681
- ISSN
- 0022-3808 (ISSN-L)
- 1537-534X
- OpenAlex
- W2025744719
- Cited by
- 404
- References
- 0
- FWCI
- 12.20
- Type
- journal article
- Language
- en
- Open access
- closed
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- Epple, D., & Sieg, H. (1999). Estimating Equilibrium Models of Local Jurisdictions. Journal of Political Economy. https://doi.org/10.1086/250074
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.