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POSITION STATEMENT
Sorting of households by income and demographic characteristics is commonplace--across neighborhoods, primary and secondary schools, municipalities, colleges and universities. If peer effects and neighborhood effects are present, sorting can have consequences for individual behavior, educational attainment, career choices, and other private and social outcomes (Benabou, 1996; Durlauf, 1996; Epple and Romano, 1998).
Models of individual choice frequently imply sorting. If high-income households are willing to pay a higher housing price premium than poor households to obtain access to neighborhoods that are of higher quality, then sorting will emerge (Ellickson, 1973). Moreover, the sorting will be such that the ordering of incomes and housing prices across neighborhoods will follow the same order as neighborhood qualities. If qualities are endogenous and determined by collective choice of local public expenditures within municipalities, then the allocation of population across locations determines and is determined by expenditure on local public services (Westhoff, 1977; Epple, Filimon, and Romer, 1984; Epple and Romer, 1991; Fernandez and Rogerson, 1996; Nechyba, 2000).
Peer and neighborhood effects provide powerful forces for sorting (Benabou, 1993). This is the case even if neighborhoods are physically identical and expenditures on local public services do not vary. For example, suppose that high-income households are willing to pay a higher housing price premium than the poor to obtain access to high quality schools. This creates a force for sorting, with higher income households choosing neighborhoods with higher housing prices and higher quality schools. School quality differentials will sustain and be sustained by such sorting if parental involvement in schools and children's peer "qualities" (motivation to do homework, refrain from disruptive behavior, etc.) tend to increase with income (Epple and Romano, 2000). Of course, income is only one of many characteristics that affect household's willingness to pay for education, local public services and neighborhood quality (Epple and Platt, 1993). Similarly, when peer and neighborhood effects are present, many characteristics of a household may be associated with their actual or perceived desirability as neighbors or school peers.
In considering the allocation of households across neighborhoods and communities in a metropolitan area, spatial proximity can be characterized in at least three ways. Geographic proximity is the most obvious, and it is particularly relevant if there are spillovers across locations. Proximity of communities may also be characterized by the extent to which their bundles of services, amenities, and peer qualities are similar. Finally, proximity of communities may be characterized by the similarity of the characteristics of their residents. The second and third types of proximity are illustrated by the example above in which school quality is determined by student peer quality. Equilibrium has the property that ordering of communities by student peer quality is the same as the ordering by household income. Thus, two communities that are adjacent in peer quality are also adjacent in income, even though they need not be physically adjacent. These three ways of thinking about proximity of communities can also be relevant in thinking about proximity of schools or of colleges and universities (Epple, Romano and Sieg, 1999).
From an empirical perspective, equilibrium models of community choice impose consistency requirements between individual choices and the aggregate distribution of households across communities and schools, or of students across colleges and universities. These consistency requirements provide a valuable mechanism for assessing the extent to which a particular model of individual choice predicts allocations of households across locations that are consistent with the observed distribution of household types across locations (Epple and Sieg, 1999; Epple, Romano and Sieg, 1999; Epple, Romer and Sieg, forthcoming). An empirical analysis can simultaneously investigate aspects of individual choice as well as aggregate outcomes. For example, micro data can be used to study the college attended by an individual with a given income and SAT score and the financial aid awarded by the institution that admits and attracts the student. Aggregate data can be used to investigate consistency of the model of individual choice and college admission policy with aggregate outcomes, such as the distribution of SAT scores in each college and the distribution of SAT scores across colleges.
Developing equilibrium models of population sorting and developing and implementing methods of estimating those models is a promising approach for improving understanding of the stratification of population across communities, schools, and colleges and universities. Such models also have the potential to enhance understanding of peer and neighborhood effects, and the quality of education and local public services received by households as a function of their incomes and demographic characteristics. These models can also serve as a mechanism to provide a comprehensive evaluation of policy changes (Sieg, Smith, Bahzhaf, Walsh, 2000 ).
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REFERENCES
Benabou, Roland, "Equity and Efficiency in Human Capital Investment: The Local Connection," Review of Economic Studies, 63(2), April 1996, 237-264.
Benabou, Roland, "Heterogeneity, Stratification, and Growth: Macroeconomic Implications of Community Structure and School Finance," American Economic Review, 86(3), June 1996, 584-609.
Durlauf, Steven N., "A Theory of Persistent Income Inequality," Journal of Economic Growth, 1, March 1996, 75-93.
Ellickson, Bryan, "Jurisdictional Fragmentation and Residential Choice," American Economic Review, 61, May 1971, 334-339.
Epple, Dennis, Radu Filimon, and Thomas Romer, "Equilibrium Among Local Jurisdictions: Toward an Integrated Treatment of Voting and Residential Choice," Journal of Public Economics, 24, August 1984, 281-308.
Epple, Dennis and Glenn J. Platt, "Equilibrium and Local Redistribution in an Urban Economy when Households Differ by Preferences and Incomes," Journal of Urban Economics, 43, January 1993, 23-51.
Epple, Dennis and Richard Romano, "Competition between Private and Public Schools: Vouchers and Peer Group Effects," American Economic Review, 88(1), March 1998, 33-62.
Epple, Dennis and Richard Romano, "Neighborhood Schools, Choice, and the Distribution of Educational Benefits," National Bureau of Economic Research, Working Paper 7850, August 2000.
Epple, Dennis, Richard Romano and Holger Sieg, "Peer Effects, Financial Aid, and Selection of Students into Colleges and Universities," Working Paper, 1999.
Epple, Dennis and Thomas Romer, "Mobility and Redistribution," Journal of Political Economy, 99, August 1991, 828-858.
Epple, Dennis, Thomas Romer and Holger Sieg, "Interjurisdictional Sorting and Majority Rule: An Empirical Analysis," Econometrica, forthcoming.
Epple, Dennis and Holger Sieg, "Estimating Equilibrium Models of Local Jurisdictions," Journal of Political Economy, 107(4), August 1999, 645-681.
Fernandez, Raquel and Richard Rogerson, "Income Distribution, Communities, and the Quality of Public Education," Quarterly Journal of Economics, 111(1), February 1996, 135-164.
Nechyba, Thomas, "Mobility Targeting and Private School Vouchers," American Economic Review, 90(1), March 2000, 130-146.
Sieg, Holger, V. Kerry Smith, Spencer Banzhaf, and Randy Walsh, "Estimating the General Equilibrium Benefits of Large Policy Changes: The Clean Air Act," National Bureau of Economic Research Working Paper 7744, June 2000.
Westhoff, Frank, "Existence of Equilibrium in Economies with a Local Public Good," Journal of Economic Theory, 14, February 1977, 84-112.
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