Spatial equilibrium models have been analyzed extensively in public finance, urban and environmental economics. While economists have gained a good understanding of the theoretical properties of these models, there is an apparent need to estimate and test these models. This project is an effort in that direction. Building on work by Epple and Sieg the empirical approach outlined fully specifies and estimates a general equilibrium model. As such, it allows for the potential endogeneity of public good provisions, housing prices, tax rates and the underlying distribution of agents across communities. Parameter estimates obtained by estimation of the structural model can then be used in simulations of alternative policy regimes. The research has been organized to meet the following objectives: The project provides a methodological contribution to research in public finance by developing a new empirical approach for analyzing the impact of locally provided public goods and other locational amenities on residential decisions of households in system of jurisdictions. It develops a class of spatial equilibrium estimators which allow for the endogeneity of community characteristics. This research provides an analytical framework for applied policy analysis. Based on the estimation results, one can simulate the benefits of policy interventions like improvement of educational achievements in local schools, crime prevention, improvements of air and water quality. Benefit measures are behaviorally consistent since they account for general equilibrium effects. This approach provides a unified framework for measuring the impact of government policy on the socio economic composition of communities and neighborhoods. It can therefore be used to evaluate the distributional effects of these policies. By gathering a unique data set which combines available information from different sources like the census, government agencies and commercially available data on housing transactions, this approach avoids some of the data problems which have plagued previous research.

Agency
National Science Foundation (NSF)
Institute
Division of Social and Economic Sciences (SES)
Application #
9808951
Program Officer
Daniel H. Newlon
Project Start
Project End
Budget Start
1998-11-15
Budget End
2001-10-31
Support Year
Fiscal Year
1998
Total Cost
$154,739
Indirect Cost
Name
Duke University
Department
Type
DUNS #
City
Durham
State
NC
Country
United States
Zip Code
27705