ESTIMATION AND HYPOTHESIS TESTING FOR NONPARAMETRIC HEDONIC HOUSE PRICE FUNCTIONS |
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| Authors: | Daniel P. McMillen Christian L. Redfearn |
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| Affiliation: | 1. Institute of Government and Public Affairs, Department of Economics, University of Illinois at Urbana‐Champaign, 1007 W. Nevada St., Urbana, IL 61801. E‐mail: mcmillen@illinois.edu;2. School of Policy, Planning and Development, University of Southern California, Los Angeles, CA 90089‐0626. E‐mail: redfearn@usc.edu |
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| Abstract: | ABSTRACT In contrast to the rigid structure of standard parametric hedonic analysis, nonparametric estimators control for misspecified spatial effects while using highly flexible functional forms. Despite these advantages, nonparametric procedures are still not used extensively for spatial data analysis due to perceived difficulties associated with estimation and hypothesis testing. We demonstrate that nonparametric estimation is feasible for large datasets with many independent variables, offering statistical tests of individual covariates and tests of model specification. We show that fixed parameterization of distance to the nearest rapid transit line is a misspecification and that pricing of access to this amenity varies across neighborhoods within Chicago. |
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