Jeffrey E. Zabel

The Impact of School Characteristics on House Prices: Chicago 1987-1991

Do estimates of the prices attached to different school characteristics depend on the characteristics utilised in the hedonic analysis or on the decision to use district-level or school level measures? To answer this question, we merge information from the American Housing Survey and the Illinois School Report Cards and assign to each house the school-level data for the closest school. In both district- and school-level analyses, we find that per-pupil expenditures and test scores have similar impacts on house values. However, unlike the district-level results, the school-level results imply that individuals respond to the racial composition of schools when choosing a home.

Interactions, neighborhood selection and housing demand

This paper contributes to the growing literature that identifies and measures the impact of social context on individual economic behavior. We develop a model of housing demand with neighborhood e®ects and neighborhood choice. Modelling neighborhood choice is of fundamental importance in estimating and understanding endogenous and exogenous neighborhood effects. That is, to obtain unbiased estimates of neighborhood effects, it is necessary to control for non-random sorting into neighborhoods. Estimation of the model exploits a unique data set of household data that has been augmented with contextual information at two di®erent levels (“scales”) of aggregation. One is at the neighborhood cluster level, of about ten neighbors, with the data coming from a special sample of the American Housing Survey. A second level is the census tract to which these dwelling units belong. Tract-level data are available in the Summary Tape Files of the decennial Census data. We merge these two data sets by gaining access to confidential data of the U.S. Bureau of the Census. We overcome some limitations of these data by implementing some significant methodological advances in estimating discrete choice models. Our results for the neighborhood choice model indicate that individuals prefer to live near others like themselves. This can perpetuate income inequality since those with the best opportunities at economic success will cluster together. The results for the housing demand equation are similar to those in our earlier work [Ioannides and Zabel (2000] where we find evidence of significant endogenous and contextual neighborhood effects. (This abstract was borrowed from another version of this item.)

Estimating the Economic Benefits of Cleaning Up Superfund Sites: The Case of Woburn, Massachusetts

Superfund was established in 1980 to deal with closed and abandoned hazardous waste sites. Given the large amounts of money being spent on cleanups of Superfund sites, one might hope that the money is being spent in a cost-effective manner, but there is little evidence that the estimated benefits from cleanup affect the cleanup decision. We apply the hedonic method to house prices to estimate the individual willingness to pay (WTP) to clean up a Superfund site. We then show how the individual WTP can be used to calculate the total benefits from cleaning up the site so that a cost-benefit analysis of Superfund cleanup can be undertaken. We apply our technique to the two Superfund sites in Woburn, Massachusetts. We find that the benefits from cleaning up these sites are in the range of

Estimating fixed and random effects models with selectivity

72 million to

Amenity-Based Housing Affordability Indexes

122 million (1992 dollars). It is likely that these benefits are greater than the present value of the estimated costs of cleaning up these sites. Thus it appears that the cleanup of the Woburn Superfund sites results in positive net benefits to society.

Evaluating the Usefulness of the American Housing Survey for Creating House Price Indices

Abstract This paper develops an alternative estimator to the one for the fixed effects model with selectivity that is presented in Verbeek (1990). The random effect in the selectivity equation is specified as a function of the means of time varying variables. This helps to alleviate the bias caused by the correlation between the random effect and the regressors in the selectivity equation.

The Effects of Critical Habitat Designation on Housing Supply: An Analysis of California Housing Construction Activity

The recent slump notwithstanding, substantial increases in house prices in many parts of the United States have served to highlight housing affordability for moderate-income households, especially in high-cost, supply-constrained coastal cities such as Boston. In this article, we develop a new measure of area affordability that characterizes the supply of housing that is affordable to different households in different locations of a metropolitan region. Key to our approach is the explicit recognition that the price/rent of a dwelling is affected by its location. Hence, we develop an affordability methodology that accounts for job accessibility, school quality and safety. This allows us to produce a menu of town-level indexes of adjusted housing affordability. The adjustments are based on obtaining implicit prices of these amenities from a hedonic price equation. We thus use data from a wide variety of sources to rank 141 towns in the greater Boston metropolitan area based on their adjusted affordability. Taking households earning 80% of area median income as an example, we find that consideration of town-level amenities leads to major changes relative to a typical assessment of affordability.

Controlling for Quality in House Price Indices

The American Housing Survey (AHS) is a valuable source of information on houses and occupants over time. The AHS has several advantages over sales data for use in the creation of price indices: it is readily available, has frequent observations over time and space, has data from the late 1970s through the mid-1990s, includes houses that do not sell, as well as those that do, and has information on the occupants. The drawbacks include: a time lag between the interview and the release of the data, data suppression issues, owner-stated house values, and a lack of neighborhood information. In this study, we use the metropolitan version of the AHS, which has been supplemented with the original survey data as well as Census tract data for three cities over 14 years to examine whether the AHS can be used to create indices. Indices are estimated using hedonic, repeat valuation, and hybrid techniques, overcoming some of the problems inherent in the estimation of indices. We find that the data-suppression issues and the owner-stated house values are not problematic. The biggest drawback of the AHS is its lack of objective information on neighborhood quality.

The path not taken: How does school organization affect eighth-grade achievement?

Under the Endangered Species Act, the U.S. Fish and Wildlife Service is required to designate critical habitat for listed species. Designation could result in modification to or delay of residential development projects within habitat boundaries, generating concern over potential housing market impacts. This paper draws upon a large dataset of municipal-level (FIPS) building permit issuances and critical habitat designations in California over a 13-year period to identify changes in the spatial and temporal pattern of development activity associated with critical habitat designation. We find that the proposal of critical habitat results in a 20.5% decrease in the annual supply of housing permits in the short-run and a 32.6% decrease in the long-run. Further, the percent of the FIPS area that is designated as critical habitat significantly affects the number of permits issued. We also find that the impact varies across the two periods in which critical habitat is designated and by the number of years relative to when critical habitat was first proposed.

Spending, Size, and Grade Span in K-8 Schools.

Given the importance of house prices it is not surprising that house price indices are used for many purposes. One of the factors that differentiates these indices is the house price determinants (such as structural characteristics and neighborhood quality) that are accounted for—that is, held constant. Indices are usually generated from house price regressions. It is shown that, regardless of the desired level of accounting, it is necessary to control for all significant determinants of house prices in these regressions to obtain unbiased estimates of the growth in house prices. An empirical example shows that not controlling for neighborhood quality can lead to substantial biases in estimates of house price appreciation rates even if the index does not account for this factor.