1. PROJECTING THE BENEFITS OF BROWNFIELD REDEVELOPMENT Radcliffe G. Edmonds, Jr. (redmond@siue.edu) Donald Elliott (delliot@siue.edu) Stanford Levin (slevin@siue.edu) Southern Illinois University Edwardsville Brownfields 2004: Gateway to Revitalization St. Louis, MO September, 2004

2. Overview Research sponsored by grant from EPA to St. Louis Regional Chamber and Growth Association “Brownfields”—unutilized or underutilized parcels that are (or are thought to be) contaminated to such an extent that private- sector redevelopment may not be profitable without government assistance.

3. Local impact of brownfield redevelopment –New jobs and income –Appreciation of neighboring property Additional revenue for local government Environmental justice?

4. Research Questions How can one estimate the impact of proposed brownfield redevelopment on a local community? –Policy use by local decision-makers: evaluate proposed projects and garner public support. –Robust, transportable methodology Will the redevelopment of brownfields ameliorate environmental justice by benefiting lower income, minority residents who live near brownfield sites?

5. Literature Hedonic studies of disamenities: Dale, Murdoch, Thayer, and Waddell. Land Economics (1999) –Summarize literature demonstrating adverse effect of negative environmental effects on neighboring property values. –Use pooled cross-section-time series hedonic analysis to show that remediation and redevelopment of former lead smelter in Dallas increased neighboring property values.

6. Environmental justice –1990s literature on “environmental racism” and “environmental justice” Correlation between concentrations of low-income and racial minorities and loci of contaminated environmental sites Policy implication: remediating and redeveloping toxic sites will benefit low-income and/or minority residents

7. –Challenge based on housing market filtering Been. Yale Law Journal (1994): current environmental disparities result of housing market dynamics, not discriminatory siting of polluting industries Lambert and Boerner. Yale Journal on Regulation (1997): in-migration of poor and minority households accounts for current environmental disparities in St. Louis industrial and waste facilities

8. METHODOLOGY PRIMARY EFFECTS  IMPLAN model tailored to regions of zip-code clusters  Specific redevelopment project chosen for exports from region  Estimate dollar value of employment and income effects of project for two phases --Reclamation and reconstruction --Subsequent ongoing operation

9. METHODOLOGY SECONDARY EFFECTS  Hedonic regression for residential property market  Estimate the effect of each dimension of a property on its sales price  Dimensions include --those of the property itself --those of the neighborhood, with no variation in most public goods --proximity to disamenities, e.g., brownfields: adds a spatial character

10. HEDONIC REGRESSION WITH SPATIAL DIMENSIONS Single brownfield site: --measure distance from each sale to site to use as a regressor --omission of distances to other relevant sites creates bias

11. HEDONIC REGRESSION WITH SPATIAL DIMENSIONS Multiple brownfield sites: --measure distance from each sale to each site, creating multiple regressors many more regressors—possible d.f. problem severe multicollinearity from masking --measure distance from each sale to nearest site of each type

12. DATA SOURCES  MLS for residential properties  Census block-group data for neighborhood  Brownfield data generally unavailable --Anecdotal approach with local experts --Historical land-use data for potential sites

13. SAMPLE-LIMITING PROBLEMS  Availability of arm’s-length sales  Completeness and comparability of MLS data  Multicollinearity limits regions & sites with multiple sites

14. SPECIFICATION  Functional form: linear vs. non-linear  Distance variable: inverse  Choice of region and included sites or clusters of sites  Site-specific or citywide average estimation

15. ESTIMATION IN SOUTH ST. LOUIS  Included sites for given region: clusters of pair-wise correlations => 25 of 75 sites  Correction for heteroskedasticity  9 of 25 significantly negative

16. RESULTS FROM SITE-SPECIFIC MODEL IN SOUTH ST. LOUIS  Effect of disamenity declines with distance  Estimate of aggregate effect  Distribution of benefits of a specific redevelopment project

17. RESULTS FROM MODEL WITH TYPE AND AGE OF NEAREST SITE  Only average estimate of redevelopment benefits by type of potential brownfield  Provides ranking of perceived disamenity of different types of site  Shows logical decline of perceived disamenity with age of site

18. Conclusions Analysis that includes both primary (jobs and income) and secondary effects (property appreciation) of brownfield redevelopment provides local decision makers with more comprehensive information on which to decide public support. –Based on case studies, the secondary effects may far exceed the primary effects.

19. Such analysis is possible using a combination of impact analysis from a local input-output model and simulation of a hedonic model. –IMPLAN may be used to create the input- output model. –Multilist data may provide residential sales for hedonic modeling. –Either local experts or historic property use may substitute for a census of brownfield sites.

20. Empirical case studies for the St. Louis metro area confirm the sensitivity of neighboring residential property values to: –Proximity of brownfield sites –Notoriety of brownfield sites –Severity and type of contamination associated with brownfield sites –Age of contamination at brownfield sites Contrary to the literature on racial and environmental justice, remediation of brownfield sites is likely to benefit landowners rather than low-income or minority residents.