Low-income housing has no impact on nearby home values (2016)

Using the latitude and longitude of these projects, we constructed two distance buffers—one up to 2,000 feet from the project, and another from 2,001 to 4,000 feet. We then identified homes within these buffers and captured Trulia home value data for each of these homes from 1996 to 2006. Trulia home value data is collected as an annual snapshot on June 1^st of each year. In order to avoid large shifts in prices from new construction, we only include homes with property records for the entire time period under study. The analysis in this report uses home value per square foot in order to control for changes for housing quality and mix as well as potential changes in value from renovations during the study period.

We use a basic differences-in-differences regression framework to estimate the difference in home values in the inner ring compared to the outer ring after the LIHTC project is placed into service. Differences-in-differences offers a way to identify the effect of a policy by examining relative changes in outcomes in treatment and control groups. In this report, the treatment group consists of those homes located in the inner ring, or nearby the LIHTC projects, and the control group are those in the outer ring. The assumption is that these homes, on average, only differ in terms of their relative proximity to the LIHTC project. Note that after plotting the median home value per square foot of the two distance rings before and after the project, we felt confident home values between distance rings prior to the time projects were placed into service shared common trends. The treatment occurs once the project is put into place, so the differences-in-differences reflects the difference between the treatment group and control group (a proxy for the counterfactual) in the post-treatment period compared to the pre-treatment period.

In order to control for idiosyncratic differences in home values within years and different metro areas, we include year fixed effects (and metro fixed effects for regressions containing projects across all 20 metros). Additionally, we implement cluster-robust standard errors on individual LIHTC projects in order to correct for likely correlation of errors terms within the clusters. Our results yielded differences that were statistically significant in three metro areas. In Boston and Cambridge, the estimated effect of living near LIHTC projects was -$18.05 and -$19.05 per square foot. In Boston the effect was significant at the 99% confidence level and in Cambridge at the 95% confidence level. In Denver the estimated effect was $7.35 and significant at the 95% confidence level.

Affordability is defined as the percent of a median household’s income in that market that would be needed to afford a mortgage payment on the median listing price of a home in that market. These median listing prices reflect Trulia listing data from Q3, 2016. Population figures in this report come from the 2000 Census.

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