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«A Journal of Policy Development and Research HoPe VI Volume 12, Number 1 • 2010 U.S. Department of Housing and Urban Development Office of Policy ...»

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Heritage Crossing, with a larger sample size, shows no indication of positive spillover effects. In fact, the coefficients on the post-micro variables in all three models are negative. Although the initial difference-in-differences estimate is negative and statistically significant, the estimate becomes smaller and less statistically significant when we control for property characteristics and tract fixed effects, suggesting that the initial estimate was biased by the changing composition of properties for sale. The second model, controlling for property characteristics and tract fixed effects, shows that overall property sales prices after completion were on average about $12,000 higher than prices before completion (an increase of 40 percent, which is the Halvorsen-Palmquist-translated coefficient in the model using the log of sales prices as the outcome), but the increase was smaller for similar properties close to the HOPE VI redevelopment. Including year fixed effects, the estimate is still negative but not statistically significant.

Broadway Overlook is the only HOPE VI project that shows convincing evidence of positive spillover effects. The graph in exhibit 7 shows that sales in the microneighborhood and outside it followed a similar pattern from about 1995 until 2003, the year of HOPE VI completion, where property values in the microneighborhood began to grow a bit faster. The impact estimate from the basic difference-in-differences model is about $8,000, and this estimate does not change when structural characteristics and census tract fixed effects are included in the model, suggesting little variation in structural characteristics of the properties being sold before and after completion across the macroneighborhood and little difference across census tracts within the macroneighborIn a log-linear model, coefficients on dummy variables are not accurate estimates of the relative effects when they are large. To get a more accurate estimate of the baseline percentage difference between the microneighborhood and macroneighborhood, the coefficient c must be used in the formula 100 X {exp(c) – 1} (Halvorsen and Palmquist, 1980).

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hood. The large coefficient on post shows a large overall increase in property values, reflecting the fact that this was an up-and-coming neighborhood during the study period. On average, a property in the macroneighborhood sold for $88,000 more after completion than it had sold for before completion, which makes it especially important to account for the upward trend in sales prices with the year fixed effects. Different volumes in sales per year or variations in the types and quality of housing for sale from year to year could bias the impact estimate. Results from the model including year fixed effects, where similar properties are compared to one another within years, show a larger and statistically significant estimate of spillover effects. Properties close to the HOPE VI redevelopment experienced an additional $17,000 (10 percent, according to the model using the log of sales price) increase after redevelopment compared with properties farther away but in the same macroneighborhood.

It is possible that the positive effect of the Broadway Overlook redevelopment on surrounding property values is understated by this analysis. Unlike the Townes at the Terraces and Heritage Crossing HOPE VI sites, the new Broadway Overlook development did not directly replace public housing; because of the property swap, the new development was built diagonally across the street from Broadway Homes highrises, the original public housing projects. The old projects were demolished and replaced by JHMI buildings, and the Broadway Overlook project replaced a lower rise, low-income housing development. Because the former Broadway Homes site is included in Broadway Overlook’s microneighborhood, some of the properties immediately surrounding the former public housing project are included in the area outside Broadway Overlook’s microneighborhood. If the removal of the highrise public housing projects had a positive effect on surrounding property values independent of any positive effect of the Broadway Overlook redevelopment, the effect of the removal would be captured in the sales prices of some properties outside the microneighborhood, thus understating any relative difference between price changes in each part of the neighborhood.

Exhibit 9 presents results of the model replacing the post*micro dummy variable with a series of interactions between year and micro for all years after completion (2003–06). Disaggregating

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the postcompletion period allows for effects to vary by year after redevelopment. The results of this model do not give a strong indication that the positive spillover effects are either growing or shrinking over time. The model shows no effects in the year of completion (the project was not completed until August of 2003), a very large and statistically significant effect the year after completion, and estimates in the following 2 years that are smaller but still sizable, although the standard errors are larger relative to the effect size.

Timing of Impacts This comparison of before and after completion measures any impact of completion on prices.

Personal interviews with city and neighborhood experts, however, indicated that part of the impact may be attributable not to the redevelopment, but to the removal of highrise public housing projects—the main source of blight, drug activity, and crime in the neighborhood (Seipp, 2007;





Shea, 2006). To test this theory, I applied the same models using the demolition date instead of the completion date. This method cannot isolate the effects of each stage in the development on surrounding property values and thus does not answer the question of how much of the impact can be attributed to the removal of the public housing projects and how much to the development of the new mixed-income projects. Seeing how replacing the completion date with the demolition date changes our estimates, however, can provide some general insight into the matter.

If the positive spillover effects are due to the removal of blight rather than the development of the HOPE VI projects, then the impact estimates in the model using the demolition date as the intervention point should be larger (and possibly more statistically significant) than those in the model using the completion date. In the latter model, any positive impact occurring before project completion would be incorporated into the precompletion price level, thus underestimating the true impact of the HOPE VI project.

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Conclusion This study evaluates whether the three completed HOPE VI redevelopments in residential neighborhoods in Baltimore contributed to the improvement of their surrounding neighborhoods.

Heritage Crossing did not show any evidence of positive spillover effects, suggesting that investors and homebuyers may not have ventured too close to the HOPE VI site. Although Townes at the Terraces showed a hint of a positive effect on surrounding property values, Broadway Overlook was the only project with significant positive effects. Qualitative evidence of HOPE VI’s effect on surrounding neighborhoods is fairly consistent with these empirical estimates.

Baltimore’s experience with these three HOPE VI redevelopments suggests that, even within the same city and under a single housing authority, implementation varies greatly. All HOPE VI projects have in common the removal of highrise public housing projects and their replacement with lowrise, mixed-income developments. But beyond these similarities, differences in design and management resulted in very different projects.15 Townes at the Terraces and Heritage Crossing are physically isolated from their surrounding neighborhoods, but Broadway Overlook’s design integrates the development into its surrounding neighborhood. Townes at the Terraces and Heritage Crossing both include two housing types—public housing units and low- to moderate-income homeownership units—whereas Broadway Overlook has a more diverse mix of public housing units, subsidized rental and homeownership units, and market-rate rental and homeownership units. Social and community services in Townes at the Terraces and Heritage Crossing were designed and managed by the city housing authority, but in Broadway Overlook these services were designed and managed by a partnership between the private developer and the tenant organization. The fact that Broadway Overlook had the strongest evidence of a positive spillover effect raises the possibility that adherence to the HOPE VI Program’s main principles may influence a project’s ability to improve surrounding neighborhoods.

This study cannot tease apart the influence of implementation on spillover effects from that of another potential influence: neighborhood conditions at the time of redevelopment. The Broadway Overlook redevelopment occurred in a neighborhood that was less distressed and more stable than the West Baltimore neighborhoods where the Townes at the Terraces and Heritage Crossing redevelopments occurred. Unlike the neighborhoods in West Baltimore, Broadway Overlook’s neighborhood was already improving before HOPE VI redevelopment. The evidence of positive spillover effects indicates that the surrounding neighborhood experienced even greater improvement due to the HOPE VI redevelopment. This evidence raises the question of how HOPE VI funding can best be targeted. On the one hand, it seems logical to give priority to the most distressed public housing projects, because they are most in need of physical redevelopment and their residents suffer most from the consequences of concentrated poverty. In fact, the idea of HOPE VI originated in response to the question of how to deal with the country’s most distressed and deteriorated public housing projects. On the other hand, because the HOPE VI model relies heavily on attracting private investment and tenants willing to pay market-rate housing prices, the most efficient use of See Brophy and Smith (1997) for a case-study analysis of characteristics of successful mixed-income developments. The authors found that design, management, and location are primary factors for success.

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its funding may be to target projects in neighborhoods that do not have overwhelming barriers to revitalization, such as problems with drugs, crime, and poverty. This question is part of a broader debate in urban policy about whether investment should target the neediest, most distressed neighborhoods or those neighborhoods that show some sign of stability or social organization, and therefore may have a greater capacity to take advantage of additional resources.16 Another important question raised by these results is one of cost effectiveness. Do the estimated positive spillover effects justify the 20 to 30 million dollar investments in each HOPE VI project?

Improving the surrounding neighborhoods of former public housing projects is not the only goal of HOPE VI, and any weighing of costs and benefits should take into account the full range of potential benefits, including the improvement of living conditions for public housing residents.

Still, the lack of strong evidence of substantial positive effects on surrounding neighborhoods, particularly in Townes at the Terraces and Heritage Crossing, should serve to caution policymakers that even a major redevelopment that replaces a dominant source of blight in a neighborhood with better quality housing and lower concentrations of poor households may not be enough to turn around a distressed neighborhood. Although we see more evidence of spillover effects in the Broadway Overlook site, it is unclear how central the role of HOPE VI redevelopment was in the overall improvement of the neighborhood, where property values were already on the rise when redevelopment began. Therefore, the question in the case of Broadway Overlook is whether the additional neighborhood improvement caused by HOPE VI (reflected in the additional jump in property values), along with other benefits not measured in this study, was worth the major investment required to redevelop a public housing project.

Although Baltimore’s HOPE VI experience reveals potential relationships between positive neighborhood spillover effects and the project’s implementation and the neighborhood’s stability, conclusions about the independent effects of these factors, or about whether these patterns occur in other HOPE VI projects in other locations, cannot be drawn from the results of this study alone.

We need comparable analyses of the effects of the HOPE VI Program in other cities that carefully take into account these different aspects of the program if we are to understand what is most important in meeting the goal of improving surrounding neighborhoods. In addition to learning what makes a HOPE VI project most effective, it is also important to consider evidence of positive spillover effects within a larger context of program costs and relative improvements within the surrounding neighborhood.

See Sviridoff (1994) for a more detailed discussion of this debate.

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Appendix A Missing Values Appendix A describes how missing values in the Maryland Property View 2005 and Baltimore City property sales 2006 data sets were handled in this analysis.

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There was no apparent pattern in these missing values. The lot size, housing type, and tenure variables originated from the Baltimore City 2006 property sales data set, and the remaining variables originated from the Maryland Property View 2005 data set.

Multiple Imputation Because the missing values were scattered among the different variables (for example, observations missing a value for age were not necessarily also missing a value for lot size, observations missing a value for lot size were not necessarily also missing a value for construction type), excluding each observation with a missing value for at least one variable would have omitted almost two-thirds of the observations in the regressions. Therefore, instead of running the models on only those observations with no missing values, I imputed values for each missing value. A few exceptions

include the following:



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