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Graduate School of Public and International Affairs, University of Pittsburgh Throughout the city of Pittsburgh and its surrounding first-ring suburbs, concentrated areas exist with high percentages of blighted, abandoned, and vacant properties. Blighted, abandoned, and vacant properties pose significant risks to the welfare of residents as well as to the area’s economy and built environment. This technical report reviews methods used by other cities that are dealing with similar issues, identifies indicators that can be used to predict oncoming blight or vacancy, and lays out a framework for data collection to further the movement toward neighborhood stabilization and redevelopment. Quantitative research includes a combination of statistical analysis and the mapping of trends from Geographic Information System and the Pittsburgh Neighborhood and Community Information Survey. The report concludes with recommendations for resolutions to be brought forth at the annual Congress of Neighboring Communities in June 2011.

The$Identification$of$Blight$Indicators$and$Their$Role$in$Neighborhood$Stabilization$and$Redevelopment$

Ryan Ambrose

Lauren Ashcraft

Caitlin Butler

Sarah Decesaris

Evan Hutchinson

Joseph Joyce

Ed Nusser

Eric Peccon

Thomas Roehl

Adam Szumski

Nancy Whelan

Jennifer Zaffuto

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Table of Contents Introduction ................................................................................................................................................... 3!

Motivation ................................................................................................................................................. 3!

Background ............................................................................................................................................... 3!

Scope ......................................................................................................................................................... 3!

Limitations ................................................................................................................................................ 3!

Content ...................................................................................................................................................... 4!

Organization .............................................................................................................................................. 4!

Objectives ...................................................................................................................................................... 5!

Background ................................................................................................................................................... 5!

Case Study: Cleveland .............................................................................................................................. 7!

Case Study: Detroit ................................................................................................................................... 8!

Case Study: Buffalo ................................................................................................................................ 10!

Case Study: Philadelphia ......................................................................................................................... 11!

Methodology ............................................................................................................................................... 11!

Analysis of Results ...................................................................................................................................... 11!

Conclusions ................................................................................................................................................. 18!

Recommendations ....................................................................................................................................... 18!

References or Bibliography ......................................................................................................................... 18!

Appendices .................................................................................................................................................. 22!

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Introduction Pittsburgh, like many cities across the Rust Belt and the United States, has been ravaged by decreasing population. With shrinking population comes an abundance of housing stock. The result is blighted, abandoned, and vacant properties, often occurring in “pockets.” When the condition is present, it is often contagious, and pervasive through the area. Nationwide, many tactics have been brought to the forefront to stabilize neighborhoods experiencing blight, abandonment, and vacancy. Some of these strategies include right-sizing, the conversion of vacant or blighted blocks to open space, and urging residents to relocate to other neighborhoods in an effort to streamline public services. Because the Pittsburgh region is poised to realize population growth, an opportunity presents itself to redirect the redevelopment of the blighted neighborhoods to create sustainable and accessible communities to serve all segments of the population.

Motivation In an effort to identify best practices to help guide organizations, such as the Congress of Neighboring Communities (CONNECT), undertaking stabilization and redevelopment projects, this report examines how other cities approach the issue of blight, abandonment, and vacancy, and how it may apply to the Pittsburgh region. The goal of the research on case studies of other cities is two-fold. First, it is used to help design a definition of blight, which may be accepted by the city of Pittsburgh and the first-ring suburbs surrounding it. Second, the factors identified by other cities as root causes of blight, abandonment, and vacancy are incorporated into quantitative research in the Pittsburgh region. The goal of the quantitative research is to create the foundation for determining a set of neighborhood indicators that may be used in order to identify the state of neighborhoods’ built environments and to indicate appropriate remediation or rehabilitation efforts to correct blight, abandonment and vacancy within it.

Background Urban decay, more specifically referred to as blight, has been defined in a variety of ways by state and metropolitan governments. It is traditionally seen as an unintended consequence of post-World War II urban design plans. Policies favoring suburbanization, the creation of the Interstate Highway System, and the growth of the automobile industry have all interacted to incentivize movement out of urban areas and led to a phenomenon now referred to as “white flight.” As the most economically mobile residents moved out of urban areas, the ability to sustain the full scope of the urban area began to disintegrate as tax revenue and other funding declined. State and local governments have implemented an assortment of urban renewal projects in response to blight, from economic strategies like enterprise zones to physical redevelopment like brownfield development. One of the considerations necessary while undertaking a redevelopment project in a blighted region is the potential for development to lead to neighborhood level gentrification that further isolates an already economically disenfranchised population.

Scope This report was initiated as an examination of issues facing the housing stock of Pittsburgh as well as the currently implemented strategies for addressing those issues. Strategies implemented by several other similarly impacted cities such as Cleveland, Ohio and Buffalo, New York were analyzed for potential applications in a Pittsburgh context, and to more accurately define potential policy responses. One of the obstacles encountered during these analyses was the lack of universal definitions and ratings of housing stock conditions. This report seeks to address this with the belief that a more universal system will allow for more transparent and accessible neighborhood profiles.

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Limitations Currently, little to no coordination exists between city administrators and the county system, complicating processes like sheriff’s sales of property. The lack of an integrated regional strategy for on the ground land use problems, such as municipal competition for demolition funds, needs to be addressed. Additionally, tax incentives for land purchases and funding streams take place in a disjoint manner. While many existing strategies are conducted at the municipal level, from the reporting of at-risk properties to the process of taking owners before a magistrate, the impact of blight and abandonment has a much broader impact. Gaining control of vacant properties is a significant obstacle for many municipalities, due to problems related to treasurer or sheriff sales, or many other issues.

Content This report contains the products of quantitative and qualitative research that has been performed to first determine a policy problem and then begin to outline potential solutions to the issue. The background section contains the majority of the qualitative research, discussing general information on the built environment in the Pittsburgh region, and then examining the cases of several other cities experiencing blight, abandonment, and vacancy. The case studies of other cities include Cleveland, Ohio; Buffalo, New York; the state of Michigan and the city of Detroit; and Philadelphia, Pennsylvania. Similarities and differences to the Pittsburgh region are noted, and strategies used in the other cities’ cases have been analyzed to determine their suitability for the Pittsburgh region. The concluding paragraph of each case study summarizes the city’s approach and highlights tactics that may be suitable for local implementation. In addition to the qualitative analysis of various community practices this report creates a community risk analysis based on census track data. The risk analysis is a computation of variables from the United States Census and Home Mortgage Disclosure Act Loan Application Registry data. This data is then ranked on a scale of 0 to 1 to create a benchmark ranking for potential vacant and abandoned properties. This quantitative approach is a tool to indentify risks of future blight so that proactive polices rather than reactive polices can be implemented and ensure consistent economic viability within a community. This data is linked to Geographic Information System (GIS) maps to illustrate at-risk areas. The risk analysis is not inclusive of all census tracts, rather it is a sample of 11 census tracts and provides instructions for additional analysis through the CONNECT partnership. Further, GIS maps are used to create a visual understanding of current vacancies within the City of Pittsburgh and first-ring suburbs. The products of the qualitative and quantitative research is then integrated to produce recommendations that CONNECT may follow as it continues to work with the city of Pittsburgh and the surrounding first-ring suburbs to determine new methods to mitigate and reverse blight, abandonment, and vacancy.

Organization This report begins by stating its objective, in the form of the policy problem statement, which is supported by the background information and studies of other cities. The study of the other cities helped to identify factors in and around the city of Pittsburgh to be quantitatively analyzed. A synopsis of quantitative methodology, with data results, maps, and figures follows. The conclusion then restates the findings of the research. The “recommendations” section includes suggested resolutions to be presented at the annual Congress of Neighboring Communities in June 2011.

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Objectives In order to combat blighted, abandoned, and vacant properties in the city of Pittsburgh and the first-ring suburbs surrounding it, it is crucial to first identify a definition of the terms blight, abandoned, and vacant that are accepted by all parties. It is further necessary to develop identifiers of blight, and indicators of prospective blight. Identifiers include characteristics such as percentage and type of vacancy, property tax delinquency, and records of private financial institutions. Indicators may include consideration of structural characteristics of housing units, property tax delinquencies, sheriff sales, housing grants from public agencies, structure fire records, and census tract level housing and population data. This report aims to provide definitions of blight, abandonment, and vacancy that can be accepted region-wide. It intends to outline identifiers and indicators of blight, and design a continuum of those factors so that communities can discern what methods may be the best intervention for their respective cases. The study lastly creates a framework for future data collection, so that CONNECT and other regional organizations can continue to gather information.

Background As a result of Pittsburgh’s dramatic population decline over the past sixty years, more than 17,000 properties stand vacant or abandoned (Jones 2010). Over time, many of these properties become blighted or abandoned. Blighted and abandoned properties often fall into disrepair and threaten the neighborhoods in which they are situated with decreased property values, increased crime, and public safety issues. Today, of the 145,695 lots in the City of Pittsburgh, nearly 17,000 are vacant. Of these vacant lots, approximately 9,900 are publicly-owned. 5,800 are privately-owned and delinquent on property taxes, and 3,441 are privately-owned and not delinquent on property taxes1. These structures and lots often fall into disrepair, posing health and safety risks to those still residing in the neighborhoods in which the structure or lot is situated. Of the 17,000 vacant or abandoned properties in the city of Pittsburgh, roughly 6,000 are buildings that have been abandoned (Graziani, Kim, Director of Neighborhood Initiatives, City of Pittsburgh 2009).!Pittsburgh, along with cities experiencing similar difficulties, has outlined many potential solutions to be introduced to mitigate the deleterious effects of abandoned buildings. Some of these solutions include Smart Growth tactics, which focuses on downsizing a city’s footprint in order to spur revitalization (Billitteri 2010); the creation of Land Banks, to acquire and manage vacant and abandoned property (Colin 2010); and property receivership strategies, in which community-based nonprofit organizations act directly to renovate vacant buildings if they can acquire them (Kelly 2004).

1!Stephany,!Rob,!Executive!Director,!Urban!Redevelopment!Authority.!"Taking!Control!of!Vacant!and!Tax!Delinquent!Land!in!Pittsburgh:!Local!Context."!City%of%Pittsburgh:%Land%Recycling%Task%Force.!March!4,!2010.!http://www.pittsburghpa.gov/landrecycling/!(accessed!February!4,!2011).!!

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Patterns( Visible( in( the( CONNECT( and( County( 200092010( Vacancy( Maps A clear pattern of increasing vacancy emerges when comparing the 2000 to 2010 maps for both Allegheny County as a whole as well as across the CONNECT area. This trend of increasing vacancy is not only demonstrated by more severe vacancy becoming apparent on the maps, but also by moderate vacancy becoming more pervasive across the studied areas. Several notable characteristics exist. The first is that although three new census tracts were formed, apparently no units are yet developed on them. Secondly, though some areas improved vacancy counts, a general trend of increasing vacancy is observed along the rivers.

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Comparing County Vacant Property 2000 to County Vacant Property 2010, similar patterns are evident. Areas along the rivers clearly worsen along with the overall map. Although a few small areas improve, the overall map of Allegheny County seems to go from a dark green to a lighter green/yellow. There is no doubt that the number of vacancies grew for the CONNECT area and around the whole county between 2000 and 2010.

Case(Study:(Cleveland,(Ohio(Strengthened code enforcement is a proactive policy that can work to stabilize communities and to prevent minor nuisances from becoming major hazards. The Cleveland Code Enforcement Partnership provides a model that is not only relevant to areas that are suffering from advanced stages of decay, but also to those attempting to control localized problems. Within the city of Cleveland, community development corporation (CDC) employed inspectors work on the front lines of the battle against abandonment, as the Department of Building and Housing refers all “routine” complaints to these organizations to conduct exterior field studies. The CDCs are subsequently charged with categorizing and inventorying structures about which a complaint is received; they also are tasked with maintaining a database of vacancy and foreclosure rates within their district, which can help the city to recognize neighborhood trends and potential future problem properties. Filing preliminary paperwork for interior inspections or demolitions is also an assigned CDC duty, as the city has effectively delegated the authority to these organizations to determine which structures pose the greatest risk to the community. In addition to conducting inspections, Cleveland’s CDCs provide initial contact to building owners about code violations and suggest avenues for remedying infractions, including placing residents in contact with government assistance programs. The CDCs perform follow up evaluations to determine if issues have been addressed and recommend prosecution for those that remain out of compliance. Although data has yet to be collected to verify the city’s argument, Cleveland makes a convincing case that this process yields better outcomes in terms of persuading property holders to take corrective action. We would expect that Allegheny County residents would also be more receptive to these community organizations, who they may view as concerned with the plight of citizens, as opposed to the collection of fines. The Code Enforcement Partnership has been vital for allowing Cleveland to continue to investigate violations, even after a budget crisis slashed Building and Housing’s staff by 25 percent. The Pittsburgh Bureau of Building Inspection, the largest code enforcement agency in the area, has maintained a stable budget, but partnering with CDCs can allow local governments to allocate funds to other areas.2 Furthermore, the program, which features monthly meetings between Cleveland’s chief inspector and the CDCs, could be used in Allegheny County to enhance communication with an already vibrant non-governmental sector and to prevent code enforcement cases from remaining open indefinitely.

Case(Study:(Michigan(Several cities and municipalities in Michigan, including Detroit, Flint, and Ypsilanti, face the challenge of widespread blight throughout their communities. As the problem was growing, these communities petitioned the Michigan Legislature to allow for the creation of an administrative court to tackle blighted properties. The legislature approved the idea, and gave these administrative courts (referred to as “blight courts”) significant powers to deal with property owners who fail to take care of their buildings and parcels.

2!“2011!Budget.”!2011.!City%of%Pittsburgh.!!

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The court has the authority to impose fines that range from $25 to $10,000, and to make the fines stick the courts are empowered to garnish wages and bank accounts. To address the problem of absentee property owners, the Michigan Legislature allows for liens to be placed on properties outside the municipality in which the blighted property is located. Because they have the ability to levy fines upon property owners, they have a funding stream that does not require increased taxation. In Detroit’s case, the revenue generated by fines has exceeded the costs of the operation of the court; these excess funds could then be used for other types of blight elimination and mitigation activities (i.e. demolition and clearance efforts, establishment of land banks, creation of urban park space, etc). Unlike the Housing Courts that are allowed to be created under Pennsylvania’s Act 90, the Michigan administrative courts deal with all types of properties. While they have only collected a small amount of the fines owed to them, they have at least made progress in reducing the amount of blighted properties. These blight courts have been far more successful at processing cases than the previous district court, and have reduced the load on other courts at the same time3. Overall, Michigan's state government has found the blight courts to be a success. Detroit’s Right Sizing Initiative Perhaps no other city in America has suffered from population decline in a way comparable to Detroit. The city’s population fell from 1.85 million in 1950 to 912,000 in 2008. The city faces a 30% vacancy rate citywide, and scores of blighted and abandoned buildings. While the previously mentioned blight courts are an effective tool, they alone cannot solve Detroit’s crisis regarding urban decay4. Accordingly, newly elected mayor Dave Bing has proposed a radical solution: shrinking or “right sizing” the city. Under Bing’s plan, the city would demolish entire neighborhoods in order to conserve resources to save those neighborhoods which can be saved. Bing’s plan would cut city services and infrastructure to the most blighted and vacant neighborhoods in the city, while channeling resources to restore remaining neighborhoods. This approach would require many citizens in the most vacant neighborhoods to move to more stable neighborhoods. What would remain is a smaller, healthier city with a footprint to match its population and resources. Some experts argue against the idea of right sizing, pointing out that it has yet to work successfully anywhere. These critics point to the experiences of cities throughout the United States-Denver’s Lower Downtown, Society Hill in Philadelphia, and even Detroit’s own Cass Avenue Corridor. These critics feel that cities are better off preserving antique housing stock and using it as a launching pad for future growth5. The first steps in Bing’s plan are already complete. The city began clearing over 3,000 unsafe homes throughout Detroit in 2010. Some estimate that ultimately as many as 12,000 could end up being demolished throughout the Motor City. In February of 2010, the city also completed a 3!Gagnon,!Geoffery.!"City!of!Blight."!Legal%Affairs.!Aug.!2005.!Web.!!4!Glaeser,!Edward!L.!"Shrinking!Detroit!Back!to!Greatness."!Economix!Blog.!New!York!Times,!16!Mar.!2010.!Web.!<http://economix.blogs.nytimes.com/2010/03/16/shrinking]detroit]back]to]greatness/>.!5!Gratz,!Robert!B.!"Shrinking!Cities:!Urban!Renewal!Revisited?!|!Planetizen."!Planetizen.!19!Apr.!2010.!Web.!<http://www.planetizen.com/node/43826>.!

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detailed study of all properties in the city in February of 2010. The study aimed to identify the state of all properties in the city and to determine which neighborhoods were the most stable and which were the most distressed. This study will serve as the baseline for “right sizing” Detroit’s urban footprint to match its available resources and population6. The next steps in the process will be hugely contentious; the city would have to determine winners and losers under Bing’s plan. There is already much opposition to the idea of forced relocations, and the process promises to be acrimonious. Certainly, Bing’s plan for Detroit is among the most ambitious and radical in the nation.

Case(Study:(Buffalo(There are several core challenges that Buffalo faces as a result of vacancy. The major include, but are not limited to the following:

• The city footprint is larger than the population warrants. • Blight is expensive. • Blight and abandonment spread to the suburbs

In order to address the three major issues caused by rampant vacancy, Blueprint Buffalo outlined three action items and one strategic platform. The three policy action items included:

1) A citywide vacant properties initiative that calls for the following: a. A comprehensive citywide code enforcement program b. A land banking entity c. The adoption of right-sizing and greening policies

2) The creation of a first-tier (first-ring) vacant properties agenda through the following

means: a. A series of forums attended by first-ring communities b. The establishment of a network of the first-ring communities c. Development and implementation of a regional framework to prevent blight

3) The formation of a Vacant Properties Coordinating Council to:

a. Act as liaison between public and private enterprise b. Become the governing body to enforce the initiatives set to combat blight c. Create a framework for the vacant properties work plan, and segue into a plan for

regional growth

4) The charter of Buffalo as a Living Laboratory by a. The creation of a management framework with the University of Buffalo b. The institution of pilot projects c. Emphasizing performance-based regulations d. Emulating the German International Building Exhibition model, which holds

design competitions, manages pilot projects, facilitates planning and zoning code reforms, and serves as a forum for community participation on right-sizing discussions (Schilling, Blueprint Buffalo, 2006).

6!"Survey:!A!Third!of!All!Detroit!Lots!Are!Vacant!or!Abandoned."!Detroit!News.!20!Feb.!2010.!Web.!<http://www.mlive.com/news/detroit/index.ssf/2010/02/survey_a_third_of_all_detroit.html>.!

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Many of the initiatives outlined in Blueprint Buffalo address problems that Buffalo and Pittsburgh have in common. Thus, many of the policy action items could also be implemented in Pittsburgh. In fact, Pittsburgh has already taken some of the steps outlined above. The city of Pittsburgh formed the Land Recycling Task Force in 2009 to examine vacancy issues within the city limits, and the city of Pittsburgh has been a strong supporter of House Bill 712, which was introduced to allow the formation of land banks in the state of Pennsylvania (Summary of HB 712, 2010). Like Buffalo, the city of Pittsburgh is addressing the problem at the regional level (Buffone, 2009). Regional organizations have also begun to focus on the topic, as well. For example, the CONNECT already serves as a forum for first-ring suburbs to discuss vacancy issues.

Case(Study:(Philadelphia(The City of Philadelphia uses logistical regression to analyze data from the Philadelphia Neighborhood Information System in order to determine which properties were most likely to become imminently dangerous. Several characteristics of the properties, including whether they were vacant, had outstanding housing code violations, and tax arrearages as well as characteristics of nearby properties were identified as significant predictors. There are a multitude of early-warning signs that could be fed into Pittsburgh’s blight and abandonment indicator system: Owners receive code violations and complaints from tenants, city agencies receive complaints from tenants and neighbors, while utility companies have unpaid accounts. Although these individual signs are not necessarily causal factors, together they signal where a property is in the abandonment process.

Furthermore, the Philadelphia Indicator system breaks down abandonment into three separate groups:

• Functionally abandoned: Property is no longer fulfilling its role as a residence

(suspension of mail service, vacancy, etc.). • Financially abandoned: The disinvestment that occurs when owners stop meeting their

minimum financial responsibilities and properties begin to accumulate debt because of equity

• Physically abandoned: When owners neglect the interior or exterior upkeep of a property.

By classifying abandoned properties into these sub-groups, analysts are better able to devise cause-and-effect relationships at the community and block level. Pittsburgh should compile a list of several key indicators of foreclosure, and adopt a more prescriptive approach to prevention strategies. Methodology The risk indicator was developed through compiling the variables listed below.

• Median Income: The Median Income variable gauges the status of economic stability within a census tract. A low median income for a census tract can indicate poverty, which then correlates to having a potential for blight. Areas that have a low median income are scored closer to 1.

• Percent Sub-Prime Loans Home Purchase/Refinancing: Sub-prime loans are much riskier than the prime market, and therefore have a higher likelihood of default. Due to this risk, the more sub-prime loans there are in a neighborhood, the greater the risk for vacant and abandoned properties. A higher score indicates a greater amount of sub-prime

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loans within a census tract, while the ratio spread within the data base is greater than or equal to 3%. Ratio spreads that are above 3% of the treasury rate are a strong indicator of subprime loans.7 This variable is derived using HMDA data for the past three years for home purchasing and refinancing. To collect data one must gather total home purchase loans and refinancing loans for each tract for the past three years and sum the count together. This step is repeated but isolating subprime loans (those above 3% ratio spread) and summing subprime home purchase and refinancing for the past 3 years. Divide the total count of subprime loans by the total count of loans. Formula: Subprime (home + refinancing)/Total Loan Count

• Percent Population of 65 years old: This variable attempts to measure future turnover in population. Large quantities of older generations within a population are indicative of negative population growth, due to the fact that they lack an adequate replacement upon death. Because of the disproportionate death of older generations, the older a population is within a census tract, the greater the risk of blight and abandonment. A score closer to 1 indicates a greater risk.

• Percent Vacant: This variable depicts the percentage of vacant units in a given area. The

higher the percentage of vacancy, the greater the likelihood of blight and abandonment, with high percentages scoring closer to 1.

• Growth Ratio: This ratio denotes the status of housing stock relative to the population in

a given area. It is based on the assumption that if housing stock increases and population decreases, the ratio will be negative and result in an increased risk for vacancy and abandonment. Areas with positive ratios indicate that the indices of housing and population growth or decline correlate with each other, and therefore lack vacancy and abandonment problems. Numbers that are negative will be scored closer to 1. The ratio uses total housing units from 2000 and 2010 and total population from 2000 and 2010. The formula is: (HU2010-HU2000) ÷ (Pop2010-Pop2000)=Growth Ratio.

• Single Mother Families: This is an easily accessible variable within the census and

serves as a sign of social stability. The single mother families variable can be used as an aggregate measure of family disruption, neighborhood disadvantage and economic hardship8. Disadvantaged populations have a greater presence in poverty-stricken areas and have a better chance of living in sub-standard housing stock. Tracts that have a large amount of single mothers will be scored closer to 1, while areas that have low number of single mothers will be scored closer to 0.

• Change In Renter Occupied: This variable measures the percent change in renter

occupied parcels over a ten-year span. Locations with a large amount of renters are used as an indicator of potential instability, as renters are less likely to make long-term investments in infrastructure and aesthetics due to their transitory state. Areas that have a large change will be scored closer to 1. This variable uses percent renter for 2000 and 2010. The formula is: (%Renter2010-%Renter2000) ÷ %Renter2000

7!Economic Justice Project: New York Law School HMDA Analysis. http://hmdanalysis.nyls.edu/glossary/index.php#spl 8 Mikelbank, Brian M. An Indicator Analysis to Identify Potential Vacant Residential Properties. Analysis, Cleveland: Federal Reserve Bank of Cleveland, 2010.!

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• Percent Renter Occupied: Areas that have high amounts of renting are used as an indicator of potential instability. Areas that have high amounts of renting will be scored closer to 1.

*The data collected can be gathered at The American Fact Finder that is found at census.gov and HMDA LAR Raw Data at www.ffiec.gov/hmda . All variables except subprime loans use the American Fact Finder. HMDA data should be used for the subprime loans. To obtain this data download HMDA LAR Raw Data for 2007, 2008, and 2009.

The creation of a blight risk indicator was modeled after a similar effort by a Federal Reserve Bank of Cleveland visiting scholar9. Once the aforementioned variables were collected for the eleven census tracts, summary statistics and histograms were analyzed to determine possible break points for each indicator. In similar fashion to the Federal Reserve study, two separate procedures were used to determine how each variable distribution was divided: natural breaks in the distribution or quartiles. In our analysis, variables with greater variability were divided into four categories: 0.25, 0.5, 0.75, and 1, with 1 indicating the highest level of blight risk. For instance, the “percentage of renters” and the” percentage of individuals age 65 and older” variables were divided into four categories based on distribution quartiles. Variables with less variability were divided into three categories: 0.33, 0.67, and 1. After each of the seven variables were recoded, the average score was computed for each tract. Recoding and indicator computation was performed in R, the statistical freeware program. However, these processes can also be carried out in Microsoft Excel and SPSS. See the Appendix for variable summary statistics, break points for each variable, and related histograms. It is important to note that the introduction of more CONNECT community census tracts will inevitably add to the variability of each preliminary indicator and thus shift break points. Furthermore, this preliminary example of a blight risk indicator should be used to advance discussions pertaining to other relevant variables that can be included in an analysis of Pittsburgh and first-ring municipalities. As noted by Brian Mikelbank, the indicator can be “customized to reflect the unique market characteristics” of the region to which it is applied.10

9!ibid!10!Ibid.!p.!6.!

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(

Risk Indicator Map for Mount Lebanon

Risk Indicator Map for the CONNECT Region

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Risk Indicators Map

Our graphical interface compares Uptown and McKees Rocks (two areas with high risk ratings according to our indicators) to Mount Lebanon (an area that has relatively low risk ratings). The green coloration on all census tracts within this community, combined with the moderate scores on our scale, demonstrates that blight presents only a relatively minor future risk. Conversely, Uptown and McKees Rocks are revealed to have a higher degree of immediate trouble, as is shown by the combination of the yellow and orange colors on our maps and the higher rating on our risk assessment.

Risk Indicator Map for Uptown

Risk Indicator Map for McKees Rocks

Analysis of Results After running a distribution of the identified housing indicators in each census tract, the results imply that indicator risk scores are somewhat correlated with what the visual cues of each area already project. Graphic 1 is an illustration of the final risk analysis scores for each of the census tracts assessed.

Census tract 4644 and 4639 (McKees Rocks) exhibit the greatest risk of blight and abandonment, while 4734.2 (Mt. Lebanon) appears to be the least susceptible to such issues. The eight census tracts that comprise Mt. Lebanon all score in the low to moderate risk range of the distribution,

Table 1: Community Risk Indicator Score

Scores: 0.3-0.5 Low Risk; 0.51-0.7 Moderate Risk; 0.71-1 High Risk Tracts Community Risk Indicator Level of Risk

4644 McKees-Rocks 0.96 High 4639 McKees-Rocks 0.89 High 103 Uptown, City of Pittsburgh 0.73 High

4732 Mt. Lebanon 0.59 Moderate 4733 Mt. Lebanon 0.52 Moderate

4736.02 Mt. Lebanon 0.51 Moderate 4735 Mt. Lebanon 0.45 Low 4731 Mt. Lebanon 0.40 Low

4734.01 Mt. Lebanon 0.40 Low 4736.01 Mt. Lebanon 0.40 Low 4734.02 Mt. Lebanon 0.33 Low

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while census tract 103 (Uptown) must pay serious attention to pressing blight and abandonment issues with their score indicating that they are highly at risk as well. Table 1 is a ranking of the census tract scores and level of risk. The statistical analysis information and computation of the scoring is attached in the appendix section of this report. At one extreme, census tract 4644 in McKees Rocks possesses several factors that pose as immediate threats to the inference of blight and neglect. The age distribution of their tract is disproportionate with a large segment of their population over age 65 (1), which is compounded by already high vacancy rates of property and a low median household income, both of which were scored as 1. Additionally, there is a large presence of sub-prime loans in the area (1), which indicate a greater risk of blight and abandonment due their high likelihood of default. Many of the units in McKees Rocks are renter-occupied, which have a large presence of single parent families as their tenants and owners, therefore those tracts are scored at 0.75 and 1. Due to these factors, the municipality of McKees Rocks must work to improve their prescriptive elements of blight and abandoned property, as their nearly-perfect index score of .9642 indicates that they are at serious risk.

On the other hand, census tracts in Mt. Lebanon range from .33 to .59, which indicate a low to moderate susceptibility to neighborhood blight. Tract 4734.02 has the lowest risk indicator among the 11 with a score of 0.3314, which can be attributed to their lower rates of rental properties (.25), an area growth ratio that is adequately proportioned to the available housing stock (.25), their low levels of vacancy (.33) and higher median incomes (.33). Tract 4734.02 possesses a relatively small amount of single parent homes and a moderate but not excessive portion of their population being over the age of 65 (.5). Tract 4732, also in Mt. Lebanon, poses a much higher threat to blight and abandonment due to its much defined presence of renters,

Table 2: Variable Scores For Each Census Tract Community and Tract

% 65yr+ Growth %Vacant Income Subprime %Renter Single Parent

Uptown, 103 0.25 0.5 1 1 0.67 1 0.67 McKees-Rocks, 4639 1 0.5 1 1 1 0.75 1 Mckees-Rocks, 4644 1 0.75 1 1 1 1 1 Mt. Lebanon, 4731 0.5 0.75 0.33 0.33 0.33 0.25 0.33 Mt. Lebanon, 4732 0.75 0.75 0.33 0.67 0.33 1 0.33 Mt. Lebanon, 4733 0.5 1 0.33 0.33 0.67 0.5 0.33 Mt. Lebanon, 4734.01

0.25 0.5 0.33 0.33 0.33 0.75 0.33

Mt. Lebanon, 4734.02

0.5 0.25 0.33 0.33 0.33 0.25 0.33

Mt. Lebanon, 4735 0.25 0.75 0.33 0.33 0.67 0.5 0.33 Mt. Lebanon, 4736.01

0.5 0.75 0.33 0.33 0.33 0.25 0.33

Mt. Lebanon, 4736.02

1 0.75 0.33 0.33 0.33 0.5 0.33

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older population and disproportionate growth index. Since, Mt. Lebanon is at a low to moderate risk there is no immediate need for policy intervention to stave off vacant and abandoned properties. However, municipal leaders should be aware of areas that score in the moderate to high risk in order to monitor those tracts for potentially harmful change. Although more suitable than McKees Rocks, the census tract comprising the Uptown region indicates high risk for blight and abandonment, due to its extreme shortfalls in vacancy (1), income (1), and its housing stock that is dedicated almost entirely to renters (1). If Uptown is able to improve on those three factors while capping the decline of others, their susceptibility for blight and abandonment should decrease significantly. Uptown’s relatively smaller older population is the primary reason why their risk score is lower than Mckees Rocks. The risk indicator is extremely beneficial for municipalities. By looking at individual variable scores and overall risk indicator scores, leaders can begin to implement policies that would work to reduce their risk for vacant and abandoned properties. The utilization of such an analysis tool will create crucial conversations with civic leaders, community advocacy groups, and the citizens of the community that enable specific areas of concern to be addressed. This tool illustrates how raw data from easily accessible resources can be integrated to create useful and actionable information (Mikelbank 2010). This analysis can be further tailored to fit unique community features. Additional information such as total foreclosures, property appreciation values, and gas or water shut off data would further the value of the spatial analysis. At this time that data is not easily accessible for communities outside of the City of Pittsburgh. This risk analysis is a vital starting point to grasp the pervasiveness of vacant and abandoned properties within the City of Pittsburgh and the first-ring suburbs. Conclusions By using our risk indicators to assess the needs of each community, municipalities can understand the different appropriate methods that can be used to combat blight, abandonment, and vacancy. These approaches range from prevention and mitigation to major intervention. From least severe to most severe:

• Blight prevention – strong code enforcement to help effectively prevent future blight and abandonment;

• Acquisition – tools to take control of blighted and abandoned property; • Disposition – tools to transfer property; • Redevelopment Incentives – encourages and support private market reinvestments in

formerly blighted and abandoned properties.

Recommendations There are several recommendations to streamline the collection and flow of information and move toward a goal of developing a regional strategy for mitigating and rehabilitating blighted, abandoned, and vacant properties. These recommendations are in the form of suggested

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resolutions to be brought forward at the annual Congress of Neighboring Communities in June. They include: 1. All participating municipalities and the city of Pittsburgh accept a common definition of

blight, abandonment, and vacancy. Coordinating work toward a common goal is meaningless if the common goal, and more importantly, the problem driving the need for that common goal is not well defined. With that in mind, we also recommend that CONNECT and all of its members adopt a uniform definition of vacancy, abandonment, and blight. The proposed definitions are a result of case study research and interpretation of US Census data. Vacancy “Excluding seasonal vacancies and properties currently on the real estate market, a residential or commercial unit (store front, shop, etc) that has not had a tenant for 30 consecutive days and has not undergone any improvement or renovation in that time shall be considered vacant.” The latter clause in the sentence allows for the recognition that homes and storefronts can easily be vacant for much more than 30 days while undergoing renovations. However, due to the large presence of former industrial parks in our region, special attention must be paid to those as well. We recommend that “Any industrial park or industrial plant be declared vacant if it has not had a tenant for 180 days.” Abandonment It is proposed that CONNECT and its members adopt Philadelphia’s definitions of abandonment, as detailed earlier in this report. These terms apply to both residential and commercial properties. The definitions are:

• “Functionally abandoned” - Property is no longer fulfilling its role as a residence (suspension of mail service, vacancy, etc.).

• “Financially abandoned” - The disinvestment that occurs when owners stop meeting their minimum financial responsibilities and properties begin to accumulate debt because of equity

• “Physically abandoned” - Owners have neglected the interior or exterior upkeep of a property.

Blight The definition of blight has been never been agreed upon beyond a community level. Blight is naturally subjective to a degree, but there are markers of blight that determine its threshold. If these markers are agreed upon, progress will be facilitated. It is crucial for Pittsburgh, like Philadelphia, to recognize that blight and abandonment manifest differently and at different stages.

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It is recommended that CONNECT define blight as “including both environmental blight and structural blight. Environmental blight covers things such as tall grass and weeds and the presence of trash. Structural blight refers to vacant buildings with broken windows, boarded up doors/windows, and crumbling exteriors (including but not limited to the roof, porch, and siding).” Environmental blight can be corrected by individual action, and in the case of a vacant or abandoned property, does not require the property owner to be active in the process. Structural blight is a larger problem and requires concerted action by various actors, including the property owner. 2. CONNECT should expand its role as a coordinator of action and clearinghouse for

information. In the city alone there are numerous players involved in mitigating and redeveloping blight, including but not limited to, the Urban Redevelopment Authority (URA), Bureau of Building Inspection (BBI), CDC’s, private developers, and of course, neighborhood residents. All of these stakeholders must work together around the issues of blight mitigation and redevelopment. Several of the case studies highlighted in this paper have shown innovative ways that other rust-belt cities have coordinated action. While these cities have taken good steps, we see Pittsburgh as having a natural advantage because so many of the initial steps are already in place. Philadelphia’s predictive regression first requires significant data inputs, which PNCIS already maintains, and Blueprint Buffalo calls for an assembly of first-ring suburbs, which is a role CONNECT already fulfills. The city of Pittsburgh also has been working with Pittsburgh Community Reinvestment Group on a Land Recycling Task Force. The framework is in place, but it needs to be grown, and CONNECT can lead the way in this. With so many players involved in different aspects of blight redevelopment and mitigation, we recommend that CONNECT play the lead role in coordinating all of these efforts. This would mean a significant upgrade to CONNECT in both information sharing and personnel. Ideally, CONNECT would gather, store and disseminate all data on blighted and abandoned properties. This must be done by playing to different organization’s strengths. PNCIS already has a significant data library. They could provide a vacancy/blight specific map/data system. CDC’s have working knowledge of their neighborhoods and what is and isn’t working; they should be brought on board to report about newly vacant, or continuing troubled properties. CDC involvement has been used in the Cleveland model and proven quite effective. BBI, in the city of Pittsburgh, can come to the table and offer its guidelines for determining structural soundness and which buildings should be razed. These guidelines will help CDCs provide more useful information. If CONNECT can collect all of this information, they are in a unique position to disseminate not just to the city of Pittsburgh, but to first-ring suburbs as well, which as we have shown earlier, are experiencing problems with blight and abandonment as well. An area of immediate concern relates to the great need for coordination between communities and local governments in the process of selecting buildings for demolition and creating plans for redevelopment of the parcel. Although tearing down dilapidated structures is important, a vacant

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lot isn’t much of an improvement over a blighted building. If CONNECT were to serve as a depository of information on condemned structures, the organization could work to target demolitions in areas where redevelopment can take place quickly. It is important to point out that the previous stated idea runs the risk of razing and redeveloping only in growing neighborhoods and exacerbating the problems in areas that are not seen as growing. But, CONNECT can also carry out the Philadelphia regression model and use those patterns to predict problems before they occur. Also, by involving CDCs in this process, neighborhood information can, and should, be used to market neighborhoods and leverage redevelopment. Through CDC partnerships, increased information sharing, and increased neighborhood marketing, blight mitigation can improve throughout the city and first-ring suburbs. 3. Agree on parameters for data collection, information flow, and transparency. 4. Adoption of the risk indicators metric and the continuum of corrective action that assigns

particular palliative tasks according to the severity of blight experienced.

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Appendices

Variable Rankings For CONNECT Communities Variable If Value is

Greater Than

If Value is Less Than or Equal To

Indicator Value

Growth Ratio (Change in Housing Units/ Change in Households 2000-2010)

5 0 -5

5 0 -5

1 0.75 0.5 0.25

Change in Percent Renter Occupied, 2000-2010)*

Percent Renter Occupied, 2010 0.50 0.38 0.17

0.50 0.38 0.17

1 0.75 0.5 0.25

Percent Single Mothers, 2010 this only had two levels 0.15 0.10

0.15 0.10

1 0.67 0.33

Median Household Income 52,770 30,000

52,770 30,000

0.33 0.67 1

Percent Population Over 65 0.335 0.281 0.232

0.335 0.281 0.232

1 0.75 0.5 0.25

Percent Subprime (Home Purchase and Refinance) 0.80 0.40

0.80 0.40

1 0.67 0.33

Percent Vacant Units 0.20 0.10 0.0

0.20 0.10

1 0.67 0.33

*Change in Percent Renter Occupied is not available as of 4/17/11 due to data not being released by the United States Bureau of Census

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Summary Statistics

Variable Distributions

!

Plus!65!Percent!

Growth!Ratio!

Percent!Vacant!!

Median!Income!

Percent!Subprime!

Percent!Renter!

Percent!Single!Parent!Household!

Minimum! 0.192! ]12.143! 0.041!!!!!!!!!!!!!!!!!!!!!!!!

11,515!! 0.000! 0.067! 0.060!1st!Quarter! 0.232! ]0.035! 0.052!

!!!!!!!!!!!!!!!!!!!!!!!30,853!! 0.026! 0.171! 0.069!

Median! 0.275! 0.426! 0.062!!!!!!!!!!!!!!!!!!!!!!!!

59,119!! 0.037! 0.380! 0.076!

Mean! 0.281! 0.194! 0.097!!!!!!!!!!!!!!!!!!!!!!!!

52,770!! 0.043! 0.338! 0.091!3rd!Quarter! 0.335! 0.763! 0.114!

!!!!!!!!!!!!!!!!!!!!!!!71,408!! 0.049! 0.456! 0.095!

Maximum! 0.394! 9.880! 0.273!!!!!!!!!!!!!!!!!!!!!!!!

88,914!! 0.108! 0.729! 0.247!

Missing! !! !! !! 1! !! !! !!

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