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Dynamic Neighborhood Taxonomy

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1 Dynamic Neighborhood Taxonomy
“Building New Capacity for Neighborhood Development” City of Seattle, May 5, 2009 A Project of LIVING CITIES By RW Ventures, LLC

2 Agenda Background: Developing New Tools for the Field I
Applying the DNT Tools: City Planning Examples II Moving Forward: Implications and Next Steps III Discussion IV 2

3 LIVING CITIES PARTNERS:
About Living Cities “A partnership of financial institutions, national foundations and federal government agencies that invest capital, time and organizational leadership to advance America’s urban neighborhoods.” AXA Community Investment Program Bank of America The Annie E. Casey Foundation J.P. Morgan Chase & Company Deutsche Bank Ford Foundation Bill & Melinda Gates Foundation Robert Wood Johnson Foundation The Kresge Foundation John S. and James L. Knight Foundation John D. and Catherine T. MacArthur Foundation The McKnight Foundation MetLife, Inc. Prudential Financial The Rockefeller Foundation United States Department of Housing & Urban Development LIVING CITIES PARTNERS: 3

4 The Challenge: Scarce Resources, Many Options
Community-Based Organizations: select interventions, identify assets and attract investment Governments: tailor policy and interventions Businesses: identify untapped neighborhood markets Foundations: target interventions, evaluate impacts Need for Relevant, Timely and Accessible Information Resources

5 Information Resources
Data Increasingly available, but more progress to be made Gap between practitioners and academics: need “Clinical Economics”(Sachs) Knowledge Tools Few decision systems for neighborhood practitioners, investors and service providers

6 A New Capacity for Neighborhood Development
Strategic planning linking neighborhood, city and region Centralized data and information systems Integrated analytic tools and impact monitoring Ongoing evaluation of results Strategy adjustment and refinement

7 Comprehensive Neighborhood Taxonomy
DIMENSIONS  Neighborhood Metrics Business People Real Estate Amenities Social Environment EVOLUTION Improvement or deterioration within type Gradual vs. Tipping point From one type to another DRIVERS Employment Education Crime Housing stock Investment activity TYPOLOGY Port of entry Bohemian Retirement Urban commercialized DYNAMIC TAXONOMY

8 Theory and Data Change in Price Change in Amenities
Change in Demand for the Neighborhood Change in Quantity PHYSICAL: Distance from CBD, vacancies, rehab activity, … TRANSPORTATION: Transit options, distance to jobs, … Over 2,500 variables, spanning 15 years, covering over 2,000 census tracts CONSUMPTION: Retail, services, entertainment, … PUBLIC SERVICES: Quality of schools, police and fire, … SOCIAL INTERACTIONS: Demographics, crime rates, social capital…

9 Theoretical Framework
Housing Price Structure Rent Amenities Use Demand for Housing as Proxy for Neighborhood Health Look at Quality Adjusted Housing Values to Capture Neighborhood Amenities Look at Change in Quantity of Housing to Account for Supply Effects

10 Final Product: The DNT RSI
RSI Estimation Coverage Using Case/Shiller Method Time Period: RSI Estimation Coverage Using DNT RSI Method Time Period: Improving upon traditional repeat sales indices, the DNT RSI can be estimated for very small levels of geography, and is more accurate, more robust and less volatile.

11 11

12 The Big Picture: Drivers of Neighborhood Change
“The Goldilocks Theory” … Mobility is the key mechanism of change Movers are attracted to areas with undervalued housing but sound economic fundamentals (employment, income, education, young adults) Being connected is important: proximity to job centers, access to transit, lower commuting times are positive Cultural and Recreational Amenities (art galleries, bars and restaurants) help, but are not the main event … Neighborhoods of Opportunity are “Just Right.”

13 The “Little” Picture: Few Silver Bullets
DETROIT—Notorious for its abandoned buildings, industrial warehouses, and gray, dilapidated roads, Detroit's Warrendale neighborhood was miraculously revitalized this week by the installation of a single, three-by-four-foot plot of green space. The green space, a rectangular patch of crabgrass located on a busy median divider, has by all accounts turned what was once a rundown community into a thriving, picturesque oasis, filled with charming shops, luxury condominiums, and, for the first time ever, hope. The Johansens, who just moved to Warrendale, enjoy some outdoor time. 3'-By-4' Plot Of Green Space Rejuvenates Neighborhood FEBRUARY 11, 2008 | ISSUE 44•07

14 Exploring the Relative Importance of Different Drivers of Change
( Random Effects Model, Standardized Coefficients with 95% Confidence Interval)

15 Summary  Implications
Two major implications: We need a framework for understanding neighborhoods as dynamic, specialized, and nested in larger systems We need much better tools for customized analysis of local economies

16 Neighborhoods are Complex

17 Neighborhoods are Complex
PEOPLE Ethnicity, Age, Family Structure AMENITIES Physical environment, Entertainment venues, Public transit GOVERNANCE Infrastructure, Policing, Social Services SOCIAL ENVIRONMENT Civic engagement, Social networks, Community organizations BUSINESS Number, size and type of businesses REAL ESTATE Commercial and Residential, Type and Quality of Housing

18 Neighborhoods are Dynamic
PEOPLE Change or lose jobs; have kids; move AMENITIES Environmental deterioration; development of parks, institutional anchors GOVERNANCE Changing infrastructure, services, enforcement demands SOCIAL ENVIRONMENT Change in crime, participation, social behaviors BUSINESS Entry, Investment, Failure REAL ESTATE Deterioration and renewal A Web of Interdependent Activities: “Organized Complexity” (Jacobs)

19 Neighborhoods are Nested in Larger Systems which drive the Flow of Capital and People
Neighborhoods are Nested in Larger Systems Which Drive the Flows of People and Capital ECONOMIC SYSTEMS SOCIAL SYSTEMS POLITICAL SYSTEMS Labor Markets Social Capital Government Services Business Markets Civic Networks Infrastructure Housing Markets Public Goods Capital Markets Governance Consumer Markets Neighborhoods arise from the interaction of regional economic, social and political systems with physical place.

20 Goal: Neighborhoods that Build Capacity and Opportunity (Amartya Sen)
Functioning Neighborhoods Connect Residents and Assets to Larger Systems Connectedness Isolation Employment networks Entrepreneurial opportunities Business, real estate investment Expanded products and services Productive, healthy communities Poverty Productivity Undervalued, underutilized assets Goal: Neighborhoods that Build Capacity and Opportunity (Amartya Sen)

21 Applying the Framework
STEP 1A: What type of neighborhood do you want to be?

22 Applying the Framework
STEP 1A: What type of neighborhood do you want to be? Starter Home Community

23 Applying the Framework
STEP 1A: What type of neighborhood do you want to be? STEP 1B: What drivers will get you there? Specific Retail Amenities Child Care Schools Safety Affordability Starter Home Community

24 Applying the Framework
STEP 2: Identify Relevant System ECONOMIC SYSTEM Retail Markets Starter Home Community

25 Applying the Framework
STEP 3: Identify Change Levers Within System ECONOMIC SYSTEM Commercial Land Assembly (production – costs) Retail Markets Specialized Market Data (exchange – finding costs) Starter Home Community

26 Applying the Framework
STEP 4: Specify Interventions Interventions Land banking Buying power models ECONOMIC SYSTEM Commercial Land Assembly (production – costs) Retail Markets Specialized Market Data (exchange – finding costs) Starter Home Community

27 Developing New Tools for the Field
Question/Goal Tool Tracking Neighborhood Change DNT Repeat Sales Index (RSI) How will a specific intervention affect its surrounding area? Impact Analyst What drivers differentiate neighborhoods with respect to a specific outcome of interest? CART Identify comparable neighborhoods based on drivers of change and other key characteristics Neighborhood Typology What neighborhoods are similar along particular factors of interest? Custom Typologies How does the impact of an intervention vary in different places? Geographically Weighted Regression Track affordability and neighborhood housing mix Housing Diversity Metric Anticipate and manage neighborhood change Pattern Search Engine Identify “true” neighborhood boundaries NeighborScope 27

28 The Product Development Process Testing and Refinement
Where We Are Today The Product Development Process Concept Design Prototype Testing and Refinement Launch Scaling Up

29 The Product Development Process Testing and Refinement
Where We Are Today The Product Development Process Concept Design DNT Prototype Testing and Refinement Launch Scaling Up

30 Agenda Background: Developing New Tools for the Field I
Applying the DNT Tools: City Planning Examples II Moving Forward: Implications and Next Steps III Discussion IV 30

31 Agenda Applying the DNT Tools II
a. Neighborhood Planning in Southeast Seattle b. Informing Use of the Housing Levy c. Zoning Changes in Northgate d. Ongoing Impact Monitoring

32 Neighborhood Planning in Southeast Seattle
Key Issues: Leverage light rail investment Retain existing businesses and attract new ones Minimize displacement as neighborhood improves Analytic Tools: Neighborhood Typology DNT RSI Affordability reports Impact Analyst

33 Area of Focus: North Beacon Hill
33

34 Logic and Approach Quickly Assess Current Conditions and Trends:
Select relevant indicators, compare North Beacon Hill to city and peers Identify Opportunities and Risk Factors Related to Light Rail Construction: What do we know about impact of light rail and other changes taking place to this type of neighborhood? Select Interventions and Support Implementation: What programs/interventions would make the most difference and how should they be implemented? Monitor Outcomes and Evaluate Results: Are interventions achieving the desired outcomes? What could be done differently?

35 Current Conditions and Trends: Neighborhood Reports

36 Current Conditions and Trends: Neighborhood Reports

37 Current Conditions and Trends: Neighborhood Reports
37

38 “Neighborhood Reports +”: Applying the DNT Neighborhood Typology
Key Dimensions: People Income Age Foreign Born Place Land Use Housing Stock Business Types Variables 38

39 “Neighborhood Reports +”: Applying the DNT Neighborhood Typology
Key Dimensions: People Income Age Foreign Born Place Land Use Housing Stock Business Types Variables Type 4: “Port of Entry” 39

40 “Neighborhood Reports +”: Applying the DNT Neighborhood Typology
Type 4-D, “Port of Entry: Stable Residents”: Lower income, single family homes, stable resident base. High foreign-born population, high business diversity. Appreciating faster than its peers: since 2000, the RSI has increased by 98%, compared to 91% for its peer group. Over the past 2 years, properties have maintained their values, while they depreciated in mid-south Beacon Hill. A Neighborhood in Transition: Type 4-D neighborhoods can transition to Type 5-B, “Urban Tapestry: High Diversity” (higher income, lower foreign born population, lower unemployment). Based on HMDA data trends, it appears that such a transition is taking place, making this area more similar to the southern portion of North Beacon Hill. Potential Issues: Signs of Financial Distress: high sub-prime lending activity; credit indicators (accounts past due, credit balance to limit ratios) reveal distress. Impact of Light Rail?

41 Possible Applications: Evaluate the impact of a development policy
Anticipating Change: Measuring the Effect of Light Rail Using the Impact Analyst What This Tool Does: Estimates impact of an event (e.g. construction of a light rail stop) on surrounding housing values (or on other outcomes, e.g. crime) Possible Applications: Evaluate the impact of a development policy Identify expected changes Choose among alternative interventions based on estimated benefits to the surrounding community Advocate for a specific intervention 41

42 How It Works Estimated Distance Decay Function – LIHTC Projects DNT Repeat Sales Index, 1 = No Impact Homes within 1000 ft of an LIHTC site appreciate at a 4% higher rate than homes between 1000 ft and 2000 ft. Distance from Project Location (in Miles) Monte Carlo Simulation to Estimate Impact Variation with Distance PRELIMINARY – FOR ILLUSTRATION PURPOSES ONLY 42

43 Expected Impact in North Beacon Hill
Comparable Case Study: Dallas Light Rail Stop in Type 6 Neighborhood, 1996 Property values likely to increase significantly following construction of light rail stop

44 Key Issue: Minimize Displacement as Neighborhood Improves
What characterizes the neighborhoods that improved with less displacement?

45 DNT Findings: Drivers of “Improvement in Place”
Improvement with Low Turnover Is Associated With: High Home Ownership Rates Low Vacancy Rates Access to Transit Reduction in Unemployment Presence of Employment Services High Social Capital High Percentage of Young Adults "Homeownership, Social Capital and Reduction of Unemployment are Key to Improving Neighborhoods with Less Displacement

46 Select Interventions: What Should We Focus on Here?
Challenges and Opportunities Related to Light Rail Investment: Helps connect people to jobs Catalyst for commercial and mixed-use development Drives up property values, potentially causing displacement of original residents Analytic Tools Can Help Select and Implement Appropriate Interventions: Identify parcels for land banking Develop inclusionary zoning policy Target employment services and workforce development

47 Additional Tools and Applications
Impact of Light Rail Stops on Other Factors (e.g. Crime, Congestion, Retail Sales, etc.) Leveraging Light Rail Investment: Analyze impact of light rail in conjunction with other factors (e.g. different retail mixes, condo vs. rental, etc.) using DNT RSI and other outcome measures Commercial Corridor Analysis (Econsult): Current shopping patterns and factors affecting them Performance of individual shopping centers Model impact of changes in one corridor on other retail centers in the city Ongoing Impact Monitoring

48 Agenda Applying the DNT Tools II
a. Neighborhood Planning in Rainier Valley b. Informing Use of the Housing Levy c. Zoning Changes in Northgate d. Ongoing Impact Monitoring 48

49 Informing Use of the Housing Levy
Key Issues: Making the Case for Affordability Targeting location of affordable housing units Informing Implementation Analytic Tools: DNT RSI Affordability reports Impact Analyst Neighborhood Typology

50 Logic and Approach Making the Case for Affordable Housing
Track changes in housing affordability over time Targeting Interventions Opportunities for preservation: identify existing pockets of affordability Siting new projects: examine characteristics of project locations that have worked in the past, identify current comparables Informing Implementation Identify features associated with affordable housing projects that maximize their impact on residents and community

51 Making the Case: Percentage of Affordable Homes, 1986-2006
“Affordable” defined with respect to a household making AMI and spending 30% on housing 51

52 1988 Percentage of Affordable Homes, 1986-2006
“Affordable” defined with respect to a household making AMI and spending 30% on housing 52

53 1990 Percentage of Affordable Homes, 1986-2006
“Affordable” defined with respect to a household making AMI and spending 30% on housing 53

54 1992 Percentage of Affordable Homes, 1986-2006
“Affordable” defined with respect to a household making AMI and spending 30% on housing 54

55 1994 Percentage of Affordable Homes, 1986-2006
“Affordable” defined with respect to a household making AMI and spending 30% on housing 55

56 1996 Percentage of Affordable Homes, 1986-2006
“Affordable” defined with respect to a household making AMI and spending 30% on housing 56

57 1998 Percentage of Affordable Homes, 1986-2006
“Affordable” defined with respect to a household making AMI and spending 30% on housing 57

58 2000 Percentage of Affordable Homes, 1986-2006
“Affordable” defined with respect to a household making AMI and spending 30% on housing 58

59 2002 Percentage of Affordable Homes, 1986-2006
“Affordable” defined with respect to a household making AMI and spending 30% on housing 59

60 2004 Percentage of Affordable Homes, 1986-2006
“Affordable” defined with respect to a household making AMI and spending 30% on housing 60

61 2006 Percentage of Affordable Homes, 1986-2006
“Affordable” defined with respect to a household making AMI and spending 30% on housing 61

62 Targeting Interventions: Identifying Existing Pockets of Affordability
The affordability report data can be used to generate surfaces that identify the areas 62

63 Developing New Projects: What Worked in the Past?
Estimated Distance Decay Function – Seattle LIHTC Projects Impact analysis of LIHTC projects: LIHTC Projects generally positive for surrounding property values No significant effect on crime rates DNT Repeat Sales Index, 1 = No Impact Distance from Project Location (in Miles) Seattle Results: Larger, rehab projects had best results, particularly in lower income areas 63

64 Developing New Projects: What Worked in the Past?
Analyzing Individual Projects (EXAMPLE: Roxbury LIHTC)

65 Developing New Projects: What Worked in the Past?
Analyzing Individual Projects (EXAMPLE: Roxbury LIHTC)

66 Developing New Projects: What Worked in the Past?
EXAMPLE: Working with developer to identify promising sites based on neighborhoods where previous projects were successful APPROACH: Develop scorecard using RSI, Typology and housing values

67 Result: Scorecard Identifies Most Promising Candidates
Next Step: Isolate Factors Leading to Project Success

68 Additional Tools and Applications
Refine Affordability Measures: Incorporate public and subsidized housing stock, tie size of available units to size of households in need Identify Rapidly Appreciating Areas Apply NeighborhScope tool to identify areas at most risk of displacement Impact of Other Housing Programs: Section 8, Trust Fund, ... Inform Implementation: Analysis of impact of specific projects Housing mix: best mix of housing for different types of neighborhood “Housing in Context:” Identify mix of amenities and supporting services that maximize positive impact for residents and communities Ongoing Impact Monitoring

69 Agenda Applying the DNT Tools II
a. Neighborhood Planning in Rainier Valley b. Informing Use of the Housing Levy c. Zoning Changes in Northgate d. Ongoing Impact Monitoring 69

70 Zoning Changes in Northgate
Key Issues: Informing Visioning Process Guide Land Use Decisions Analytic Tools: Neighborhood Typology Impact Analyst

71 Logic and Approach Use Neighborhood Typology to Inform Visioning Process What type of neighborhood do you want to be? What demographics are you seeking to attract? What mix of uses does that imply? Evaluate Impact of Alternative Uses What will be the impact of different land uses on property values, crime, traffic, etc.? Support Land Development Process Commercial parcels database to help track ownership, tax status, etc. to facilitate land assembly Specialized market analysis to identify most promising type of retail and attract tenants

72 Possible Trajectories for the Neighborhood
Given Current status and type, 2 alternative visions are attainable: Type 7: “No Place Like Home” Mostly residential, very stable neighborhoods with a “suburban” feel. The single family homes that line the streets of these communities house middle income families raising their children, as well as retirees that stay in the neighborhood after their nests are empty. Type 8: “Close, Cool, Commercial” Vibrant neighborhoods with high turnover in their population, which is composed primarily of young professionals living in high-end rental units and condos. Few children frequent the streets in these communities, but the population of year-olds enjoys a high diversity and concentration of retail, services and entertainment venues.

73 Transitioning to a Different Neighborhood Type: Land Use Implications
Comparing Across Types: Type 6 New Development (Current) Type 7 Homeowners Type 8 Young Professionals Percent Year Old 35% 27% 44% Home Ownership Rate 25% 64% 23% Mixed Use Development 0.1% 0.3% 1% Commercial Land Use 8% 2% Single Family Housing 24% 75% 21% Entertainment Venues 3.69 2.43 4.26 What Would it Take to Become a Different Type of Neighborhood? 73

74 Evaluate Impact of Alternative Uses
EXAMPLE: New Shopping Center on Chicago’s Southwest Side New Shopping Center Estimated benefits to the community: $29 million in increased property values, or an average of $1,300 per home owner. 74

75 Additional Tools and Applications
Facilitate Land Assembly: Reduce land assembly costs by increasing availability of info on developable parcels, including location, ownership, tax status, etc. Identify Most Promising Sectors: Perform retail market analysis to identify leakage by retail sector Attract Developers and Retailers: Compile key market potential metrics by site (including leakage, buying power, psychographic profiles, etc.) to attract developers and retailers Ongoing Impact Monitoring

76 Agenda Applying the DNT Tools II
a. Neighborhood Planning in Rainier Valley b. Informing Use of the Housing Levy c. Zoning Changes in Northgate d. Ongoing Impact Monitoring 76

77 Logic and Approach Track Impact Over Time Conduct Formal Evaluation
See what’s working and what isn’t Mitigate side effects Conduct Formal Evaluation Formal impact analysis of alternative policies and programs Evaluate what works best where Tie Impact to Cost Evaluate cost-effectiveness of alternative strategies

78 Ongoing Impact Monitoring
Monitor intervention results using select outcome measures Outcomes may include property values, crime, vacancy rates, unemployment rates, etc. Relate outcome to costs in order to evaluate where the program is more or less effective

79 Monitor Impact: Modeling Strategies
Starting at least 1 year after program inception, conduct formal impact analysis to evaluate interventions. Evaluate in which areas the program has worked best, and why. Identify most cost-effective implementation strategies. Impact comparisons can be made across sub-areas within the same community area, and across sub-areas in different community areas but are the same neighborhood “type”. Results can be used to refine strategies and implementation, thus improving the effectiveness of future interventions.

80 Agenda Background: Developing New Tools for the Field I
Applying the DNT Tools: City Planning Examples II Moving Forward: Implications and Next Steps III Discussion IV 80

81 Where You Are Headed: Information Resources for the 21st Century
Data Integrated data platform routinely collects information from city departments and outside sources Established feedback loops between “change theories” and implementation results refine knowledge base Knowledge Tools Automated analytic systems deliver answers, not just data, to inform decision making and expand market activity

82 From Data to Decision-Making Tools

83 Next Steps: How Do We Get There?
Incrementally Build Information Infrastructure: Begin with centralized data capacity Expand database over time Start with metrics and tools that can be easily automated (e.g. RSI, Affordability) Build technical skill set to refine analytics Develop user-friendly platform Integrate strategic planning approach Establish feedback loops to refine plan and strategies based on implementation results

84 Agenda Background: Developing New Tools for the Field I
Applying the DNT Tools: City Planning Examples II Moving Forward: Implications and Next Steps III Discussion IV 84

85 Dynamic Neighborhood Taxonomy
“Building New Capacity for Neighborhood Development” City of Seattle, May 5, 2009 A Project of LIVING CITIES By RW Ventures, LLC


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