Preserving Affordable Rental Housing: The Role of Data

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Preserving Affordable Rental Housing The Role
of Data

• Anne Ray, Consultant
• Patricia Roset-Zuppa, Research Analyst
• Florida Housing Data Clearinghouse
• Shimberg Center for Affordable Housing,
  University of Florida
• 2007 Housing Policy Conference National Low
  Income Housing Coalition
• February 26, 2007

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Introduction

• Shimberg Center for Affordable Housing
• Florida Housing Data Clearinghouse
• MacArthur research by Shimberg and Florida
  Housing Finance Corporation
• Research of assisted housing preservation data
  and the development of risk assessment tools

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Extensive vs. Intensive Data Collection
Extensive Portfolio-wide, few key variables
Intensive Individual property, detailed
information
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Extensive Data Collection

• Purposes early warning, scope
• Data owner type, funding, key dates, rents,
  capital needs summary

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Intensive Data Collection

• Purposes tenant advocacy, subsidy allocation,
  preservation transaction
• Data financial detail, land use restrictions,
  owners intent, rehab needs

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Moving Data to the Public

• Data available, useful for preservation-minded
  organizations

Agencies collect data for various purposes
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Assisted Housing Inventory (AHI)

• Public database with development-level
  information for subsidized rental housing in
  Florida
• Since 2003
• Currently 2,244 properties with 279,201 units

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AHI Data Users and Uses

• Policymakers, Planners, Developers, Advocates
• Housing supply analysis for purpose of
• Preservation of existing affordable stock
• Program analysis and legislation
• Housing Element of Local Comprehensive Plan
• Consolidated Plan

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Assisted Housing Inventories
HUD USDA-RHS FHFC LHFAs
AHI-General
AHI-Preservation
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Data Variables

• Shim ID and link to map
• Development name and address details
• Unit count
• Bedroom breakdown
• Occupancy status
• Target population
• Funding source and program
• Approximate year built or year of funding
• Type of ownership
• Funding/affordability expiration dates

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HUD Preservation Files

• Quarterly Excel files with property data on
• Prepaid mortgages
• Opt-outs
• Potential opt-outs (from notices)
• Refinanced mortgages
• Mark-to-Market

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Limitations of Data from Sources

• Lack of unique property IDs
• Discrepancy in development data among data
  sources
• Holes in essential data
• Reporting lags

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From Raw Data to AHI Our Technical Approach

• Matching and merging of data files
• Unique Shim IDs
• Business rules
• Property-level investigation

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AHI What it Takes

• Cost
• Setup 2 full-time equivalents for 2 years
• Maintenance 1-1.25 full-time equivalents
• Database expert, housing expert, tech support
• Clearinghouse funding
• State 60-65
• Internal funding 30
• Grants and external contracts 5-10

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Strengths of AHI

• Comprehensive data sources and variables
• Relationships with data providers
• Critical data fields for preservation
• Funding and affordability expiration dates
• Type of ownership
• Year of construction
• Updated annually, some quarterly
• Public access
• Downloadable to Excel

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Our Challenges/Opportunities

• Marketing the site
• Tracking of properties
• Accessing local data
• Accessing other critical preservation-related
  variables

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Website

• Florida Housing Data Clearinghouse
• www.flhousingdata.shimberg.ufl.edu/
• Assisted Housing Inventory
• www.flhousingdata.shimberg.ufl.edu/
• AHI_introduction.html

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• Shimberg Center for Affordable Housing
• University of Florida
• 203 Rinker Hall
• PO Box 115703
• Gainesville, FL 32611-5703
• Tel [phone]
• Fax [phone]
• Anne Ray annelaurieray_at_yahoo.com
• Patricia Roset-Zuppa roset_at_dcp.ufl.edu
• Diep Nguyen diep_at_ufl.edu