1. 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

2. 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

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

4. Extensive Data Collection Purposes: early warning, scope Data: owner type, funding, key dates, rents, capital needs summary

5. Intensive Data Collection Purposes: tenant advocacy, subsidy allocation, preservation transaction Data: financial detail, land use restrictions, owner’s intent, rehab needs

6. Moving Data to the Public Data available, useful for preservation- minded organizations Agencies collect data for various purposes

7. 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

8. 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

9. Assisted Housing Inventories AHI-General AHI-Preservation HUD USDA-RHS FHFC LHFAs

10. 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 Data Variables

15. Quarterly Excel files with property data on: Prepaid mortgages Opt-outs Potential opt-outs (from notices) Refinanced mortgages Mark-to-Market HUD Preservation Files

16. Limitations of Data from Sources Lack of unique property IDs Discrepancy in development data among data sources Holes in essential data Reporting lags

17. From Raw Data to AHI: Our Technical Approach Matching and merging of data files Unique Shim IDs Business rules Property-level ‘investigation’

18. 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%

19. 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

20. Our Challenges/Opportunities –Marketing the site –Tracking of properties –Accessing local data –Accessing other critical preservation- related variables

21. Website Florida Housing Data Clearinghouse: www.flhousingdata.shimberg.ufl.edu/ Assisted Housing Inventory: www.flhousingdata.shimberg.ufl.edu/ AHI_introduction.html

22. Shimberg Center for Affordable Housing University of Florida 203 Rinker Hall PO Box 115703 Gainesville, FL 32611-5703 Tel: 352-273-1192 Fax: 352-392-4364 Anne Ray: annelaurieray@yahoo.com Patricia Roset-Zuppa: roset@dcp.ufl.edu Diep Nguyen: diep@ufl.edu