2. Filtering down/up is a decline/increase in real value of a quality-adjusted unit of housing. The Filtering Model

3. 1. Y = Real Income 2. QL = Quality Measure 3. V = Real Value 4. Housing Market is assumed to be in Equilibrium: housing prices are stable and follow an identifiable path. Model Assumptions

4. Limits to Filtering-Up Supply price (quality adjusted) ≤ market value Limits to Filtering-Down Revenue (quality adjusted) ≥ Prime costs (fixed + user costs) Limits to Filtering up or Down

5. Equilibrium Description Number of housing units supplied = number demanded Quality of housing supplied ≥ quality demanded (over time … <) Demand for better quality housing will increase over time

6. Shifts From Equilibrium Price distortions in housing occur because of excess demand for higher quality space and excess supply of deteriorating space Switching and Transactions costs make it infeasible to repair, remodel, renovate or rebuild housing space as often as is necessary for “traditional” equilibrium to occur.

7. Low Income Housing Removal of Housing Slums Supply of Housing Slums Does the Filtering Model Work?

8. Neighborhood Externalities Profitability Bias Social Costs Sub-optimality of Housing Slums

9. When Is a Parcel or Property Subject to Filtering? Fixtures are obsolete or expended Neighborhood is in “transition” to highest and best use –or “second best” use “Quality” standards are unclear, undefined Holding period for investor is very long (10 to 20 years)

10. Filtering Solutions Market: redeveloping space Minimize land use and zoning restrictions Problem: Externalities and refiltering Public Policy: rehabilitating/renovating space Tax Credits Additional tax deductions Problem: what is low-income housing

11. Market Based Redevelopment Developer’s objective Developer’s observed behavior Develop and “hold” (manage) Develop, lease-up, sell Develop, sell Rent requirement: turning the pro-forma on its head Risk and sensitivity analysis