Neighborhood Effects of Concentrated Mortgage Foreclosures Schuetz, Been, Gould Ellen

1. Neighborhood Effects of Concentrated Mortgage ForeclosuresSchuetz, Been, Gould Ellen

2. Key Questions • What effect do foreclosures have on the value of surrounding properties? • How do the following factors effect the sale prices of nearby homes? • # of foreclosures in the immediate area • proximity of foreclosure(s) to the home for sale • timing of the foreclosure(s) in relation to the sale date of the nearby property

3. Terminology • Hedonic Regression • Typically used for real estate valuation. • Method of estimating value of real estate whereby the house being valued is “decomposed” into characteristics (# of bedrooms, sq footage, plot size, etc) • Used in lieu of specific market transaction data • Longitudinal Study • A correlational research study that involves repeated observations of the same items over long periods of time • Cross-Sectional Study • Observational study which takes place at a single point in time

4. Existing Research

5. Foreclosure Process In New York State • Stage 1 – borrower fails to make mortgage payments required by mortgage contract • 3 months unpaid • Lender options • Forbearance • Begin foreclosure process • Borrower options: • Make payments • Restructuring • Refinancing with different lender • Sell property (short-sale) • Convey deed

6. Foreclosure Process In New York State • Stage 2 – lender files lis pendens • Lis Pendens (LP) – notice filed by lender that states their intention to sue the property owner and reclaim the property if loan is not brought current • First public record of foreclosure process in NY • Study treats the lis pendens filing as starting point for foreclosure

7. Foreclosure Process In New York State • Stage 3 – Auction of Property • Judgment of Foreclosure and Sale • Notice of Sale is published • Date, time, location of auction • Address of property • Names of borrower and lender • MUST be advertised in newspaper or other media for 4 weeks

8. Foreclosure Process In New York State • Auction Proceedings • Property sold to highest bidder • 10% of purchase price upfront, balance within 30 days • Lender will usually buy if no private buyer • If Lender Purchases Property • Attempt to recover unpaid portion of loan • Re-sell • Bought and held (REO inventory)

9. Foreclosure Process In New York State • Foreclosure from lis pendens to auction is typically an 18-month process • Property is “unproductive” during this time • Equity right of redemption state

10. Hypotheses 1. Foreclosures Have a Negative Impact on Surrounding Housing Prices Reasons Why: • Property owners have less incentive to maintain a property they will lose • Visible signs of neglect drag down values of nearby properties • Vacant properties attract vandalism and crime • Adds to the local supply of available units • Auctioned properties are more likely to be sold to investors who will turn home into rental property • Higher turnover • Less stability in neighborhood • Maintenance issues • Property likely to sell at a discount • Negatively affect “comparables”

11. Hypotheses 2. Negative impacts of foreclosures will last for 18 months after filing the lis pendens and then diminish gradually as the property is returned to productive use • 18 months is average start to finish time of foreclosure in NY State

12. Data and Empirical Strategy • n ≈ 90,000 property sales • Dependent Variable = per unit sales price of residential properties in NYC • Restricted to sales between 2002-2005 • LP’s filed between 2000-2005 • 4 of the 5 Boroughs (excludes Staten Island) • Excludes LP’s not related to mortgage foreclosures (tax liens, mechanics liens, etc.) • Excludes non-residential properties & condos

13. Data and Empirical Strategy • Distance Bands > 0-250ft, 250-500ft, 500-1000ft • Time Intervals > identified the # of LP’s filed within each of those distance bands > 0-18 months prior to sale > 18+ months prior to sale - tests whether the impact of foreclosures extend beyond 18 mos. > 0-18 months post-sale (future foreclosures)

14. Data and Empirical Strategy • LPRICEijt = β0 + β1 LPijt + β2PropCharsij + ZIPj + Boro * quarter * year + εijt • LPRICEijt = log per sales price of property i in Zip code j in Quarter t • LPijt = number of LP filings within a given time and distance interval of property i • β2PropCharsij = characteristics describing property i • Square footage of lot, building, and unit • Unit age • Structure type (SF detached, SF attached, Duplex) • Distance to nearest subway stop • Building height (1,2+ stories) • ZIPj = set of zip code area fixed effects that control for time-invariant amenities • and characteristics of the local neighborhood • In plain English – NYC zips are small, fairly homogenous demographic and economic make-up • within. Therefore, they are reasonable approximations of neighborhoods. • Boro * quarter * year = borough-quarter-year time fixed effects • Control for time-varying economic trends that differ between borough

15. Data and Empirical Strategy • LP’s • highly concentrated • neighborhoods with low incomes, high % of minority residents, high # of subprime loans • Direction of Causality Concern • Do foreclosures reduce property values, or do foreclosures occur more frequently in lower-income and minority neighborhoods that typically have lower property values? • Use of longitudinal data helps to control for initial differences between properties that are located in the type of neighborhoods where foreclosures tend to occur.

16. Subprime Lending and Lis Pendens 2000-2005

17. Data and Empirical Strategy • > 32.3% of sales were within 0-250ft of an LP that had been filed in the prior 18 months • > 50.7% of sales were within 250-500ft of an LP that had been filed in the prior 18 months • > 75.8% of sales were within 500-1000ft of an LP that had been filed in the prior 18 months

18. Limitations • Cannot estimate the marginal effects of additional foreclosures in the smallest distance band because there are too few sales with 3+ foreclosure starts within 250ft. • More than 80% of foreclosure starts occurred in Brooklyn or Queens. Low # of foreclosure starts in Bronx or Manhattan. • Geographic concentration of foreclosures makes it difficult to identify the effect of a single foreclosure start. • Only 2,870 sales (out of 90K) did not have a foreclosure within 1,000 feet between 2000-2005. • Not a problem with 250ft and 500ft bands.

19. Limitations

20. Limitations • Geographic concentration also means many ZIPs lack either treatment or control sales • Limited sample to only zips that had at least one control sale and one treatment sale • PROBLEM > this method excludes neighborhoods hardest hit by foreclosure. There are no control sales there. • Limited information about the outcomes of distressed properties and the amount of time between LP and Resolution. • Do different outcomes have different effects on sale prices? • Timing and visible signs of deterioration vary between properties and these differences likely effect valuation of nearby properties.

21. Regression Results – Linear Model

22. Regression Results – Linear Model • The proximity of the foreclosure is significant. • the closer the foreclosure the greater the negative effect on price • conversely, the size of the impact decreases as distance between the sale and LP increases. • Prices are sensitive to small #’s of foreclosures in close proximity, while at greater distances, one or two foreclosures have no discernable impact.

23. Regression Results – Linear Model • Foreclosures continue to have an impact on nearby prices for longer than 18 months • Data suggests that the occurrence of future foreclosure starts is correlated with current conditions and property values. • Proximity of the future foreclosure is significant

24. Regression Results – Linear Model

25. Regression Results – Key Finding • Once post-sale measures are added, the coefficients on the counts of foreclosures in the 0-18 month time frame shrink to the point where they no longer provide statistically significant evidence that LP’s within 500ft prior to the sale decrease property values.

26. Regression Results – But Wait, There’s More • Authors argue that the marginal effects diminish with each additional foreclosure. • Propose a model that uses dummy variables to capture foreclosure activity. • Dummy Variables • Simple “Yes” or “No” tabulation • Yes = 1, No = 0

27. Regression Results – Dummy Table

28. Regression Results – Dummy Table • What does the Dummy tell us? • Properties near any LP’s within 0-18 months prior to sale sold at a discount, for all three distance bands. • Size of the impact decreases as the as the distance between LP and sale increases • Impact of LP’s 18+ months old are significant • Post-sale foreclosures are weakly significant

29. Regression Results – Dummy Table • Move from Single Dummy (Any) to Dummy Sets (1-2, 3+, 6+) • Column 4 • Indicates that in the 0-18 month window, only 3+ foreclosures within 250ft are significant • In the 500-1000 ft band, 0-18 month window, only 6+ foreclosures have a significant impact on sale price. • Column 5 • Same Model as Column 4, but only includes Zips with control and treatment sales • Excludes one-third of the Zips

30. Regression Results – Dummy Table

31. Regression Results • Alternative Tests on Data Revealed Similar Results • Used two bands instead of three (0-500ft and 500-1000ft) • Went below Zip Code level and included characteristics of the surrounding census tract • Similar results • Analyzed the significance of neighborhood density • Little to no impact. • Authors suggest this makes their study applicable to cities that are less dense

32. Regression Results • Evidence of a threshold effect; Being near a very small number of LP’s does not appear to consistently depress property values. • Housing prices are significantly lower in neighborhoods in which foreclosures will occur. • must control for pre-existing price differences or study will suffer from selection bias

33. Implications • Author suggests results justify government intervention • Threshold effect may help guide the targeting of resources • Do not treat all foreclosures equally • Direct prevention measures toward neighborhoods that have not yet had large numbers of foreclosures in order to prevent them from reaching the impact threshold

34. Implications • Idiosyncratic nature of the NYC market may make this study difficult to apply elsewhere • strong market in NYC during years from which data were collected • high rate of property value appreciation • foreclosed properties sell at a smaller discount and are vacant for shorter periods in strong markets • New York is a supply constrained market, whereas as California and Florida (where foreclosures are rampant) were over-built • NYC is more dense, has more multi-family units, and more rental units than anywhere else in the country

35. Additional Thoughts • Lis Pendens vs. Completed Foreclosures • Minimal impact if resolved quickly after filing of LP • May underestimate the negative effects of foreclosure • Does not tell us anything about the effect of foreclosures on property values in a declining or flat market • Is 18 months the appropriate limit? • Other sources suggest a shorter window for foreclosures in NY (120-180 days) • Source: Foreclosure.com

36. Additional Thoughts • Home prices in the Charlotte market fell 8.2% in January from a year earlier. • They fell 1.2% in January from December. • The 8.2% price decline was the fifth-smallest among the 20 markets tracked by the Standard & Poor’s/Case-Shiller Home Price Index. Source: Charlotte Business Journal, Charlotte Home Prices Fall 8.2%, 3/31/09

37. Additional Thoughts Foreclosure Filings Source: Charlotte Business Journal, Local Foreclosures Up 4% in 2008, 1/15/09

38. Foreclosure Activity – Charlotte, NC Source: RealtyTrac, February 2009

39. Foreclosure Activity – Charlotte, NC Foreclosure Filings – February 2009 Source: RealtyTrac, February 2009

40. Additional Thoughts • Is the study applicable to Charlotte? • Lower density • Fewer homes within bands (0-250 ft, 250-500ft) • Different real estate & foreclosure laws