Mortgage Choices and Housing Speculation
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1 Mortgage Choices and Housing Speculation Barlevy and Fisher Discussion by Amir Sufi University Chicago Booth School of Business and NBER September 2010
2 Overview of Discussion 1. The Credit Supply View of Housing Boom and Bust 2. Do Barlevy and Fisher supplant this view? Do they provide another manifestation of this view? 3. Main concern: Strong evidence that timing goes the opposite way: House price increases Use of interest only mortgages
3 The Credit Supply View of the U.S. Housing Boom/Bust A sharp increase in the willingness of lenders to provide mortgage finance is the primary explanation for the housing boom Why this increase in willingness? Evidence strongly contradicts productivity or income stories (Mian and Sufi (QJE, 2009)), which explains why this boom ended so badly Potential mispricing of risk given frictions in securitization (e.g., Keys, Mukherjee, Seru, Vig (QJE, 2010), Demyanyk and Van Hemert (RFS, 2010), Dell Ariccia, et al (2010)) Government policy
4 Consensus View? William Dudley, President of New York Fed, 2010 Similarly, the recent housing boom was driven by two innovations: (1) in housing finance, where subprime lending made mortgage credit available to households that were much less creditworthy, and (2) in structured finance instruments such as collateralized debt obligations (CDOs). Ben Bernanke, Chairman of the Federal Reserve Board, 2010 The availability of these alternative mortgage products proved to be quite important and, as many have recognized, is likely a key explanation of the housing bubble. Slide 8 shows the percentage of variable-rate mortgages originated with various exotic features, beginning in As you can see, the use of these nonstandard features increased rapidly from early in the decade through 2005 or Because such features are presumably not appropriate for many borrowers, Slide 8 is evidence of a protracted deterioration in mortgage underwriting standards, which was further exacerbated by practices such as the use of no-documentation loans.
5 House Price Appreciation in Subprime Versus Prime Zip Codes (Inelastic Housing Supply Cities) FCSW 150 W house pric ce index Prime zip codes (2000) Subprime zip codes (2000)
6 Barlevy and Fisher: Theory This study is related to the credit supply view, but the channel through which financing is related to house prices is quite different Theory: Allen and Gale (2000) inspired model in which house price bubble emerges because of uncertainty regarding a fundamental demand shock Numerical solution shows that back-loaded contracts (i.e., interest only mortgages) are preferred jointly by lenders and borrowers when prices are expected to rise above fundamentals This is a theory about timing rather than causation. Interest only y g y mortgages predict bubbles because they are used in anticipation of a bubble
7 Barlevy and Fisher: Empirics Concern #1: How is the IO mortgage channel related to the credit supply view? Is IO lending just a proxy for subprime lending? Or does it supplant subprime lending as the main predictor of boom/bust? we find no relationship between house price appreciation at the city level and the peak of subprime mortgages. Thus, expansion of the subprime market does not seem to be relevant for explaining why some cities experienced large boom- bust cycles in housing prices The answer to both questions is no.
8 Subprime and House Price Growth Strongly Correlated at MSA Level (Inelastic MSAs).8 FCSW Riverside-San Bernardino-Ontario, CA Miami-Miami Beach-Kendall, FL.8 Zillow.8 FHFA.4.6 ce growth, House pric.2 Los Angeles-Long Beach-Glendale, CA Fort Lauderdale-Pompano Beach-Deerfield Beach, FL Orlando-Kissimmee, FL West Palm Beach-Boca Raton-Boynton Beach, FL Port St. Lucie, FL Tampa-St. Petersburg-Clearwater, FL Oxnard-Thousand Oaks-Ventura, Atlantic City-Hammonton, CA NJ San Francisco-San Mateo-Redwood City, CA Newark-Union, NJ-PA Santa San Cruz-Watsonville, Jose-Sunnyvale-Santa Santa New CA Haven-Milford, Clara, CA CT Santa Rosa-Petaluma, CA Chicago-Naperville-Joliet, IL Jacksonville, FL.4.6 ce growth, Salinas, CA Portland-Vancouver-Beaverton, OR-WA Seattle-Bellevue-Everett, WAVallejo-Fairfield, CA Charleston-North Charleston-Summerville, SC Santa Barbara-Santa Diego-Carlsbad-San Maria-Goleta, CA Oakland-Fremont-Hayward, New York-White Marcos, CA CA Plains-Wayne, NY-NJ Barnstable Town, Milwaukee-Waukesha-West MA Allis, WI Boston-Quincy, MA House pric.2 Miami-Miami Beach-Kendall, FL Riverside-San Bernardino-Ontario, CA Fort Lauderdale-Pompano Beach-Deerfield Beach, FL Deltona-Daytona Beach-Ormond Virginia Beach-Norfolk-Newport Beach, FL News, VA-NC Orlando-Kissimmee, FL Los Angeles-Long Beach-Glendale, CA Atlantic City-Hammonton, NJ Palm West Bay-Melbourne-Titusville, Palm Beach-Boca Raton-Boynton FL Beach, FL Port St. Lucie, FL Tampa-St. Petersburg-Clearwater, FL Jacksonville, FL Oxnard-Thousand Oaks-Ventura, CA Seattle-Bellevue-Everett, Portland-Vancouver-Beaverton, WA OR-WA Salinas, CA Vallejo-Fairfield, CA Newark-Union, NJ-PA Santa Cruz-Watsonville, San Diego-Carlsbad-San Oakland-Fremont-Hayward, CA Marcos, CA CA Santa New Haven-Milford, New CT York-White Plains-Wayne, NY-NJ San Jose-Sunnyvale-Santa Rosa-Petaluma, Santa Barbara-Santa CA Maria-Goleta, CA Clara, CA San Francisco-San Mateo-Redwood City, CA Salt Lake City, UT Milwaukee-Waukesha-West Allis, WI Chicago-Naperville-Joliet, IL Barnstable Town, MA.4.6 ce growth, Charleston-North Charleston-Summerville, SC House pric.2 Riverside-San Bernardino-Ontario, Miami-Miami CA Beach-Kendall, FL Los Angeles-Long Beach-Glendale, CA Fort Lauderdale-Pompano Beach-Deerfield Beach, FL Port West Palm St. Palm Bay-Melbourne-Titusville, Lucie, Beach-Boca FL Raton-Boynton Beach, FL Deltona-Daytona Beach-Ormond FL Beach, FL Orlando-Kissimmee, FL Virginia Beach-Norfolk-Newport News, VA-NC Tampa-St. Oxnard-Thousand Oaks-Ventura, Atlantic City-Hammonton, Petersburg-Clearwater, CA NJ FL Salinas, CA Jacksonville, FL Vallejo-Fairfield, CA Santa Barbara-Santa Maria-Goleta, CA San Diego-Carlsbad-San Marcos, CA Portland-Vancouver-Beaverton, OR-WA Seattle-Bellevue-Everett, Oakland-Fremont-Hayward, WANew York-White CA Plains-Wayne, NY-NJ Newark-Union, NJ-PA Santa Rosa-Petaluma, CA San Santa Francisco-San Cruz-Watsonville, Jose-Sunnyvale-Santa Mateo-Redwood CA City, CA New Salt Clara, Haven-Milford, Lake City, CA UTCT Barnstable Town, MA Chicago-Naperville-Joliet, IL Milwaukee-Waukesha-West Allis, WI Boston-Quincy, MA Charleston-North Charleston-Summerville, SC New Orleans-Metairie-Kenner, LA Boston-Quincy, MA Cleveland-Elyria-Mentor, OH Cleveland-Elyria-Mentor, OH Cleveland-Elyria-Mentor, OH Subprime share of population, Subprime share of population, Subprime share of population, 2000 Why do the authors find no correlation between subprime share and house price growth? 1. Because their measure of subprime is awful: Their subprime share is only barely correlated with actual subprime borrowers data from Equifax 2. They use FHFA house price data, which completely ignores house price growth in subprime areas
9 Is Interest Only Simply a Proxy for Subprime (Properly Measured)? Dependent Variable: Zillow House Price Growth, 2002 to 2006 (1) (2) (3) (4) Max IO OShare 0.530** 0.546** 0.546** (0.099) (0.094) (0.094) Subprime Share 0.688** 0.723** 0.716** (0.176) (0.161) (0.172) Saiz Elasticity ** * * (0.014) (0.012) (0.013) (0.013) Subprime LPS (8.280) Constant 0.308** 0.266** (0.042) (0.061) (0.065) (0.065) Observations R-squared Th ff t b th t d l t th l! The effects are both strong and close to orthogonal! Correlation is very robust, not simply a proxy for expansion in credit supply Definitely something new here!
10 But What if Timing Goes the Wrong Way? I am definitely convinced that the correlation between interest only mortgages and house price growth is not just another channel for credit expansion to subprime borrowers There is something new and interesting here, and I agree that it is related to speculation But I remain concerned about timing 1. Authors want us to believe: IO mortgages house price growth 2. But other theories (credit constraints) would suggest: house price ( ) gg p growth IO mortgages
11 Test #1: When is Max House Price Growth Quarter Relative to Max IO Share Quarter? Zillow.04 Dens sity Max HP growth quarter - Max IO share quarter 77% of sample MSAs have their highest house price appreciation quarter before their highest IO share quarter! For FHFA house price index, also 77%. For FCSW house price index, 83%
12 The Usual Suspects (Highest 10 House Price Booms) MSA Max FCSW HP growth quarter Max Zillow HP growth quarter Max FHFA HP growth quarter Max IO Share quarter Las Vegas-Paradise, NV 2004q3 2004q3 2004q3 2006q4 Phoenix-Mesa-Scottsdale, AZ 2005q3 2005q3 2005q4 2006q4 Bakersfield, CA 2005q1 2005q1 2005q2 2007q1 Merced, CA 2005q q2 2007q1 Riverside-San Bernardino-Ontario, CA 2004q3 2004q3 2004q3 2007q1 Visalia-Porterville, ille CA 2005q2 2005q2 2005q1 2007q1 Lakeland-Winter Haven, FL 2005q4 2005q4 2006q1 2006q4 Orlando-Kissimmee, FL 2005q4 2005q3 2005q4 2007q1 Stockton, CA 2005q1 2005q1 2005q2 2007q2 Modesto, CA 2005q2 2005q2 2005q2 2007q1
13 Test #2: Granger Causality In light of results above, I was quite surprised with Granger causality test Authors restrict sample for Granger causality tests to (1) quarters before 2006q4 and (2) MSAs with a max IO share of at least 0.4 Results are very sensitive to these restrictions, and I m not sure why SAMPLE: Replicating Authors Decrease IO Share Max By 10% Full Sample up to 2006q1 Same MSAs as Authors, but extend to 2007q4 FHFA HP growth IO share IO share IO share IO share FHFA HP growth lagged 0.623** ** 0.186** 0.508** (0.029) (0.045) (0.027) (0.012) (0.046) IO share lagged 0.185** 0.412** 0.342** 0.172** 0.470** (0.023) (0.036) (0.024) (0.013) (0.040) Constant 0.008** 0.009** 0.005** 0.001* ** (0.001) (0.002) (0.001) (0.000) (0.002) Observations ,690 6, R-squared
14 Conclusions 1. The correlation between interest only mortgages and house price growth is extremely strong and is unrelated to the standard credit supply view supports the importance of speculation 2. But it does not supplant the credit supply view house price growth strongly positively correlated with the share of the population that is subprime 3 Authors need to work on showing IO mortgages predict house price 3. Authors need to work on showing IO mortgages predict house price growth and not vice versa
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