Credit Standards and Segregation Amine Ouazad Assistant Professor - PowerPoint PPT Presentation

Credit Standards and Segregation Credit Standards and Segregation Amine Ouazad Assistant Professor of Economics, INSEAD Romain Rancière Professor of Economics, Paris School of Economics GREQAM, Marseille, March 20, 2012

Credit Standards and Segregation Introduction Volume and LTI of Mortgages 4 3 2 1 1995 2000 2005 2010 year Whites African Americans Hispanics Asians

Credit Standards and Segregation Introduction Loan-to-Income Ratio 3 2.8 2.6 2.4 2.2 2 1995 2000 2005 year Whites African Americans Hispanics

Credit Standards and Segregation Introduction Missing Income Loans .08 .06 .04 .02 1995 2000 2005 year Whites African Americans Hispanics

Credit Standards and Segregation Introduction Mortgage credit boom Literature on Credit Supply, Lending Standard and Prices: Mian-Sufi (2009), Imbs and Favara (2010), Rajan-Ramcharan (2011), Dell’Arricia, Igan and Laeven (2009), Keys, Mukherjee, Seru and Vig (2010) Literature on Segregation and Market Prices: Cutler, Glaeser and Vidor (1999). Prices as barrier to integration. Literature on household preferences and schooling quality: Bayer, Ferreira, McMillan (2007), Bayer, Ferreira, Reuben (2004),

Credit Standards and Segregation Introduction Segregation matters Educational Achievement : Higher black-white test score gap in more segregated MSAs (Card and Rothstein 2007). Peer Effects in schools (Jackson 2010, Epple & Romano, 2010; Hoxby 2008; Angrist et al. 2004; Hoxby 2000; Zimmerman 2003), in neighborhoods (Case and Katz 1991; Maurin 2007) Employment: Cutler and Glaeser 1997, Topa 2001. Taxation Spillovers : Benabou 1996.

Credit Standards and Segregation Introduction Outline: Should more credit lead to more/less racial segregation? 1 Theoretical Predictions 2 Empirical Analysis 3 Conclusion

Theoretical Predictions

Credit Standards and Segregation Theoretical Predictions Framework The City Land & Housing Neighborhood 1, price p 1 . Neighborhood 2, price p 2 . Elasticity of housing supply ε j . Households Valuation v r , j of neighborhood j for race r . Minority and white households, income ω r . Density 2 of households overall, with a share s of minorities.

Credit Standards and Segregation Theoretical Predictions Framework Household Utility ∞ � β t U ( c j , r ( i ) , t ) + ν j , r ( i ) + I h ( i , j ) .ζ + ε i , j V i , j = t = 0 consumption c j , r , t in period t for race r in neighborhood j . β : time discount factor. ν j , r : valuation of neighborhood j . ν j , r = φ r W j + u j , r , φ r strength of social interactions, W j : fraction white in neighborhood j , u j , r : exogenous valuation of neighborhood j by race r . I h ( i , j ) = 1 if homeowner in neighborhood j . ζ : utility value of homeownership. Tax advantage, protection against fluctuations of rents, social status. ε i , j : extreme-value distributed unobserved utility.

Credit Standards and Segregation Theoretical Predictions Framework Credit Standards Lenders approve mortgages based on LTI and volume. In each neighborhood j , i , j = α j + β j · p j O ∗ + η i , j , O i , j = 1 if O ∗ i , j > 0 ω r η i , j extreme-value distributed unobservables. I h ( i , j ) = O i , j . Remarks Interpretation as lenders’ cost benefit analysis of lending. No discrimination assumption (cf Boston Fed Study). Potential correlation corr ( η i , 1 , η i , 2 ) = ρ .

Credit Standards and Segregation Theoretical Predictions Framework Housing Supply 1 /ε j MC ( H j ) = H j ε j : elasticity of housing supply in neighborhood j . Indifference between production for rental and production for homeownership. p j : price of the house, χ j : rental payments. No arbitrage condition: � t ∞ � 1 p j � p j = ⇒ χ j = χ j ⇐ 1 + ρ 1 + ρ − 1 t = 1

Credit Standards and Segregation Theoretical Predictions Framework Equilibrium Households choose consumption, neighborhood and housing status optimally. Competitive Developers supply housing in order to maximize profits. Competitive Lenders break even on loans originated. Housing market clears at prices p ∗ j , j = 1 , 2. Equilibrium : d j ( p ∗ 1 , p ∗ 2 , W 1 , W 2 ) = s j ( p ∗ 1 , p ∗ 2 ) , j = 1 , 2 W j = d White ( p ∗ 1 , p ∗ 2 , W 1 , W 2 ) , j = 1 , 2 j Existence and uniqueness proven for α 2 = ∞ . Equilibria in stochastic models with social interactions: Brock and Durlauf (2001).

Credit Standards and Segregation Theoretical Predictions Framework Segration and Lending Standards W j W · W j � Isolation w = s j j 1 a leverage effect results from higher probabilities of origination for a given level of income and for a given price 2 a general equilibrium effect results from an upward shift in demand, which drives prices up in the most valued neighborhood. dp ∗ d Isolation 2 , α, β ) = ∂ Isolation ∂ Isolation � j ( p ∗ 1 , p ∗ ( p ∗ 1 , p ∗ 2 , α, β ) + · d β ∂β ∂ p ∗ d β j j = 1 , 2 (1) The first term is typically negative, The sign and magnitude of this second effect depend on races’ incomes and valuations of the two neighborhoods.

Credit Standards and Segregation Theoretical Predictions Analytical Results Analytical Results Proposition (Fixed Supply, Equal valuations, Different incomes) If minority and nonminority households value neighborhoods equally, but minority households have lower income, then a relaxation of credit standards will lower racial segregation. Proposition (Fixed Supply, Different valuations, Equal incomes) If minority households value neighborhood 1 relatively more than nonminority households, and minority and nonminority households have the same income, then a relaxation of credit standards will increase racial segregation.

Credit Standards and Segregation Theoretical Predictions Simulations Simulations: Common Parameters Parameter Value Definition r 0 . 05 interest rate s 0 . 2 share of minority ω w 60 , 000 whites’ annual income ω b 40 , 000 minorities’ annual income γ 0 . 1 risk aversion α w = α b 2 . 5 no discrimination. σ 1000 standard deviation of the idiosyncratic valuation ε i , j ǫ 1 0 . 3 housing supply elasticity in neighborhood 1 ǫ 2 3 housing supply elasticity in neighborhood 2 ζ 10000 utility value of home ownership φ r , r = w , m 0 no social interactions

Credit Standards and Segregation Theoretical Predictions Simulations Simulations #1 and #2 Scenario v 2 , white ν 1 , white ν 1 , minority ν 2 , minority 1 10,000 2,000 10,000 2,000 2 10,000 2,000 5,000 2,000 Looseness of leverage constraint: β 1 = β 2 = β ∈ [ − 0 . 5 , 0 ]

Simulation #1: Equal Valuations Denial Rates Ownership rates 0.7 1 White (Neigborhood 1) White Minority (Neigborhood 1) Minority White (Neigborhood 2) Minority (Neigborhood 2) 0.6 0.9 0.5 0.8 0.4 0.7 0.3 0.6 0.2 0.5 0.1 0 0.4 −0.7 −0.6 −0.5 −0.4 −0.3 −0.2 −0.1 0 −0.7 −0.6 −0.5 −0.4 −0.3 −0.2 −0.1 0 Looseness of Leverage Constraint Looseness of Leverage Constraint

Credit Standards and Segregation Theoretical Predictions Simulations Simulation #1: Equal Valuations Relative Price 5 4.5 4 3.5 3 2.5 2 −0.7 −0.6 −0.5 −0.4 −0.3 −0.2 −0.1 0 Looseness of Leverage Constraint

Simulation #1: Equal Valuations Probability that Minorities live in Neighborhood 1 Isolation of Minorities 0.75 0.208 Probability that Minorities live in Neighborhood 1 Share of Population living in Neighborhood 1 0.207 0.7 0.206 0.65 0.205 0.6 0.204 0.203 0.55 0.202 0.5 0.201 0.45 0.2 −0.7 −0.6 −0.5 −0.4 −0.3 −0.2 −0.1 0 −0.5 −0.45 −0.4 −0.35 −0.3 −0.25 −0.2 −0.15 −0.1 −0.05 0 Looseness of Leverage Constraint Looseness of Leverage Constraint

Simulation #1: Equal Valuations Isolation of Whites Exposure of Whites to Minorities 0.2 0.88 0.1998 0.86 0.1996 0.84 0.1994 0.82 0.1992 0.8 0.199 0.78 0.1988 0.76 0.1986 0.74 0.1984 0.72 0.7 0.1982 −0.7 −0.6 −0.5 −0.4 −0.3 −0.2 −0.1 0 −0.5 −0.45 −0.4 −0.35 −0.3 −0.25 −0.2 −0.15 −0.1 −0.05 0 Looseness of Leverage Constraint Looseness of Leverage Constraint

Simulation #2: Different Valuations Relative Price Denial Rates 5 0.7 White (Neigborhood 1) Minority (Neigborhood 1) White (Neigborhood 2) Minority (Neigborhood 2) 0.6 4.5 0.5 4 0.4 3.5 0.3 3 0.2 2.5 0.1 2 0 −0.7 −0.6 −0.5 −0.4 −0.3 −0.2 −0.1 0 −0.7 −0.6 −0.5 −0.4 −0.3 −0.2 −0.1 0 Looseness of Leverage Constraint Looseness of Leverage Constraint

Simulation #2: Different Valuations Ownership rates Probability that Minorities live in Neighborhood 1 1 0.8 White Probability that Minorities live in Neighborhood 1 Minority Share of Population living in Neighborhood 1 0.7 0.9 0.6 0.8 0.5 0.7 0.4 0.6 0.3 0.5 0.2 0.4 0.1 −0.7 −0.6 −0.5 −0.4 −0.3 −0.2 −0.1 0 −0.7 −0.6 −0.5 −0.4 −0.3 −0.2 −0.1 0 Looseness of Leverage Constraint Looseness of Leverage Constraint

Simulation #2: Different Valuations Isolation of Minorities Isolation of Whites 0.5 0.48 0.88 0.46 0.86 0.44 0.84 0.42 0.82 0.4 0.8 0.38 0.78 0.36 0.76 0.34 0.74 0.32 0.72 0.7 −0.7 −0.6 −0.5 −0.4 −0.3 −0.2 −0.1 0 −0.7 −0.6 −0.5 −0.4 −0.3 −0.2 −0.1 0 Looseness of Leverage Constraint Looseness of Leverage Constraint