Bealey, Timothy and Meads, Neil and Surico, Paolo (2010): Risk heterogeneity and credit supply: evidence from the mortgage market. Published in: External MPC Unit Discussion Paper No. No.29 (22. February 2010)
Download (615kB) | Preview
This paper uses a unique data set on more than 600,000 mortgage contracts to estimate a credit supply function which allows for risk-heterogeneity. Non-linearity is modelled using quantile regressions. We propose an instrumental variable approach in which changes in the tax treatment of housing transactions are used as an instrument for loan demand. The results are suggestive of considerable risk heterogeneity with riskier borrowers penalised more for borrowing more.
|Item Type:||MPRA Paper|
|Original Title:||Risk heterogeneity and credit supply: evidence from the mortgage market|
|Keywords:||individual mortgage data, credit supply, risk pricing, heterogeneous effects, instrumental variable.|
|Subjects:||D - Microeconomics > D1 - Household Behavior and Family Economics > D10 - General
E - Macroeconomics and Monetary Economics > E2 - Consumption, Saving, Production, Investment, Labor Markets, and Informal Economy > E21 - Consumption ; Saving ; Wealth
G - Financial Economics > G2 - Financial Institutions and Services > G21 - Banks ; Depository Institutions ; Micro Finance Institutions ; Mortgages
|Depositing User:||Neil Meads|
|Date Deposited:||24. Feb 2010 06:03|
|Last Modified:||07. Jul 2015 10:53|
Abadie, A., J., Angrist, and G. Imbens, 2002, Instrumental Variables Estimates of the Effect of Subsidized Training on the Quantiles of Trainee Earnings, Econometrica 70, pp. 91--117
Blundell, R., A. Duncan and C. Meghir, 1998, Estimating Labor Supply Responses Using Tax Reform Data, Econometrica 66, pp. 827--861.
Chernozhukov, V. and C. Hansen, 2005, An IV model of quantile treatment effects, Econometrica 73, pp. 245--262.
Chernozhukov, V. and C. Hansen, 2004, The effects of 401(k) Participation on the Wealth Distribution: an Instrumental Quantile Regression Analysis, Review of Economics and Statistics 86, pp.735--751.
Chesher, A., 2005, Nonparametric identification under discrete variation, Econometrica 73, pp. 1525-1550.
Chiang, R.C., Y.F. Chow and M. Liu, 2002, Residential Mortgage Lending and Borrower Risk: the Relationship between Mortgage Spreads and Individual Characteristics, Journal of Real Estate Finance and Economics 25, pp. 5--32.
Deng, Y.H., J. Quigley, and R. Van Order, 2000, Mortgage Terminations,Heterogeneity and the Exercise of Mortgage Options, Econometrica 68, pp. 275---307.
Garcia, J., P. Hernandez and A. Lopez-Nicolas, 2001, How Wide is the Gap? An Investigation of Gender Wage Differences Using Quantile Regression,Empirical Economics 26, pp. 149--167.
Kau, J.B. and D.C. Keenan, 1995, An Overview of the Option-Theoretic Pricing of Mortgages, Journal of Housing Research 6, pp. 217---244.
Keys, B.J., T.K. Mukherjee, A. Seru, and V. Vig, 2009, Did Securitization Lead to Lax Screening? Evidence from Subprime Loans, Quarterly Journal of Economics, forthcoming.
Koenker, R. and G.S. Bassett, 1978, Regression quantiles, Econometrica 46, pp. 33--50.
Mian, A. and A. Sufi, , 2009, The Consequences of Mortgage Credit Expansion: Evidence from the U.S. Mortgage Default Crisis, Quarterly Journal of Economics 124, pp. 1449-96.
Miles, D,.2004, The UK Mortgage Market: Taking a longer-term view, HM Treasury
Miles, D,.1994, Housing, Financial Markets and the Wider Economy,Wiley.
Stock, J., Wright, J.H. and M. Yogo, 2002, A Survey of Weak Instruments and Weak Identification in Generalized Method of Moments,Journal of Business & Economic Statistics 20, pp. 518--529.
Stock, J. and M. Yogo, 2001, Testing for Weak Instruments in Linear IV Regression, unpublished manuscript, Harvard University.
Tsai, M.S., S.L. Liao and S.L. Chiang, 2009, Analyzing Yield, Duration and Convexity of Mortgage Loans under Prepayment and Default Risks, Journal of Housing Economics 18, pp. 92---103.