Replication data for: A Simple Model of Subprime Borrowers and Credit Growth
Principal Investigator(s): View help for Principal Investigator(s) Alejandro Justiniano; Giorgio E. Primiceri; Andrea Tambalotti
Version: View help for Version V1
Name | File Type | Size | Last Modified |
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P2016_1087_data | 10/26/2021 02:00:PM | ||
LICENSE.txt | text/plain | 14.6 KB | 12/07/2019 07:51:AM |
Project Citation:
Justiniano, Alejandro, Primiceri, Giorgio E., and Tambalotti, Andrea. Replication data for: A Simple Model of Subprime Borrowers and Credit Growth. Nashville, TN: American Economic Association [publisher], 2016. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2019-12-07. https://doi.org/10.3886/E116314V1
Project Description
Summary:
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The surge in credit and house prices that preceded the Great Recession was particularly pronounced in ZIP codes with a higher fraction of subprime borrowers (Mian and Sufi, 2009). We present a simple model with prime and subprime borrowers distributed across geographic locations, which can reproduce this stylized fact as a result of an expansion in the supply of credit. Due to their low income, subprime households are constrained in their ability to meet interest payments and hence sustain debt. As a result, when the supply of credit increases and interest rates fall, they take on disproportionately more debt than their prime counterparts, who are not subject to that constraint.
Scope of Project
Subject Terms:
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Steady state analysis;
General equilibrium model;
Model simulation
JEL Classification:
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D14 Household Saving; Personal Finance
E32 Business Fluctuations; Cycles
E44 Financial Markets and the Macroeconomy
G01 Financial Crises
G21 Banks; Depository Institutions; Micro Finance Institutions; Mortgages
R31 Housing Supply and Markets
D14 Household Saving; Personal Finance
E32 Business Fluctuations; Cycles
E44 Financial Markets and the Macroeconomy
G01 Financial Crises
G21 Banks; Depository Institutions; Micro Finance Institutions; Mortgages
R31 Housing Supply and Markets
Geographic Coverage:
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United States
Time Period(s):
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1/2000 – 12/2006
Data Type(s):
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program source code
Methodology
Unit(s) of Observation:
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ZIP codes,
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