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150128 ||| eng |
| 020 |
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|a 9781451872262
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|a Pinheiro, Marcelo
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| 245 |
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|a Exposure to Real Estate Losses
|b Evidence from the US Banks
|c Marcelo Pinheiro, Deniz Igan
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| 260 |
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|a Washington, D.C.
|b International Monetary Fund
|c 2009
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| 300 |
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|a 33 pages
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| 651 |
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4 |
|a United States
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| 653 |
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|a National accounts
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| 653 |
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|a Depository Institutions
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| 653 |
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|a Micro Finance Institutions
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| 653 |
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|a Money and Monetary Policy
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| 653 |
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|a Real estate prices
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| 653 |
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|a Loans
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| 653 |
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|a Macroeconomics
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| 653 |
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|a Credit
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| 653 |
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|a Personal income
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| 653 |
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|a Cycles
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| 653 |
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|a Banks
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| 653 |
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|a Real Estate Markets, Spatial Production Analysis, and Firm Location: General
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| 653 |
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|a Property & real estate
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| 653 |
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|a Monetary economics
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| 653 |
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|a Nonagricultural and Nonresidential Real Estate Markets
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| 653 |
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|a Housing
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| 653 |
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|a Prices
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| 653 |
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|a Mortgages
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| 653 |
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|a Financial institutions
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| 653 |
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|a Income
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| 653 |
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|a Business Fluctuations
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| 653 |
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|a Personal Income, Wealth, and Their Distributions
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| 653 |
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|a Banks and Banking
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| 653 |
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|a Banks and banking
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| 653 |
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|a Banking
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| 653 |
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|a Household Behavior: General
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| 653 |
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|a Monetary Policy, Central Banking, and the Supply of Money and Credit: General
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| 653 |
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|a Bank credit
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| 653 |
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|a Real Estate
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| 653 |
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|a Finance
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| 653 |
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|a Money
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| 653 |
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|a Industries: Financial Services
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| 700 |
1 |
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|a Igan, Deniz
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| 041 |
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7 |
|a eng
|2 ISO 639-2
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| 989 |
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|b IMF
|a International Monetary Fund
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| 490 |
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|a IMF Working Papers
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| 028 |
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|a 10.5089/9781451872262.001
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| 856 |
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|u https://elibrary.imf.org/view/journals/001/2009/079/001.2009.issue-079-en.xml?cid=22830-com-dsp-marc
|x Verlag
|3 Volltext
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|a 330
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| 520 |
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|a We implement a three-step procedure to assess the extent of exposure to real estate in commercial banks. First, we demonstrate interest rates and income to be the major determinants of delinquency. Then, we adopt a stress testing approach to calculate the impact of any adverse changes in these determinants. This suggests that a 1.3 percentage point increase in mortgage interest rate leads to a 20 percent decrease in a typical bank's distance to default. Finally, we look at the cross-sectional differences and indentify the banks with rapid loan growth along with high cost-income ratio as the most vulnerable
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