Financial Regulation and Securitization: Evidence from Subprime Loans

By Benjamin J. Keys, Tanmoy Mukherjee, Amit Seru, Vikrant Vig. 2009

295 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/32ded916d40d04f6e3dc1d5bdaff0949b8eb4d5b

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Citations in the corpus

Advertising Expensive Mortgages (2016, methodology): “, Keys et al. (2010)), we capture loan performance using an indicator that takes a value of one if the borrower becomes 90 or more days late (90+ delinquent) in making payments within two”
Who Facilitated Misreporting in Securitized Loans (2016, background): “The figure highlights a discontinuity at a credit score of 620 for low/nodocumentation loans and a discontinuity at a credit score of 580 for full-documentation loans (for fulldocumentation loans we find the discontinuity at 600 shown in Keys et al. (2010), but at 580 the discontinuity in our sample”
Securitization and Distressed Loan Renegotiation: Evidence from the Subprime Mortgage Crisis (2010, unknown): “The reason to focus on these loans is that several studies provide evidence that potential screening on unobservables is less important for these types of loans (Keys et al., 2009; Keys et al., 2010; Rajan et al., 2008).”
Securitization is Not that Evil after All (2011, unknown): “Keys et al (2009) also look at securitization and moral hazard.”
Stronger Risk Controls, Lower Risk: Evidence from U.S. Bank Holding Companies (2012, unknown): “These results are related to the finding in Keys et al. (2009) that lenders with relatively powerful risk managers, as measured by the risk manager’s share of the total compensation given to the five highest-paid executives in the institution, had lower default rates on the mortgages they…”
Asset Quality Misrepresentation by Financial Intermediaries: Evidence from the RMBS Market: Asset Quality Misrepresentation by Financial Intermediaries (2015, unknown): “Not surprisingly, a wide body of research shows that the information collected by credit bureaus, summarized in their credit scores, has a strong predictive power in explaining borrower risk (see Keys et al. (2010)).”
Housing, Finance and the Macroeconomy (2014, unknown): “They model a heterogeneous agent economy two “Lucas”-type trees, non-housing goods and housing, as in the model of Piazzesi, Schneider, and Tuzel (2007). The aggregate endowment of dividends of both trees is stochastic, and households differ in their realizations of the non-housing endowment (labor ”
Macroprudential Policy - A Literature Review (2012, unknown): “Keys et al. (2009) find that in US states with more stringent laws on mortgage brokers, lending standards were loosened to a lesser degree as a result of securitization than in other states in the United States.”
Wall Street and the housing bubble (2014, background): “…towards lax screening of subprime borrowers (Agarwal and Ben-David, 2012; Berndt and Gupta, 2009; Demyanyk and Van Hemert, 2011; Jiang, Nelson and Vytlacil, 2011; Keys et al., 2009, 2010, 2012; Mian and Sufi, 2009; Piskorski, Seru and Witkin, 2013; Purnanandam, 2011; Rajan, Seru and Vig, 2012).”
Monetary Policy and the Global Housing Bubble (2011, unknown): “For example, the evidence in Nadauld and Sherlund (2009) suggests that raising capital requirements on assets that are long on the bubble might limit the growth of that bubble; in another example, Keys et al. (2009) find that in states with laws that require mortgage brokers to have ‘skin in the gam”