Mortgage Loan-Flow Networks and Financial Norms∗

We develop a theoretical model of a network of intermediaries, which gives rise to heterogeneous financial norms and systemic vulnerabilities. The optimal behavior of each intermediary regarding its attitude toward risk, the quality of the projects that it undertakes, and the intermediaries it chooses to interact with, is affected by the behavior of its counterparties. These strategic network effects influence the financial strength and systemic vulnerability of individual intermediaries, as well as in aggregate. We apply the model to the mortgage-origination and securitization network of financial intermediaries in the U.S., using a data set containing all of the more than three million private-label, fixed-rate mortgages originated and securitized between 2005 and 2007, for which we track the ex-post default performance using loan flows to define linkages. We find that default risk was closely related to network position and evolved in a predictable manner among linked nodes, and document a positive relationship between a firm’s estimated quality and its labor intensity. This suggests that network effects are of vital importance in the U.S. mortgage market. JEL classification: G14. ∗A previous version of this paper was circulated under the title “Securitization Networks and Endogenous Financial Norms in U.S. Mortgage Markets.” We are grateful for financial support from the Fisher Center for Real Estate and Urban Economics. We thank seminar participants at the 2015 meeting of the Western Finance Association, the 2015 NBER Summer Institute conference on Risks of Financial Institutions, the Consortium for Systemic Risk Analytics (MIT), the Institute for Pure and Applied Mathematics (IPAM, UCLA), the Fall 2014 Journal of Investment Management Conference, FIRS 2016, the 2016 ITAM Finance, the 2016 meeting of the European Finance Association, BI Norwegian Business School, Carnegie Mellon, the Federal Reserve Bank of San Francisco, London Business School, London School of Economics, NYU Stern, Swedish Institute for Financial Research (SIFR), University of Alberta, University of Oregon, University of Lausanne, University of Wisconsin-Madison, the Norwegian School of Economics, and Stanford GSB. We are grateful to Daron Acemoglu, Maryam Farboodi, Xavier Gabaix, Michael Gofman, Burton Hollifield, George Papanicolaou, Roger Stein, and Stijn Van Nieuwerburgh for helpful comments and suggestions. Walden thanks the 2015 IPAM program on financial mathematics for hosting his visit, during which part of this research was carried out, and the Swedish House of Finance for valuable support. †Haas School of Business, U.C. Berkeley, [email protected]. ‡Haas School of Business, U.C. Berkeley, [email protected]. §Haas School of Business, U.C. Berkeley, [email protected].