Abstract
This paper shows that household leverage as of 2006 is a powerful statistical predictor of the severity of the 2007–09 recession across U.S. counties. Those counties that experienced a large increase in household leverage from 2002 to 2006 showed a sharp relative decline in durable consumption starting in the third quarter of 2006—a full year before the official beginning of the recession in the fourth quarter of 2007. Similarly, counties with the highest reliance on credit card borrowing reduced durable consumption by significantly more following the financial crisis of the fall of 2008. Overall, the statistical model shows that household leverage growth and dependence on credit card borrowing as of 2006 explain a large fraction of the overall consumer default, house price, unemployment, residential investment, and durable consumption patterns during the recession. The findings suggest that a focus on household finance may help elucidate the sources of macroeconomic fluctuations.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Notes
For example, reduced recreational vehicle sales in Los Angeles County because of household leverage may lead to a sharp increase in unemployment in Elkhart County, Indiana, even though Elkhart County has low household leverage.
In a concurrent analysis, Glick and Lansing (2010) find similar results in the cross-section of western countries.
Iacoviello (2005) is an important exception.
See Carol D. Leonnig, “How HUD Mortgage Policy Fed the Crisis,” Washington Post, June 10, 2008. Available via the Internet: www.washingtonpost.com/wp-dyn/content/article/2008/06/09/AR2008060902626.html.
Throughout, the household default rate refers to the default rate on all household debt, including housing- and nonhousing-related debt. In our sample as of 2006, housing-related debt (mortgages and home equity lines) is on average 80 percent of total debt across U.S. counties. Further, a regression of housing-related default rates on total default rates yields an R2 of 0.98. In other words, most of the variation across counties in household default rates is driven by variation in housing-related default rates.
County-level census data are available at www2.census.gov/prod2/statcomp/usac/excel/.
The results using the full sample and equally weighting counties are qualitatively similar but are smaller in magnitude. This is consistent with higher measurement error in very small counties. Consistent with this explanation, the R2 of equally weighted regressions using the full sample are only between one-third and one-half as large as the R2 of population weighted regressions using the full sample.
In an unreported specification, we include census, 2001 economic condition, and 2001 industry share control variables in the column 6 specification and find similar results.
The correlation across counties between the increase in the debt-to-income ratio from 2002 to 2006 and the credit card utilization rate as of the fourth quarter of 2006 is statistically significantly negative. As a result, we are able to separately test the household leverage growth channel from the credit card reliant-consumer channel.
Deposit data by county for each bank are constructed using the Federal Deposit Insurance Corporation (FDIC) Summary of Deposit data. Data on charge-offs and net income are from Call Report data.
The covenant violation data are described in detail in Nini, Smith, and Sufi (2009). The corporate default data are from Moody's Default and Recovery Database.
All of these numbers are calculated using our sample.
By using predicted values, this magnitude assessment ignores unexplained (residual) variation. In other words, we compare magnitudes by using the economic outcomes that our model predicts for counties with varying degrees of household leverage, and ignoring any “unexplained” variation not predicted by our model.
Counties in the lowest leverage growth decile have a change in the debt-to-income ratio from 2002 to 2006 just above zero. The constant therefore represents an in sample prediction for these lowest decile leverage growth counties.
We focus on the lowest decile counties, because we prefer to avoid out of sample predictions. We should point out however, that household leverage growth and credit card utilization rates are strongly negatively correlated with a correlation coefficient of −0.31. Nonetheless, there exist counties that lie in the intersection of bottom deciles for the two factors.
References
Bernanke, Ben, and Mark Gertler, 1989, “Agency Costs, Net Worth, and Business Fluctuations,” American Economic Review, Vol. 79, No. 1, pp. 14–31.
Chari, V., Lawrence Christiano, and Patrick Kehoe, 2008, “Facts and Myths about the Financial Crisis of 2008,” Federal Reserve Bank of Minneapolis Working Paper No. 666.
Christiano, L., R. Motto, and M. Rostagno, 2007, “Financial Factors in Business Cycles,” (unpublished; European Central Bank, Frankfurt).
Demyanyk, Y., and O. Van Hemert, forthcoming, “Understanding the Subprime Mortgage Crisis,” Review of Financial Studies (article in press).
Dunkelberg, William, 2008, “Economic Responses to the Monetary Policy Signals of 2007: A Small Business Perspective,” University of Michigan RSQE Conference Proceedings.
Fisher, Irving, 1933, “The Debt-Deflation Theory of Great Depressions,” Econometrica, Vol. 1 (October), pp. 337–357.
Fisher, J., 2001, “Heterogeneous Investment Dynamics” (unpublished; Federal Reserve Bank of Chicago).
Gao, Pengjie, and Hayong Yun, 2009, “Commercial Paper, Lines of Credit, and the Real Effects of the Financial Crisis of 2008: Firm-Level Evidence from the Manufacturing Industry” (June 2009). Available via the internet: www.ssrn.com/abstract=1421908.
Glick, Reuvan, and Kevin Lansing, 2009, “U.S. Household Deleveraging and Future Consumption Growth,” Federal Reserve Bank of San Francisco Economic Letter No 2009-16 (May 15).
Glick, Reuvan, and Lansing, Kevin, 2010, “Global Household Leverage, House Prices, and Consumption,” Federal Reserve Bank of San Francisco Economic Letter No 2010-01 (January 11).
Gross, David, and Nicholas S. Souleles, 2002, “Do Liquidity Constraints And Interest Rates Matter For Consumer Behavior? Evidence from Credit Card Data,” The Quarterly Journal of Economics, Vol. 117, No. 1, pp. 149–185.
Iacoviello, M., 2005, “House Prices, Borrowing Constraints and Monetary Policy in the Business Cycle,” American Economic Review, Vol. 95, No. 3, pp. 739–764.
Ivashina, Victoria, and David Scharfstein, forthcoming, “Bank Lending during the Financial Crisis of 2008,” Journal of Financial Economics (article in press).
Keys, Benjamin, Tanmoy Mukherjee, Amit Seru, and Vikrant Vig, 2010, “Did Securitization Lead to Lax Screening: Evidence from Subprime Loans,” Quarterly Journal of Economics, Vol. 125, No. 1, pp. 307–362.
King, Mervyn, 1994, “Debt Deflation: Theory and Evidence,” European Economic Review, Vol. 38, No. 3–4, pp. 419–455.
Kiyotaki, Nobuhiro, and John Moore, 1997, “Credit Cycles,” Journal of Political Economy, Vol. 105, No. 2, pp. 211–248.
Leamer, Edward, 2007, “Housing Is the Business Cycle,” NBER Working Paper No. 13428 (Cambridge, Massachusetts, National Bureau of Economic Research).
Leamer, Edward, 2009, Macroeconomic Patterns and Stories: A Guide for MBAs (New York, Springer Publications, 1st ed.).
Mayer, Christopher, and R. Glenn Hubbard, 2008, “House Prices, Interest Rates, and the Mortgage Market Meltdown,” Columbia Graduate School of Business Working Paper.
Mian, Atif R., and Amir Sufi, 2009, “The Consequences of Mortgage Credit Expansion: Evidence from the U.S. Mortgage Default Crisis,” Quarterly Journal of Economics, Vol. 124, No. 4, pp. 1449–1496.
Mian, Atif R., and Sufi, Amir, forthcoming, “House Prices, Home Equity-Based Borrowing, and the U.S. Household Leverage Crisis,” American Economic Review.
Mishkin, Frederic, 1978, “The Household Balance Sheet and the Great Depression,” Journal of Economic History, Vol. 38, No. 4, pp. 918–937.
Nini, Greg, David Smith, and Amir Sufi, 2009, “Creditor Control Rights, Corporate Governance, and Firm Value,” Chicago Booth School of Business Working Paper.
Obstfeld, Maurice, and Kenneth Rogoff, 2009, “Global Imbalances and the Financial Crisis: Products of Common Causes,” Federal Reserve Bank of San Francisco Asia Economic Policy Conference Paper.
Saiz, Albert, 2008, On Local Housing Supply Elasticity (July 31). Available via the Internet: www.ssrn.com/abstract=1193422.
Tovar, Camilo E., 2008, “DSGE Models and Central Banks,” BIS Working Paper No. 258 (Basel, Bank for International Settlements).
Additional information
*Atir Mian is an Associate Professor of Economics, Finance and Real Estate at the University of California, Berkeley and Amir Sufi is an Associate Professor of Finance at the University of Chicago Booth School of Business. The authors thank Pierre-Olivier Gourinchas, Ayhan Kose, Kevin Lansing, two anonymous referees, and seminar participants at the University of Chicago (Booth), Duke University (Fuqua), Purdue University (Krannert), Harvard Business School, Princeton University, Wharton, NYU (Stern), and the Annual Research Conference at the IMF for comments. Timothy Dore provided superb research assistance. Thanks as well to the National Science Foundation, the Initiative on Global Markets at the University of Chicago Booth School of Business, the Center for Research in Security Prices, and the FMC Corporation for funding.
Appendix I
Appendix I
See Table A1.