The U.S. Household Debt Overhang Karen Dynan Brookings Institution These slides were prepared for the 15 th Annual DNB Research Conference, “Household Finances and Behavior in Times of Crisis,” in Amsterdam, The Netherlands on October 25-26, 2012.
2 Popular interpretation of what has been going on …
3 “Debt overhang” refers to high levels of leverage that resulted from housing bust 0.7 Mortgage leverage jumped 0.6 when home prices plunged 0.5 0.4 Ratio 0.3 0.2 0.1 0.0 1980 1985 1990 1995 2000 2005 2010 Note. Ratio of U.S. home mortgage debt to the value of U.S. residential real estate. Shaded area denotes period of rapid home price declines. Data from the U.S. flow of funds accounts. Last value is 2012:Q2.
4 The Causes of the U.S. Household Debt Overhang
5 Underpinnings of the mortgage debt boom Strong U.S. housing demand in early 2000s: • » Solid economic fundamentals » Low interest rates » Increased prevalence of “affordable” mortgage products Boom became self-reinforcing: the more prices rose, the • more eager homeowners were to buy, the more willing lenders were to lend, the more willing investors were to supply funds » Neither regulators nor market discipline put a check on the cycle
6 Look more closely at the debt buildup using the Panel Study of Income Dynamics PSID background: • » Longitudinal household survey launched in 1968 » Currently done once every two years; most recently released full wave is for 2009 (8000 interviews) » Preliminary balance sheet data for 2011 Key concepts from Dynan (2012): • » Highly leverage homeowners = those in top quintile of mortgage leverage as of 2007 » Housing boom states = those in the top quartile of home price appreciation, 2000-2006 » Consumption = nonhousing consumption
7 Rapid house price appreciation was integral to the build-up of risk As of 2007, highly leveraged homeowners in housing boom states had … ... more debt ... more debt service ... higher consumption 0.5 0.5 Median ratio of mortgage debt to income Median ratio of consumption to income Median ratio of debt service to income boom boom boom 3 states states states 0.4 0.4 other other other states states states 0.3 0.3 2 0.2 0.2 1 0.1 0.1 0 0 0 Source: Dynan (2012)
8 Did it look risky? Depends on odds one attached to home prices reversing 90 th Percentile of 2007 Mortgage Leverage, by State Mortgage Leverage at 90th Percentile Mortgage Leverage at 90th Percentile Under assumption that Actual Actual Assuming Home Prices Fall* home prices reverted 1.8 1.8 Mortgage Leverage (P90 for State) Mortgage Leverage (P90 for State) 1.4 1.4 1 1 .6 .6 .2 .2 0 50 100 150 0 50 100 150 Percent Change in State Home Prices, 2000-2006 Percent Change in State Home Prices, 2000-2006 Source: Dynan (2012).
9 The Effects of High Leverage on Consumer Spending
10 Clear that U.S. regions with larger housing busts had deeper recessions Changes in Unemployment and Home Prices by State Trough-to-peak change inunemployment rate 12 10 8 6 4 2 0 -70 -60 -50 -40 -30 -20 -10 0 Peak-to-trough % change in home prices Source: First American Corelogic and U.S. Department of Labor.
11 But what was the role of leverage? The simplest models of consumption: • C i = f( Y i , W i , r i , preferences , uncertainty, etc ) » But debt and leverage typically do not enter. Reasons to think high leverage might matter: • » Households may be uncomfortable with leverage beyond a certain level » Financial institutions may be less willing to lend to and or refinance loans for high leverage (or high debt burden) households
12 Highly leveraged homeowners had a larger decline in consumption … 0 Median % decline in consumption -5 Other homeowners -10 -15 Highly leveraged homeowners -20 Note: Sample restricted to boom states. Source: Dynan (2012).
13 A larger decline in consumption … ... and notwithstanding a smaller ... even controlling for income decline in wealth 0 0 -0.02 -0.2 Median ∆W/Y Median ∆ C/Y -0.04 -0.4 Other homeowners -0.06 -0.6 Highly Highly leveraged -0.08 -0.8 leveraged homeowners Other homeowners homeowners -0.1 -1 Note: Sample restricted to boom states. Source: Dynan (2012).
14 To formalize, I estimate: ∆ C i ,09 = α + β W ∆ W i ,09 + β Y ∆ Y i ,09 + + β lev D/A i ,07 + γ X i ,09 + ε i ,09 Notes: Use ex ante leverage because ex post leverage might be • endogenous (also tried instrumenting ex post) Focus on mortgage leverage only because of incomplete • information about non-mortgage debt Downweight large values by applying the inverse hyperbolic • sine transformation
15 Selected regression results Dependent variable = change in nonhousing consumption Estimated for 2007-2009 change Pooled sample: Ex post Boom Non-boom 07-09 & 05- Baseline leverage states states 07 changes (IV) Δ State unemployment -.01 3.52 -1.11 .11 -.42 rate (1.77) (5.51) (2.66) (1.78) (1.21) Δ Income .11 ** .12 ** .05 * .11 ** .11 ** (.02) (.05) (.03) (.02) (.01) Δ Wealth .02 ** .03 *** .02 ** .02 ** .01 (.00) (.01) (.01) (.01) (.00) -6.07 * -7.80 * -5.40 ** Mortgage leverage -11.60 -4.62 (3.25) (9.17) (5.30) (4.11) (2.27) * Significant at 10 percent level, ** Significant at 5 percent level. Note. Standard errors in parentheses.
16 Implications for the U.S. Economy
17 Quantifying the macro effects At face value, point estimates suggest high leverage might be • holding back aggregate consumption growth by ¼ to ½ percentage point per year But lots of caveats: • » Measurement error could be attenuating coefficients » There might be nonlinearities in the relationship » The effects may have changed as conditions have evolved » Cannot tell for sure whether it’s leverage that matters or debt service, which has moved differently
18 U.S. household debt has declined 1.6 1.4 1.2 Ratio 1.0 0.8 0.6 0.4 0.2 0.0 1980 1985 1990 1995 2000 2005 2010 Note: Plot shows ratio of U.S. household debt to disposable personal income. Last value is 2012:Q2. Data from U.S. flow of funds accounts and U.S. national income and product accounts.
19 But, the decline in aggregate debt has been very uneven A large share has been accounted for by defaults • Another substantial share has been accounted for by • reduced new borrowing » First-time homeownership has fallen to extremely low levels by historical standards The implication is that defaulters and would-be borrowers • have much less debt than they otherwise would
20 Many other households made little progress deleveraging between 2009 and 2011 10 2009 2011 Percent of PSID sample 8 6 4 2 0 0-0.1 0.1-0.2 0.2-0.3 0.3-0.4 0.4-0.5 0.5 + Amount by which leverage ratio exceeded benchmark Note. Benchmark is 2005 leverage, except for new homeowners, whose benchmark is assumed to be 0.9. Source: Dynan (2012).
21 Policy Challenges Related to Balance Sheets
22 To save or not to save
23 Is debt forgiveness the solution? Debt forgiveness or “principal writedown” programs could lead • to an immediate strengthening of balance sheets—good for the short run and for the long run But lenders not likely to do this on their own • » Unprofitable to write down loans for the large numbers of underwater borrowers that are still current » Writedowns for just delinquent borrowers would encourage others to stop paying Obstacles to using tax payer dollars to incentivize • » Politically controversial » Opportunity cost of the money
24 Lessons and directions for future research Research suggests that high leverage is holding back U.S. • economic activity. But need more work on: » Quantitative importance of high leverage » Channels through which it is affecting consumption Experience of last few years has implications for tools used • by policy analysts » Need better tools for detecting buildups of risk (especially in the tails) » Need to recognize the limits of macro models and complement with micro analysis
25 References Dynan, Karen. 2012. “Is a Household Debt Overhang Holding Back Consumption?” Brookings Papers on Economic Activity Spring 2012 . Available at: http://www.brookings.edu/~/media/projects/bpea/spring%202012 /2012a_dynan.
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