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Consumer Revolving Credit and Debt Over the Life-Cycle and Business Cycle

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Consumer Revolving Credit and Debt Over the Life-Cycle and Business Cycle Consumer revolving credit and debt over the life-cycle and business cycle Scott L. Fulford1 and Scott Schuh2 1Boston College [email protected] 2Federal Reserve Bank of Boston [email protected] The views expressed in this paper are the author’s and do not necessarily reflect the official position of the Federal Reserve Bank of Boston or the Federal Reserve System. FDIC Credit and debt Scott L. Fulford and Scott Schuh -1- Changing credit and changing debt The relationship between consumer credit and debt On three different levels: In aggregate over business cycle On average over life-cycle For individuals Focus on credit cards Widely available and used Limits observable Start with descriptive and reduced from, then add insights from consumption theory to make sense of results Key distinction between credit cards as payments mechanism, and credit as a way to accumulate debt Introduction Credit and debt Scott L. Fulford and Scott Schuh -2- Background For most households, credit is larger than liquid assets, and is the marginal source for smoothing (Fulford (2015b) EER) Credit limits are much more volatile than income (Fulford (2015a) JME ) Household debts severely understudied (Zinman, forthcoming) Introduction Credit and debt Scott L. Fulford and Scott Schuh -3- Background For most households, credit is larger than liquid assets, and is the marginal source for smoothing (Fulford (2015b) EER) Credit limits are much more volatile than income (Fulford (2015a) JME ) Household debts severely understudied (Zinman, forthcoming) Other work has established increases in credit->increases in debts (Agarwal et al., 2015; Gross and Souleles, 2002) Limitations: Generally short term, for single credit accounts, and does not distinguish uses of credit cards for payments Introduction Credit and debt Scott L. Fulford and Scott Schuh -3- Background For most households, credit is larger than liquid assets, and is the marginal source for smoothing (Fulford (2015b) EER) Credit limits are much more volatile than income (Fulford (2015a) JME ) Household debts severely understudied (Zinman, forthcoming) Other work has established increases in credit->increases in debts (Agarwal et al., 2015; Gross and Souleles, 2002) Limitations: Generally short term, for single credit accounts, and does not distinguish uses of credit cards for payments Little empirical work on consumer credit over the life-cycle Some on mortgage debt over life-cycle, recent work on student loans Introduction Credit and debt Scott L. Fulford and Scott Schuh -3- Data Sources Equifax/CCP 5% sample of all credit accounts, with full history for an account (for computational reasons, actually use a smaller sample) Quarterly 1999-2015 Other than age, limited individual information beyond credit and debts Does not distinguish between those who revolve debt and those who pay full bill every month Survey of Consumer Payment Choice In field since 2008 Asks questions on consumer preferences and adoption of payment options Survey of Consumer Finances Data description Credit and debt Scott L. Fulford and Scott Schuh -4- Credit and debts vary, use does not 1 14000 .9 .9 .8 .7 10000 .6 8000 .5 .4 Credit utilization Credit .3 6000 Credit and debt ($ log ($ debt log scale) and Credit .2 5000 .1 0 4000 2000q1 2005q1 2010q1 2015q1 Date Mean credit card limit Mean credit card debt Mean credit utilization (right axis) Source: Author’s calculations from Equifax/CCP Business cycle Credit and debt Scott L. Fulford and Scott Schuh -5- Credit limits and debts increase with age Credit Card Limit 100 50 20 10 5 Credit Card Debt credit card limit or debt, thousands (if (if positive) thousands limit debt, card or credit 1 20 40 60 80 Age Credit utilization decreases slowly .8 Credit Utilization .6 .4 .2 Credit card debt / Credit Card limit Card / debt card Credit Credit 0 20 40 60 80 Age Life cycle Credit and debt Scott L. Fulford and Scott Schuh -7- Distribution of credit utilization All ages Age 20-30 Age 30-40 2 5 2.5 4 2 1.5 3 1.5 1 Density Density Density 2 1 .5 1 .5 0 0 0 0 .2 .4 .6 .8 1 1.4 0 .2 .4 .6 .8 1 1.4 0 .2 .4 .6 .8 1 1.4 Credit card utilization ratio Credit card utilization ratio Credit card utilization ratio Age 40-50 Age 50-60 Age 60-80 5 8 3 4 6 2 3 4 Density Density Density Density 2 1 2 1 0 0 0 0 .2 .4 .6 .8 1 1.4 0 .2 .4 .6 .8 1 1.4 0 .2 .4 .6 .8 1 1.4 Credit card utilization ratio Credit card utilization ratio Credit card utilization ratio Life cycle Credit and debt Scott L. Fulford and Scott Schuh -8- Credit utilization Credit utilizationit = θt + θa + αi + βCredit utilizationi,t− 1 + eit Credit utilizationt Credit utilizationt−1 0.874*** 0.868*** 0.647*** (0.000876) (0.000892) (0.00131) Constant 0.0479*** (0.000461) Observations 347,642 347,642 347,642 R-squared 0.741 0.743 0.429 Fixed effects No No Yes Age and year effects No Yes Yes Number of accounts 10,451 Frac. Variance from FE 0.477 Credit utilizationit = Dit /Bit Dit : Credit card debt (including both revolving and non-revolving) Bit : Credit limit (if positive) Life cycle Credit and debt Scott L. Fulford and Scott Schuh -9- Credit utilization: non-parametric 1.1 1.1 1.1 1 1 1 .9 .9 .9 .8 .8 .8 .7 .7 .7 .6 .6 .6 .5 .5 .5 one year two years one quarter .4 .4 .4 .3 .3 .3 Credit utilization in Credit utilization in Credit utilization in Credit utilization .2 .2 .2 .1 .1 .1 E[y|x] = 0.041 + 0.896x E[y|x] = 0.077 + 0.786x E[y|x] = 0.100 + 0.698x 0 0 0 0 .1 .2 .3 .4 .5 .6 .7 .8 .9 1 1.1 0 .1 .2 .3 .4 .5 .6 .7 .8 .9 1 1.1 0 .1 .2 .3 .4 .5 .6 .7 .8 .9 1 1.1 Credit utilization today Credit utilization today Credit utilization today .5 .5 .5 .4 .4 .4 .3 .3 .3 .2 .2 .2 .1 .1 .1 0 0 0 one year two years −.1 −.1 −.1 one quarter −.2 −.2 −.2 −.3 −.3 −.3 Difference in utilization incredit Difference in inutilization credit Difference in utilization incredit Difference −.4 −.4 E[y|x] = 0.666x −.4 E[y|x] = 0.339x E[y|x] = 0.128x −.5 −.5 −.5 −.5−.4−.3−.2−.1 0 .1 .2 .3 .4 .5 −.5−.4−.3−.2−.1 0 .1 .2 .3 .4 .5 −.5−.4−.3−.2−.1 0 .1 .2 .3 .4 .5 Difference in credit utilization Difference in credit utilization Difference in credit utilization from own mean from own mean from own mean Life cycle Credit and debt Scott L. Fulford and Scott Schuh -10- A little theory Convenience users: Credit card debts are some fraction of consumption. Should behave like consumption: Di,t = ωi,t Ci,t Revolvers: Credit card debts accumulate (or are paid off). Should behave like negative assets: Dit +1 = (1 + r )(Dit + Cit − Yit ) Life cycle Credit and debt Scott L. Fulford and Scott Schuh -11- A little theory Convenience users: Credit card debts are some fraction of consumption. Should behave like consumption: Di,t = ωi,t Ci,t Revolvers: Credit card debts accumulate (or are paid off). Should behave like negative assets: Dit +1 = (1 + r )(Dit + Cit − Yit ) Different relationships between past debts and current debts for revolvers and convenience users. Use to separate statistically between them (EM algorithm) Life cycle Credit and debt Scott L. Fulford and Scott Schuh -11- Fraction Convenience By age By utilization .8 .8 .6 .6 .4 .4 Fraction convenience users Fraction convenience users .2 0 .2 20 40 60 80 0 .5 1 Age Credit Utilization Fraction convenience: Estimated SCF Fraction convenience: Estimated SCF Life cycle Credit and debt Scott L. Fulford and Scott Schuh -12- Fraction revolving SCPC, conditional on having card .7 .6 revolving .5 Fraction .4 .3 20 30 40 50 60 70 Age Group Source: Author’s calculations from SCPC Life cycle Credit and debt Scott L. Fulford and Scott Schuh -13- Age and utilization .6 .4 utilization Credit .2 0 20 40 60 80 Age Convenience users Revolvers Overall utilization Life cycle Credit and debt Scott L. Fulford and Scott Schuh -14- Credit utilization Credit utilizationit = θt + θa + αi + βCredit utilizationi,t− 1 + eit Credit utilizationt All All All Revolvers Credit utilizationt−1 0.874*** 0.868*** 0.647*** 0.766*** (0.000876) (0.000892) (0.00131) (0.00125) Constant 0.0479*** (0.000461) Observations 347,642 347,642 347,642 R-squared 0.741 0.743 0.429 Fixed effects No No Yes Yes Age and year effects No Yes Yes Yes Number of accounts 10,451 Frac. Variance from FE 0.477 Life cycle Credit and debt Scott L. Fulford and Scott Schuh -15- Credit into debt Log Debtit = θi + θt + θa + αLog Limiti,t− 1 + βLog Debti,t− 1 + eit Log Debtt All All All Revolvers [1] [2] [3] [4] Log Debtt−1 0.505*** 0.758*** 0.604*** 0.859*** (0.00157) (0.00119) (0.00132) (0.000594) Log Credit Limitt−1 0.414*** 0.134*** 0.313*** 0.132*** (0.00262) (0.00148) (0.00243) (0.000784) Observations 296,369 296,369 361,280 361,280 R-squared 0.432 0.667 0.610 0.927 Accounts 10,028 10,718 10,718 Fixed effects Yes No Yes Yes Zero included No No Yes No Age effects Yes Yes Yes Yes Long term credit impact 0.862 0.875 0.879 0.990 Credit salience σ 0.443 0.665 0.530 0.754 Life cycle Credit and debt Scott L.
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