Working Paper: NBER ID: w13694
Authors: Sumit Agarwal; Chunlin Liu; Nicholas S. Souleles
Abstract: We use a new panel dataset of credit card accounts to analyze how consumers responded to the 2001 Federal income tax rebates. We estimate the monthly response of credit card payments, spending, and debt, exploiting the unique, randomized timing of the rebate disbursement. We find that, on average, consumers initially saved some of the rebate, by increasing their credit card payments and thereby paying down debt. But soon afterwards their spending increased, counter to the canonical Permanent-Income model. Spending rose most for consumers who were initially most likely to be liquidity constrained, whereas debt declined most (so saving rose most) for unconstrained consumers. More generally, the results suggest that there can be important dynamics in consumers' response to "lumpy" increases in income like tax rebates, working in part through balance sheet (liquidity) mechanisms.
Keywords: Consumer Spending; Debt; Tax Rebates; Credit Card Data
JEL Codes: D91; E21; E51; E62; G2; H31
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| tax rebates (H20) | initial increase in credit card payments (G21) |
| initial increase in credit card payments (G21) | temporary increase in liquidity (E51) |
| temporary increase in liquidity (E51) | subsequent increase in spending (E62) |
| tax rebates (H20) | increase in spending on credit card account (G51) |
| liquidity constraints (E41) | increased spending for liquidity constrained consumers (D12) |
| debt decline (H63) | increased savings among unconstrained consumers (E21) |
| dynamics of consumer behavior (D12) | operate through balance sheet liquidity mechanisms (G21) |
| randomized timing of rebate disbursement (G35) | clean identification of causal effects (C22) |