Contract Terms, Employment Shocks, and Default in Credit Cards

Layer 1 — Overview

Research Question

This paper asks two related questions bearing on financial inclusion policy in developing countries: (1) How effective are credit card contract term changes — specifically interest rate reductions and minimum payment increases — in limiting default among new borrowers? (2) How large is the effect of formal-sector job loss on default relative to these contract term interventions, and can the difference in magnitudes be explained by differential cash flow impacts?

Setting and Data

The study is set in Mexico during 2007–2009 and exploits a large nationwide stratified randomized controlled trial implemented by a major commercial bank (“Bank A”) on its financial-inclusion credit card — a product that accounted for approximately 15% of all first-time formal-sector loans in Mexico as of 2010. The study card was targeted at borrowers with limited or no formal credit history (the bank’s “C, C- and D” customer segments); 47% of the experimental sample held it as their first formal loan product. A sample of 144,000 pre-existing cardholders was stratified into nine cells based on bank tenure (6–11 months, 12–23 months, 24+ months) and past repayment behavior, then randomly allocated to eight treatment arms combining two minimum payment levels (5% or 10% of the outstanding balance) and four annual interest rates (15%, 25%, 35%, 45%), for 26 months (March 2007 to May 2009). The study sample is representative of the bank’s national portfolio of approximately 1.3 million study card customers. Card-level data run through December 2014 — five years after the experiment ended — allowing examination of both short- and long-run effects. The experimental sample is matched to Mexico’s Social Security database (IMSS), providing monthly formal employment histories from January 2004 to December 2012 for 59% of the sample; and to credit bureau data, allowing observation of defaults across all formal financial institutions.

Main Findings with Quantitative Magnitudes

Result 1 — Interest rate effects are modest in aggregate. A 30 percentage point (pp) decrease in the annual interest rate (from 45% to 15%, a 67% reduction relative to the baseline rate) decreased cumulative default by 2.5 pp over the 26-month experiment, for a default elasticity of +0.20. Over the same 18-month horizon used for unemployment comparisons, the implied effect is 1.03 pp. These magnitudes are substantially smaller than predictions elicited from Mexican central bank regulators (mean predicted decrease: 8.6 pp) and from participants on the Social Science Prediction Platform (mean predicted decrease: 5 pp). Default continued to decline in the lower-rate arm for approximately three years after the experiment ended, reaching −1 pp by March 2012, after which effects became statistically indistinguishable from zero.

Result 2 — No effect on the newest borrowers. For the newest borrowers (those with 6–11 months of tenure when the experiment began — the group with a 36% cumulative default rate over 26 months versus 18% for those with 24+ months of tenure), the interest rate reduction has no effect on default over the 26-month period, with point estimates consistently small and statistically indistinguishable from zero. This is in contrast to older borrowers, who are meaningfully responsive.

Result 3 — Minimum payment increases increase short-run default but reduce long-run default. Doubling the minimum payment from 5% to 10% of outstanding balance increased cumulative default by 0.8 pp by the end of the experiment (26-month elasticity: +0.04; p = 0.016), driven primarily by defaults occurring within the first year. The short-run increase is concentrated among the most liquidity-constrained borrowers — those with the highest baseline debt utilization and those in the minimum-payer stratum (baseline debt utilization rate of 85%). After the experiment ended and all arms were returned to the same 4% minimum payment, the previously higher-minimum-payment arm exhibited persistently lower default, reaching a 1 pp decline by the end of the sample (p = 0.054 at end of study period), relative to a base default rate of 41% at that point.

Result 4 — Job displacement effects are seven times larger than contract term effects. Formal-sector job displacement (identified using mass layoff events at firms with 50+ employees, defined as year-on-year employment contractions exceeding 30% of prior-year average employment) increased cumulative default by 4.8 pp after 12 months and 7.6 pp after 18 months. This is seven times larger than the effect of a 30 pp interest rate decrease (1.03 pp over 18 months) and nine times larger than the effect of doubling minimum payments (0.8 pp). Formal job loss alone can explain approximately 14% of total study card default during the experiment (calculation: 19.8% of formally employed study card borrowers lose their job at least once in the first 18 months; multiplied by the 7.6 pp default increase per spell, this yields 1.5 pp of the 10.8% base default rate at 18 months). Results are corroborated using a nationally representative matched credit bureau–IMSS sample of 600,339 borrowers, which yields 8,723 mass layoff events and similar estimates.

Per-peso normalization. A back-of-the-envelope calculation normalizes all three shocks by their respective cash flow impacts. The interest rate decrease reduces cumulative required minimum payments due by 2,917 MXN pesos over 18 months; the minimum payment doubling increases them by 1,325 MXN pesos; formal job loss reduces total labor earnings by an estimated 21,328 MXN pesos (adjusting formal-sector earnings losses of 77,555 MXN pesos downward by 72.5% to reflect that 82% of workers who lose formal employment transition to informal employment in the following quarter, with total earnings falling only 27.5%). The per-peso default effects are: 0.36 pp per 1,000 MXN pesos for the interest rate intervention; 0.51 pp for the minimum payment intervention; and 0.36 pp for job displacement. The null hypothesis that all three per-peso effects are equal cannot be rejected (p = 0.78).

Interpretation

The authors present a simple two-period optimizing model emphasizing the role of previously accumulated debt and liquidity constraints. The model generates four testable predictions consistent with the data: (1) lower interest rates decrease default via reduced debt burden; (2) higher minimum payments increase short-run default by tightening liquidity constraints; (3) “surprise” minimum payment increases (where borrowers anticipated they would continue) reduce post-experiment default via debt reduction; (4) negative income shocks (modeled as first-order stochastic dominance deterioration in period-2 income) increase default. The per-peso normalization supports the interpretation that cash flow impacts — not differential per-peso susceptibility to shocks — drive the relative magnitudes of the three effects.

Layer 2 — Q&A

Q1: Why is the interest rate elasticity of default (0.20) so much lower than prior estimates in the literature?

A: The paper contrasts its 26-month elasticity of +0.20 with estimates from Karlan and Zinman (2019) (1.8) and Adams et al. (2009) (2.2), and notes it falls in the same range as Karlan and Zinman (2009) (0.27) and DeFusco et al. (2021) (0.01). The paper proposes that variation in borrower tenure may partly explain cross-study differences, as default elasticities appear to be increasing in bank tenure. The newest borrowers — the most policy-relevant subgroup — show zero elasticity, pulling the overall estimate down. The paper also argues that in this context, interest-rate-driven moral hazard (all channels: debt burden, concurrent, and dynamic) is collectively small.

Q2: What mechanism explains why newer borrowers are entirely unresponsive to interest rate changes?

A: The paper hypothesizes that newer borrowers place a higher continuation value on the card (captured by parameter v in the model) because they have fewer formal credit alternatives; at baseline, only 64% of the 6–11 month stratum held a card with another bank versus 78% of the 24+ month stratum. A higher continuation value implies more muted responses to interest rate changes (formally derived in Appendix E.3). Newer borrowers also respond more strongly to credit limit increases, consistent with tighter liquidity constraints. A regression controlling for age, gender, baseline card ownership, debt utilization, labor force attachment, and earnings cannot explain away the differential treatment effect between new and old borrowers (differential remains significant at p = 0.05), suggesting the tenure gradient in responsiveness is not simply a composition effect.

Q3: Why does increasing minimum payments raise short-run default but reduce long-run default?

A: In the short run, the doubling of minimum payments tightens liquidity constraints for already-constrained borrowers. The increase in default is concentrated among borrowers in the highest baseline debt-utilization tercile and among minimum-payers (baseline debt utilization of 85%), and is preceded by a sharp rise in delinquencies in months 3–5 (which trigger 350 MXN peso fees per occurrence, further worsening the repayment burden). In the long run, borrowers who anticipated continuing higher minimum payments (the experiment ended without advance notice, so borrowers expected the new terms to persist) chose lower debt levels during the experiment. Since all arms were returned to the same low minimum payment when the experiment ended, the lower-debt borrowers in the higher-minimum-payment arm were better positioned to weather subsequent shocks, producing the 1 pp post-experiment decline in default. The hypothesis that this is driven by habit formation in payment behavior is ruled out by the absence of any effect of past higher minimum payments on post-experimental payment levels.

Q4: How is the mass-layoff identification strategy designed and validated?

A: The paper uses the universe of IMSS formal employment records to define a mass layoff at a firm (50+ employees) as the first month in which year-on-year employment declines by more than 30% of average employment in the prior 12 months. An individual is “displaced” if they lost their job in the same quarter as their employer’s mass layoff event. The identification assumption is that, conditional on individual and time fixed effects, the exact timing of the mass layoff is uncorrelated with workers’ potential default outcomes. This is supported by: (1) mass layoffs occurring in every period, making coincidence with credit market shocks unlikely; (2) time fixed effects absorbing common trends; and (3) the absence of statistically distinguishable pre-trends in default between displaced and non-displaced workers. The paper implements both standard two-way fixed effects and the staggered DiD estimator of de Chaisemartin and D’Haultfoeuille (2024), which remains valid under heterogeneous and dynamic effects, and the results are similar across methods.

Q5: How does the paper account for informal employment when estimating the cash flow impact of job loss?

A: Formal-sector earnings losses over 18 months post-displacement are estimated at 77,555 MXN pesos using IMSS wage data in an event-study design paralleling the default equation. However, since more than 4/5 of workers who lose formal employment are informally employed in the following quarter (based on Mexico’s ENOE labor force survey panel), and total labor earnings fall by only an estimated 27.5% over the three post-displacement quarters, the paper scales the formal earnings loss down to 21,328 MXN pesos (≈ 0.275 × 77,555). This brings the estimated earnings loss closer to prior developed-country estimates of displacement costs and is treated as a lower bound relative to the raw formal-earnings loss figure.

Q6: Does the cost of default deter borrowers from defaulting, and what is the cost?

A: The paper argues that defaulters face substantial consequences. Using an instrumental variables strategy (treatment assignment as instrument for default on the study card), the probability of having a new loan one year after default is estimated to be 65 pp lower relative to the non-default counterfactual (p = 0.03). A selection-on-observables approach also shows that study card default is associated with the complete absence of any subsequent credit card for at least four years. These costs should provide strong incentives to remain current, making the high observed default rates primarily attributable to cash flow shocks rather than strategic default. The value of formal credit is further confirmed by the finding that a 100 MXN peso increase in the study card’s credit limit translates into 32 MXN pesos of additional debt (instrumental variable estimates are more than twice as large as OLS), and by the comparison of informal loan terms (annual rates averaging 291%, loan amounts of 3,658 MXN pesos, durations of 0.52 years) with formal loan terms (94 pp lower rates, 9,842 MXN peso average amounts, 1.07 year durations).

Q7: Are the default treatment effects different across the interest rate and minimum payment interventions, or do they interact?

A: The paper tests for and cannot reject separability between the two interventions at standard significance levels. At the end of the experiment (May 2009), the p-value for the null that the minimum payment effect is constant across interest rate arms is 0.44; five years later it is 0.65. The null that the interest rate effect is constant across both minimum payment arms yields p = 0.08 at end of experiment and p = 0.411 five years later. The fully saturated specification yields results indistinguishable from the parsimonious linear-separable specification.

Q8: Are there spillover effects from the contract term changes onto other loans held by study participants?

A: No spillover effects on default on other loans are found, either during the experiment or after it ended, based on credit bureau data covering all formal-sector loans held by the experimental sample. There is also no evidence of crowd-out or crowd-in from other lenders in terms of new loans or loan closures. The only minor exception is a small decrease in default (3%, or approximately 2 pp out of a 61 pp base) on other Bank A loans in the high minimum payment arm.

Q9: Why does the effect of unemployment on default exceed the model’s predictions from cash flow alone?

A: The paper’s back-of-the-envelope normalization finds that the per-peso effects of all three shocks on default are statistically indistinguishable (p = 0.78 for the null that all three λ estimates are equal), with point estimates of λ_IR = 0.36, λ_MP = 0.51, and λ_U = 0.36 pp per 1,000 MXN pesos. This implies that job loss does not have a larger per-peso effect on default than contract term changes; the larger absolute effect of displacement arises entirely from its larger cash flow impact. Additional consequences of job loss beyond cash flow (health, mental health) do not appear to generate additional default beyond what can be attributed to income loss.

Q10: How do the experimental results compare to what experts predicted?

A: Expert predictions were systematically too large. Mexican central bank regulators predicted a mean decrease of 8.6 pp from a 30 pp interest rate reduction at the 18-month horizon, versus the actual estimated effect of 1.03 pp. Social Science Prediction Platform respondents predicted a mean decrease of 5 pp. For minimum payments, regulators on average predicted a 0.4 pp decrease in default from doubling the minimum payment, whereas the actual effect was a 0.8 pp increase. Three-quarters of SSPP respondents correctly predicted the sign of the minimum payment effect (an increase in default), but the predicted mean increase was 6.4 pp, far larger than the estimated 0.8 pp.

Q11: Do the job displacement results generalize beyond the experimental sample?

A: Yes. The paper repeats the displacement event study on the intersection of the nationally representative credit bureau sample (approximately 600,339 individuals with both credit information and employment histories) with the universe of IMSS data for October 2011–March 2014, yielding 8,723 mass layoff events. This sample is representative of the population of Mexican borrowers with formal employment histories, and the estimated effects on default for any loan in the credit bureau are similar in magnitude to the experimental-sample results, providing a measure of external validity.

Q12: What do the debt dynamics during the experiment reveal about the mechanisms for interest rate effects on default?

A: The data show that purchases (net of payments) increase in response to interest rate decreases, consistent with downward-sloping demand for credit; yet total debt declines in lower-rate arms. This is consistent with the model’s prediction that the mechanical compounding effect (lower rate applied to previously accumulated debt) exceeds the behavioral new-purchase response. Confirmed empirically: the debt elasticity to the interest rate is estimated to be positive, with preferred estimates in the range [+0.18, +0.54]. The decline in default is further concentrated among borrowers with the highest baseline debt utilization rates, those for whom the debt compounding effect is strongest — consistent with the debt channel as the primary mechanism.

Key Concepts

Cumulative Default Measure: Default is defined as three consecutive monthly payments each below the required minimum payment due, at which point Bank A automatically revokes the card. The outcome variable is coded as Yit = 1 if borrower i has defaulted in any month s ≤ t and 0 otherwise, making it a cumulative (absorbing) measure. This allows estimation on an unchanging sample, avoiding attrition biases that would arise from conditioning on not having defaulted in the prior period.

Minimum Payment Due (mpd): The paper uses the required minimum payment due to avoid delinquency as its central cash-flow normalization variable. This is a comprehensive measure that incorporates not only the contractually specified fraction of outstanding balance but also interest charges, fees, and endogenous borrower responses (changes in debt and purchases). It serves as the common denominator for benchmarking the cash flow impacts of the two contract term interventions and formal job loss against one another.

Free Cash Flow / Per-Peso Normalization (λ): The paper defines per-peso default effects (λ^IR, λ^MP, λ^U) by dividing each intervention’s average treatment effect on cumulative default (in percentage points) by the cumulative change in the minimum payment due (or equivalent cash flow impact) induced by that intervention over 18 months. The resulting ratio is expressed as percentage points of default per 1,000 MXN pesos of cash flow change. This normalization is explicitly not treated as an instrumental variable estimate; it is a descriptive back-of-the-envelope calculation intended to equate the scale of the three shocks.

Mass Layoff / Displacement: A mass layoff at the firm level is defined as the first month in which year-on-year firm employment declines by more than 30% of average employment in the prior 12 months, restricted to firms with 50+ employees. An individual worker is classified as displaced if they lost formal-sector employment in the same calendar quarter as their employer’s mass layoff event. This definition follows Jacobson et al. (1993) and subsequent literature and is used to isolate plausibly involuntary (exogenous) separations from voluntary quits or individually driven terminations.

Continuation Value (v): In the paper’s two-period optimizing model, v is the reduced-form utility parameter capturing future flow of card benefits, warm glow from card ownership, or the option value of retaining access to formal credit, experienced only if the card is not in default. The paper uses v to rationalize the zero interest-rate response of newer borrowers: ceteris paribus, higher v implies that borrowers will remain current on the card even when interest rates are high, because they value continued access. Higher v thus implies more muted responses to interest rate changes.

Bank Tenure Strata: Borrowers are stratified into three groups based on length of relationship with the study card: “new customers” (6–11 months), medium-term (12–23 months), and long-term (24+ months). Tenure is used both as a stratification variable for the experiment and as a primary dimension of heterogeneity in treatment effects, reflecting differing default rates (36% vs. 18% at 26 months), labor market vulnerability (1.34× higher job loss probability for new vs. long-term), and interest rate responsiveness (zero for new, significantly positive for long-term borrowers).

Debt Burden Channel vs. Concurrent Moral Hazard: The paper distinguishes three channels through which interest rate changes can affect default: (a) the debt burden channel — higher rates mechanically increase the stock of interest-accruing debt, making repayment harder; (b) concurrent moral hazard — higher current interest rates alter the incentive to default on existing obligations, holding debt constant; and (c) dynamic moral hazard — higher future interest rates reduce the benefit of remaining current. The paper’s finding of a modest total effect (elasticity 0.20) implies that the sum of all three channels is small in this context, with the debt burden channel being the primary driver of what effect does exist.