Significance The impact of chronic debt on the poor is psychological, not just financial. We hypothesize that chronic debt impairs psychological functioning and decision-making, contributing to the poverty trap. This is because debt is not considered fungible and is viewed as costly mental accounts that consume cognitive bandwidth. We test this using quasiexperimental evidence from a one-off, unanticipated debt-relief program worth several months’ household income. Comparing the poor before and after debt relief, those with more debt accounts paid off experienced greater improvements in cognitive functioning, reported less anxiety, and became less present-biased. These findings provide actionable evidence for poverty-alleviation policy.

Abstract We examine how chronic debt affects behavior by studying how a large, unanticipated debt-relief program affected psychological functioning and economic decision-making in beneficiaries. A charity granted low-income households debt relief worth up to Singapore dollars 5,000 (∼3 month’s household income). We exploited quasiexperimental variation in the structure of debt relief: For the same dollar amount of relief, some beneficiaries had more debt accounts eliminated, while others had fewer paid off. Comparing 196 beneficiaries before and after debt relief, and controlling for debt-relief amount, having an additional debt account paid off improves cognitive functioning by about one-quarter of a SD and reduces the likelihood of exhibiting anxiety by 11% and of present bias by 10%. To achieve the same effect on cognitive functioning of eliminating one debt account, a beneficiary must receive debt relief worth ∼1 month’s household income. There is no effect of debt-relief magnitude on anxiety and decision-making. We exclude training and calendar effects, debt-causing behaviors, and liquidity constraints as explanations. Instead, these results support the hypothesis that chronic debt impairs behavior because the mental-accounting costs of owing distinct debt accounts consume mental bandwidth. Poverty-alleviation policies aimed at the indebted poor should consider addressing mental accounting and bandwidth taxes.

Recent studies provide a new perspective on the causes of poverty traps: The demands of daily life under scarcity create “bandwidth taxes” that sap mental resources, impairing cognitive ability and causing counterproductive behavior which perpetuates poverty (1⇓–3). While this theory has opened a new frontier on poverty research and policy, the pathways through which poverty reinforces itself through bandwidth taxes remain a black box.

We shed light on these pathways by examining how chronic indebtedness creates bandwidth taxes for the poor. Chronic indebtedness is endemic to poverty in rich and poor nations alike (4, 5). The burden of debt is severe: One in four US families in the lowest income quintile spend >40% of household income on servicing debt (5). The monetary costs of debt exacerbate poverty because the repayment burden diverts resources from more productive uses (6). However, the way debts are structured may create large bandwidth costs that are just as, if not more, detrimental. The reason is that debt, like money, is not perceived to be fungible. People do not think about personal finances in a consolidated way and instead think narrowly about the gains and losses of separate mental accounts for their mortgage, their car loan, their power bill, and their other debts (7, 8).

This implies that debt structure matters. Conditional on owing the same amount, having more creditors is costlier psychologically because more accounts are “in the red,” and losses loom larger, on the margin, for the first few dollars of each debt (7⇓–9). These debt mental-accounting costs are painful and explain why laboratory subjects pay off smaller debts entirely when possible rather than minimize overall interest costs (10). Under this view, the poor may have great difficulty improving their situation simply because debt mental accounting imposes a background cognitive load, causing bandwidth tax that impairs cognitive functioning. In addition, the psychological pain from multiple debt mental accounts may explain why chronic debt is frequently associated with stress and negative affect (11, 12). Impaired cognition and negative affect, in turn, may focus attention on safer choices that yield immediate benefits at the expense of longer-term risky investments and may impair the ability of the deliberative, economically rational “system 2” to restrain “system 1” impulses to seek safe, near-term benefits (1⇓–3, 13⇓–15).

Although debt mental accounting is not limited to the poor, the poor are more likely than the nonpoor to owe multiple chronic debts because they lack the financial resources to streamline debts. Consider a household replacing a fridge which unexpectedly fails. A richer household could pay from savings or consolidate the purchase with others on a credit card. No new debt account is added. In contrast, a poorer household may have to pay using store credit or by borrowing from informal lenders, creating a new debt account and increasing their cognitive burden. While an unexpected expenditure is painful for both groups, the psychological cost of payment is short-lived for the nonpoor, but could linger as chronic debt for the poor.

If debt mental accounting creates bandwidth tax, policy interventions that streamline debts would significantly improve cognitive and psychological functioning and reduce counterproductive behavior. We test this hypothesis with quasiexperimental evidence from a charity-funded debt-relief program, which restructured and repaid debts owed by participating low-income, chronically indebted households in Singapore. Because social workers (and not participants) allocated debt relief, debt structure varied quasiexperimentally: For a given dollar amount of relief, some participants had more debt accounts cleared, while others had fewer (SI Appendix, Fig. S1). We studied the same participant before and after debt relief, testing whether their chronic indebtedness affected their cognitive functioning, anxiety, and attitudes toward risk and time discounting. We then tested whether changes in debt accounts had greater impact, compared with changes in overall debt levels.

The key concern with our research design is that social workers may structure debt relief to maximize the outcomes of interest or select participants with greater potential for improvement, leading us to overestimate the effects of debt relief. However, institutional features mitigate this. Social workers had no formal training in debt restructuring and had no incentive to select only high-potential participants because they were not directly accountable to, or financially dependent on, the program sponsor. Moreover, selection effects were naturally limited; each social worker was only responsible for a few potential applicants, as eligible households were distributed throughout the country and were served by the closest social-service agency.

To further limit bias, we avoided discussing the study outcomes during the fieldwork to ensure that social workers could not target improvement in our outcome measures. We were also careful to account for training and calendar effects, debt-causing behaviors, and liquidity constraints as confounding explanations. Nevertheless, the caveat remains: As our evidence is quasiexperimental rather than from a randomized controlled trial, identification concerns cannot be completely eliminated.

Two additional caveats must be noted. First, chronic indebtedness in the poor has complex causes. Besides the structural financial stresses of poverty—such as irregular employment, low wages, and exposure to uninsurable health and income shocks—it is possible that counterproductive behavioral traits exacerbate indebtedness. But regardless of cause, if debt impairs cognitive and psychological functioning, it could be extremely challenging for the indebted poor to escape poverty.

Second, apart from mental-accounting costs, other psychological mechanisms play a role in explaining the persistence and burden of chronic debt. Previous studies have examined how repayment strategies affect motivation to pay off debts (16, 17). We set aside the question of how to best repay debts and focused instead on elucidating the psychological burden of indebtedness. Our study also does not directly separate mental accounting from the other bandwidth costs of managing debt, such as scheduling and optimizing repayments (2). However, subjects in laboratory experiments eliminate debt accounts even when there are no costs of debt-account management (10), suggesting that mental-accounting costs are substantial. More importantly, the link between mental accounting and bandwidth tax motivates new policy interventions that consolidate multiple mental accounts, rather than just providing payment reminders or financial counseling to the poor.

Field Study In 2015, a Singapore-based charity, Methodist Welfare Services, administered a one-off debt-relief program for chronically indebted, low-income Singapore households. Participation was restricted to households with monthly per capita income less than Singapore dollars (SGD) 1,500 (the lowest third of households by income) and that had outstanding chronic debts owed for at least 6 mo. In 2015, one SGD was worth $1.15 United States dollars (USD) at purchasing power parity exchange rates, so participant households had monthly purchasing power less than USD 1,725 per capita. Eligible debts included housing (mortgage or rental), utilities, town council taxes, telco bills, and hire purchase debts. Other debts were considered on a case-by-case basis. Unsecured consumer debts were generally excluded because low-income households in Singapore are restricted by policy from accessing consumer credit and because the charity targeted debts from nondiscretionary spending. The program was administered through Family Service Centres, which provide local social services in Singapore. Family Service Centre social workers had discretion to identify and endorse eligible clients and debts for relief. Clients could not apply directly. Thus, while clients with greater outstanding debts generally received more relief (up to the program limit of SGD 5,000), conditional on initial debt structure, there was extensive idiosyncratic variation in both the amount of relief granted and the number of debt accounts paid off. Our study sample consisted of 196 participants, recruited from 656 applicants to the debt-relief program (Methods). Participants were surveyed before receiving debt relief and again 3 mo after debt relief. Table 1 reports income and debt characteristics of our sample; additional data and comparisons with all program applicants are in SI Appendix, Table S1. Before debt relief, average monthly household income per capita (conditional on positive income) was SGD 364, compared with SGD 541 for the first income decile in Singapore. Although Singapore does not have an official poverty line, the average five-member household in our sample had annual purchasing power worth USD 24,674, below the US Census poverty line of USD 28,741 for a family of five. The average and median debt was SGD 6,257 and SGD 3,574, respectively; the median debt-to-monthly-income ratio was 2.27 (conditional on positive income). On average, households had 3.27 debt accounts. There were some very large debts exceeding the sample average annual income, mostly due to mortgages in arrears; these did not affect the results (SI Appendix, Table S2). Table 1. Participant summary statistics pre- and post-debt relief Participants received an average debt relief of SGD 2,548, with 25% receiving the maximum relief of SGD 5,000. Three months after debt relief, average debts fell from SGD 6,257 to SGD 4,265, while median debts fell from SGD 3,574 to SGD 1,128, and 90% of participants reported holding less debt. Average debt accounts fell from 3.27 to 2.21.

Discussion The impact of debt on the poor is psychological, not just financial. Debt causes significant psychological and cognitive impairment and alters decision-making. However, debt has these effects not just because of the economic costs of holding debt, but because debt mental accounting creates bandwidth taxes that impair cognitive processes. Understanding this pathway motivates new approaches to poverty policy. As an illustration, consider two possible housing policies to improve the cognitive functioning of low-income tenants who fall behind on their bills. A policy that considers mental-accounting costs would combine bills for rent, power, water, and maintenance into one statement instead of billing tenants separately. But a policy which ignores mental-accounting costs might simply apply automatic payments, send tenants reminders, or coordinate billing on the same repayment schedule (46). Our study suggests that policies which consider mental-accounting costs may be more effective. Going further, we propose two important emerging areas for policy and research. The first is to examine the relative cost-effectiveness of targeting the psychological, vs. economic, costs of debt. While debt relief is effective, it is costly and must be implemented with care to avoid dependence. In comparison, debt restructuring and financial consolidation to reduce mental-accounting costs in the poor may be a more sustainable policy. The second is to critically evaluate the bandwidth tax trade-offs of policies that encourage people to narrowly bracket decisions as mental accounts to shape behavior. These include commitment devices such as child-education accounts or job-performance targets in the task economy. When people have resources, mental accounting may help motivate people to overcome their self-control problems and achieve outcomes that are genuinely welfare enhancing. But in tandem with poverty, or any other deficit of resources, encouraging excessive mental accounting, particularly when loss frames are evoked, imposes psychological costs that may far outweigh other benefits.

Methods Recruitment and Ethics. The National University of Singapore (NUS) Institutional Review Board approved the study (NUS 2518). All participants provided informed consent. Participation was voluntary, could be withdrawn at any time, and did not affect debt-relief benefits. We recruited our sample of 196 participants through social-worker referral (with participant consent) from the 656 applicants to the program. Privacy laws prevented access to applicant data for random sampling. We received 281 referrals and completed initial interviews with 238. After excluding debt-relief rejections, clients receiving relief for noneligible debts (indicating exceptions to policy), and clients uncontactable in the follow-up wave, we were left with 196 participants. Measures of Psychological Functioning and Economic Decision-Making. Cognitive functioning was measured with the Eriksen flanker task (20). Each participant completed 20 trials, where a central stimulus was presented, surrounded by distracting stimuli (“flankers”). The participant exercised executive control to ignore the distracting stimuli and identify the central stimulus quickly and accurately. Psychological functioning was measured by using self-reported responses to the eight-question battery for GAD in the DSM-IV (21). Risk aversion was measured with a lottery-choice task (30). Participants chose one of six lotteries: (SGD 28/SGD 28), (SGD 36/SGD 24), (SGD 44/SGD 20), (SGD 52/SGD 16), (SGD 60/SGD 12), or (SGD 70/SGD 2), each with a 50–50 chance of winning the higher or the lower reward. Time discounting was measured with two multiple-price lists (32⇓–34). In each price list, participants traded off receiving a varying smaller payoff earlier (the smallest was SGD 32) vs. a larger fixed payoff of SGD 50 at a later date. The first price list offered payoffs today vs. 1 mo later, while the second offered payoffs at 6 mo vs. 7 mo later. More details are in SI Appendix, sections 1–3. Data Sharing. Debt-relief program administrative data are owned by the charity and are not publicly available. These administrative data were required to compute SI Appendix, Table S1. The charity can be contacted at https://mws.sg. All other data required to replicate all analyses in the paper are available as Datasets S1 and S2.

Acknowledgments We thank Paul Cheung, Jack Knetsch, Ivan Png, Frank Schilbach, Heather Schofield, Stephanie Wang, and Jiaying Zhao for their helpful comments; Mayves Gan, Andrew Lim, Yingxian Lim, Grace Tan, and Jian Qi Tan for excellent research assistance; and Methodist Welfare Services and all participating social service agencies for support. This work was supported by Quantedge Foundation and NUS Humanities and Social Sciences Research Fund.

Footnotes Author contributions: Q.O., W.T., and I.Y.H.N. designed research; Q.O., W.T., and I.Y.H.N. performed research; Q.O. and W.T. analyzed data; and Q.O., W.T., and I.Y.H.N. wrote the paper.

The authors declare no conflict of interest.

This article is a PNAS Direct Submission. S.M. is a guest editor invited by the Editorial Board.

This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10.1073/pnas.1810901116/-/DCSupplemental.