Credit Card Spending Research Articles

Vaccination Policy, Delayed Care and Health Expenditures

Abstract This paper evaluates the effect of COVID-19 vaccination on the individual propensity to delay or skip medical care. Our research design exploits the arguably exogenous variation in age-specific vaccine eligibility rollout across states and over time as an instrument for individual vaccination status. We find that receiving a COVID-19 vaccine reduces the likelihood of delaying care for any medical condition by 37%. Furthermore, our analysis reveals that children are significantly less likely to delay or skip healthcare as a result of their parents becoming vaccine eligible, indicating the presence of a positive health spillover within households that extends beyond protection against infection. Our analysis also shows that vaccination reduces concerns about contracting or spreading COVID-19, leading to increased mobility and potentially reducing delays or avoidance in seeking healthcare. Additionally, we find that vaccination notably increased access to elective care and surgeries, but had no significant impact on emergency department admissions, mental health cases or other medical conditions. Our results highlight the important role that vaccines play in, not only protecting against coronavirus, but also safeguarding against the worsening of health due to delayed or foregone medical care. The decline in delayed or foregone care caused by vaccination is particularly strong among minorities and those with a low socioeconomic background, revealing an important role that vaccination efforts can play in narrowing inequities in health and healthcare. In supplementary analysis, we use novel data on debit and credit card spending to demonstrate that increased vaccine uptake has a positive, albeit statistically insignificant, effect on consumer healthcare spending in the short run. Taken together, our findings imply that advancements in vaccine development coupled with a regulatory process that accelerates the availability of vaccines to the public in a safe manner can have the additional benefit of tackling unmet healthcare needs during a public health crisis.

Exploratory Data Analysis of Debit and Credit Card Spending Across Types of Banks in India

Exploratory Data Analysis of Debit and Credit Card Spending Across Types of Banks in India

The Asymmetric Effects of Consumer Confidence on Credit Card Spending in Turkey

This paper analyzes the asymmetric effects of consumer confidence on personal credit card expenditures in Turkey. To this end, the impact of the consumer confidence index on real credit card spending is investigated from January 2013 to June 2023 using the threshold generalized method of moments (GMM). The linear GMM model findings indicate that consumer confidence increases real credit card expenditures. Furthermore, when the threshold GMM model is estimated using the annual percentage change of the consumer confidence index as a threshold variable, the coefficients differ across low- and high-confidence regimes. More specifically, the consumer confidence index has a statistically significant positive impact on credit card expenditure in the low-confidence regime but not in the high-confidence regime. This indicates that the optimistic expectations of economic units in a low-confidence environment may stimulate credit card spending.

The COVID-19 shock and consumer credit: Evidence from credit card data

We study the dynamic effect of the COVID-19 shock on credit card use in 2020. Local case incidence had a strong negative effect on credit card spending in the early months of the pandemic, which diminished over time. This time-varying pattern was driven by the fear of the virus, rather than government support programs, consistent with the “pandemic fatigue” of consumers. Local pandemic severity also had a strong effect on credit card repayments. These spending and repayment effects offset each other, resulting in no effect on credit card borrowing, consistent with credit-smoothing behavior. The local stringency of nonpharmaceutical interventions also had a negative effect on spending and repayments, albeit smaller in magnitude. We conclude that the pandemic itself was a more important driver of changes in credit card use than the public health policy response.

RaKShA: A Trusted Explainable LSTM Model to Classify Fraud Patterns on Credit Card Transactions

Credit card (CC) fraud has been a persistent problem and has affected financial organizations. Traditional machine learning (ML) algorithms are ineffective owing to the increased attack space, and techniques such as long short-term memory (LSTM) have shown promising results in detecting CC fraud patterns. However, owing to the black box nature of the LSTM model, the decision-making process could be improved. Thus, in this paper, we propose a scheme, RaKShA, which presents explainable artificial intelligence (XAI) to help understand and interpret the behavior of black box models. XAI is formally used to interpret these black box models; however, we used XAI to extract essential features from the CC fraud dataset, consequently improving the performance of the LSTM model. The XAI was integrated with LSTM to form an explainable LSTM (X-LSTM) model. The proposed approach takes preprocessed data and feeds it to the XAI model, which computes the variable importance plot for the dataset, which simplifies the feature selection. Then, the data are presented to the LSTM model, and the output classification is stored in a smart contract (SC), ensuring no tampering with the results. The final data are stored on the blockchain (BC), which forms trusted and chronological ledger entries. We have considered two open-source CC datasets. We obtain an accuracy of 99.8% with our proposed X-LSTM model over 50 epochs compared to 85% without XAI (simple LSTM model). We present the gas fee requirements, IPFS bandwidth, and the fraud detection contract specification in blockchain metrics. The proposed results indicate the practical viability of our scheme in real-financial CC spending and lending setups.

Liquidity Constraints, Consumption, and Debt Repayment: Evidence from Macroprudential Policy in Turkey

Abstract Using account-level credit card data from a large Turkish bank, we study the impact of a unique credit card policy that increases minimum payment on consumption and debt repayment. We show that the policy reduces credit card spending and debt, boosts existing debt repayment, and reduces credit card delinquency. The credit card debt of affected consumers falls on average by 50$\%$ two years into the policy’s implementation. An increase in minimum payment has a stronger effect than does a decrease of a similar magnitude. We build a benchmark life cycle model with soft liquidity constraint to explain the reduction in credit card spending. Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.

Consumer Behavior in the Face of the Coronavirus Pandemic: An Analysis of Credit and Debit Card Spending at Brazilian States

The paper analyzes credit and debit card consumer spending and correlates it with the social isolation measures enacted as a result of the 2020 coronavirus pandemic. Correlations were estimated between the variation in spending in different economic sectors and the Social Distancing Index (IDS) proposed by IPEA. The results show the importance of the essentiality of goods, the mobility of consumers during the pandemic and quarantine and the way in which social isolation measures affect each consumer sector. Essential sectors without mobility problems had an increase in consumption and oscillatory behavior of consumption spending during the period. Non-essential goods sectors saw a sharp reduction in consumption spending followed by a gradual recovery. Sectors associated with mobility (whether essential or not) had a sharp reduction and did not have a clear recovery in the period. In addition, there is strong evidence that possibly institutional variations between states have relevant effects.

Finansal Risk Toleransının Finansal Tutum ve Davranışlar Üzerindeki Etkisi: Z Kuşağı Üzerine Bir Araştırma

Günümüzde önemi giderek artan finansal okuryazarlık kavramı ve yakın gelecekte hem Türkiye’de hem de iş dünyası üzerinde baskın hale gelecek olan Z kuşağı ile ilgili çok sayıda araştırma yapılmıştır. Çalışmada, Z kuşağının finansal tutum ve davranışları ile finansal risk toleransları arasında bir ilişki olup olmadığı incelenmiştir. Araştırmanın verileri, kolayda örnekleme yöntemi ile seçilen ve Ankara’da yaşayan 431 Z kuşağı gençlerden anket yöntemiyle toplanmıştır. Verilerin analizi neticesinde, Z Kuşağına mensup bireylerin finansal risk toleransının ortalama ve ortalama üstünde olduğu görülmüştür. Z kuşağının finansal tutum ve davranışlarının cinsiyete, babanın eğitim düzeyine, aylık kredi kartı harcamasına ve sahip olunan kredi kartı sayısına göre değiştiği; ayrıca daha önce finansal konularda eğitim almış olanların finansal risk toleranslarının yüksek olduğu belirlenmiştir. İlaveten finansal risk toleransındaki değişimin finansal tutum ve davranışları etkilediği sonucuna varılmıştır.

Monetary Policy and Credit Card Spending

Monetary Policy and Credit Card Spending

Consumer Spending and the Cross-Section of Stock Returns

Using a unique dataset of individual transactions-level data for a universe of US consumer facing stocks, we examine the information content of consumer credit and debit card spending in explaining future stock returns. Our analysis shows that consumer spending data positively predict various measures of a company’s future earnings surprises up to three quarters in the future. This predictive power remains strong in both large- and small-cap universes of consumer discretionary firms in our sample and is robust to the type of transactions data considered (credit card, debit card, or both), although the relationship is stronger in the small-cap universe where informational asymmetries are more pronounced. Based on this empirical observation, we build a simple long–short strategy that takes long–short positions in the top/bottom tercile of stocks ranked on our real-time sales signal. The strategy generates statistically and economically significant returns of 16% per annum net of transaction costs and after controlling for the common sources of systematic factor returns. A simple optimization exercise to form (tangency) mean–variance-efficient portfolios of factors leads to an optimal factor allocation that assigns almost 50% weight to our long–short portfolio. Our results suggest that consumer transaction level data can serve as a more accurate and persistent signal of a firm’s growth potential and future returns.

Revealing the revealed preferences of public firm CEOs and top executives: A new database from credit card spending

AbstractResearch SummaryWe introduce a new database which provides an unprecedented window into the off‐the‐job lives and interests of public firm top executives as reflected by their personal income allocation. We construct this database by matching household credit card spending data with the population of executives in Execucomp. To overcome the significant computational challenges associated with matching these data, we build on the statistical record‐linking literature in a way that allows us to generate reliable matches with limited information. To facilitate research exploring new questions made possible with this database, we make our matching crosswalk freely available for academic use.Managerial SummaryThis article describes the matching procedures associated with the development of a database which sheds new light on the revealed preferences of public firm top executives. Prior work on upper echelons has routinely stressed how preferences and characteristics of top executives often manifest in firm behaviors and are important predictors of firm outcomes. Nevertheless, the lack of a reliable paper trail capturing executive preferences, particularly at a large scale, has been a friction slowing comprehensive empirical research on this topic. We describe how we address this limitation by linking top executives listed in the database Execucomp with credit card spending data provided by the consumer data provider L2 and outline a number of new research questions made possible by our matching efforts. The results of our matching efforts (Execucomp‐L2 unique identifier crosswalk) are available at https://github.com/dfehder/FRT_2022_SMJ_CEO_TopExec_Preferences.

Consumption Response to Government Income Subsidies: Korea’s Case

The Republic of Korea Government implemented a universal consumption subsidy program to combat the coronavirus disease 2019 (COVID-19) economic downturn in 2020. Using granular, micro-level transaction data, we find that the subsidy scheme has stimulated household consumption immediately after receipt. Moreover, lower income groups demonstrate higher marginal propensity to consume than middle and higher income groups; this holds true even when creating synthetic control groups that model rational spending behavior. This can have a significant implication on the effectiveness of fiscal impulse. Using income and average historical credit card spending, we also demonstrate credit and liquidity constraints are major factors affecting consumption responses.

Mortgage Debt, Hand-to-Mouth Households, and Monetary Policy Transmission

Abstract Using a representative sample of credit card holders from a leading Chinese commercial bank, we investigate how consumers respond to an unexpected interest rate decrease that automatically reduces interest expenses for all mortgage borrowers in the country and thereby generates significant positive disposable-income shocks. Our difference-in-differences analysis shows that compared with homeowners without mortgage obligations, mortgage borrowers increased their monthly credit card spending by 8.7% after the 230-bps mortgage rate reduction announced in September 2008. We find a significant spending response both immediately after the announcement and during the post-reset period. The credit card delinquency rate also decreased after the mortgage rate reset. Subsequent to an interest-rate increase episode, mortgage borrowers symmetrically reduced their credit card spending. Hand-to-mouth mortgage borrowers experienced a more pronounced spending increase. The debt-service channel plays an important role in transmitting monetary policy—our estimate implies a marginal propensity to consume 0.40–0.54 through credit card spending.

Comment on “Big Data in Asian Central Banks”

Comment on “Big Data in Asian Central Banks”

The COVID-19 Inflation Weighting in Israel

Abstract Significant shifts in the composition of consumer spending as a result of the COVID-19 crisis can complicate the interpretation of official inflation data, which are calculated by the Central Bureau of Statistics (CBS) based on a fixed basket of goods. We focus on Israel as a country that experienced three lockdowns, additional restrictions that significantly changed consumer behavior, and a successful vaccination campaign that has led to the lifting of most of these restrictions. We use credit card spending data to construct a consumption basket of goods representing the composition of household consumption during the COVID-19 period. We use this synthetic COVID-19 basket to calculate the adjusted inflation rate that should prevail during the pandemic period. We find that the differences between COVID-19-adjusted and CBS (unadjusted) inflation measures are transitory. Only the contribution of certain goods and services, particularly housing and transportation, to inflation changed significantly, especially during the first and second lockdowns. Although lockdowns and restrictions in developed countries created a significant bias in inflation weighting, the inflation bias remained unexpectedly small and transitory during the COVID-19 period in Israel.

Emergency unemployment benefits and health care spending during Covid.

ObjectiveTo estimate the impact of the $600 per week Federal Pandemic Unemployment Compensation (FPUC) payments on health care services spending during the Covid pandemic and to investigate if this impact varied by state Medicaid expansion status.Data SourcesThis study leverages novel, publicly available data from Opportunity Insights capturing consumer credit and debit card spending on health care services for January 18–August 15, 2020 as well as information on unemployment insurance claims, Covid cases, and state policy changes.Study DesignUsing triple‐differences estimation, we leverage two sources of variation—within‐state change in the unemployment insurance claims rate and the introduction of FPUC payments—to estimate the moderating effect of FPUC on health care spending losses as unemployment rises. Results are stratified by state Medicaid expansion status.Extraction MethodsNot applicable.Principal FindingsFor each percentage point increase in the unemployment insurance claims rate, health care spending declined by 1.0% (<0.05) in Medicaid expansion states and by 2.0% (<0.01) in nonexpansion states. However, FPUC partially mitigated this association, boosting spending by 0.8% (<0.001) and 1.3% (<0.05) in Medicaid expansion and nonexpansion states, respectively, for every percentage point increase in the unemployment insurance claims rate.ConclusionsWe find that FPUC bolstered health care spending during the Covid pandemic, but that both the negative consequences of unemployment and moderating effects of federal income supports were greatest in states that did not adopt Medicaid expansion. These results indicate that emergency federal spending helped to sustain health care spending during a period of rising unemployment. Yet, the effectiveness of this program also suggests possible unmet demand for health care services, particularly in states that did not adopt Medicaid expansion.

Card spending dynamics in Turkey during the COVID-19 pandemic

This paper provides an extensive analysis of card spending during the COVID-19 pandemic in Turkey by using weekly aggregated and sectoral credit and debit card spending data from March 2014 to December 2020. At an aggregated level, we show that aggregate demand decreases significantly at the early stages of COVID-19 and seems to reinstate its pre-COVID trend. However, when we include the pre-existing conditions of Turkey, the 2018 currency crisis, we observe that the recovery in demand is not that strong. To highlight the underlying reasons for structural change in aggregate demand, we estimate the model with stringency index and unemployment-related search index. The estimated model indicates that containment measures and restrictions and fear of job/income loss mainly explain the overall impact of COVID-19 on aggregate demand. We also examined sectoral data to understand aggregate demand dynamics better. Only stable and delayable sector groups have reached a trend above their pre-pandemic trajectories. However, the social and work-related sectors are far from their respective pre-pandemic trend.

What pandemic inflation tells: Old habits die hard

COVID-19 has led to changes in individuals’ consumption habits, which will cause the calculation of inflation based on the average consumption basket to give distorted information. Using debit and credit card spending data of Turkey, we build CPI weights and compute an alternative pandemic consumption basket price index for Jan 2020–Feb 2021. Our findings show that the pandemic inflation is higher than the official inflation rate during the first lockdown, suggesting a behavioral change in consumption. However, in the reopening period, old habits come back. During the second lockdown, the difference between the pandemic and the official inflation rates is trivial in comparison with the first lockdown.

High-Frequency Data and a Weekly Economic Index during the Pandemic

This paper describes a weekly economic index (WEI) developed to track the rapid economic developments associated with the onset of and policy response to the novel coronavirus in the United States. The WEI, with its ten component series, tracks the overall economy. Comparing the contributions of the WEI's components in the 2008 and 2020 recessions reveals differences in how the two events played out at a high frequency. During the 2020 collapse and recovery, it provides a benchmark to interpret similarities and differences of novel indicators with shorter samples and/or nonstationary coverage, such as mobility indexes or credit card spending.

The Stock Market and Household Financial Behavior

In this JPMorgan Chase Institute report, we document a high-frequency relationship between stock market returns and patterns observed in consumer spending and investing behavior. The analysis draws from a core sample of approximately 12 million active Chase credit card users since 2012, and we seek to explain how the distribution of monthly credit card spending changes responds to stock market returns. The right tail of this distribution—characterized by spending increases double or triple a person’s typical level— is over two times more sensitive to the market than the center of the distribution. The relationship is more pronounced for male investors than non-investors and women. Applying the same econometric framework for stock market returns to changes in checking account-based spending and changes in labor income does not yield a statistically discernible relationship in our sample. Meanwhile, individuals’ transfers to investment accounts display a notable correlation with lagged stock returns, consistent with “returns chasing.” Such transfers roughly doubled around the onset of the COVID national emergency, alongside sharp declines in spending. Our findings imply that policies seeking to exert control over business cycles via the stock market may be successful over short time horizons. However, since stock market gains are associated with spending “splurges” on credit cards and flows into investment brokerage accounts, stimulus aimed at supporting asset prices can come with costs in the form of households’ financial vulnerability. If gains in stock prices are not followed by an improving labor market, households that over-extend themselves in terms of spending or equity market exposure would face risks.