Consumer Finances Research Articles

The distribution of privately held business assets in the United States

Although privately held businesses are central to the economy and society, little is known about how their assets are distributed among the population. To better understand rising and persistent wealth inequalities, this paper describes the household distribution of private business assets in the United States and examines how it has changed over time. Using data from the 1989–2019 Survey of Consumer Finances, we show that the relative number of business owners has remained stagnant at low levels and that assets in privately held firms have become increasingly concentrated. In 2019, the top 1 % of households controlled nearly 80 % of the equity in private businesses, up from about 70 % in the late 1980s. Moreover, we find that these trends appear to be quite general and do not merely reflect dynamics among elites or in specific sectors of the economy. We discuss implications for the organization of the US economy, wealth inequality, and public policy.

Prioritizing Usage of the Survey Respondent Over the Reference Person or Head in the Survey of Consumer Finances

The Survey of Consumer Finances is the gold standard for researchers interested in the finances of American families, yet it is a complex dataset. One methodological choice regards the use of the respondent’s demographics versus those of the reference person. When the respondent and reference person are not the same (40.4% of couples in 2022), many researchers use the demographics of both individuals (e.g., the race of the respondent and the education of the reference person). This mixed usage can introduce misclassification and androcentric bias, and it can shift results significantly (e.g., net worth estimates by education vary by 5.0%–35.2%). We argue that the optimal solution is to always use the demographics of the respondent. This is especially critical when the analyses include race and ethnicity variables (which from 1989 to 2019 were only collected from the respondent), or when they include sex and marital status because the reference person is almost always male in coupled households.

Trends in the retirement security of Black and Hispanic households in the US: A setback for Black Americans but continued progress for Hispanics

Retirement income security refers to the ability of households to provide an adequate stream of income during the period of their retirement from the labor force. Expected retirement income is based of four components: (i) standard non-pension wealth holdings, (ii) defined contribution (DC) pension holdings, (iii) actual or expected defined benefit (DB) pension entitlements, and (iv) actual or expected Social Security benefits. The first two components are converted into an annuity. All the data (except rates of return) for these calculations are available from the Survey of Consumer Finances. Results indicate that both Black and Hispanic households made remarkable progress in terms of mean and median retirement income, poverty reduction, and replacement rates from 1989 to 2007 in both absolute terms and relative to whites. However, for Black households, this was followed by a reversal of fortune from 2007 to 2019, with expected median retirement income declining, the projected poverty rate rising, and the projected replacement rate falling, though expected mean retirement income does rise. Hispanics also experienced a setback in mean retirement income but continued progress in replacement rates and reducing poverty from 2007 to 2019.

Greater wealth, greater uncertainty: Changes in racial inequality in the Survey of Consumer Finances

Greater wealth, greater uncertainty: Changes in racial inequality in the Survey of Consumer Finances

Post-ACA health insurance decisions: A survey on risk attitudes and consumer confidence

Objective: This study investigates the reluctance of individuals in the United States to get health insurance, specifically examining the psychological and sociodemographic aspects that contribute to this reluctance within the Affordable Care Act (ACA) framework. The research objective is to ascertain the behavioral factors contributing to insurance hesitation and offer valuable perspectives for decreasing the number of individuals without health insurance and enhancing health security. Methodology: The study uses data from the 2022 Survey of Consumer Finances to analyze the impact of specific variables such as risk tolerance, consumer confidence, income, education, age, and marital status on health insurance coverage choices. We also address issues related to cost, perceived health requirements, previous experiences, and misunderstandings about eligibility. Conclusion: The study demonstrates that higher customer confidence, frequently associated with financial stability, decreases reluctance to obtain insurance. By contrast, individuals with more risk tolerance exhibit more hesitancy, opting to depend on internal resilience. Furthermore, substantial demographic disparities indicate the presence of several obstacles in acquiring comprehensive coverage. Implications and Recommendations: The results underscore the necessity of tailored policy interventions that address the unique requirements of different demographic groups. It is crucial to consider both psychological and sociodemographic aspects to promote insurance adoption and ensure universal health security. The present study makes a valuable contribution to the current body of literature by offering a comprehensive examination of health insurance hesitation following the Affordable Care Act (ACA) implementation.

Financial literacy of Russians: The relationship with socio-demographic and psychological characteristics

The goal of the study is to reveal the relationship between the financial literacy of Russians and socio-demographic and psychological factors using data from three waves of the All-Russian Panel Survey of Consumer Finances (2018, 2020 and 2022). Fixed effects regression shows that the age of an individual is related non-linearly with financial literacy and the profile has the inverted U-shape. The association of education with financial literacy is positive: respondents with specialized secondary and higher education are more financially literate compared to people with general secondary education or lower. Income, Internet use, the presence of a spouse, paid employment, and a bank account are also positively related to financial literacy. Individuals with higher risk appetite, low ability to control their emotions, and short-term time preferences are worse literate in personal finance. Robustness tests allowed us to conclude that the influence of gender on the level of financial literacy in Russia is insignificant.

Financial Risk Tolerance as a Mediator Between Financial Literacy and Stock Market Participation: Evidence From Single Men and Women

Anchored upon the theory of planned behavior, the study examines a mediator, financial risk tolerance, in the relationship between financial literacy and stock market participation among single men and women. Using data from the 2019 Survey of Consumer Finances, the study uncovers an indirect effect of financial literacy on stock market participation through the mediating role of financial risk tolerance. This effect is observed in both genders, with a more pronounced mediation effect for men than for women. The study suggests that this gender disparity in the mediating mechanism is driven by the stronger correlation between financial risk tolerance and stock market participation among men, as the study finds that men exhibit a higher propensity to invest in the stock market when their financial risk tolerance increases compared with women. Consequently, the study asserts that addressing the gender gap in stock market participation may hinge on empowering women to transform their financial risk tolerance into concrete investment actions.

The Relationship Between Self-Control Factors and Household Saving Behavior

We examined the effect of self-control factors on saving behavior based on the behavioral life cycle hypothesis, using the 2016 and 2019 Survey of Consumer Finances datasets. A model which included self-control factors (behavioral life cycle variables) had a more significant effect on saving behavior than a model that included only normative life cycle variables. Among self-control factors, having at least one saving rule was positively associated with saving behavior but saving goals were not significantly associated with saving behavior. Having a foreseeable major expense was negatively associated with saving behavior. The findings of this study can assist financial planners, counselors, and educators in developing and implementing strategies related to self-control factors to enhance saving behavior.

The COVID-19 Pandemic and Family Economic Well-being: Evidence from the Survey of Consumer Finances

The COVID-19 pandemic caused severe disruptions to the U.S. labor market and economic activity. We establish connections between family experiences of the pandemic, their income under normal conditions, and their later economic well-being using the 2022 Survey of Consumer Finances. By their interview, one-third of families experienced net employment declines, one-third had teleworked, and one-fifth had significant COVID-19-related health events. These experiences strongly reflected families’ positions in the income distribution, with lower-income families bearing the brunt. They also tightly predict income and wealth after the initial disruptions, signifying that the pandemic economy likely amplified pre-pandemic differences and fostered new divides.

Heterogenous Rates of Return on Homes: Do The Rich Do Better?

AbstractRecent work on wealth inequality using the capitalization method wherein aggregate wealth totals are distributed proportionately to property income like dividends motivates concern about whether rates of return on assets vary across the income or wealth distribution. Here I use accrued capital gains and imputed rent on homes estimated from the Survey of Consumer Finances to address this issue. Both capital gains and imputed rent form part of total income. I find strong econometric evidence that returns vary directly with wealth level and are considerably higher for very wealthy compared to poorer households. However, I do not find evidence that higher income households receive higher returns once controlling for overall market house price trends. Returns are also strongly related to overall market house price movements, suggesting that timing the market is a key determinant. However, paradoxically, adding housing returns to baseline household wealth reduces overall wealth inequality.

The Evolution of Student Debt 2019–2022: Evidence from the Survey of Consumer Finances

In recent years, economists and policymakers have been interested in the burden of student debt across socioeconomic groups. In this Economic Commentary, we use the two most recent waves of the Survey of Consumer Finances, collected in 2019 and 2022, to study changes in the joint distribution of student debt and two measures of “ability-to-pay,” income and net worth. We find that between 2019 and 2022, both the fraction of families with student debt and real student debt per family were essentially unchanged, and aggregate student debt fell as a fraction of aggregate income and net worth. However, over the same period, the distribution of student debt shifted toward higher-income and wealthier families, with a rise in the average student debt in the highest quintile of both income and net worth. Further, this shift was not driven by changes in the distribution of debtors, but, instead, in the amount of debt per family.

Personal bankruptcy prediction using machine learning techniques

It has become crucial to have an early prediction model that provides accurate assurance for users about the financial situation of consumers. Recent studies focused on predicting corporate bankruptcies and credit defaults, not personal bankruptcies. Due to that, this study fills the literature gap by comparing different machine learning algorithms to predict personal bankruptcy. The main objective of the study is to examine the usefulness of machine learning models such as random forest, XGBoost, LightGBM, AdaBoost, CatBoost, and support vector machines in forecasting personal bankruptcy. The research relies on two samples of households (learning and testing) from the Survey of Consumer Finances, which was conducted in the United States. Among the estimated models, CatBoost and XGBoost showed the highest effectiveness. Among the most important variables used in the models are income, refusal to grant credit, delays in the repayment of liabilities, the revolving debt ratio, and the housing debt ratio.

Challenges in access, representativeness, and bias in smart financial data relating to income volatility and economic insecurity.

Introduction & BackgroundFinancial transaction data are highly valuable sources of digital footprints data for behavioural and economic research, but to properly create impact we must closely consider their limitations. Financial institutions hold a wealth of consumer data with untapped potential for community intelligence. These datasets combine excellent coverage with extremely granular information on consumer finances, income and spending, yet these institutions face great challenges in leveraging this data for social good. Smart Data Foundry is a university-owned, non-profit organisation that facilitates safe access to these datasets for researchers and provides insights to enable government bodies to tackle today's major challenges including the cost-of-living crisis and climate change. Objectives & ApproachWe will explore the opportunities afforded by these datasets for social and economic research. For example, using pseudonymised individual consumer banking data from NatWest Group, we have developed metrics for understanding income volatility and economic insecurity in collaboration with the Joseph Rowntree Foundation. We can also use these data to study consumer spending patterns and responses to economic changes such as interest rate rises and the net zero transition. We will assess the limitations of the data including issues of representativeness, bias, and missing data, and describe methods and mitigations to account for these challenges. We also discuss the barriers to accessing this type of data, in both relationship development with data partners, and privacy and governance concerns. Relevance to Digital FootprintsIndividual level customer transaction data provides a rich and novel form of digital footprint for behavioural and economic analyses. Every point of income or expenditure is recorded in a uniquely valuable digital footprint by financial institutions. These can provide a variety of insights, such as responses to macroeconomic shocks across demographic sets, emerging areas of financial distress, and help us better understand the drivers and risks of financial vulnerability. In both its aggregated and individual form, the data can provide an additional layer of understanding for trends we may see in other data, such as health or administrative data. Conclusions & ImplicationsHaving addressed the challenges of data access and data quality, we demonstrate that consumer banking data is an incredibly valuable form of digital footprints data, capturing key information on consumer behaviour. We conclude with a call for further research to develop use cases of this data for social good.

The Retirement Plan Dilemma: Who Is Best Prepared for Retirement in Today’s Environment?

This study examines the factors affecting retirement preparation through employer-sponsored retirement plans using the Survey of Consumer Finances’ (SCF) 2019 data. Various socio-economic and demographic variables are analyzed for significance regarding employee participation in and contributions to employer sponsored retirement plans. Our results indicate that gender, marital status, age, race, financial literacy, risk tolerance, inheritance expectation, and income are all important factors that affect plan participation rates as well as contribution levels. For minority women, income appears to be the most crucial factor in increasing participation. The results provide some implications for policymakers about improving retirement plan policies for women and minorities. The findings may also help individuals make better retirement planning decisions, especially in the face of possible social security benefit shortages and pension plan changes. This study is of great importance, as current retirement plans place a greater responsibility on both employers and individuals for retirement planning.

Analytic Approaches to Measuring the Black-White Wealth Gap

Does the measurement of the racial wealth gap shift depending on the model, method, and dataset used? We contrast the traditional mean Oaxaca-Blinder decomposition with the distributional Recentered Influence Function (RIF) methods. The untransformed, logarithm-transformed, and inverse hyperbolic sine-transformed versions in both the Survey of Consumer Finances and Panel Study of Income Dynamics datasets exhibit similarities. The Oaxaca-Blinder (mean) decomposition highlights that receiving an inheritance explains a larger portion of the racial wealth gap than educational attainment. Conversely, the RIF method at the median suggests that educational attainment accounts for more of the wealth gap than inheritance receipt.

High Risk, Constrained Return: Impact of Student Loans on Agricultural Real Estate

A farming household’s decision to continue producing agricultural commodities within the United States is influenced by a multitude of factors. Thus, this study seeks to examine whether the outstanding student loan balance of any member within a farming household may explain why the total number of acres devoted to the production of agriculture in the United States continues to decline. Panel data from the 2007–2009 Survey of Consumer Finances are analyzed via a fixed effect model to estimate the effect of outstanding student loan balances on farmland acreage owned, controlling for other factors like farm income, debt, and land prices. The results suggest that for each additional dollar of outstanding student loan debt, there is an associated decrease of 0.0064 acres in total farmland ownership. This suggests that student loan debt may also be a factor in the decline in real estate devoted to agriculture production. The estimated effect is both economically and statistically significant. This study contributes to the literature on the risks and constraints associated with farming households that own or seek to procure additional acres of agricultural producing real estate.

Bit by Bit: Household Characteristics of Cryptocurrency Owners — Early Evidence From the 2019 Survey of Consumer Finances

Bit by Bit: Household Characteristics of Cryptocurrency Owners — Early Evidence From the 2019 Survey of Consumer Finances

The Evolution of Redlining in the United States Housing Market

This article explores the lasting effects of redlining in the United States on wealth creation and economic opportunity. Due to rising mortgage rates and low supply, housing costs are growing. Redlining is the practice of discrimination in the homebuying and lending market that resulted in significant housing inequality. While illegal since the 1970s, redlining has not disappeared but rather evolved. Institutional economics provides a framework to understand the history, consequences, and solutions to modern redlining that can generate greater housing equality in the United States. This article uses the latest Federal Reserve Bank’s Survey of Consumer Finances (2023) data to analyze the size and effects of housing inequality resulting from redlining practices and what groups are most affected. From these empirical findings, public policy solutions are presented to create a more financially stable and equitable housing market.

Does it Pay to Send Multiple Pre-Paid Incentives? Evidence from a Randomized Experiment

To encourage survey participation and improve sample representativeness, the Survey of Consumer Finances (SCF) offers an unconditional pre-paid monetary incentive and separate post-paid incentive upon survey completion. We conducted a pre-registered between-subject randomized control experiment within the 2022 SCF, with at least 1,200 households per experimental group, to examine whether changing the pre-paid incentive structure affects survey outcomes. We assess the effects of: (1) altering the total dollar value of the pre-paid incentive (“incentive effect”), (2) giving two identical pre-paid incentives holding the total dollar value fixed (“reminder effect”), and (3) offering multiple pre-paid incentives of different amounts holding the total dollar value fixed (“slope effect”) on survey response rates, interviewer burden, and data quality. Our evidence indicates that a single $15 pre-paid incentive increases response rates and maintains similar levels of interviewer burden and data quality, relative to a single $5 pre-paid incentive. Splitting the $15 into two pre-paid incentives of different amounts increases interviewer burden though lengthening time in the field without improving response rates, reducing the number of contact attempts needed for a response, or improving data quality, regardless of whether the first pre-paid is larger or smaller than the second.

Altruistic Bequests: Giving Motive and Receipt Expectation Using the 2019 Survey of Consumer Finances

This study uses Altruistic Bequest Theory to update research by Kao et al. (1997) exploring the factors driving the giving and receiving of bequests using data collected from the 2019 Survey of Consumer Finances (SCF). Altruistic variables demonstrated significant, although at times weak, relationships across the three categories of the analysis (bequest versus no bequest, bequest versus maybe bequest, maybe bequest versus no bequest). Alternatively, results show economic, attitudinal, and sociodemographic variables as the main drivers for the giving and receiving of bequests.