October 15, 2021 | by Ryan Goodstein, Alicia Lloro, and Jeffrey Weinstein

Note: The views and opinions expressed in this blog post are solely those of the authors and do not necessarily reflect the views of the Board of Governors of the Federal Reserve System, the Federal Deposit Insurance Corporation, or the United States.

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Recognizing the importance of credit to households and communities, policymakers have had a longstanding interest in ensuring equal access to credit and expanding access to credit.

Legislative examples include the Equal Credit Opportunity Act of 1974, the Community Reinvestment Act of 1977, and the creation of the Community Development Financial Institutions Fund in 1994. Policymakers have also explored ways to increase the availability of small-dollar credit (e.g., Federal Deposit Insurance Corporation, 2018; Board of Governors of the Federal Reserve System et al., 2020), and the Consumer Financial Protection Bureau has examined how to expand credit access among the nearly 20% of adults who are credit invisible or unscorable (e.g., Brevoort et al., 2015; Brevoort and Kambara, 2017). Despite these efforts, Black and Hispanic households are much less likely to have credit than White households. For example, in 2015 about 75% of White households had a credit card or a personal loan or line of credit from a bank, compared with 45% of Black households and 50% of Hispanic households (Federal Deposit Insurance Corporation, 2016).

In our article in the RIM Special Issue of Journal of Consumer Affairs, we examine the extent to which household characteristics, access to financial providers, and neighborhood population characteristics can explain these racial and ethnic differences in credit use. We utilize unique, nationally representative data on over 30,000 households from the June 2015 Unbanked and Underbanked Supplement to the Current Population Survey (CPS). These data include a rich set of household characteristics, such as income, education, age, and bank account ownership. In particular, the data contain two factors—income volatility and subjective attitudes about banks—that have not been explored in previous literature.

We also explore how access to financial providers (e.g., geographic proximity to bank branches and nonbank financial providers) and neighborhood population characteristics (e.g., census block group measures of income, education, race, and ethnicity) can affect households’ use of credit. Understanding whether residential location is associated with differences in credit use is of particular interest in light of recent work establishing the importance of neighborhoods in affecting a variety of socioeconomic outcomes (e.g., Chetty et al., 2016; Chetty and Hendren, 2018a, 2018b; Aaronson et al., 2020).

Our focus is on credit products that households may use to smooth consumption: bank credit (i.e., a credit card or a personal loan or line of credit from a bank) and nonbank credit (i.e., a rent-to-own service or a payday, auto title, pawn shop, or tax refund anticipation loan). For many households, use of nonbank credit may depend on whether they have access to bank credit (e.g., Bhutta et al., 2015). In particular, households without a credit card likely do not have sufficient credit history to generate a credit score and likely face substantially reduced access to credit. Without a credit score, a household may have to meet its credit needs with costlier forms of credit, including bank overdrafts or nonbank credit products like payday loans, which typically have triple-digit annual percentage rates (APRs).

Our results show that household characteristics such as income and education can account for much of the raw disparities in bank credit use between Black and White households and between Hispanic and White households. While residential proximity to bank branches and nonbank financial providers has little impact on the remaining racial and ethnic disparities in bank credit use, accounting for neighborhood population characteristics has a meaningful impact.

For instance, neighborhoods might affect household-level economic outcomes such as credit use through several channels, including structural features (e.g., segregation and school quality) and cultural factors and social norms (e.g., identity norms and role models). To our knowledge, our study is the first to show that neighborhoods contribute to racial and ethnic disparities in credit use.

Moreover, after accounting for household characteristics and residential location, both Black and Hispanic households are substantially less likely than White households to use any of the credit products analyzed (i.e., to use bank or nonbank credit), raising questions about how well formal credit markets are serving the needs of Black and Hispanic households.

Despite our extensive set of controls for household characteristics and residential location, residual disparities in credit use are generally large in magnitude. We rule out several potential explanations for the residual disparities, including differences in households’ socioeconomic characteristics, credit scores, family background, financial literacy, subjective attitudes toward debt and credit, and residential locations not observed in our data. Instead, we argue that the residual disparities are most likely related to unobserved differences in lenders’ provision of credit, such as banks’ marketing and pricing of credit.

For policymakers and other stakeholders interested in expanding access to credit among underserved populations, our results indicate substantial scope for targeted policy efforts to improve credit access. In particular, innovations in the ways that banks market and extend credit may improve certain households’ ability to utilize credit products to smooth consumption.

Read the full article: link

Ryan Goodstein is a Senior Economist in the Center for Financial Research at the Federal Deposit Insurance Corporation (FDIC). His research interests include consumer finance, banking, and mortgage markets. He has provided technical and analytic support on several FDIC data collection efforts, including the biennial FDIC Survey of Household Use of Banking and Financial Services. Ryan earned his PhD in Economics from the University of North Carolina at Chapel Hill in 2008.

Alicia Lloro is a Senior Economist at the Federal Reserve Board of Governors, where she co-leads the Survey of Household Economics and Decisionmaking (SHED). Prior to joining the Federal Reserve Board, Alicia worked on the FDIC Survey of Household Use of Banking and Financial Services. Alicia’s research interests include consumer finance, survey methodology, and econometrics. Alicia earned her PhD in Economics from the University of California, Irvine in 2013.

Jeffrey Weinstein is a Senior Financial Economist in the Center for Financial Research at the Federal Deposit Insurance Corporation. His research interests include consumer finance, economics of education, public economics, and urban economics. Since joining the FDIC in 2014, he has worked on economic inclusion research projects, including the biennial FDIC Survey of Household Use of Banking and Financial Services. Jeffrey earned his PhD in Economics from Yale University in 2008.

References

Aaronson, D., Hartley, D. and Mazumder, B. (2020) The effects of the 1930s HOLC “redlining” maps. Federal Reserve Bank of Chicago Working Paper No. 2017–12.

Bhutta, N., Skiba, P.M. and Tobacman, J. (2015) Payday loan choices and consequences. Journal of Money, Credit and Banking, 47(2–3), 223–260.

Board of Governors of the Federal Reserve System, Federal Deposit Insurance Corporation, National Credit Union Administration, and Office of the Comptroller of the Currency. (2020) Interagency guidance for responsible small-dollar loans. Federal Deposit Insurance Corporation Financial Institution Letter No. FIL–58–2020.

Brevoort, K.P., Grimm, P. and Kambara, M. (2015) Data Point: Credit Invisibles. Washington, DC: Consumer Financial Protection Bureau.

Brevoort, K.P. and Kambara, M. (2017) Data Point: Becoming Credit Visible. Washington, DC: Consumer Financial Protection Bureau.

Chetty, R. and Hendren, N. (2018a) The impacts of neighborhoods on intergenerational mobility I: childhood exposure effects. Quarterly Journal of Economics, 133(3), 1107–1162.

Chetty, R. and Hendren, N. (2018b) The impacts of neighborhoods on intergenerational mobility II: county-level estimates. Quarterly Journal of Economics, 133(3), 1163–1228.

Chetty, R., Stepner, M., Abraham, S., Lin, S., Scuderi, B., Turner, N., Bergeron, A. and Cutler, D. (2016) The association between income and life expectancy in the United States, 2001–2014. Journal of the American Medical Association, 315(16), 1750–1766.

Federal Deposit Insurance Corporation. (2016) 2015 FDIC National Survey of Unbanked and Underbanked Households. Washington, DC: Federal Deposit Insurance Corporation.

Federal Deposit Insurance Corporation. (2018) Request for information on small-dollar lending. Federal Deposit Insurance Corporation Financial Institution Letter No. FIL–71–2018.