Abstract
In the wake of the 2008 Great Recession, a section of the Dodd–Frank Act (DFA) ostensibly provided greater protection to low-income borrowers by capping bank charges on small dollar mortgages (defined here as less than $100,000) and requiring more bank oversight by outside auditors. Previous research has shown that both actions had the perverse consequence of reducing the availability of mortgage credit to low-income borrowers. Building on these findings, we investigate the following question: Did the decline in access to credit lead to a decrease in demand for homes in high poverty census tracts, and a corresponding decline in property values in these areas? Using an OLS regression model of home values and census tract data in Forsyth County, North Carolina from 2007 to 2020, we calculate that nominal home values dropped by over 40% in the county’s lowest income census tracts after the institution of the DFA, relative to the rest of the county. Our paper offers evidence that DFA has harmed those that the Act was intended to help.
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Notes
Studies differ on whether owning a home versus renting is the fastest way to build wealth, given the often-unexpected maintenance costs of home ownership, and the opportunity costs of other wealth-building opportunities, such as investing in a stock portfolio. While owning a home is not for everyone, a mortgage may create a form of “forced savings” that some people prefer over managing a stock portfolio. The average homeowner boasts a net worth of $255,000, close to 40 times that of the average renter, at $6300 (Kuo, 2021).
Owner-occupied homes make up about two-thirds of all residences, which can include single unit dwellings, condominiums, and apartment co-ops (U.S. Census Bureau, n.d.). The median value of these homes in the United States in 2020 was $230,000.
We define a small-dollar mortgage as having a loan value less than $100,000 following the convention used in recent research. Asset prices such as houses are usually reported in the literature in nominal values, and this also avoids the complication of yearly adjustments to the definition of a small dollar mortgage (McCargo, Zhu, Strochak, and Ballesteros, 2020).
These were calculated using American Community Survey 5-Year estimates for 2009 and 2020.
The full name is the Dodd-Rank Wall Street Reform and Consumer Protection Act of 2010, and its purpose was to rein in large Wall Street banks, but it affected all banks with the same rules and regulations of compliance, having 850 pages of legislative text and nearly 19,000 pages of regulatory text.
The Diversity and Disparities project uses 2020 Census data for this estimate. The percentile related to income inequality is based on the authors’ calculations according to the American Community Survey 5-Year Estimates for 2016–2020. The percentile does not incorporate counties in Puerto Rico.
We considered using the natural log of SDLOANS in order to obtain an elasticity, but there were a substantial number of zero values at the level of the census tract, so we stuck with the semi-log approach.
MapForsyth is the GIS Department for the Winston-Salem/Forsyth County, NC Government.
We also estimated the model without the three covariates with imputed values, and this did not substantially change the results or statistical significance of the remaining variables.
For evaluating semi-logged equations where the dependent variable is logged, one can use the approximate measure of the \(\beta\) i * 100 (Studenmund and Cassidy, 1987), which for small changes can be roughly comparable, and easier to directly interpret from Table 5. To form more precise estimates, following the guidance of Thornton (1989), the appropriate transformation is change = (exp(\(\beta\) i) − 1)*100. For a continuous variable, the semi log coefficient is transformed using (exp(\(\beta\) i*change in X variable) − 1) *100.
Using the transformation formula in footnote 5 did not change the impact, as both methods of interpreting coefficients yielded 5.7%.
Across the county, prior to the DFA, loans larger than $100,000 averaged 12.0 loans per census tract, while after the DFA they grew to 22.7 loans per census tract. By comparison, small dollar loans barely budged, from 4.5 loans per census tract to 5.0 loans, pre and post DFA, but East Winston saw a drop of 0.78 small dollar loans over the same time frame.
In East Winston, we calculate that pre-DFA there were an average of 3.94 small dollar loans per census tract year, which fell to 3.16 loans (post-DFA), a net drop of 0.78 loans per year. This leads to a predicted 2.6% estimated drop in property values using the 2nd formula in footnote 5, e.g., change = (exp(.0328*.78) − 1)*100 = 2.6%.
Information provided by Piedmont Community bank of North Carolina, in 3/24 email to Craig Richardson.
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Acknowledgements
Many people provided helpful feedback and constructive criticisms on earlier versions of our paper. We would like to sincerely thank Drs. Harold Black, Peter Leeson, Daniel Smith, Ramon DeGennaro, Claudia Williamson, Edward Stringham, and Ken Cyree. We would like to thank all of the attendees of the Dr. Harold A. Black Academic Conference in Chattanooga, TN in September, 2022. We would also like to thank Dr. Stephen Miller for his helpful comments. We also thank Dr. Joseph Sloop and Mr. David Toren of MapForsyth for help in acquiring necessary data.
Funding
This work was supported by the Center for the Study of Economic Mobility at Winston-Salem State University. The authors have no relevant financial or non-financial interests to disclose.
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Richardson, C.J., Blizard, Z.D. Did the 2010 Dodd–Frank Banking Act deflate property values in low-income neighborhoods?. Public Choice 197, 433–454 (2023). https://doi.org/10.1007/s11127-023-01084-7
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DOI: https://doi.org/10.1007/s11127-023-01084-7