By Austin Cummings, Research Associate
“Financial violence is racial violence: geographies of housing financialization spatialize hierarchies of death-dealing difference.”
Home improvement, repair, and update projects serve a number of purposes. They help households increase the equity in their homes, make important and necessary repairs to preserve the longevity and safety of their homes, adapt their homes to the on-going and future impacts of climate change, and acts as a means for preserving the affordable housing stock of an area. Spending on home improvement projects in the U.S dramatically increased during the COVID-19 pandemic. According to the Joint Center for Housing Studies of Harvard University, spending on home improvements and repairs grew by 24 percent between 2019 and 2021 as households modified living spaces for work, school, and leisure in response to the COVID-19 pandemic. This trend in spending on home improvements and repairs continued in the later parts of the COVID-19 pandemic, with U.S. households spending $567 billion on home improvements and repairs in 2022.
The need for home repairs across neighborhoods is not evenly distributed. Moreover, the costs and benefits accrued from home improvement projects are not evenly distributed across neighborhood types or between white and minority homeowners. Lower-income households are more likely to live in homes that need more maintenance, are in need of replacing critical systems and equipment, and susceptible to damage from inclement weather and natural disasters. Home repair and improvement projects pose considerable cost burdens for lower-income homeowners and limit their opportunities to build wealth. Despite spending less total dollars on home improvement and repair projects, lower-income households spend a higher share of their income on home improvement projects compared to higher-income homeowners. Lastly, longstanding discrimination and predatory practices in the labor market, education system, and housing market have resulted in homeowners of color having lower median incomes than white homeowners and living in housing that is in need of critical repairs. As Taylor (2019) and Satter (2010) painstakingly detail in their respective books, redlining and predatory real estate and lending practices pushed African American homebuyers into homes that were in serious disrepair without access to the loans and income needed to make critical repairs to improve the long-term safety and value of their homes.
During a time of unprecedented spending on home repair and improvement – endeavors which ultimately increased the equity, longevity, and safety of homes– lower-income and minority homeowners experienced significant barriers in accessing and accruing the benefits of taking part in home repair activities. One common way that families might seek to fund home improvement projects is through applying for a home improvement loan. Research suggests that everyone does not have equitable access to home improvement loans, and that a person’s race, income level, and geographic location might impact their likelihood of being approved for a loan.
An analysis of the 2021 HMDA data illustrated that there are disparities between accessing home improvement loans between Black and white applicants in Cuyahoga County. Notably, the analysis demonstrated:
- White applicants were over 2.1 times more likely than Black applicants to have a home improvement loan originated in Cuyahoga County.
- Black applicants were over 1.9 times more likely than white applicants to have home improvement loans denied in Cuyahoga County.
- Upper Income Black applicants (<120% Cuyahoga County median income) and Higher Upper Income Black applicants (<200% Cuyahoga County median income) are approved for home improvement loans at a lower rate than Moderate and Middle Income white applicants.
- Upper Income Black and Higher Upper Income Black applicants are denied at a higher rate than Moderate and Middle Income white applicants.
Building on these findings, this blog post examines geographic trends in home improvement loan denial and origination rates throughout Cuyahoga County. The goal of this analysis is to understand where home improvement loans are originated and denied, and if there are geographic disparities in accessing home improvement loans in Cuyahoga County.
The Persistent Impact of Redlining
Understanding the current trends in lending outcomes requires accounting for the history of racial discrimination in lending. Segregated living patterns in Cuyahoga County were, in part, created and maintained by discriminatory mortgage lending practices institutionalized through the Home Owner’s Loan Corporation (HOLC) and Federal Housing Administration (FHA) starting in the 1930s. These practices internalized the belief that nonwhite neighborhoods are not worthy of credit, and bolstered discriminatory lending practices until the passage of the 1968 Fair Housing Act. The history and practice of redlining has and continues to significantly shape life outcomes, access to wealth, exposure to environmental harms, and access to socio-economic opportunity. Previous research through the Fair Housing Center for Rights & Research has illustrated how ethnic and racial disparities in accessing home mortgages have persisted. Figure 1 and Figure 2 illustrate the demographic divides throughout Cuyahoga County and where redlining designations were compared to contemporary demographics. Figure 3 and Figure 4 illustrate median home value for residential homes at the census tract level throughout Cuyahoga County and redlining designations. The maps illustrate that Cuyahoga County is segregated and that nonwhite communities continue to live in areas that were redlined. Moreover, lower median home values are concentrated in areas that were previously redlined. The history and persistent impact of redlining, predatory lending, and other discriminatory practices in housing shape where people live and the quality and value of the housing stock throughout the county.
Geographic Distribution of Home Improvement Loans in Cuyahoga County
Housing advocates, community development practitioners, and residents discuss the geography of Cuyahoga County along two main axes: east-west and city-suburb. This analysis utilizes this divide because the county is divided along racial and socio-economic lines that fit these categories. Table 1 briefly summarizes socio-economic and demographic data across each region of Cuyahoga County. Most notably, the East Side of Cleveland and East Inner Suburbs have the highest percentage of ethnic and racial minorities in Cuyahoga County and the lowest median household incomes in the region. The East Inner Suburbs and East Side of Cleveland also have low median home values. On the other hand, the Outer Suburbs and Inner West Suburbs are predominately white and have higher concentrations of Upper and Higher Upper Income households, while also having higher median home values.
Table 1: Socio-Economic and Demographic Information across Cuyahoga County Regions
| Income Level | East Inner Suburbs | East Side Cleveland | Outer Suburb | West Inner Suburb | West Side Cleveland |
| Lower | 10.9% | 19.0% | 4.6% | 7.1% | 13.2% |
| Moderate | 13.1% | 22.0% | 7.9% | 8.8% | 19.7% |
| Middle | 20.1% | 24.3% | 15.3% | 20.1% | 21.0% |
| Upper | 27.7% | 22.7% | 28.6% | 31.0% | 25.5% |
| Higher Upper | 26.1% | 9.7% | 41.0% | 31.0% | 18.9% |
| Median Household Income | $50,215 | $28,038 | $80,523 | $62,196 | $41,354 |
| Median Home Value (1-3 Family Residential) | $74,300 | $27,800 | $170,300 | $120,900 | $59,400 |
| Percent Minority | 53.0% | 87.0% | 15.0% | 12.0% | 38.0% |
Home improvement loan application concentration, origination rates, and denial rates follow geographic patterns that suggest there is ethno-racial stratification in this part of the lending market. Table 2 illustrates that home improvement loan applications were primarily concentrated in the Outer Suburbs of Cuyahoga County in 2021, with 43% of all home improvement loan applications coming from the Outer Suburbs. The East Side of Cleveland, with the highest percentage of minority population and greatest concentration of Lower and Moderate Income communities, has the lowest number of home improvement loan applications in 2021.
Table 2: Home Improvement Loans across Region
| Region | Total Applicants | Percent of Loans |
| East Inner Suburbs | 969 | 16% |
| East Side of Cleveland | 596 | 10% |
| Outer Suburbs | 2569 | 43% |
| West Inner Suburbs | 1150 | 19% |
| West Side of Cleveland | 719 | 12% |
| Average | 1200 | 20% |
Figure 5: Home Improvement Loan Origination and Denial Rates – Cuyahoga County
The average home improvement loan origination rate for Cuyahoga County is 39.67%, while the average denial rate is 44.35%. The Outer Suburbs, West Inner Suburbs, and West Side of Cleveland have higher than average origination rates. Denial rates are highest in the East Inner Suburbs and East Side of Cleveland. In addition to having the highest concentration of home improvement loan applications, the Outer Suburbs had the highest origination rates out of any other region in Cuyahoga County in 2021, with 52% of home improvement loans applied for being originated. Overall, an applicant from the East Side of Cleveland is denied at 2.13 times the rate of an applicant from the Outer Suburbs. Moreover, an applicant from the West Side of Cleveland is approximately 2 times more likely to have a home improvement loan application originated than an applicant from the East Side of Cleveland.
As Figure 6 and Figure 7 further illustrate, there is relationship between the concentration of home improvement loan origination and denial rates and ethno-racial demographic trends across Cuyahoga County census tracts. Denials are concentrated in minority-majority census tracts and originations are concentrated in white-majority census tracts. Figure 8 and Figure 9 further illustrate home improvement loans are flowing into more affluent areas in Cuyahoga County. This suggests that predominately white, affluent communities in Cuyahoga County are able to access loans to improve and increase the equity in their homes, while minority-majority communities, with higher concentrations of lower-moderate income households are not being afforded the same opportunity by financial institutions.
Geographic Clustering of Loan Outcomes and Racial Demographics
As a previous blog post highlighted, origination and denial rates for Black applicants are different than white applicants — both within and across income categories. The comparison illustrated that Higher Upper and Upper Income Black applicants were denied at greater or equal rates to Moderate and Middle Income white applicants. Next, the analysis found that regions with higher percentages of nonwhite populations have less loans originated in them and higher amounts of loans denied.
This analysis has illustrated that there are differences in home improvement loan origination and denial rates across the different regions of Cuyahoga County. Outcomes in home improvement application may be structured by the racial demographics of neighborhoods throughout the region. To better understand the relationship between loan denial and origination rates and racial demographics, a Bivariate Local Moran’s I was conducted. This statistical approach tests if instances of two things occur together (or not) and if the clustering of the data is the result of random chance or if it, in-part, is structured by the relationship between the variables we are examining.
With our data, we would hypothesize that there is no clustering — that race doesn’t shape home improvement loan outcomes. To test that, we are going to evaluate if high denial rates occur within census tracts with high or low percentages of nonwhite-Black or Hispanic populations (discussed as nonwhite), or if there isn’t a relationship occurring between those two variables at all. The maps below will show us where different types of lending and demographic concentrations occur and if those patterns are statistically significant.
Figure 10: Bivariate Local Moran’s I: Home Improvement Denial Rate and Level of Nonwhite Hispanic Population
Figure 10 above shows the output for a Bivariate LISA (Local Indicators of Spatial Autocorrelation) conducted on instances of home improvement denial and nonwhite population level at the census tract level. The dark red areas indicate places where there are high concentrations of nonwhite populations and high denial rates. Dark blue areas are places where there are low nonwhite populations and low denial rates. The light red areas show where there are high denial rates, but low nonwhite population. The light blue areas indicate places where there are low denial rates, but high nonwhite populations. The high-high (dark red) areas are predominately concentrated on the East Side of Cleveland and Eastern Suburbs, appearing very similar to the redlining geography in Figure 2 and Figure 4.
Figure 11: Bivariate Local Moran’s I: Home Improvement Denial Rate and Level of Nonwhite Hispanic Significance Map
Figure 12: Moran’s I Test Output: Denial Rate and Nonwhite Hispanic population
Figure 11 is the significance map for the bivariate local Moran’s I conducted for denial rate and level of nonwhite population in Figure 6. This illustrates that the concentration of high-high and low-low relationship described above are statistically significant. Figure 12 shows the results of the Moran’s I test, which is 0.580. The closer the Moran’s I Test statistic is to 1, the higher likelihood the data is clustering together. This test illustrates that the distribution of high and low values in the data are more spatially clustered than would be expected if the underlying spatial processes behind loan denial were completely random and not influenced by racial demographics. This means there is clustering of high denial rates in areas with high nonwhite populations and clustering of low denial rates in areas with low nonwhite populations. In other words, originating a loan in a predominately white area significantly increased the likelihood of being approved for a home improvement loan. While applying for a home improvement loan in a minority-majority neighborhood significantly increased the likelihood of having the loan application denied.
More analysis is needed to understand if specific lending institutions are engaged in redlining or other discriminatory practices. Other factors could be structuring these outcomes. With that said, this analysis does suggest race is playing a significant role in home improvement loan application outcomes at the census tract level. Combined with the past blog post, our findings show that Black home improvement loan applicants are denied at almost twice the rate as white applicants, and home improvement loan originations are concentrated in white, affluent communities. Black applicants and nonwhite neighborhoods are being denied access to loans that help them increase the equity in their homes, preserve the longevity and safety of their homes, and improve the housing value across their neighborhoods.
Home Improvement Loan Denial is Perpetuating Racial Disparities in Cuyahoga County
Home improvement loans provide an opportunity for home owners to further invest in their home, increase the equity in their home, and help ensure they can safely inhabit their home. These all contribute to neighborhood stability while also addressing the racial wealth gap and home appreciation gap. Figure 13 and Figure 14 illustrate the geography of home improvement loan amounts throughout the Cuyahoga County for originated loans. They provide a snapshot of the disparate geography of investment in Cuyahoga County. Loans – investment, capital, money- are flowing into predominately white communities, while predominately African American communities and other nonwhite Hispanic communities are being denied access to opportunities to improve the quality of their home, increase their quality of life, and essentially accumulate wealth through their home.
Figure 13: Home Improvement Loans – Median Loan Amounts by Census Tract and Demographics in Cuyahoga County
Figure 14: Home Improvement Loans – Median Loan Amounts by Census Tract and Median Housing Value in Cuyahoga County
Overall, this analysis illustrates that home improvement loan originations are clustered in predominately white census tracts in Cuyahoga County, while denials for home improvement loans are predominately clustered in minority-majority census tracts. There are significant differences in accessing home improvement loans in Cuyahoga County between white and Black applicants. Next, it demonstrates that banks and other lending institutions are serving white neighborhoods and white applicants differently than nonwhite neighborhoods and applicants. Notably, neighborhoods with a higher percent minority population are denied at a statistically significant level compared to white majority areas. Taken together, these findings illustrate that home improvement loan origination and denial rates possibly further solidify patterns of racialized wealth inequality, racialized disparities in home value, uneven home value recovery in the wake of the 2008 mortgage foreclosure crisis, and uneven access to loans to improve the long term safety and viability of homes in minority-majority neighborhoods and for Black homeowners. Moreover, Figure 13 and Figure 14 illustrate that home improvement loan dollars are flowing into predominately white, affluent areas. These outcomes suggest that the financialization of home repair during the COVID-19 pandemic functioned to further calcify spatialized hierarchies of racial difference in Cuyahoga County, through disproportionately benefiting white homeowners, white-majority neighborhoods, and systematically denying Black homeowners and minority-majority neighborhoods from accruing the same benefits or participating in the home repair and remodeling market. Denying financial assistance for home repair and improvement perpetuates systems of violence and oppression through exposing homeowners to unmitigated environmental hazards and undermining their ability to accruing equity in their homes. Home improvement application outcomes result in racial and economic disparity that are built upon and perpetuate systemic oppression and violence.