Heartland Forward is assisting Memphis-area policymakers and entrepreneur support organizations in creating a more equitable entrepreneurship ecosystem for Black business owners. Achieving equity is key to improving quality of life in the Black community, as entrepreneurship can be a gateway to creating generational wealth for families. It is also key to unlocking the potential of the entire Memphis economy, as Black individuals account for 46 percent of all adults in the Memphis metropolitan area.
To assist the Memphis community, we analyzed both qualitative data, which resulted from focus groups we conducted in June 2023, and quantitative data, which we obtained from the Census Bureau’s Annual Business Survey database and from individual responses to the Census Bureau’s American Community Survey. This page tells the story of the quantitative data.
As we proceed through the data story, the reader will be provided interactive visuals as well as a discussion of the data displayed in those visuals. However, we encourage the reader to draw conclusions beyond those we have drawn and use the data to help answer their own specific questions.
Broad Trends in the Memphis Metro Based on Annual Business Survey Data
Data presented in this section are generally from the Annual Business Survey (ABS)1 and its predecessor, the Survey of Business Owners; through these surveys, we have data on business owners2 in the Memphis metropolitan area for the years 2012, 2018, 2019, and 2020. We will also view population data from the American Community Survey to understand how demographic groups’ population shares compare to their business ownership shares.3 We will place particular focus on how the Memphis Black community compares to the Memphis white community for different population and business ownership measures. In this section, “Black” indicates any individuals who identify as Black alone, and “white” indicates any individuals who identify as white alone.
Adult population data are a good place to begin the discussion of the quantitative data, as the relative sizes of adult populations for the Black and white communities will indicate the relative numbers of businesses we would expect to be owned by individuals in each community if each had equal access to business ownership. Figure 1 shows Black and white adult populations in the Memphis metro across time. Over the past decade, the Black population has steadily risen, while the white population has steadily declined; the two groups now make up roughly equal shares of the Memphis adult population. The large relative size of the Black population is a characteristic unique to Memphis; no other metropolitan area with a total population over 1 million people has a Black adult population share as high as Memphis (46%). This means Memphis’ economy is intrinsically tied to the success of its Black population to a degree that no other large metro is. If the Black population in Memphis is not offered sufficient career resources, entrepreneurship-related and beyond, the region’s economic progress will be limited.
Moving to entrepreneurship in the Black and white communities, the situation is less equal. However, the inequality is a bit nuanced. For example, the numbers of Black- and white-owned nonemployer firms, which are plotted in Figure 2, were roughly equal across the previous decade; unfortunately, there is no available information on the numbers of nonemployer firms in the post-March 2020 era. Nonemployer firms comprise sole proprietors and independent contractors who do not employ any other individuals in the operation of their businesses.4 As is indicated by the high numbers of firms, these are the most common type of business. However, they are the least likely to create significant owner income among the business types we will consider. Indeed, many of these firms will be necessity entrepreneurship ventures, which are businesses, such as handyman services and Uber contracting, that exist because the owners are unable to earn sufficient income by working for someone else.
Contrary to the nonemployer firm numbers, the numbers of employer firms differ significantly by race. Indeed, while the Black and white communities make up roughly equal shares of the adult population and nonemployer firms, there are more than 11 times as many white-owned employer firms as there are Black-owned employer firms. This is concerning because employer firms, due to their larger scale, have much greater potential than nonemployer firms to generate significant wealth for their owners. Additionally, we would expect a large portion of these employer firms to be examples of opportunity entrepreneurship, which contrasts with necessity entrepreneurship, as many of these businesses will have been founded to take advantage of an identified opportunity to profit. It should be noted that the number of employer firms is incredibly stable across time, reflecting the time needed to develop a business that can hire employees, as well as the stability of such businesses.
One way to capture the success of employer firms is to look at the number of employees they have. Figure 4 plots the average number of employees at employer firms by race, and interestingly shows the average number of employees at Black-owned employer firms nearly converged with the average number at white-owned firms in 2019. This indicates Black-owned businesses were finding similar levels of success to white-owned businesses once they overcame the hurdle of becoming an employer, implying that local entrepreneur support organizations should work to understand what barriers are preventing Black-owned businesses from becoming employer firms. Unfortunately, the trend toward convergence reversed in 2020, with a gap in average size jumping from 1 employee to more than 7 employees. The opening of the gap may be the result of differences between Black- and white-owned employer firms that resulted in varying impacts of the early pandemic period. For example, a larger proportion of Black-opened businesses may be restaurants, and restaurants generally struggled in 2020. Future data releases will indicate whether Black- and white-owned firms again converged in size in 2021 and 2022, or if the gap in 2020 persisted.
Our final visualization of the ABS data looks at employer firm ownership by both race and sex, allowing us to see how business ownership rates vary by sex, and how that variation impacts ownership rates by race. What is immediately clear in this visual is that there is a much greater disparity between white male and white female ownership rates than there is between Black males and Black females. However, white females own more employer firms than Black males and Black females combined. Overall, this visual captures differences in entrepreneurship opportunity across demographic groups, implying that white males have significantly more opportunities, whether because of financial backing from their families, encouragement from their social networks, or greater access to entrepreneurship mentors, than the other three groups plotted.
Diving Deeper into Black Business Characteristics
Unfortunately, we can only learn so much from the ABS data. In order to better understand the state of Black entrepreneurship, we needed to create our own metrics using individual responses to the Census Bureau’s American Community Survey.5 These data give economic and demographic characteristics for each of roughly 3 million annual respondents to the survey, allowing researchers to estimate the characteristics of communities across the US.6 Because we are constructing our own metrics, we are able to be more specific with our race selections. In particular, we will consider an individual to be Black if they identify as Black alone, or if they identify as Black in addition to another race. Additionally, we use individuals who are white alone and not Hispanic as our benchmark group. Another technical aspect of these data is that we utilize either 2-year or 5-year aggregations of the data so that we can be more confident in our metrics. Metrics for a set of years can be thought of as the average situation across that set of years. Finally, all metrics reported in each section are for the Memphis metropolitan area overall.7 See the appendix for replications of Figures 6 and 7 for Shelby County only.
For this portion of the analysis, we focus on business owners rather than businesses and utilize the term “self-employment,” which we define as individuals whose primary job is business ownership. Figure 6 plots the self-employment rate, or the share of all employed individuals who are self-employed, for the Black and white, non-Hispanic populations; data are aggregated to sets of two years. Similar to employer firms, Black individuals are significantly less likely than white individuals to be self-employed, and this inequity has been relatively steady across time. This is of concern because becoming self-employed is a key step in the journey toward entrepreneurship success. Until entrepreneurs make their business their primary economic focus, they are diverting important time that could be devoted toward growing and improving their business. A further concern is that while the white self-employment rate jumped to its highest level in the past decade during the early-COVID period, the Black rate remained relatively unchanged. While the national conversation on post-COVID entrepreneurship has focused on an uptick in entrepreneurship as people were able to rethink their career paths during the lockdown periods, only the white community in Memphis has experienced an uptick in individuals achieving self-employment status.
We can separate self-employed individuals into ones who own an incorporated business and ones who own an unincorporated business; an incorporated business is one that has registered as an LLC, S-Corp, or some other form of legal corporation. Incorporation is a key step because it legally formalizes the business, makes the process of receiving investment easier, can provide tax benefits, and reduces the liability of the business owner. Higher incorporation rates indicate that business owners both are guided on the benefits of incorporating and feel they are prepared to formalize their business. Figure 7 indicates the incorporation rate has increased over the past decade in the Memphis Black business community, from 17% in 2012-2013 to 30% in 2020-2021. The Black business incorporation rate in Memphis is now roughly equal to the white incorporation rate (35%). The convergence to the white business incorporation rate may be an indication that more self-employed individuals are receiving guidance on the benefits of incorporating. Unfortunately, we do not know how incorporation rates compare for Black and white business owners who have not achieved self-employment status.
What do the data say about the economic benefits of entrepreneurship? One notable finding, presented in Figure 8 for the 2020-2021 period, is that both Black and white unincorporated business owners are notably more likely to live in a household below the poverty line than individuals of the same race who work for someone else. However, poverty rates for incorporated business owners are comparable to those employed by someone else. Thus, Black and white individuals who own an incorporated business are no more likely to be in poverty than if they had continued to work for someone else, while we would expect their income ceiling to be higher as a business owner. While not visualized, it should be noted that the difference in poverty rates between incorporated and unincorporated business owners did not exist in the Memphis Black business community prior to the pandemic. Thus, it may be worthwhile for local entrepreneur support organizations to ask why the difference exists in the pandemic period; it may be that incorporated Black business owners were uniquely able to take advantage of the changed economic landscape or that more necessity entrepreneurs became self-employed in an unincorporated business during the pandemic period.
Note: The following 5 figures plot 5-year measures for the 2017-2021 period.
A notable economic difference between self-employed and non-self-employed workers is the homeownership rate, which is plotted in Figure 9. For the Black community, there is a 9 percentage-point difference between the self-employed homeownership rate (59%) and the non-self-employed – but still employed – homeownership rate (50%); the difference is 7 percentage points in the white, non-Hispanic community. The reason for the difference in homeownership rates between the self-employed and non-self-employed is difficult to identify. It could be that an individual who wishes to work for themself is also likely to want to own their own home; basically, the self-employed have a higher sense of agency. It could also be that self-employment improves one’s financial position, making homeownership more attainable. Finally, it could be that initially owning a home opens the door to entrepreneurship, as an individual could take out a home-equity line of credit to cover their startup and/or scaling costs. Because of the complexity of this relationship, we asked our focus group participants to help us interpret it. They indicated that the reason likely differs across individuals, but it is generally one or more of the three possible reasons just described.
Figure 10 displays a concerning infrastructure-related finding: Black individuals who are self-employed in an incorporated business are notably less likely than their white, non-Hispanic counterparts to have a high-speed internet subscription.8 More specifically, while all self-employed Black individuals and white individuals self-employed in unincorporated businesses have high-speed internet subscription rates closer to 80%, white individuals self-employed in incorporated businesses have a 90% subscription rate. This reflects either a lack of quality high-speed infrastructure or a lack of affordable high-speed internet, and the differential is an issue because it means Black self-employed individuals are less likely than the white incorporated self-employed to be able to fully operate the digital portions of their business at home. This finding does come at an opportune time, as the federal government has allocated unprecedented funding for broadband infrastructure expansion across the country via the Bipartisan Infrastructure Deal. Therefore, it is our hope that this gap will be closed within the next few years.
Looking deeper into the demographics of the self-employed, Figure 11 plots self-employment rates by race and sex. In some ways, these data align with the ABS employer firm data, but in other ways it does not. For example, white males are the most likely to be self-employed, followed by white females. However, one notable difference is that while Black males and Black females own roughly equal numbers of employer firms, Black males are much more likely to be self-employed. The most likely explanation is that self-employed Black females are more likely to be employers than self-employed Black males, resulting in a larger number of self-employed Black males who do not own employer firms than self-employed Black females.
Figure 12, which plots self-employment rates by race and age group, adds some context to the large numbers of Black-owned nonemployer firms and small numbers of Black-owned employer firms and Black self-employed individuals. In particular, the Black self-employment rate for under-40 workers is 47% of the white, non-Hispanic rate, while the Black rate for over-40 workers is 60% of the white rate. We can interpret this as an indication that white individuals are better positioned for entrepreneurship during their early career, likely because of greater family wealth to help fund their endeavors and a greater number of entrepreneurs in their social network to mentor them. The closing of the rate gap later in Black individuals’ careers is an indication they can build connections and wealth as they move through adulthood to overcome the early-career inequities. However, these early-career inequities mean that Black entrepreneurs must start their businesses later in their careers, on average, than white entrepreneurs. This delay leads to Black entrepreneurs achieving self-employment and employer status later in life, and benefiting from the wealth-creating potential of entrepreneurship for a shorter period of time than their white counterparts. Therefore, programs that address the early-career inequities between Black and white potential entrepreneurs should greatly benefit the Black business owner community, as well as the Black community overall and future generations of Black entrepreneurs.
Our final visual, Figure 13, displays self-employment rates by race and marital status. This visual clearly shows that individuals who are married, or who have previously been married, are significantly more likely to be self-employed than individuals who have never been married. One reason for this is that we would expect never-married individuals to be, on average, younger than those who are, or were, married. Another is that being married or previously married means that this individual has, or previously had, the financial and/or emotional support of a spouse that is beneficial to someone pursuing entrepreneurship. Unfortunately, the self-employment rate differential between those who have never been married and those who are, or have been, married contributes to the lower self-employment rates in the Black community. This is because the Black community marry at lower rates than the white community, which can be seen by comparing self-employment rates overall (Figure 6) to self-employment rates by marital status: Note that the 2020-2021 overall self-employment rate for the white, non-Hispanic community (10.3%) is very close to the 2017-2021 self-employment rate for white, non-Hispanic individuals who are married or who have previously been married (10.6%). Meanwhile, the overall Black self-employment rate (4.9%) is much closer to the mid-point between the Black never-married rate (2.3%) and the Black married-or-previously-married rate (7.2%). This reflects the fact that a much larger proportion of white, non-Hispanic workers are, or were, married than Black workers, and have benefited from the support a spouse can provide.
This concludes the story of the data we have analyzed for this project. We believe the data reflect the variety of uphill battles the Black community face in achieving entrepreneurship success. However, we also believe the data reflect the potential of entrepreneurship to improve economic conditions in the Black community, as well as reflect the ways in which the barriers to entrepreneurship success can be reduced. We hope the reader will consider the message of the data beyond what we have provided here, drawing their own conclusions on the current state of Black entrepreneurship in Memphis and the steps that can be taken to improve the state in the future.
Appendix I: Self-Employment Metrics for Shelby County, Tennessee
This appendix provides replications of Figures 6 and 7 for Shelby County, Tennessee, specifically. Shelby County contains the city of Memphis and is the largest county in the Memphis metropolitan area. As the city of Memphis comprises two-thirds of Shelby County’s population, data visualized in the figures will provide a better understanding of the city’s Black business ecosystem than the metropolitan area visuals.
Figure A1 plots the self-employment rate by race in Shelby County and demonstrates similar inequities to the metro overall. This reflects the fact that the city of Memphis and Shelby County are the central economic and population hubs of the metro.
Figure A2 plots the number of self-employed individuals in the county by race and incorporation status. This figure, in comparison to Figure 7, demonstrates a demographic difference between Shelby County and the metro overall; 84% of the metro’s self-employed Black individuals reside in Shelby County, compared to 63% of the metro’s self-employed white individuals. This is largely due to the fact that the Black share of the population in Shelby County is higher than the Black share of the population in the rest of the metro; the reverse is true for the white, non-Hispanic population. The implication of these data is that the economic success of the city of Memphis and Shelby County is more dependent on the success of Black businesses than metro-level metrics indicate.
1. U.S. Census Bureau. (2023). Annual Business Survey [Dataset]. Retrieved July 10, 2023 from https://data.census.gov/
2. U.S. Census Bureau. (2019). Survey of Business Owners [Dataset]. Retrieved July 10, 2023 from https://data.census.gov/
3. U.S. Census Bureau. (2023). American Community Survey [Dataset]. Retrieved July 10, 2023 from https://data.census.gov/
4. Contractors providing services to businesses are not considered employees, so it is possible that some of these nonemployer firms utilize the services of others in their operations.
5. Ruggles, S., Flood, S., Sobek, M., Brockman, D., Cooper, G., Richards, S., and Schouweiler, M. IPUMS USA (Version 13.0) [Dataset]. IPUMS. https://doi.org/10.18128/D010.V13.0
6. We would like to inform those familiar with these data that we utilized the Census Bureau recommended methods for generating measures from the individual responses, using Census Bureau-provided weights associated with each response to aggregate to community-level counts and rates. Additionally, we utilized the provided replicate weights to calculate standard errors associated with our measures, and used the standard errors to identify differences across demographic groups that are statistically significant at the 90% level – most differences were statistically significant at a much higher significance level. All differences highlighted in this section were statistically significant at the 90% level.
7. Unfortunately, we were only able to generate metro-level values using the Tennessee and Mississippi portions of the metro, excluding the Arkansas portion. However, the Arkansas portion makes up only a very small portion of the overall metro population, so we believe the values we present are close approximations of the values we would obtain if we were able to generate the data for the entire metro. We were able to confirm this by generating metric values that are also provided in the American Community Survey’s metrics database and comparing our values to the corresponding metro-level values in the database, ensuring that approximations using our “definition” of the metro produce very similar values to what we would have obtained if we could have included the Arkansas portion of the metro in our calculations. Compared metrics include the overall number of Black workers in the metro and the share of all workers who are self-employed.
8. The Census Bureau defines high-speed internet as any broadband service, such as cable, fiber optic, or DSL service.