Entrepreneurship and Race, 1989 – 2016

A look at differences in entrepreneurship participation rates across race.

This analysis examines the prevalence of entrepreneurship across U.S. households by race from 1989 to 2016. We are looking for racial differentials in entrepreneurship participation, and evidence of changes over time. The data suggest that entrepreneurship rates have been relatively constant over the time period studied, and that whites are more likely to participate in entrepreneurship.

Data

We use data from the Survey of Consumer Finances1 We use the convention of identifying entrepreneurs through a “self-employed” labor market status or through reported possession of an actively managed busienss.2 For race, we focus on the race of the households’ head, as defined in the data. Of course, there are many issues to unpackage when contemplating the Survey’s traditional methods for designating household heads, but we will bracket them here.

Results

Overall, the data appears to suggest that little has changed in self-employment rates across major race/ethnicity groups.

Entrepreneurship

Our first figure shows estimates of entrepreneurship participation rates from 1998 to 2016. These figures represent the estimated percent of U.S. households with at least one household head who is either self-employed or owns an actively-managed business.

Our estimates suggest that white-headed households’ entrepreneurship rates have been stable since the late-1990s. One can read the figure as suggesting that rates rose slightly among households whose heads chose to self-identify as black or Hispanic. If such an observation is indeed picking up on a definitive change, and is not a produce of random variation masquerading as a small trend, then one might not that most of this growth seems to have occurred in the early-2000s, and rates show no clear evidence of substantial growth afterwards. However, one could just as easily infer that there’s been very little change in entrepreneurship participation rates. That interpretation strikes me as the most conservative.

Self-Employment

Our second figure focused on self-employment rates only. The figure suggests that these rates were mostly stable among whites.

As with overall entrepreneurship participation rates, self-employment is highest among white-headed households, and has been relatively stable over the past several decades. One could read the data on Hispanic-headed households to suggest a slow long-term growth between 2001 and 2004, and stable rates thereafter. Among black-headed households, self-employment rates are lowest, and have been overall stable until 2016. It seems most prudent to wait for evidence from other data or subsequent years before believing that something changed in black self-employment rates.

Business Ownership

Our final figure looks at business ownership rates. Again, entrepreneurship is most common among white-headed households, and rates have been overall stable across major racial/ethnic groups.

Summary

Overall, this look at the data suggest that entrepreneurship participation rates have been stable over time across major racial/ethnic groups. Despite a range of policies and investments in the promotion of entrepreneurship, these rates have not risen considerably.


  1. Federal Reserve “Survey of Consumer Finances” Data from triennial survey, 1989 to 2016. Available for download at https://www.federalreserve.gov/econres/scfindex.htm
  2. SCF variables x4106, and x4706. We only consider self-employment among household heads.

For More

You can download the R Markdown file used to generate these results from Open Science Framework. The data used in this analysis is available for download here.

Zero Sales Businesses

A substantial proportion of entrepreneurs aren’t actually selling anything.

This analysis is interested in the prevalence of paper entrepreneurs, people who self-identify as self-employed or operating their own business but whose business registers no sales. An example of this kind of entrepreneur might be an unemployed person who works as a “consultant” (and lists themselves on LinkedIn as such), but do not have any clients. Another might be someone who claims to have an actively-managed business in order to construe and write off household expenses as business expenses in order to maximize tax deductions.

I expected to see a secular rise in the prevalence of no sales businesses for at least three reasons. First, I was under the impression that America’s tax system and business enviornment evolved to encourage small businesses formation. Many “zero sales” businesses might be startups at their very earliest stages of development. Given overall rates of entrepreneurship seem to have remained unchanged1, I expected the pool of small businesses to be have proportionally more startups than in the past.

Second, I presumed that the evolution of taxes would create incentives for households to declare business ownership and push household transactions through those businesses as a tax management strategy. I thought that either new regulations or laws created new opportunities to save money in this way, or that new technologies made it easier for people to recognize and capitalize on business deductions (e.g., Turbotax may alert people to the potential for business deductions, and give people a means to capitalize on them).

Third, the title of “entrepreneur” is more socially desirable than that of a retiree or unemployed, and I expected more people to assume these roles when creating public identities on web sites like LinkedIn or on their resumes. Given that job precarity and the forced “retirement” of older workers are widely-discussed as major trends, I thought there was a potential for this dynamic to raise the proportion of “zero sales” entrepreneurs.

Data and Methods

We use data from the Survey of Consumer Finances2 This analysis only considers entrepreneurs who own actively-managed businesses. The other group traditionally counted among entreprneurs – those who self-identify as self-employed – are not included because their business transacting data is not in the data set. We are interested in the percentage of households whose actively-managed businesses collectivelygenerate no sales. If a household has one business with sales, then they are not countes as zero sales entrepreneurs.

Findings

The figure below depicts the estimated percentage of business owners who make no sales. Since 1992, the proportion of actively-managed businesses that registered no sales appeared to bounce within the range of 8.8% (in 2001) and 11.8% (1995). I am not strongly confident that the large change from 1989 to 1992 represents a real change, or whether it is a byproduct of any differences in the survey or sampling mechanisms in these surveys.

Discussion

To some degree, this was an unanticipated finding to me. I found many reasons to expect a rise in these kinds of businesses. These failed expectations could be the result of faulty presumptions, including:

  • Zero sales businesses may not signal business startups
  • Tax policies or economic regulations did not change the ease of forming new businesses
  • Tax policies or technology did not change in a way that sufficiently encouraged enough people to form businesses for the purpose of tax management.
  • Comparatively few people usurp the role of “entrepreneur” to cover up unemployability

For More

You can download the R Markdown file used to generate these results from Open Science Framework. The data used in this analysis is available for download here.


  1. Cohen, J. N. (2019, March 1). Prevalence of Entpreneurship among U.S. Households, 1989 – 2016. Retrieved from <osf.io/q5xmu>
  2. Federal Reserve “Survey of Consumer Finances” Data from triennial survey, 1989 to 2016. Available for download at https://www.federalreserve.gov/econres/scfindex.htm

Personal Incomes from Entrepreneurship, 2016

The distribution of personal incomes from entrepreneurship, from 2016 Survey of Consumer Finances

This analysis examines the proceeds that entrepreneurs earn from their business enterprises using data from the Survey of Consumer Finances.

Data and Methods

We use data from the Survey of Consumer Finances1. We confine our attention to the subset of households that meet one of two conventional criteria for identifying entrepreneurs in survey data: (1) a head who reports a “self-employed” labor market status or (2) reported ownership of an activley-managed business. If either condition is met, the household is included in our analysis.

Entrepreneurial income is captured by two financial statement metrics:

  1. Self-employed income. Questions that ask self-employed respondents “how much [do you] earn before taxes in your main job”2
  2. Business Profit Taken. From questions asking “(In addition to salary,) how much [was] personally received from the business before taxes?”3

Results

Figure 1 (below) presents a bar chart depicting the distribution of entrepreneurship-related income across all households who have a self-employed head or an actively-managed business. Recall that our sub-sample is limited to entrepreneurs only. Some observations of these findings:

  • About 29% of American entrepreneurs earn no money from their businesses
  • The vast majority of American entrepreneurs (59%) did not earn enough from their businesses to sustain a livelihood above the poverty line (above $15,000).
  • About 15% earn more than a roughly median household income of $50,000.
  • A smaller minority (2%) earned more than $200 thousand in 2016.

Discussion

Entrepreneurs are often described as a comparatively wealthy group, and entrepreneurship is often portrayed as a vehicle of wealth. Only about one-seventh of U.S. households participate in entrepreneurship4 The vast majority of these businesses could only sustain the most modest livelihood, if at all. Only a small proportion of this narrow subset of American society earns enough to be counted among high income households. Overall, I read these data as suggesting that few people succeed in generating high income from their businesses.

For More

You can download the R Markdown file used to generate these results from Open Science Framework. The data used in this analysis is available for download here.


  1. Federal Reserve “Survey of Consumer Finances” Data from triennial survey, 1989 to 2016. Available for download at https://www.federalreserve.gov/econres/scfindex.htm
  2. SCF variable x4112 where Head #1 is self-employed, and x4712 where Head #2 is self-employed.
  3. Variables x4131, x4731, x3337
  4. Cohen, Joseph N. 2019. “Prevalence of Entpreneurship among U.S. Households, 1989 – 2016.” OSF. March 1. osf.io/q5xmu.

Changes in Prevalence of Entrepreneurship in U.S., 1989 – 2016

A look at the changing prevalence of entrepreneurship in America, 1989 – 2016

This analysis examines whether the prevalence of entrepreneurship has changed over the past thirty years. The data can be interpreted in one of two ways: (1) as suggesting an end to small business growth in 2004 or (2) as a random walk with no long-term change.

Data and Metrics

I use data from the Survey of Consumer Finances.1 Entrepreneurship researchers conventionally uses one of two methods for identifying entrepreneurs in survey data: (1) a “self-employed” labor market status2, or (2) reported possession of an actively-managed business.3 If either conditions holds, then the household is counted as engaged in entrepreneurship.

Findings

Figure 1 (below) depicts our estimates of entrepreneurship from 1989 to 2016, using SCF data. The dots represent the estimated percentage of U.S. households engaged in entrepreneurship, and the vertical lines emanating from those dots depict these estimates standard errors.4

Figure 1

Overall entrepreneurship rates (red line) appear to have remained constant between 1989 and 2016. About 16.6% of households qualify as being engaged in entrepreneurship in 1989, versus 16.7% in 2016. It is uncertain whether entrepreneurship was rising at a barely-perceptable long-term rise pre-2004 and similarly slow decline post-2004, or whether rates have been bouncing between a normal 14% to 18% rates.

Discussion

If we interpret these findings to suggest a slow rise and decline of entrepreneurship pre- versus post-2004, then changes in self-employment seems to be the driving these trends. From 1995 to 2004, there is a rise in the prevalence of self-employment that could credibly deemed to be significant. By contrast, there has been relatively little change in the prevalence of actively-managed businesses. This line of interpretation leads us to ask what happened around 2004 to change long-term trends in self-employment.

If we interpret these findings as suggesting no long-term change, then a different set of questions emerge. Over the past several decades, governments have launched a range of programs and policy reform initiatives designed to promote small business. Why haven’t they been able to change rates of entrepreneurial participation? In and of themselves, these findings do not serve as conclusive proof these these entrepreneurship-promoting initiatves have been ineffective. For example, it is possible that non-policy facets of the economic environment have become more hostile to entrepreneurs, and these programs have prevented what would have been a decline in entrepreneurship in their absence. Still, it is quite possible that all of the resources and energy that we are pouring into entrepreneurship promotion is not effective.

For More

You can download the R Markdown file used to generate these results from Open Science Framework. The data used in this analysis is available for download here.