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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.

Introducing the Major Office Candidates for the ASA 2019 Elections

Introducing the major office candidates in this year’s American Sociological Association leadership election.

Over the past year and a half, the Sociocast Project has sought to develop academic sociology-focused podcast programming, with the goal of developing new and qualitatively-different discussions within our profession.

So far, sociologists from across the US and Canada have collaborated with this project to pilot four series concepts: (1) The Annex, an academic sociology-oriented banter and interview show, (2) The B-Side, an academic social science show with a black community-focused orientation, (3) Sociologia con Acento, a Spanish-language social science interview program, and (4) International Perspectives on Sociology, a showcase of discussions that are topical among academic sociologists of non-US national traditions.

Today, I am proud to announce the pilot episodes of a fifth show concept.: ASA 2019 Election Coverage. It is a “disciplinary civics” project that provides the ASA’s major office candidates with a platform to share their views on the discipline. For more, please visit: www.sociocast.org/asa2019

Data Sets for Students

Looking for data for a social science thesis or dissertation? A list of publicly-available data.

This is an archived version of a page that I created for students in Queens College’s Data Analytics and Applied Research Graduate Program.  

New York City Data

NYC Open Data.  Portal for NYC Open Data initiative.

New York City Community Health Surveys (NYC-CHS)   Data on the health of New Yorkers, including neighborhood, borough, and citywide estimates on a broad range of chronic diseases and behavioral risk factors.

New York City Health and Nutrition Examination Surveys.  The New York City Health and Nutrition Examination Survey (NYC HANES) is a community-based health survey. Two surveys have been conducted, one in 2004 and the most recent one in 2013-14. The first survey conducted by the New York City Department of Health and Mental Hygiene (DOHMH), and the second by the CUNY School of Public Health and DOHMH.

NYC Youth Risk Behavior Survey.  The NYC Youth Risk Behavior Survey (YRBS) monitors priority health risk behaviors that contribute to the leading causes of mortality, morbidity, and social problems among youth in New York City.

The World Trade Center (WTC) Health Registry.  Enrollment in the WTC Health Registry was voluntary for people who lived, worked or went to school in the area of the WTC disaster, or were involved in rescue and recovery efforts.

US Data

Data.gov.  Portal for federal open data intiative.

Social Explorer.  Interactive site that allows users to explore US Census data.

Integrated Public Use Microdata Series (IPUMS).  Massive microdata repository for US and international Census data.

National Historical Geographic Information System.  Repository of GIS-compatible Census data going back to 1790.

General Social Survey.  Portal to General Social Survey data from UC Berkeley.  Tutorial on analyzing GSS data in R.

Bureau of Economic Analysis.  Major US macroeconomic data portal.

Current Population Survey.  Important source for data on US demographic and labor force statistics.  This set is the basis for many major economic indicators, including the unemployment rate.

American Community Survey.  Census Bureau survey on US communities.  Tutorial on analyzing ACS data in R.

US Department of Housing and Urban Development Data.  Data portal from HUD on US housing.

American Housing Survey.  Major survey on US housing.  Tutorial on analyzing AHS data in R.

Consumer Expenditures Survey.  Survey on how Americans spend their money.  Tutorial on analyzing CEX.

Survey of Consumer Finances.  Data on US households’ personal finances.  Tutorial on analyzing SCF.

American Time Use Survey.  Data on how Americans spend their time.  Tutorial on analyzing ATUS.

American National Election Studies.  Systematic survey of US national elections.  Tutorial on analyzing ANES in R.

National Health and Nutrition Examination Survey.  Data on Americans’ health and nutrition.  Tutorial on analyzing NHANES in R.

National Health Interview Survey.  Data tracking Americans’ health status, healthcare access, and progress towards achieving national health policy objectives.

US Historical Income Taxes.  Tables on historical US income tax rates.

USAID Demographic and Health Surveys Program.  Demographic and health data for development studies.

US Department of Homeland Security Immigration Data.  Data on immigration to USA.

National Center for Education Statistics.  Repository for US-related education data.

International Data

World Bank Data Catalog.  Data offered through the World Bank’s Open Data Initiative.  Some recommended data sets:

IMF Principal Global Indicators.  Major data compendium on international economic topics from IMF.

IMF Global Housing Watch.  Data on international cost of housing.

IMF International Financial Statistics.  International database on financial topics.

Correlates of War Project.  Data on states, international alliances, war capabilities, trade, and war.

Center for Systemic Peace.  Data on governance, political stability, and conflict.

  • INSCR Data Page.  Portal to multiple data sets on governance, political stability, and conflict, including forcibly displaced populations, state failure, terrorist bombings, membership in international governmental organizations, democracy, coups d’etat, and state fragility.
  • Polity IV Project.  Data set charting countries’ level of democracy/autocracy since 1800s.
  • Major Episodes of Political Violence, 1946 – 2014.  Data table chronicling 324 incidences of armed conflict between 1945 and 2014.  Authors claim table to be comprehensive.

LABORSTA.  International Labor Organization data on labor conditions across world’s countries.

OECDstat.  Comprehensive economic and social data covering OECD countries.

OECD Better Life Index.  Data on international living standards.

Program for International Student Assessment.  Data on students’ performance on international standardized aptitude test.  Tutorial on analysis of PISA here.

UNU-WIDER World Income Inequality Database.  Database on international income inequality.

World Database of Happiness.  Data on happiness across world’s countries.

World Values Survey.  Data on values across countries.  Tutorial on analyzing WVS.

European Social Survey.  Social data on European societies.  Tutorial on analyzing ESS here.

UK Data Archive.  Repository for UK-related data.

Migration Policy Institute Migration Data.  Data on international migration.

UN Population Data.  International population data.

China Education Panel Survey.  Data on education in China.

Long-Run Historical Data

Global Prices and Incomes Database.  Data on prices and incomes across centuries.

NBER Macrohistory Database.  Long-run data on economic topics.

Wrigley and Schonfield Historical English Population.  Table on historical English population from 1541.

Other Portals

ICPSR.  Databank with sets on a wide range of topics.