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Journal ArticleDOI

Entrepreneurship, Economic Conditions, and the Great Recession

01 Jun 2013-Journal of Economics and Management Strategy (John Wiley & Sons, Ltd)-Vol. 22, Iss: 2, pp 207-231
TL;DR: In this paper, a detailed analysis of the determinants of entrepreneurship at the individual level was conducted to shed light on the effect of recessions on business formation, showing that the positive influences of slack labor markets outweigh the negative influences resulting in higher levels of business creation.
Abstract: The “Great Recession” resulted in many business closings and foreclosures, but what effect did it have on business formation? On the one hand, recessions decrease potential business income and wealth, but on the other hand they restrict opportunities in the wage/salary sector leaving the net effect on entrepreneurship ambiguous. The most up-to-date microdata available – the 1996 to 2009 Current Population Survey (CPS) – are used to conduct a detailed analysis of the determinants of entrepreneurship at the individual level to shed light on this question. Regression estimates indicate that local labor market conditions are a major determinant of entrepreneurship. Higher local unemployment rates are found to increase the probability that individuals start businesses. Home ownership and local home values for home owners are also found to have positive effects on business creation, but these effects are noticeably smaller. Additional regression estimates indicate that individuals who are initially not employed respond more to high local unemployment rates by starting businesses than wage/salary workers. The results point to a consistent picture – the positive influences of slack labor markets outweigh the negative influences resulting in higher levels of business creation. Using the regression estimates for the local unemployment rate effects, I find that the predicted trend in entrepreneurship rates tracks the actual upward trend in entrepreneurship extremely well in the Great Recession.

Summary (3 min read)

1. Introduction

  • The U.S. Economy lost more than 8 million jobs during the recession starting in December 2007.
  • The national housing price index experienced the largest decline on record (Federal Housing Finance Agency 2009).
  • Equity in one's home is the main asset for most Americans and represents 60 percent of all wealth (U.S. Census 2008).
  • Given these opposing forces, the net effect of the recent recession on business creations is ambiguous.
  • The study provides new evidence on the potentially opposing influences of unemployment and housing markets on entrepreneurship, interactions between initial employment status and local labor market conditions, and the types of business created in weak labor market conditions.

2. The Entrepreneurial Decision

  • Theoretical models of the choice to become self-employed are generally based on a comparison of potential earnings from business ownership and wage and salary work.
  • One of the main effects is that recessions reduce consumer and firm demand for products and services provided by startups, thus decreasing potential entrepreneurial earnings, YSE.
  • Recessions may also reduce total wealth, A, which in turn would lower the likelihood of entrepreneurship.
  • In the presence of liquidity constraints, lower levels of wealth may make it more difficult for entrepreneurs to find the required startup capital to launch new ventures.
  • The net effect of these opposing forces on entrepreneurship is ambiguous.

PREVIOUS EMPIRICAL EVIDENCE

  • The previous empirical literature provides evidence on several aspects of how recessions affect the entrepreneurial decision.
  • Owners personally liable for business debts (Avery, Bostic and Samolyk 1998, Cavalluzzo and Wolken 2005).
  • Home ownership and equity are found to be associated with entrepreneurship and obtaining business loans using Finish data (Johansson 2000), U.K. data (Black, de Meza, and Jeffreys 1996), and data from the U.S. Survey of Small Business Finances (Cavalluzzo and Wolken 2005).
  • Previous research on the relationship between unemployment and entrepreneurship provides mixed results.
  • A recent paper by Stangler and Kedrosky (2010) using several data sources finds of a roughly constant rate of firm formation over time.

3. Data

  • There are very few national datasets that provide information on the determinants of entrepreneurship.
  • Longitudinal data is created by linking the CPS files over time.
  • These surveys, conducted monthly by the U.S. Bureau of the Census and the U.S. Bureau of Labor Statistics, are representative of the entire U.S. population and contain observations for more than 130,000 people.
  • Households in the CPS are interviewed each month over a 4-month period.
  • To match these data, I use the household and individual identifiers provided by the CPS.

MEASURING ENTREPRENEURSHIP

  • Measures of the number and rate of business ownership are available from several large, nationally representative government datasets, such as the Survey of Business Owners (SBO), Census PUMS files, and the American Community Survey (ACS).
  • See Fairlie (2010) for more details on matching.
  • To estimate the business formation rate in the matched CPS data, I first identify all individuals who do not own a business as their main job in the initial survey month in the twomonth pair.
  • In addition to being able to carefully define entrepreneurship, the CPS data include information on home ownership and detailed demographic information including race, gender, age, education and family income at the individual level.
  • All observations with allocated labor force status, class of worker, and hours worked variables are excluded from the sample.

4. The Great Recession and Entrepreneurship

  • As a first pass at examining recessionary effects on entrepreneurship, I present national trends in unemployment, home ownership, home values and entrepreneurship.
  • The period from the beginning of 1996 to the end of 2009 captures two downturns and two growth periods.
  • In the mid 2000s both rates declined until the start of the current recession in 2007.
  • But, the displayed patterns are somewhat deceptive.
  • Home prices have dropped sharply over the past few years as entrepreneurship rates have increased.

5. Unemployment, Home Ownership and Entrepreneurship

  • I first examine the overall relationship between unemployment rates in local labor markets and entrepreneurship.
  • Entrepreneurship rates are 0.22 percent for local labor markets with an unemployment rate under 2 percent.
  • Entrepreneurship rates for home owners do not differ from those for non home owners.
  • The relationship appears to be roughly linear.
  • The relationships between entrepreneurship and local unemployment rates, home ownership, and local home prices appear to be stronger than the relationship indicated by the national trends in these measures.

REGRESSION ANALYSIS

  • To examine the independent effects of local labor market unemployment rates and housing markets, I turn to a regression analysis.
  • The estimates indicate that women are less likely to become entrepreneurs.
  • The lowest rate of entrepreneurship is found in Manufacturing.
  • Thus, the effect of a major change in median home prices on the entrepreneurship rate is not large.
  • A positive relationship between local unemployment rates and business creation may partly capture the effects of local government policies attempting to spur job creation in high unemployment areas through encouraging business creation.

INTERACTIONS WITH EMPLOYMENT STATUS

  • The current estimates of local labor market effects capture the net effect of local economic conditions on entrepreneurship.
  • There does not appear to be a differential business creation reaction to local labor market conditions based on home equity.
  • Respond differently to local economic conditions which could provide some suggestive evidence on the two main opposing factors influencing entrepreneurship in recessions.
  • The coefficient estimate implies that individuals who are not currently employed are 0.045 percentage points more likely to start businesses when local unemployment rates rise by 5 percentage points.
  • In two specifications I find smaller, positive coefficients.

TYPES OF BUSINESSES CREATED IN SLACK LABOR MARKETS

  • Professional and Business Services and Construction continue to capture the highest shares of new businesses.
  • The distribution of industries represented by businesses created in high unemployment markets is also similar to the total for all MSAs.
  • To further investigate industry differences by newly created businesses across economic conditions, I estimate regressions for the probability of creating a business in each of the twelve listed industries.
  • The sample is limited to individuals creating businesses.

HOW MUCH DOES THE BUSINESS CYCLE AFFECT ENTREPRENEURSHIP?

  • Most importantly, the increase in the 15 All of the coefficient estimates are statistically insignificant.
  • In Figure 8, I examine how well trends in local home prices predict entrepreneurship trends.
  • Predicted entrepreneurship rates rise from an earlier level of 0.30 percent in the late 1990s to 0.31 percent at the peak of the housing market in 2006.
  • I also examine trends in predicted entrepreneurship rates based on changes in home ownership rates.

6. Conclusions

  • Using regression estimates for the local unemployment rate effects, I find that the predicted trend in entrepreneurship rates tracks the actual trend in entrepreneurship extremely well for the Great Recession.
  • "The Labor Market in the Great Recession," Prepared for Brookings Panel on Economic Activity, March 18-19, 2010.
  • 2003 Executive Report. U.S. Department of Labor, Employment and Training Administration, Unemployment Insurance Service, also known as Global Entrepreneurship Monitor.

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Entrepreneurship, Economic Conditions, and the Great Recession
Robert W. Fairlie
Department of Economics
University of California
Santa Cruz, CA 95064
rfairlie@ucsc.edu
IZA and RAND
May 2011
Abstract
The “Great Recession” resulted in many business closings and foreclosures, but what effect did it
have on business formation? On the one hand, recessions decrease potential business income and
wealth, but on the other hand they restrict opportunities in the wage/salary sector leaving the net
effect on entrepreneurship ambiguous. The most up-to-date microdata available -- the 1996 to
2009 Current Population Survey (CPS) -- are used to conduct a detailed analysis of the
determinants of entrepreneurship at the individual level to shed light on this question. Regression
estimates indicate that local labor market conditions are a major determinant of entrepreneurship.
Higher local unemployment rates are found to increase the probability that individuals start
businesses. Home ownership and local home values for home owners are also found to have
positive effects on business creation, but these effects are noticeably smaller. Additional
regression estimates indicate that individuals who are initially not employed respond more to high
local unemployment rates by starting businesses than wage/salary workers. The results point to a
consistent picture – the positive influences of slack labor markets outweigh the negative
influences resulting in higher levels of business creation. Using the regression estimates for the
local unemployment rate effects, I find that the predicted trend in entrepreneurship rates tracks
the actual upward trend in entrepreneurship extremely well in the Great Recession.
Keywords: Entrepreneurship, Great Recession, Unemployment, Self-Employment
JEL Code: L26
This research was supported by the Kauffman-RAND Institute for Entrepreneurship Public Policy
through a grant from the Ewing Marion Kauffman Foundation. I would like to thank Susan Gates,
John Robertson, Danny Leung, and seminar participants at the Small Business, Entrepreneurship,
and Economic Recovery Conference at the Atlanta Federal Reserve and the CIRPEE-IVEY
Conference on Macroeconomics and Entrepreneurship for helpful comments and suggestions.

1. Introduction
The U.S. Economy lost more than 8 million jobs during the recession starting in
December 2007. The national unemployment rate rose to over 10 percent, which is twice as high
as it was at the start of the recession. Many researchers have noted that the labor market
experienced its deepest downturn in the postwar era in the recent recession (Elsby, Hobijn and
Sahin 2010). Sparking the recession was the housing crisis -- housing prices plummeted since
reaching their peak in mid 2007. The national housing price index experienced the largest decline
on record (Federal Housing Finance Agency 2009). Home foreclosures also rose rapidly over the
past few years. In the one period for May 2010, there were 323,000 foreclosure filings,
representing an alarming 1 out every 400 housing units in the United States (Realtytrac 2010).
What effect did the recent recession, and recessions more generally, have on
entrepreneurship? Were would-be-entrepreneurs dissuaded by the recent recession from starting
businesses or did they respond to layoffs and slack labor markets by turning to self-employed
business ownership? Business bankruptcy filings and closures increased sharply in the recent
recession (U.S. Courts 2010), but the effects on business formation are less clear. Recessions
might have a negative effect on business starts because of the resulting decline in demand for the
products and services produced by businesses. The recent housing slump may have limited
entrepreneurship by restricting access to capital. Equity in one's home is the main asset for most
Americans and represents 60 percent of all wealth (U.S. Census 2008). Home equity and other
forms of personal wealth are important for starting businesses because they can be invested
directly in the business or used as collateral to obtain business loans. Bank loans, venture capital
and angel investments were also difficult to obtain during the recent recession (Federal Reserve
Board of Governors 2010, PricewaterhouseCoopers 2010).
On the other hand, the recent recession might have increased "necessity"
entrepreneurship or business creation because of the rapid rise in the number of layoffs and
unemployment in the United States. Previous studies provide evidence that job loss and reduced

2
labor market opportunities lead to entry into self-employed business ownership (Farber 1999;
Parker 2009; Krashinsky 2005). Although the motivation might differ for starting the business in
this case, many of these businesses may eventually be very successful. For example, a recent
study by Stangler (2009) finds that the majority of Fortune 500 companies were started during
recessions or bear markets.
Given these opposing forces, the net effect of the recent recession on business creations is
ambiguous. Indeed, the positive and negative influences may have even cancelled out resulting in
a relatively flat rate of business creation over the business cycle. To explore this question, I first
conduct a detailed analysis of the determinants of entrepreneurship using newly created panel
data from the most up-to-date microdata available -- the 1996 to 2009 Current Population Survey
(CPS). Although the CPS data are usually used as cross-sectional data, panel data can be created
from the underlying data files allowing one to measure business creation by individuals. Using
these data, the effects of rising unemployment rates and the decline in housing values on
entrepreneurship are examined by estimating the relationship between business creation at the
individual level and local labor and housing markets. The analysis covers two recessions and two
strong growth periods, and uses variation in unemployment and housing prices from more than
250 metropolitan areas. Estimates from this analysis are then used to examine whether rapidly
increasing unemployment rates and a declining housing market had a large effect on business
creation in the Great Recession.
This study is the first to provide a detailed analysis of the effects of the Great Recession
on business creation in the United States. It also improves on previous research on business
formation by capturing a broader range of new business activity than commonly-used Census
data focusing only on new employer firms. Detailed information on home ownership, initial
employment status, education and demographic characteristics of entrepreneurs and non-
entrepreneurs available in the CPS allow for a much more extensive analysis of the relationship
between local economic conditions, housing market conditions, and business formation than

3
previously conducted in the literature. The study provides new evidence on the potentially
opposing influences of unemployment and housing markets on entrepreneurship, interactions
between initial employment status and local labor market conditions, and the types of business
created in weak labor market conditions. The findings from this analysis may have important
policy implications because of the focus of many government programs on promoting business
ownership among the unemployed and the potential for job creation (U.S. Department of Labor
2010, Small Business Administration 2010, OECD 1992, 2005).
2. The Entrepreneurial Decision
Theoretical models of the choice to become self-employed are generally based on a
comparison of potential earnings from business ownership and wage and salary work. In the
classic economic model by Evans and Jovanovic (1989) individuals can obtain the following
income, Y
W
, from the wage and salary sector: Y
W
= w + rA, where w is the wage earned in the
market, r is the interest rate, and A represents the consumer’s assets. Earnings in the self-
employment sector, Y
SE
, are defined as: Y
SE
= θf(k)ε + r(A-k), where θ is entrepreneurial ability,
f(.) is a production function whose only input is capital, ε is a random component to the
production process, and k is the amount of capital purchased by the worker. Individuals choose to
become self-employed if the potential income from self-employment and investing remaining
personal wealth after using it for startup capital is higher than the potential income from wage and
salary work and investing personal wealth.
This simple theoretical model is useful for illustrating the main avenues through which
business cycles might affect entrepreneurship. One of the main effects is that recessions reduce
consumer and firm demand for products and services provided by startups, thus decreasing
potential entrepreneurial earnings, Y
SE
. Recessions may also reduce total wealth, A, which in
turn would lower the likelihood of entrepreneurship. In the presence of liquidity constraints,
lower levels of wealth may make it more difficult for entrepreneurs to find the required startup

4
capital to launch new ventures. Personal wealth may have declined substantially through
declining home values and home ownership rates. Recessions also make it more difficult to
acquire financing from banks, other financial institutions, angel investors, and venture capitalists.
On the other hand, the costs of production are lower in a recession, especially rent and
labor, increasing Y
SE
. The opportunity cost of capital, r, is likely to be lower in recessions also
placing upward pressure on entrepreneurship. Perhaps the largest factor having a positive effect
on the entrepreneurial decision is that compensation in the wage/salary sector decreases in
economic contractions. The positive effect of lower wages on entrepreneurship may be tempered
somewhat in recessions, however, because some workers may be reluctant to leave their jobs in a
recession because of concerns about finding another one if the business fails. The net effect of
these opposing forces on entrepreneurship is ambiguous. An empirical analysis is thus needed.
PREVIOUS EMPIRICAL EVIDENCE
The previous empirical literature provides evidence on several aspects of how recessions
affect the entrepreneurial decision. The relationship between personal wealth and business starts
has been studied extensively in the previous literature using various methodologies, measures of
wealth, and datasets from around the world. Most studies find that asset levels (e.g. net worth)
measured in one year increase the probability of entering self-employment by the following year.
1
The finding has generally been interpreted as providing evidence that entrepreneurs face liquidity
constraints and that owner's wealth is important in determining access to financial capital for
business starts. Additional evidence on the link between startup capital and owner's wealth has
been provided by examining the relationship between business loans and personal commitments,
such as using personal assets for collateral for business liabilities and guarantees that make
1
See Evans and Jovanovic (1989), Evans and Leighton (1989), Meyer (1990), Holtz-Eakin, Joulfaian, and
Rosen (1994), Lindh and Ohlsson (1996, 1998), Bates (1997), Blanchflower and Oswald (1998), Dunn and
Holtz-Eakin (2000), Fairlie (1999), Johansson (2000), Taylor (2001), Zissimopoulos and Karoly (2003),
Holtz-Eakin and Rosen (2005), Giannetti and Simonov (2004), Fairlie and Krashinsky (2010), and Nykvist
(2005).

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Abstract: Social-distancing restrictions and health- and economic-driven demand shifts from COVID-19 are expected to shutter many small businesses and entrepreneurial ventures, but there is very little early evidence on impacts. This paper provides the first analysis of impacts of the pandemic on the number of active small businesses in the United States using nationally representative data from the April 2020 Current Population Survey-the first month fully capturing early effects. The number of active business owners in the United States plummeted by 3.3 million or 22% over the crucial 2-month window from February to April 2020. The drop in active business owners was the largest on record, and losses to business activity were felt across nearly all industries. African-American businesses were hit especially hard experiencing a 41% drop in business activity. Latinx business owner activity fell by 32%, and Asian business owner activity dropped by 26%. Simulations indicate that industry compositions partly placed these groups at a higher risk of business activity losses. Immigrant business owners experienced substantial losses in business activity of 36%. Female business owners were also disproportionately affected (25% drop in business activity). Continuing the analysis in May and June, the number of active business owners remained low-down by 15% and 8%, respectively. The continued losses in May and June, and partial rebounds from April were felt across all demographic groups and most industries. These findings of early-stage losses to small business activity have important implications for policy, income losses, and future economic inequality.

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Cites background from "Entrepreneurship, Economic Conditio..."

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TL;DR: In this article, a structural equation model was used to analyze the responses of a sample of 431 experienced individuals of working-age that completed a questionnaire based on Linan & Chen's, Entrepreneurship Theory and Practice, 593-618, (2009) Entrepreneurial Intention Questionnaire (EIQ).
Abstract: Although entrepreneurial behavior is proposed as part of the solution to fragile labor markets, in particular in periods of economic and social change, policy makers are struggling to find the right levers to promote it. Despite the extant prior research on entrepreneurial behavior, little is known on the entrepreneurial behavior drivers for the individuals of working age with experience. Prior research explores the influence of entrepreneurial knowledge to study the drivers of experienced individuals evaluating whether or not to engage in an entrepreneurial behavior. This research introduces entrepreneurial knowledge to study the impact of prior experience on entrepreneurial intention. Based on the theory of planned behavior (TPB), this research work analyzes the relationship between entrepreneurial knowledge and entrepreneurial intention, and the mediating effects of the TPB perceptual variables: personal attitude (PA), social norm (SN), and perceived behavioral-control (PBC). A structural equation model (SEM) has been used to analyze the responses of a sample of 431 experienced individuals of working-age that completed a questionnaire based on Linan & Chen’s, Entrepreneurship Theory and Practice, 593–618, (2009) Entrepreneurial Intention Questionnaire (EIQ). The results showed that entrepreneurial knowledge positively influences entrepreneurial intention and that this influence is mediated by the perceptual variables of the TPB model (PA, SN, PBC). These findings contribute to the understanding of the entrepreneurial intention for experienced individuals and consolidate the use of the TPB model to study individual entrepreneurial intention. The findings suggest that policy makers should pay more attention to individual entrepreneurial knowledge, and strengthen the attractiveness of an entrepreneurial career, if they are interested in fostering entrepreneurial behavior among individuals of working age with experience.

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Cites background from "Entrepreneurship, Economic Conditio..."

  • ...2013), and how to develop policies and support mechanisms that foster it (Fairlie 2013)....

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  • ...…where new entrepreneurs are seen as part of the response to an economic and societal challenge, it is essential to improve the understanding of which factors trigger entrepreneurial behavior (Vinogradov et al. 2013), and how to develop policies and support mechanisms that foster it (Fairlie 2013)....

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Abstract: This paper asks whether startups react more to changing investment opportunities than more mature firms do. We use the fact that a region's pre-existing industrial structure creates exogenous variation in the severity of its exposure to nation-wide manufacturing shocks to develop an instrument for changing investment opportunities, and examine employment creation in the non-tradable sector as a response to those opportunities. Startups are much more responsive to changing local economic conditions than older firms. Moreover, their responsiveness doubles in areas with better access to small business finance, suggesting that financing constraints are an important brake on job creation in the startup sector. Although we focus mostly on the non-tradable sector for empirical identification, our results extend to other sectors of the economy, indicating that the mechanisms we uncover are economically pervasive. This suggests that factors like organizational flexibility and innovativeness may be important drivers of job creation among startups.

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Abstract: We examine how the entry of gig-economy platforms influences local entrepreneurial activity. On one hand, such platforms may reduce entrepreneurial activity by offering stable employment for the un- and under-employed. On the other hand, such platforms may enable entrepreneurial activity by offering work flexibility that allows the entrepreneur to re-deploy resources strategically in order to pursue her nascent venture. To resolve this tension, we exploit a natural experiment, the entry of the ride-sharing platform Uber X and the on-demand delivery platform Postmates into local areas. We examine the effect of each on crowdfunding campaign launches at Kickstarter, the world’s largest reward-based crowdfunding platform. Results indicate a negative and significant effect on crowdfunding campaign launches, and thus local entrepreneurial activity, after entry of Uber X or Postmates. Strikingly, the effect appears to accrue primarily to unfunded and under-funded projects, suggesting that gig-economy platforms predominantly reduce lower quality entrepreneurial activity by offering viable employment for the un- and under-employed. We corroborate our findings with US Census data on self-employment, which indicate similar declines following the entry of Uber X, and with a small scale survey of gig-economy participants.

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References
More filters
Journal ArticleDOI
TL;DR: The authors show that the data point to liquidity constraints: capital is essential for starting a business, and liquidity constraints tend to exclude those with insufficient funds at their disposal, and a would-be entrepreneur must bear most of the risk inherent in his venture.
Abstract: Is the capital function distinct from the entrepreneurial function in modern economies? Or does a person have to be wealthy before he or she can start a business? Knight and Schumpeter held different views on the answer to this question. Our empirical findings side with Knight: Liquidity constraints bind, and a would-be entrepreneur must bear most of the risk inherent in his venture. The reasoning is roughly this: The data show that wealthier people are more inclined to become entrepreneurs. In principle, this could be so because the wealthy tend to make better entrepreneurs, but the data reject this explanation. Instead, the data point to liquidity constraints: capital is essential for starting a business, and liquidity constraints tend to exclude those with insufficient funds at their disposal.

3,241 citations


"Entrepreneurship, Economic Conditio..." refers background or methods in this paper

  • ...In the classic economic model by Evans and Jovanovic (1989) individuals can obtain the following income, YW, from the wage and salary sector: YW = w + rA, where w is the wage earned in the market, r is the interest rate, and A represents the consumer’s assets....

    [...]

  • ...See Evans and Jovanovic (1989), Evans and Leighton (1989), Meyer (1990), Holtz-Eakin et al. (1994), Lindh and Ohlsson (1996, 1998), Bates (1997), Blanchflower and Oswald (1998), Dunn and Holtz-Eakin (2000), owner’s wealth is important in determining access to financial capital for business starts.2…...

    [...]

Journal ArticleDOI
TL;DR: In this paper, the authors used various micro data sets to study entrepreneurship and found that the probability of self-employment depends positively upon whether the individual ever received an inheritance or gift, and that the self-employed report higher levels of job and life satisfaction than employees.
Abstract: This article uses various micro data sets to study entrepreneurship. Consistent with the existence of capital constraints on potential entrepreneurs, the estimates imply that the probability of self‐employment depends positively upon whether the individual ever received an inheritance or gift. When directly questioned in interview surveys, potential entrepreneurs say that raising capital is their principal problem. Consistent with our theoretical model's predictions, the self‐employed report higher levels of job and life satisfaction than employees. Childhood psychological test scores, however, are not strongly correlated with later self‐employment.

2,218 citations


"Entrepreneurship, Economic Conditio..." refers background in this paper

  • ...See Evans and Jovanovic (1989), Evans and Leighton (1989), Meyer (1990), Holtz-Eakin et al. (1994), Lindh and Ohlsson (1996, 1998), Bates (1997), Blanchflower and Oswald (1998), Dunn and Holtz-Eakin (2000), owner’s wealth is important in determining access to financial capital for business starts.2…...

    [...]

Book ChapterDOI
TL;DR: In this article, the authors examined the process of selection into self-employment over the life cycle and the determinants of self employment earnings using data from the National Longitudinal Survey of Young Men (NLS) for 1966-1981 and the Current Population Surveys for 1968-1987.
Abstract: About 4.2 million men and women operate businesses on a full-time basis. Comprising more than a tenth of all workers, they run most of our nation’s firms and employ about a tenth of all wage workers. The fraction of the labor force that is self-employed has increased since the mid-1970s after a long period of decline.1 This paper examines the process of selection into self-employment over the life cycle and the determinants of self-employment earnings using data from the National Longitudinal Survey of Young Men (NLS) for 1966–1981 and the Current Population Surveys for 1968–1987.

2,188 citations

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TL;DR: In this paper, the authors examined the process of selection into self-employment over the life cycle and the determinants of self employment earnings using data from the National Longitudinal Survey of Young Men (NLS) for 1966-1981 and the Current Population Surveys for 1968-1987.
Abstract: About 4.2 million men and women operate businesses on a full-time basis. Comprising more than a tenth of all workers, they run most of our nation’s firms and employ about a tenth of all wage workers. The fraction of the labor force that is self-employed has increased since the mid-1970s after a long period of decline.1 This paper examines the process of selection into self-employment over the life cycle and the determinants of self-employment earnings using data from the National Longitudinal Survey of Young Men (NLS) for 1966–1981 and the Current Population Surveys for 1968–1987.

1,946 citations

Frequently Asked Questions (10)
Q1. What are the contributions mentioned in the paper "Entrepreneurship, economic conditions, and the great recession" ?

This paper used the most up-to-date microdata available to conduct a detailed analysis of the determinants of entrepreneurship at the individual level to shed light on this question. 

One of the main effects is that recessions reduce consumer and firm demand for products and services provided by startups, thus decreasing potential entrepreneurial earnings, YSE. 

Recessions might have a negative effect on business starts because of the resulting decline in demand for the products and services produced by businesses. 

The exclusion of non-employer firms is likely to lead to a substantial undercount of the rate of entrepreneurship because non-employer firms represent 75 percent of all firms (U.S. Small Business Administration 2001, Headd 2005) and a significant number of new employer firms start as non-employer firms (Davis, et. al. 2006). 

Carefully controlling for the effects of education on entrepreneurship may be especially important because education and wealth are highly correlated and education has a large positive effect on entrepreneurship and business performance. 

These results indicate that the recent rise in entrepreneurship rates is primarily due to the rapidly weakening conditions in the labor market as measured by local unemployment rates. 

Estimates for home ownership and housing equity, on the other hand, indicate a small decline in entrepreneurship since the start of the recession. 

A more detailed analysis, especially one that controls for the potentially opposing forces of rising local unemployment rates and declining home values in recessions, is needed. 

For home owners, having $100,000 more in home values results in an increase in the entrepreneurship rate of 0.017 percentage points. 

The predicted entrepreneurship rate increases from 0.29 percent in 2006 to 0.33 percent in 2009, which is very similar to the actual increase in entrepreneurship rates over this period.