Analyzing a cross-country panel of 16 OECD countries from 2002 to 2005, we find that higher unemployment benefits crowd out nascent entrepreneurial activity. Our results hold regardless of entrepreneurial motivation (necessity or opportunity) and entrepreneurial type (imitative or innovative).entrepreneurship;business startups;unemployment benefits

Koellinger, Ph.D.

Minniti, M.

English

Research Papers in Economics

 
 
 
 
 
 
Unemployment Benefits Crowd Out Nascent 
Entrepreneurial Activity 
 
 
Philipp Koellinger and Maria Minniti 
 
 
 
 
 
 
 
 
 
 
ERIM REPORT SERIES RESEARCH IN MANAGEMENT 
ERIM Report Series reference number  ERS-2008-012-ORG 
Publication   March 2008 
Number of pages  9 
Persistent paper URL  http://hdl.handle.net/1765/11808 
Email address corresponding author  koellinger@few.eur.nl 
Address   Erasmus Research Institute of Management (ERIM) 
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www.erim.eur.nl ERASMUS  RESEARCH  INSTITUTE  OF  MANAGEMENT 
 
REPORT SERIES 
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ABSTRACT AND KEYWORDS 
Abstract  Analyzing a cross-country panel of 16 OECD countries from 2002 to 2005, we find that higher 
unemployment benefits crowd out nascent entrepreneurial activity. Our results hold regardless of 
entrepreneurial motivation (necessity or opportunity) and entrepreneurial type (imitative or 
innovative). 
Free Keywords  entrepreneurship, business startups, unemployment benefits 
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 1 
 
Unemployment benefits crowd out nascent entrepreneurial activity 
 
Philipp Koellinger (a) (b) (c) (d), Maria Minniti (e) 
 
Submitted version (v1.0) 
Date of completion of manuscript: 18 March 2008 
 
 
 
 
(a) Erasmus University Rotterdam, School of Economics, Department of Applied Economics, 
P.O. Box 1738, 3000 DR Rotterdam, Netherlands; Email: koellinger@few.eur.nl, Tel.: +31-
10- 4089141, Fax: +31-10-4089141 
(b) Tinbergen Institute, Rotterdam, NL 
(c) Erasmus Research Institute of Management, Rotterdam, NL 
(d) EIM Business Policy Research, Zoetermeer, NL 
(e) Southern Methodist University, Cox School of Business, Department of Strategy and 
Entrepreneurship, P.O. Box 750333, Dallas, TX 75275-0333, USA; Email: 
mminniti@cox.smu.edu, Tel.: +1-214-7683145, Fax: +1-214-7684099 2 
 
Unemployment benefits crowd out nascent entrepreneurial activity 
 
 
Abstract 
Analyzing a cross-country panel of 16 OECD countries from 2002 to 2005, we find that higher 
unemployment benefits crowd out nascent entrepreneurial activity. Our results hold regardless of 
entrepreneurial motivation (necessity or opportunity) and entrepreneurial type (imitative or 
innovative).  
JEL Codes: M13, J23, J65 
Keywords: Entrepreneurship, Business Startups, Unemployment Benefits 
 
 
1  Introduction 
Although some evidence exists of a negative relationship between unemployment benefits and 
established self-employment (Parker and Robson, 2004), the relationship between unemployment 
benefits and start-up activity remains unclear. This is largely due to the lack of appropriate data 
since such a relationship can be properly understood only by looking at individuals who are 
actually in the process of starting a business. In other words, by considering all individuals who 
attempt to start a business rather than focusing only on those who have succeeded. Thank to new 
available data, we fill this gap by focusing on nascent rather than established entrepreneurship 
thereby capturing the effects of unemployment benefits on start-up propensity.  3 
 
Using data for 16 developed countries, we provide robust empirical evidence that generous 
unemployment benefits are negatively related to entrepreneurial activity. We show this to be true 
regardless of entrepreneurial motivation and type. To the extent that entrepreneurship is 
important for growth, our results suggest that unemployment benefits can generate a costly 
crowding out effect.  
2  Data 
Table 1 describes the data used in our analysis. Annual data on nascent entrepreneurial activity 
are taken from the Global Entrepreneurship Monitor (GEM) study. Every year, GEM conducts a 
representative population survey of at least 2000 people in each participating country. Individuals 
classify as nascent entrepreneurs if they claim to be engaged in starting a business they will at 
least partially own and that has paid wages or profits for no more than 6 months (Reynolds et al., 
2005).  
GEM data allow us to divide nascent entrepreneurs between those who are starting a business to 
pursue a profitable opportunity but could be otherwise employed (opportunity entrepreneurs), 
and those who are starting because no better employment option is available (necessity 
entrepreneurs).  The average share of necessity nascent entrepreneurs across countries and time 
in our sample is 14%.   
In an alternative, entrepreneurs may be distinguished between innovators, who consider starting a 
business because of the monopolistic rents generated by their innovation, and imitators, who 
replicate existing businesses. GEM data allow us to divide nascent entrepreneurs between those 
who have many competitors and whose technology and product or service are already established 
(imitative entrepreneurs) and those who have introduced at least some innovation (innovative 
entrepreneurs) (Koellinger, 2008). The average share of purely imitative nascent entrepreneurs 
across countries and time in our sample is 27%. 
Annual data on unemployment rates and public out-of-work income maintenance and support for 
the same countries and years are taken from the OECD Employment Outlook (2005, 2006, 2007). 4 
 
The average generosity of unemployment benefits at the individual level is approximated by an 
index obtained by dividing the public spending on out-of-work income maintenance and support, 
measured in percent of GDP, by one plus the current unemployment rate. This index controls for 
the fact that an increase in unemployment rises public spending on out-of-work income 
maintenance and support without necessarily increasing unemployment benefits at the individual 
level. A high index value suggests generous average unemployment benefits compared to the 
national income. Unfortunately, our proxy for unemployment benefits does not capture possible 
differences in support schemes enjoyed by formerly employed and self-employed although such 
differences may be important (Hessels et al., 2007). 
Analysis 
We analyze a balanced cross-country panel with 16 countries and four annual observations (2002 
to 2005) using random and fixed effects linear models that control for unobserved heterogeneity 
across countries (Wooldridge, 2002). Thus, we rule out alternative explanations for the estimated 
coefficients which might be due to unobserved heterogeneity. We estimate two alternative 
models with different measures for the generosity of unemployment benefits, one using the 
unemployment support index and another using the original share of public out-of-work income 
maintenance and support as percent of GDP. All regression results are qualitatively identical for 
both measures.  
Table 2 shows regression results for the prevalence of nascent entrepreneurial activity across 
countries and time. The results suggest that high levels of unemployment benefits crowd out 
nascent entrepreneurial activity. Unemployment benefits are negatively associated to nascent 
entrepreneurial activity and highly significant in all models. Specification tests suggest that 
unobserved heterogeneity is highly significant and the difference in coefficients between random 
and fixed effects is not significant according to the Hausman test, thus supporting the random 
effects specification. 
In Table 3, necessity nascent entrepreneurs are excluded. Our results show again a significant 
negative effect of unemployment benefits. Thus, the results suggest that higher unemployment 5 
 
benefits influence negatively even the share of individuals trying to start businesses because they 
perceive desirable opportunities. Furthermore, Table 4 shows that the share of opportunity and 
necessity entrepreneurs is unaffected by variations in unemployment benefits. 
We now turn to the distinction between innovative and imitative entrepreneurs. In Table 5, 
imitative nascent entrepreneurs are excluded. Again, our results show a significant negative effect 
of unemployment benefits. This suggests that generous unemployment benefits crowd out 
innovative entrepreneurial activity.  
In addition, Table 6 shows no influence of unemployment benefits on the ratio of innovative to 
imitative nascent entrepreneurs. Across the countries in our sample, such ratio is about 7 to 3 on 
average, with significant fluctuations across countries and time. Unemployment levels, however, 
do affect the ratio: Not surprisingly, higher levels of unemployment are associated with lower 
shares of innovative and higher shares of purely imitative nascent entrepreneurs.  
Conclusion 
Our results fill a gap in the employment choice literature by providing evidence that generous 
unemployment benefits are negatively related to nascent entrepreneurship and that this is true 
regardless of entrepreneurial motivation and type. In other words, higher unemployment benefits 
seem to reduce the overall entrepreneurial propensity of a country. If entrepreneurial activity is 
important for economic growth, our results suggest that the opportunity costs of unemployment 
benefits may be higher than what is normally assumed in the labor economics studies.  6 
 
References 
Hessels, J., A. van Stel, P. Brouwer, S. Wennekers, 2007, Social security arrangements and early-
stage entrepreneurial activity, Comparative Labor Law and Policy Journal 13, 37-46. 
Koellinger, P., 2008, Why are some entrepreneurs more innovative than others? Small Business 
Economics Journal, forthcoming. 
Parker, S.C., Robson, M.T., 2004, Explaining international variations in self-employment: 
Evidence from a panel of OECD countries, Southern Economic Journal 71(2), 287–301. 
OECD, 2007, 2006, 2005, OECD Unemployment Outlook. (OECD Publishing, Paris). 
Reynolds, P., Bosma, N., Autio, E., Hunt, S., de Bono, N., Servais, I., Lopez-Garcia, P., Chin, N., 
2005, Global Entrepreneurship Monitor: Data collection design and implementation 1998-2003, 
Small Business Economics Journal, 24, 205-231. 
Wooldridge, J., 2002, Econometric Analysis of Cross Section and Panel Data. (Cambridge, MA 
and London, England: MIT Press). 7 
 
Table 1: Four year averages for nascent entrepreneurial activity, unemployment, and public unemployment expenditures 
in 16 countries, 2002-2005 
Country Nascent 
entrepreneurs  
(% of adult pop 
18-64)* 
Share of 
opportunity 
nascent 
entrepreneurs 
(% of adult 
nascent 
entrepreneurs)*  
Share of 
innovative 
nascent 
entrepreneurs 
(% of adult 
nascent 
entrepreneurs)* 
Unemployment 
rate (% of adult 
pop 18-64)
+
Unemployment 
support
1 (% of 
GDP)
+
Unemployment 
support index
2
Australia 5.73  87  77  5.8  0.69  0.65 
Belgium 2.37  91  68  8.1  1.96  1.81 
Canada 5.24  85  76  7.3  0.71  0.66 
Denmark 2.90  94  84  5.1  1.81  1.72 
Finland 2.96  88  67  8.8  1.53  1.41 
France 3.05  73  68  9.3  1.57  1.44 
Germany 3.99  75  70  9.1  2.23  2.05 
Ireland 4.84  81  78  4.5  0.80  0.76 
Japan 0.92  83  68  5.0  0.47  0.45 
Netherlands 2.59  90  72  3.9  1.98  1.90 
New Zealand  8.41  86  73  4.4  0.67  0.64 
Norway 4.14  92  74  4.4  0.82  0.78 
Spain  2.60 85  56  10.5 1.44 1.31 
Sweden 1.66  90  76  6.0  1.19  1.12 
UK 2.66 86  80  4.9  0.25 0.23 
USA 7.66  86  76  5.6  0.34  0.32 
* Data from Global Entrepreneurship Monitor  
+ Data from OECD Employment Outlook
  
1 Public out-of-work income maintenance and support 
2 Support index = (Public out-of-work income maintenance and support in % of GDP)
 + / (1 + Unemployment rate in % of total 
labour force)
 +
 8 
 
 
Table 2: Regression results on prevalence of nascent entrepreneurial activity across 16 countries, 2002-2005 
  Random effects  Fixed effects  Random effects  Fixed effects 
Unemployment support index
+ -176.7** (84.36)  -294.6*  (163.3) -  -  -  - 
Unemployment support in % of GDP  -  -  -  -  -1.67**  (0.80)  -2.83*  (1.57) 
Unemployment rate  0.13  (0.18)  0.35 (0.27)  0.15  (0.19)  0.39  (0.28) 
Constant 4.64**  (1.15)  4.52**  (1.43) 4.52**  (1.14)  4.36**  (1.40) 
Model diagnostics 
Hausman Test (Prob > Chi2)  0.94  0.94 
R2  0.13  0.11 0.13 0.11 
Rho  0.87**  0.88** 0.87** 0.88** 
N = 64. Standard errors in parentheses. 
All models include time dummies. 
** significant at > 95% confidence 
* significant at > 90% confidence 
 
 
 
 
 
Table 3: Regression results on prevalence of opportunity nascent entrepreneurial activity across 16 countries, 2002-2005 
  Random effects  Fixed effects  Random effects  Fixed effects 
Unemployment support index
+ -146.7** (69.54)  -247.4*  (133.0) -  -  -  - 
Unemployment support in % of GDP  -  -  -  -  -1.38**  (0.66)  -2.36*  (1.28) 
Unemployment rate  0.55  (0.15)  0.23 (0.22)  0.07  (0.15)  0.26  (0.23) 
Constant 4.23**  (0.95)  4.19**  (1.17) 4.13**  (0.94)  4.04**  (1.14) 
Model diagnostics 
Hausman Test (Prob > Chi2)  0.94  0.93 
R2  0.15  0.12 0.15 0.12 
Rho  0.87  0.89 0.87 0.89 
N = 64. Standard errors in parentheses. 
All models include time dummies. 
** significant at > 95% confidence 
* significant at > 90% confidence 
 
 
 
 
 
Table 4: Regression results on the share of opportunity vs. necessity nascent entrepreneurs across 16 countries, 2002-2005 
  Random effects  Fixed effects  Random effects  Fixed effects 
Unemployment support index
+ 1.65 (2.54)  -7.07  (12.5)  -  -  -  - 
Unemployment support in % of GDP  -  -  -  -  0.02  (0.02)  -0.07  (0.12) 
Unemployment rate  -0.02  (0.01)  -0.01 (0.02)  -0.02  (0.01)  -0.01  (0.02) 
Constant 0.94**  (0.04)  1.01**  (0.11) 0.94**  (0.04)  1.01**  (0.11) 
Model diagnostics 
Hausman Test (Prob > Chi2)  0.98  0.98 
R2 0.14  0.04  0.14  0.04 
Rho 0.36  0.60  0.36  0.60 
N = 64. Standard errors in parentheses. 
All models include time dummies. 
** significant at > 95% confidence 
* significant at > 90% confidence 
 9 
 
 
Table 5: Regression results on prevalence of innovative nascent entrepreneurial activity across 16 countries, 2002-2005 
  Random effects  Fixed effects  Random effects  Fixed effects 
Unemployment support index
+ -133.3** (63.4)  -221.3*  (123.5) -  -  -  - 
Unemployment support in % of GDP  -  -  -  -  -1.26**  (0.60)  -2.11*  (1.18) 
Unemployment rate  0.02  (0.14)  0.17 (0.20)  0.04  (0.14)  0.19  (0.21) 
Constant 3.90**  (0.86)  3.91**  (0.00) 3.81**  (0.86)  3.78**  (1.05) 
Model diagnostics 
Hausman Test (Prob > Chi2)  0.96  0.96 
R2  0.17  0.14 0.17 0.14 
Rho  0.87**  0.88** 0.87** 0.88** 
N = 64. Standard errors in parentheses. 
All models include time dummies. 
**significant at > 95% confidence 
* significant at > 90% confidence 
 
 
 
Table 6: Regression results on the share of innovative vs. imitative nascent entrepreneurs across 16 countries, 2002-2005 
  Random effects  Fixed effects  Random effects  Fixed effects 
Unemployment support index
+ 0.34 (2.32)  6.11  (15.0)  -  -  -  - 
Unemployment support in % of GDP  -  -  -  -  0.00  (0.02)  0.06  (0.14) 
Unemployment rate  -0.02**  (0.01)  -0.02 (0.02)  -0.02**  (0.01)  -0.02  (0.03) 
Constant 0.85**  (0.04)  0.78**  (0.13) 0.85**  (0.04)  0.78**  (0.00) 
Model diagnostics 
Hausman Test (Prob > Chi2)  1.00  1.00 
R2 0.34  0.18  0.34  0.18 
Rho 0.18  0.41*  0.18  0.41* 
N = 64. Standard errors in parentheses. 
All models include time dummies. 
** significant at > 95% confidence 
* significant at > 90% confidence 
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Unemployment Benefits Crowd Out Nascent Entrepreneurial Activity

Unemployment Benefits Crowd Out Nascent Entrepreneurial Activity

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