The impact of the financial crisis on early-stage entrepreneurship

in Europe

Aggelos Tsakanikas*, Ioannis Giotopoulos ***Assistant Professor Laboratory of Industrial and Energy Economics, National Technical University of

Athens (LIEE/NTUA) Research Director, Foundation for Economic and Industrial Research (FEIR/IOBE)

**Assistant Professor, Department of Economics, University of Peloponnese, Research Associate, Foundation for Economic & Industrial Research (IOBE)

T2S 2013 Conference, 8-9 November 2013, Bergamo, Italy

Motivation (I) Need for a more in depth analysis for

entrepreneurship at micro (individual) level of analysis

Entrepreneurship is a key driver for Job generation (Birch, 1987; Baptista et al.,

2008) Innovation (Malerba and Orsenigo, 1996;

Breschi et al., 2000; Baumol, 2010) Productivity (e.g. Audretsch and Keilbach, 2004) Economic growth (Wennekers and Thurik, 1999;

Van Stel et al., 2005; Caree and Thurik, 2005)

3

Motivation (II) Investigation of start-ups is significant in adverse times

The recent financial crisis has been the most severe in decades and its cost has been high for real economic activity (OECD, 2012; ECB, 2012)

Entrepreneurs have suffered a double shock: a drastic drop in demand for goods and services and a credit crunch (OECD, 2009)

Financial crisis affects entrepreneurship in a negative way (Klapper and Love, 2011)

Current global crisis exhibits a dramatic effect on the financing of innovative entrepreneurship (Lerner, 2010)

But in which way do the structural characteristics of start-ups evolve in times of crisis?

4

The topic addressed: research questions

5

The topic Explore the effects of financial crisis on the

structural characteristics of early-stage entrepreneurship in European countries

Research questions Which individual factors drive the innovativeness,

internationalization and future job growth of start-ups in such adverse times?

How do the linkages between venture characteristics and demographic/personal characteristics of early-stage entrepreneurs evolve before and after the beginning of the recent financial crisis?

In which way these nexuses differ among country groups (south, north and transition countries)?

State-of-the-art Demographic and personal characteristics of

entrepreneurs at individual level can explain to a great extent the entrepreneurial behaviour (e.g. Arenius and Minniti, 2005)

Entrepreneurial innovativeness depends on individual factors --demographic and personal-- (Koellinger, 2008)

The degree of internationalization of new and small ventures is mainly influenced by personal factors (e.g. Manolova et al. 2002) and demographic characteristics (e.g. Cooper et al., 1994; Moini, 1995)

Entrepreneurial job growth aspirations are affected by demographic characteristics of entrepreneurs such as individual’s education and individual’s household income (Autio, 2005; Autio and Acs, 2010)

6

Data source: Global Entrepreneurship Monitor (GEM) A non-profit academic research consortium coordinated by

London Business School and Babson College From a comparison of 10 countries (1999) to 68 countries in

2012 Annual world report comparing and contrasting levels of

entrepreneurial activity across countries. GEM focuses on three main objectives:

To measure differences in the level of entrepreneurial activity between countries

To uncover factors determining the levels of entrepreneurial activity

To identify policies that may enhance the level of entrepreneurial activity

Collected Data: Adult population (telephone) survey conducted to minimum

2,000 respondents per country. Expert survey: in-depth interviews with at least 36 experts in

each country from finance, policy, government programmes, education and training, technology transfer, support infrastructure and wider society/culture.

Macroeconomic data (World bank, IMF, Eurostat, UN, OECD)

Total Entrepreneurial activity (TEA index):Early Stage Entrepreneurship

PotentialEntrepreneur

Knowledge & capabilities

NascentEntrepreneur

Starting a business

NewEntreprene

ur

(< 42 months)

EstablishedEntrepreneur

(firm> 3,5 years)

Idea Creation of a venture

Survival

Three types of identified entrepreneurs, two phases: Early stage entrepreneurs:

a) Nascent entrepreneurs: Those individuals (18 - 64 years old), who have taken some action towards creating a new venture (operating up to 3 months). b) New entrepreneurs: Owner-managers of firms who have paid wages for more than 3 months and less than 42 months

Established Entrepreneurial Activityc) Owner-managers of firms who have paid wages for more than 42 months: they operate for at least 3,5 years

The concept of entrepreneurship in GEM

Advantages of using GEM dataTouches upon the individual level and

estimate all attempts to create a new venture, self employment included

Global coverage: many European and non European countries

Time series (annual survey in most countries)

But It does not measure corporate

entrepreneurship, it is not addressed to firms It gives only a prevalent rate: trends and

attitudes of the population towards entrepreneurial activity

Data used (in the specific paper) Countries: 31 European countries that can be classified

in (at least) 3 country groups:M Peripheral countries under a tough fiscal adjustment

program (GIIPS): Greece, Italy, Ireland, Portugal, SpainM Northern countries: France, Germany, Netherlands,

Belgium, Austria, Iceland, Sweden, Switzerland, Norway, Denmark, Finland, UK.

M Transition countries: Slovenia, Slovakia, Serbia, Bosnia & Herzegovina, Romania, Croatia, Czech Republic, Poland, Estonia, Latvia, Lithuania, FYROM, Montenegro, Turkey.

Study period: 2005-2011 (7-year time period) Two sub-periods: Before (2005-2008) and after the

crisis outbreak (2009-2011) Size of the total sample: 24327 early-stage

entrepreneurs

10

Methodology Three separate equations were estimated by

applying ordered probit regressions (1) Innovation; (2) Internationalization (export performance); (3) Expected Job Growth

f {Age, Gender, Education, Household income, Fear of failure, Motives (opportunity vs necessity), Knowing other entrepreneurs, Opportunity perceptions, Confidence in one’s skills, Competition intensity, New technology use, GDP per capita(ln)}

11

Dependent variables Innovation: how many of the customers

consider this product/service new and unfamiliar? (none=1; some=2; all=3) Internationalization: what proportion of your

customers live outside your country? (none=1; 1%-10%=2; 11%-25%;=3 ; 26%-

75%=4; 76%-100%=5) Expected Job Growth: how many jobs do you

expect to create five years from now? (no jobs=1; 1-5 jobs=2; 6-19 jobs=3; 20+jobs=4)

12

Independent variables: demographics and personal characteristics Demographic characteristics:

age(ln); gender, education (none=1; some secondary=2; secondary

degree=3; post secondary=4; grad exp=5); Income (lowest 33%=1; middle 33%=2;

upper33%=3) Motives: opportunity (=1) or necessity (=0) Personal characteristics:

knowing other new entrepreneurs; (yes / no) opportunity perceptions; (yes / no) confidence in own skills; (yes / no) fear of failure (yes / no)

13

Independent variables: venture characteristics

Venture characteristics: competition intensity ( how many businesses

offering the same product/service to customers? none=1; few=2; many=3);

Technologies used to produce (have the technologies/procedures required for this product/service been available for longer than 5 years (=1), between 1 to 5 years (=2), less than a year (=3)).

GDP per capita (ln)

14

Table 1: Innovativeness of Early-Stage Entrepreneurs in Europe

Ordered probit (marginal effects)

Total Period(2005-2011)

Pre-Crisis Period (2005-2008)

Post-Crisis Period(2009-2011)

Age -0.0275***(0.0065)

-0.0198**(0.00823)

-0.0400***(0.0104)

Gender 0.0041(0.0039)

0.0019(0.0050)

0.0075(0.00643)

Education 0.0079***(0.0018)

0.0063***(0.0021)

0.0123***(0.0035)

Household income -0.0056**(0.0024)

-0.0050*(0.0030)

-0.0055(0.00431)

Motives (opportunity vs necessity)

0.0269***(0.0043)

0.0262***(0.0056)

0.0258***(0.0069)

Knowing other entrepreneur 0.0175***(0.0039)

0.0179***(0.0050)

0.0159**(0.0064)

Opportunity perceptions 0.0174***(0.0039)

0.0118**(0.0049)

0.0241***(0.0063)

Confidence in one’s skills 0.0073(0.0060)

0.0147*(0.0077)

-0.0048(0.0098)

Fear of failure 0.0019(0.0045)

0.0117**(0.0059)

-0.0121*(0.0069)

Competition intensity -0.0962***(0.00292)

-0.0930***(0.0037)

-0.1018***(0.00466)

New technologies use 0.0502***(0.0029)

0.0495***(0.0038)

0.0517***(0.0044)

GDP per capita -0.0091(0.0058)

-0.0220**(0.0087)

-0.0006(0.0081)

Log likelihood -17648.376 -10989.81 -6643.91

LR test 1940.56*** 1071.99*** 894.75***

Number of obs 19262 11903 7359

Discussion of results: innovativeness of entrepreneurs

During the post-crisis period the probability to become an innovative entrepreneur: Increases for younger entrepreneurs increases with higher education (i.e. human capital matters even more in adverse times)

is positively related to opportunity perceptions (much stronger) and opportunity motives: crisis creates entrepreneurial opportunities (!)

is negatively related with the fear of failure (entrepreneurs become risk-averse), while the opposite holds for the pre-crisis period (entrepreneurs appear risk-lovers)

Competition intensity is negatively related to innovation both before and after the crisis: innovation comes from oligopolistic markets - niche ventures

New technologies matter both before and after the crisis16

Table 2: Internationalization of Early-Stage Entrepreneurs in EuropeOrdered probit (marginal effects)

Total Period(2005-2011)

Pre-Crisis Period (2005-2008)

Post-Crisis Period(2009-2011)

Age -0.0098***(0.0038)

-0.0118**(0.0049)

-0.0053(0.0059)

Gender -0.0152***(0.0023)

-0.0114***(0.0029)

-0.0216***(0.0037)

Education 0.0043***(0.0011)

0.0031**(0.0012)

0.0078***(0.002)

Household income 0.0070***(0.0014)

0.0082***(0.0018)

0.0025(0.0025)

Motives (opportunity vs necessity)

0.0046*(0.0026)

-0.0018(0.0036)

0.0141***(0.00386)

Knowing other entrepreneur 0.0189***(0.0022)

0.0212***(0.0029)

0.0155***(0.0036)

Opportunity perceptions 0.0090***(0.0022)

0.0036(0.0029)

0.0182***(0.0036)

Confidence in one’s skills -0.0005(0.0036)

0.0016(0.0047)

-0.0025(0.0056)

Fear of failure 0.0028(0.0026)

0.0026(0.0034)

0.0039(0.0041)

Competition intensity -0.0166***(0.0017)

-0.0175***(0.0022)

-0.0146***(0.0026)

New technologies use 0.0172***(0.0017)

0.0213***(0.0023)

0.0113***(0.0025)

GDP per capita -0.0129*** (0.0033)

-0.00002(0.0050)

-0.0256***(0.0046)

Log likelihood -25091.22 -15313.68 -9739.43

LR test 554.03*** 343.93*** 249.18***

Number of obs 19262 11903 7359

Table 3: Expected Job Growth of Early-Stage Entrepreneurs in Europe Ordered probit (marginal effects)

Total Period(2005-2011)

Pre-Crisis Period (2005-2008)

Post-Crisis Period(2009-2011)

Age -0.0399***(0.0050)

-0.0367***(0.0061)

-0.0450***(0.0084)

Gender -0.0439***(0.0031)

-0.0364***(0.0037)

-0.0585***(0.0053)

Education 0.0050***(0.0013)

0.0017(0.0015)

0.0131***(0.0028)

Household income 0.0207*** (0.0019)

0.0231***(0.0022)

0.0210***(0.0035)

Motives (opportunity vs necessity)

0.0354***(0.0031)

0.0333***(0.0038)

0.0361***(0.0053)

Knowing other entrepreneur 0.0296*** (0.0029)

0.0294***(0.0036)

0.0282***(0.0050)

Opportunity perceptions 0 .0224***(0.0029)

0.0141***(0.0036)

0.0334***(0.0052)

Confidence in one’s skills 0.0155***(0.0043)

0.0145***(0.0054)

0.0143**(0.0072)

Fear of failure -0.0165***(0.0032)

-0.0154***(0.0039)

-0.0165***(0.0054)

Competition intensity -0.0242***(0.0022)

-0.0221***(0.0027)

-0.0284***(0.0037)

New technologies use 0.0206***(0.0022)

0.0202***(0.0028)

0.0222***(0.0036)

GDP per capita -0.0763***(0.0045)

-0.0795***(0.0064)

-0.0829***(0.0066)

Log likelihood -22848.48 -13982.43 -8827.56

LR test 1684.86*** 919.86*** 811.59***

Number of obs 19262 11903 7359

Discussion of results: internationalization (exports) and job growth of entrepreneurs Export performance and job generation are both

affected by gender since a gender gap exists against female entrepreneurship. However, this gap increases after the beginning of crisis

The higher the education level of entrepreneurs, the greater their export intensity and their expected job growth in times of crisis

During the post-crisis period entrepreneurs recognize more opportunities to export and create jobs in the future

Fear of failure affects negatively job growth but does not affect internationalization of entrepreneurs

Competition intensity affects negatively venture performance in both pre and post crisis periods

New technologies matter in both pre and post crisis periods

19

Table 4: Innovativeness of Early-Stage Entrepreneurs in Europe Ordered probit (marginal effects)

GIIPS North Countries Transition Countries

Pre-Crisis Period

(2005-2008)

Post-Crisis Period

(2009-2011)

Pre-Crisis Period

(2005-2008)

Post-Crisis Period(2009-2011)

Pre-Crisis Period (2005-2008)

Post-Crisis Period

(2009-2011)Age 0.0274*

(0.0152)0.0033)(0.0227)

-0.0189*(0.0099)

-0.0287**(0.0143)

-0.1131***(0.0242)

-0.0648***(0.0192)

Gender 0.0083(0.0089)

0.0046(0.0128)

0.0001(0.0057)

0.0091(0.0088)

-0.0265(0.0164)

0.0083(0126)

Education 0.0057(0.0036)

0.0189***(0.0064)

0.0096***(0.0025)

0.0092*(0.0052)

0.0229***(0.0075)

0.0075(0.0067)

Household income -0.0218***(0.0058)

-0.0038(0.0087)

0.0011(0.0033)

-0.0167***(0.0057)

-0.0144(0.0102)

0.0144(0.091)

Motives 0.0384***(0.0101)

-0.0020(0.0144)

0.0135**(0.0069)

0.0418***(0.0095)

-0.0005(0.0172)

0.0181(0.0128)

Knowing other entrepreneur

0.0317***(0.0089)

0.0121(0.0124)

0.0164***(0.0058)

0.0287***(0.0087)

0.0004(0.0180)

-0.036(0.0127)

Opportunity perceptions 0.0342***(0.0088)

0.0160(0.0133)

0.0082(0.0058)

0.0184**(0.0087)

0.0271*(0.0152)

0.0036***(0.0123)

Confidence in one’s skills 0.0316**(0.0150)

0.0274(0.0195)

0.0002(0.0089)

0.0034(0.0130)

-0.0361(0.0272)

-0.0268(0.0190)

Fear of failure 0.0030(0.0097)

-0.0415***(0.0123)

0.0101(0.0074)

0.0026(0.0108)

-0.0398**(0.0170)

0.0008(0.0136)

Competition intensity -0.1008***(0.0068)

-0.1043***(0.0088)

-0.0951***(0.0046)

-0.1133***(0.0069)

-0.0642***(0.0117)

-0.0754***(0.0088)

New technologies use 0.0527***(0.0073)

0.0777***(0.0085)

0.0563***(0.0044)

0.0550***(0.0067)

0.0167*(0.0101)

0.0293***(0.079)

GDP per capita -0.1459***(0.0514)

0.0860(0.0540)

0.0003(0.0274)

-0.0318(0.0301)

0.0272(0.0230)

0.1053***(0.0209)

Log likelihood -4565.62 -1714.33 -4979.39 -2783.06 -12.63.08 -2055.67

LR test 388.19*** 328.81*** 858.01*** 531.36*** 92.30*** 162.26***

Number of obs 4700 2035 5830 3162 1373 2162

Discussion of results: country comparisons of Innovativeness of early stage entrepreneurs Similarities across countries

Competition intensity is negatively related to innovation in all group of countries before and after the crisis: niche markets create innovation

The use of new technologies is positively related to innovation in all group of countries before and after the crisis

Gender, confidence in skills not important whatsoever

21

Discussion of results: country comparisons of Innovativeness of early stage entrepreneurs Significant differences across countries

Education: much more important for GIIPS after the crisis,

Younger entrepreneurs used to innovate more in transition and Northern countries before the crisis: they still do but to a much less extent in transition countries

Opportunity Motives: not important after the crisis in GIIPS and transition, whereas it becomes much more important on Northern countries

Opportunities perception become less important after the crisis in GIIPS, whereas it becomes more important for innovation in Northern and transition countries

Fear of failure : highly negative factor in GIIPS after the crisis

22

Conclusions

Human capital (in terms of education) matters for venture performance in adverse times

Crisis creates indeed entrepreneurial opportunities to innovate, export and grow

Younger early stage entrepreneurs tend to be more innovative in times of crisis

Fear of failure effects on innovation show a risk-loving behaviour before crisis, and a risk-averting behaviour after the crisis

Gender gap broadens as regards the internationalization and job growth of early-stage entrepreneurs after crisis outbreak: female entrepreneurship seems to suffer

23

Thank you

Aggelos Tsakanikas: atsakanikas@iobe.gr Ioannis Giotopoulos: giotopoulos@iobe.gr