The impact of the financial crisis on early-stage entrepreneurship in Europe

1. 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

2. 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 • 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)?

5. State-of-the-art 6 • 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)

7. New Entrepreneur (< 42 months) The concept of entrepreneurship in GEM Total Entrepreneurial activity (TEA index): Early Stage Entrepreneurship Nascent Potential Established Entrepreneur Entrepreneur Entrepreneur Starting a business Knowledge & capabilities (firm > 3,5 years) Creation of a venture Survival Idea 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 Activity c) Owner-managers of firms who have paid wages for more than 42 months: they operate for at least 3,5 years

8. Advantages of using GEM data • Touches 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

9. Data used (in the specific paper) 10 • Countries: 31 European countries that can be classified in (at least) 3 country groups: • Peripheral countries under a tough fiscal adjustment program (GIIPS): Greece, Italy, Ireland, Portugal, Spain • Northern countries: France, Germany, Netherlands, Belgium, Austria, Iceland, Sweden, Switzerland, Norway, Denmark, Finland, UK. • 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 14 • 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)

15. 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 crisis

18. 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

20. 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

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