Disparities in entrepreneurial activity and attitude across EU countries

ABSTRACT

The levels and characteristics of entrepreneurship differ widely across EU countries and regions. Taking as reference data provided by the Global Entrepreneurship Monitor on entrepreneurial activity and entrepreneurial attitude, this paper analyses the disparities in entrepreneurship indicators among EU member countries in 2007 and 2013, highlighting the most significant changes that occurred during the Great Recession. Some of the major indices of inequality are calculated (Gini, Theil and Atkinson) and the change in the Gini coefficient between these two years is additively decomposed into mobility and progressivity components. Overall, we find that cross-national inequalities tend to increase in the procyclical aspects of entrepreneurial activity and attitude, while they tend to decrease in the countercyclical aspects. For entrepreneurial activity indicators, we reveal that heterogeneity increases in indicators such as opportunity-driven entrepreneurial activity and total entrepreneurial activity, while necessity-driven entrepreneurial activity becomes more homogeneous across countries. Regarding entrepreneurial attitudes, disparities among countries decrease in all indicators, except in perceived opportunities, for which cross-national inequality grows considerably during the crisis period.

KEYWORDS:

• Entrepreneurship
• GEM
• spatial disparities
• Great Recession
• EU countries

JEL CLASSIFICATION:

• L26
• O12
• O52

Acknowledgements

The authors are grateful for the helpful suggestions from discussions at the 28th International Conference of Applied Economics-ASEPELT and 25th ACEDE Conference. We also thank the two anonymous referees for their useful comments.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1. Note that the GEM 2013 Global Report provides data for 70 countries, including 23 EU member states (EU28, except Austria, Bulgaria, Cyprus, Denmark and Malta) (Amorós & Bosma, 2014). We also calculate the indices of inequality among these 23 EU countries, with consistent results with those shown in Table 1. They are available from the authors upon request.

2. The European Commission (2003) highlights that entrepreneurship is the mindset and process to create and develop economic activity by blending risk-taking, creativity and/or innovation with sound management, within a new or an existing organization. Closely linked to this approach, the OECD points out that entrepreneurship is a phenomenon associated with entrepreneurial activity, which is enterprising human action in pursuit of the generation of value, through the creation or expansion of economic activity, by identifying and exploiting new products, processes or markets (Ahmad & Seymour, 2008). In relation to the European Commission and OECD approaches, it may be noted that the GEM adopts a global coverage (developed and developing countries), uses the individual as the unit of analysis (OECD usually employs the company) and focuses on all participants in the entrepreneurship process, not just companies, employers or self-employed persons, taking a wider perspective than other approaches.

3. Bosma and Sternberg (2014) specify that considering spatial or geographical aspects in entrepreneurship means distinguishing between four spatial levels: supranational (e.g. EU), national (country), regional (e.g. urban area) and local (e.g. neighbourhood), although not all studies accurately distinguish between these levels.

4. Other studies use the GEM data to analyse disparities in entrepreneurship in other countries, including some developing countries (see, e.g. Naudé, Gries, Wood, & Meintjies, 2008, for South Africa).

5. Some researches even uphold the absence of direct effects of a macroeconomic crisis, suggesting that more attention should be paid to environmental jolts in a particular industry or location (see, e.g. Davidsson & Gordon, 2016).

6. See also, for instance, Parker (2012), Koellinger and Thurik (2012) and Fairlie (2013) on the interplay between entrepreneurship and business cycle, with both theoretical and empirical analyses.

7. We can find other arguments in the literature supporting the recession-push hypothesis. For instance, Binks and Jennings (1986) suggest that as firms close down in recessions, the availability and affordability of second-hand capital equipment increases, reducing barriers to entry. Parker (2009) also points to the effect of falling wages in recessions, which may lower the opportunity costs for starting a business and encourage marginal types of entrepreneurship.

8. Parker (2012) and Parker, Congregado, and Golpe (2012) reveal that the potential procyclicality of entrepreneurship is consistent with time series evidence from the UK and Spain, but not with data from the U.S.A. In this line, Fairlie (2013) observes for the U.S.A a positive relationship between entrepreneurship and local unemployment rates, so that the historically rapid rise in unemployment rates in the Great Recession resulted in an increase in entrepreneurship rates.

9. Bosma and Schutjens (2011) reveal that urban regions showing high economic growth, low unemployment rates and vibrant entrepreneurial contexts where people come across other start-up entrepreneurs yield a milieu where entrepreneurial attitudes are easier to develop than elsewhere.

10. In recession periods, fear of criticism in case of failure may no longer be significant because self-employment is now practically the only possible option, and this need to set up a business makes individuals consider opportunities where in other conditions they would not have done so.

11. The long-term unemployment rate refers to the share of unemployed persons for 12 months or more in the total active population.

12. In general terms, the three inequality indices move in the same direction. However, the findings highlighted by such indices may differ to some degree. In fact, each of the indices incorporates different value judgements in the measurement of inequality. Rather than considering just one, analysts often consider a range of measures to examine inequality, especially if there is no Lorenz dominance among the distributions being compared.

13. Although Jenkins and Van Kerm (2006) provide this mathematical expression for the generalized Gini coefficient [ΔG(υ) = R(υ) − P(υ)], in our case we specifically consider the conventional Gini coefficient, which corresponds to the case υ = 2. Let us recall that larger values of υ involve greater weight of inequality differences among lower ranked observations.

14. Greece is the country with the highest level of Fear of failure rate before and after the crisis period, followed by Spain in 2007 and Italy in 2013, and Hungary being the country with the largest increase in considering fear of failure as a deterrent to entrepreneurship over the period of economic downturn.

Additional information

Funding

This work was supported by the Andalusian Regional Government and the University of Malaga [grant FC14-ECO-16].