This paper aims to improve knowledge of individual heterogeneity in affecting the entrepreneurial attitude, taking socioeconomic drivers under control thanks to a cross-country analysis. The authors operate a “selection” of proxy for individual heterogeneity, mainly based on gender, demographical features, personal attitude and intrinsic motivation.
This exploration is supported by an empirical analysis based on the Global Entrepreneurship Monitor (GEM), for the period 2001-2012, and for a selection of 37 countries. It is expected that gender and further individual variables have an impact on the probability to become a nascent entrepreneur (e.g. age, level of education, self-confidence, social perception of self-employment as career choice). This paper evaluates the degree of consistency of these variables across very dissimilar countries.
Gender and confidence on own skill play a significant and consistent effect on the entrepreneurial attitude, so these personal features are, per se, the driving-strength of entrepreneurial intent. Conversely, fear of failure and belief on the status are not always statistically significant, or not homogenous in their relationship: socioeconomic or country-specific characteristics are strong and sort out in an unpredictable relationship between these variables and the willingness to run new ventures.
A limited selection of individual features constrained by availability of information from the GEM data set.
The motivation of this paper is to focus-back attention on intra-individual features that may affect entrepreneurship and to support evidence of whether individual heterogeneity is able to affect the entrepreneurial attitude, taking socioeconomic drivers under control.
An institutional and political commitment should be intensified to reduce the waste of opportunities that is associated with any forms of self-exclusion from entrepreneurship, such as those based on gender (being women) or (low) self-esteem.
Due to the “individual” perspective, this paper adds to previous studies that exploited the GEM data set because they mostly follow an institutional conceptual framework.
