An inquiry into the drivers of an entrepreneurial economy: A Bayesian clustering approach

Understanding the worldwide drivers of qualified entrepreneurship is a key issue in economic policy design. To help policy decisions exert their intended impact, we aim to cluster a wide range of countries on the basis of their levels and trends in self-employment productivity using a finite mixture model applied to a new large dataset of 121 countries covering the period of 1991–2019. Our results point to three groups of high-, medium-, and low-productive means and tendencies, the geographical distribution of which suggests that they can be reinterpreted using the three stages of economic development, namely, innovation-, efficiency-, and factor-driven economies. Notably, we find that widespread digitalization and low unemployment enhance the probability of transitioning into a highly productive cluster. However, we failed to find that industry weight or employment protection legislation strictness serve as determinants in the transition between groups. Suggestive rationales for these results and implications for the entrepreneurship policy agenda are also provided.