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

Maximo Camacho, Emilio Congregado and Ana Rodriguez-Santiago ()
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Maximo Camacho: University of Murcia
Emilio Congregado: University of Huelva
Ana Rodriguez-Santiago: University of Huelva

Journal of Evolutionary Economics, 2024, vol. 34, issue 4, No 10, 1012 pages

Abstract: Abstract 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.

Keywords: Entrepreneurship; Productive self-employment; Model-based clustering; Finite mixture models; Cross-country analysis; Transition probabilities (search for similar items in EconPapers)
JEL-codes: C11 J24 M13 O43 (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s00191-024-00863-9

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