RT Journal Article
T1 An inquiry into the drivers of an entrepreneurial economy: A Bayesian clustering approach
A1 Camacho Alonso, Máximo Cosme
A1 Congregado Ramírez de Aguilera, Emilio
A1 Rodríguez Santiago, Ana María
AB 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 selfemployment 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. 
PB Springer
SN 0936-9937
SN 1432-1386 (electrónico)
YR 2024
FD 2024-05
LK https://hdl.handle.net/10272/23829
UL https://hdl.handle.net/10272/23829
LA eng
NO Camacho, M., Congregado, E., & Rodriguez-Santiago, A. (2024). An inquiry into the drivers of an entrepreneurial economy: A Bayesian clustering approach. In Journal of Evolutionary Economics. Springer Science and Business Media LLC. https://doi.org/10.1007/s00191-024-00863-9
NO Funding for open access publishing: Universidad de Huelva/CBUA. The authors acknowledge funding from the Spanish Ministry of Science, Innovation and Universities through project PID2020-115183RB-C22; from Junta de Andalucía through grant P20-00733 and Research Group SEJ-487 (Spanish Entrepreneurship Research Group – SERG); and from Research and Transfer Policy Strategy of the University of Huelva 2021. M. Camacho is grateful for the support of grant PID2022-136547NB-I00 funded by MICIU/AEI/https://doi.org/10.13039/501100011033and by FEDER, UE. 
DS Repositorio Institucional de la Universidad de Huelva
RD 13 jun 2026