Longitudinal study of necessity- and opportunity-based entrepreneurship upon COVID lockdowns - The importance of misery and economic freedom indexes
Yilsy M. Núñez and
Gustavo Morales-Alonso
Technological Forecasting and Social Change, 2024, vol. 200, issue C
Abstract:
The economic progress of a society and its economic growth are strongly grounded on the country's rate of entrepreneurial activity. In turn, the decision to create a new venture is known to be highly influenced by the context in which it will be created. Institutional contexts that are prone to confiscation risks will be less conducive towards entrepreneurship, especially during an exogenous economic shock. In the present study, we gathered entrepreneurial aspirations data from the Global Entrepreneurship Monitor and analyzed it in light of contextual factors taken from the World Bank and the Fraser Institute. The sample is composed of panel data that were analyzed through machine learning techniques (Artificial Neural Networks). We gathered data from 30 countries for 2017, 2018, 2019, and 2020 to account both for regular years and a year subjected to an exogenous economic shock – the one caused by the COVID-19 pandemic in 2020. We found that economic freedom might be occasionally overvalued when used as a predictor for entrepreneurship, especially for high income economies. At the same time, however, the academic community may not be paying enough attention to economic hardship as a predictor for entrepreneurship, which can be of the greatest importance in case of an exogenous economic shock.
Keywords: Economic development; Artificial neural networks; Machine learning; COVID-19 lockdowns; Entrepreneurship; Economic hardship (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0040162523007643
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:200:y:2024:i:c:s0040162523007643
DOI: 10.1016/j.techfore.2023.123079
Access Statistics for this article
Technological Forecasting and Social Change is currently edited by Fred Phillips
More articles in Technological Forecasting and Social Change from Elsevier
Bibliographic data for series maintained by Catherine Liu ().