Abstract
The aim of this paper is to analyse self-employment survival, with special interest in the role of human capital and regions. Using Spanish administrative data and multilevel models, we followed two cohorts of new entrepreneurs for 2 years. According to our findings, the survival rate of new entrants into self-employment is approximately 53%, with this rate decreasing during the economic downturn by ten points. The results for both cohorts underline the necessity of considering personal and contextual factors in elaborating policy recommendations on entrepreneurship. Young workers and those with lower levels of informal human capital have low survival rates, so they need stronger support. The estimations also offer evidence of the relevance of regions. The inherent characteristics of regions contribute to explaining the survival of new start-ups. Again, the design of entrepreneurial policies should take into account these results. Additionally, the reason for entering self-employment seems to be more relevant in times of crisis.
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Notes
In 2010, the growth in start-up subsidies was 17.7%, compared to 3.2% for job training expenditures. After 2011, to reduce public expenditures, the amount dedicated to active labour market policies was drastically reduced. However, while the reduction in training expenditures was over 20% in 2012–2013, start-up subsidies were reduced by less than 5%.
The incentive to become self-employed due to unemployment is also called the “refuge effect” (Thurik et al. 2008).
The agricultural sector has special characteristics that make it different from industry and services. Moreover, in the Spanish context, agricultural workers fall under special social security regimes.
The qualification group is related to the level of education, but this variable also reflects the position of the worker in the firm. There are ten groups: from engineers and graduates to labourers. The contribution to social security depends on this qualification group.
In 2005, 22.3% of the population had a university degree. This proportion increased to 23.6% in 2009 and to 26.5% in 2013.
A disadvantage of our data set is the inability to distinguish between unemployment and non-participation. Social security administrative records provide information about the exact dates workers were unemployed and receiving unemployment benefits. However, if unemployed workers are not entitled to receive benefits, this information is not recorded administratively. Therefore, non-participation means unemployment without benefits (mainly long-term unemployed individuals) and inactive workers.
The Spanish autonomous cities of Ceuta and Melilla are excluded.
Small intraclass correlation coefficients are more common.
In this case, the null hypothesis is at the boundary of the parameter space \( (\psi \ge 0) \). Thus, the correct asymptotic sampling distribution is \( 0.5\chi_{0}^{2} + 0.5\chi_{1}^{2} \).
We test the null hypothesis of no random intercepts in the model using the likelihood-ratio test, and the results are statistically significant.
The table is in “Appendix”.
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Acknowledgements
Authors gratefully acknowledge funding by Ministry of Economics and Competitiveness (Projects with references: ECO2016-75805-R and ECO2017-86402-C2-1-R).
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Cueto, B., Suárez, P. & Mayor, M. Effects of human capital and regional context on entrepreneurial survival. Ann Reg Sci 66, 331–357 (2021). https://doi.org/10.1007/s00168-020-01023-0
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DOI: https://doi.org/10.1007/s00168-020-01023-0