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Determinants of self-employment survival in Europe

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An Erratum to this article was published on 11 June 2010

Abstract

This paper investigates the determinants of self-employment survival in Europe in two stages. The first one focuses on the effect of variables at the individual level, while the second raises questions regarding specific regional factors through the introduction of macro variables. In conducting this analysis, discrete choice models, including both single and competing risks frameworks, are applied to data drawn from the European Community Household Panel from 1994 to 2001. Different destination states are considered: paid employment, unemployment and inactivity. This allows us to search for the underlying determinants of these different hazards. The results suggest a positive impact on survival of formal education and previous experience within the labour market. In addition, we find that entering self-employment from unemployment has a strong negative effect on survival within self-employment. However, our results also show that the expenditure on start-up subsidies decreases the risk of exiting self-employment specifically for the group of individuals entering self-employment from unemployment. Therefore, the availability of these incentives might be seen by policymakers as not only a route to increase entry into self-employment, but also as an adequate instrument for equalising survival chances across individuals entering self-employment from unemployment and those entering with a different starting status.

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Notes

  1. Other tools are multiple state models, threshold models, decomposition techniques and particularly discrete choice models.

  2. To the best of our knowledge, Williams (2004) is the only work to date that refers to Europe as a whole.

  3. See Taylor (1999); Carrasco (1999); Falter (2002); Martínez-Granado (2002); Jensen et al. (2003); van Praag (2003); Cueto and Mato (2006); Georgellis et al. (2007); Oberschachtsiek (2008); Andersson and Wadensjö (2007); Muñoz and Cueto (2008); Ejrnæs and Hochguertel (2008); Andersson (2010); Georgarakos and Tatsiramos (2009) and Tokila (2009).

  4. See Evans and Leighton (1990); Meager (1996); Wiessner (1998); Carrasco (1999); Reize (2000, 2004); Pfeiffer and Reize (2000a, b); Del Monte and Scalera (2001); Meager et al. (2003); Cueto and Mato (2006); Andersson and Wadensjö (2007); Ejrnæs and Hochguertel (2008); Baptista et al. (2010), Caliendo and Kritikos (2010); Haapanen and Tervo (2009) and Tokila (2009).

  5. See Reize (2000); Bruce (2002); Nziramasanga and Lee (2002); van Praag (2003); Gurley-Calvez (2006); Fertala (2008); Gurley-Calvez and Bruce (2008); Kugler and Pica (2008) and Muñoz and Cueto (2008).

  6. The ECHP data are used with the permission of Eurostat (contract ECHP/2006/09, held with the Universidad de Huelva).

  7. These authors stress the importance for firm survival of the existing opportunities outside the firm for educated entrepreneurs in emerging and developing economies, such as India or Zimbabwe.

  8. Luxembourg and Sweden have to be excluded from our analysis because these countries present missing values for relevant variables.

  9. Those individuals entering self-employment before 1981 are excluded from our sample because we do not have information about the exact self-employment spell duration. However, the number of self-employed individuals within this group is smaller than 3% of the initial sample, and their exclusion does not affect our results in a significant way.

  10. The way we handle left-truncation and right-censoring problems is described in Sect. 4.

  11. Table 3 (Appendix) presents the distribution of observations and spells across countries. Table 4 (Appendix) summarises the mean values of all self-employment spells, distinguished by destination states: censored and exiting to paid employment, unemployment or inactivity.

  12. We decided not to include part-time employment in our estimations. This is because those individuals working two jobs at the same time might face short-term problems in one of the two activities and look for complementary income for a certain period of time. That would make the determinants of survival of those individuals simultaneously performing both jobs different from the determinants of those who opt for a single activity. We believe, therefore, that part-time self-employment duration needs to be independently analysed.

  13. Self-employment incomes are corrected by purchasing power parities (comparability across countries) and harmonised consumer price indexes (comparability across time). In addition, this variable is lagged 1 year due to the possible endogeneity problem of the changes in these incomes related to business failures.

  14. For each country, EPL is described using 18 basic items that can be grouped in three main areas: (1) employment protection of regular workers against individual dismissal; (2) specific requirements for collective dismissals; (3) regulation of temporary forms of employment. For further detail regarding the aggregation of these items, see OECD (1999). More information on the evolution of and updates to these indexes is available at OECD (2004).

  15. This section draws especially on the Stephen P. Jenkins’ Lecture Notes corresponding to the course Survival Analysis by Stephen P. Jenkins, provided by the University of Essex Summer School, among other universities and institutions.

  16. Following usual conventions, we model random individual effects and assume this term as a normally distributed random variable with mean 0, variance u n and independence from all observable characteristics.

  17. For persons with censored spells, all observations are censored; for persons with a completed spell, all observations are censored except the final one.

  18. Before proceeding with the estimation, we performed the Hausman test (Hausman and McFadden 1984) on the assumption of independence of irrelevant alternatives (IIA). Our results in Table 5 (Appendix) tell us that the null hypothesis of IIA is accepted. In addition, Table 5 reports the results of Wald and likelihood ratio tests used to examine the null hypothesis that the coefficients of the alternatives do not differ significantly from each other for all possible combinations. In both tests, none of the categories should be combined because the null hypothesis is rejected. Therefore, the multinomial logit specification seems to be appropriate.

  19. Tables S1 and S2 are included in the on-line appendix available at SpringerLink.

  20. Comparisons between specifications (I), (II) and (III) show that the inclusion of the variables accounting for wealth and weekly working hours does not alter the obtained effects for other variables, which is consistent with an absence of endogeneity problems caused by these variables. In addition, a likelihood ratio test confirmed that the inclusion of these variables significantly improves the explanatory power of the model at the 1% significance level.

  21. Within our sample, exits to inactivity involve education or training (6.1%), early retirement (before 59 years of age—9.4%), doing housework, looking after children or other persons (45.1%) and some other activities (39.4%).

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Acknowledgements

The authors would particularly like to thank the editor, Rui Baptista, two anonymous referees, Javier Álvarez, José I. García, Juan A. Máñez, María E. Rochina and Juan A. Sanchis for their helpful comments and suggestions. They also thank Raquel Carrasco, Jolanda Hessels, Simon Parker, Roy Thurik, Mirjam van Praag, André van Stel, Peter van der Zwan and participants at a Max-Planck-Institut für Ökonomik Seminar (Jena 2005), the XI Spring Meeting of Young Economists (Sevilla 2006), the IX Applied Economics Meeting (Oviedo 2006) and the I Workshop on Applied Entrepreneurship Research (Huelva 2008). This research is part of the project PRY115/09, which has been funded by the Fundación Centro de Estudios Andaluces (5th announcement for research projects grants). The usual disclaimer applies.

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Correspondence to José María Millán.

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An erratum to this article can be found at http://dx.doi.org/10.1007/s11187-010-9289-0.

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Appendix

Appendix

Variable definitions are reported below.

 

Dependent variables

Single risk models

Dependent variable equals 1 for individuals who are full-time self-employed workers in period t and enter paid employment in period t + 1. The variable equals 2 for individuals who are full-time self-employed workers in period t and enter unemployment in period t + 1. The variable equals 3 for individuals who are full-time self-employed workers in period t and enter inactivity in period t + 1. Finally, the variable equals 0 for individuals who are full-time self-employed workers in periods t and t + 1, or the information about the labour status in t is censored

Competing risks models

Dependent variable equals 1 for individuals who are full-time self-employed workers in period t and exit self-employment in period t + 1. The variable equals 0 for individuals who are full-time self-employed workers in periods t and t + 1, or the information about the labour status in t + 1 is censored

Demographic characteristics

Male

Dummy equals 1 for males

Age

Age reported by the individual, ranging from 21 to 59

No education/very basic education (reference category)

Dummy equals 1 for illiterate, no schooling individuals, or individuals with primary schooling as highest education level achieved

Primary schooling/secondary schooling

Dummy equals 1 for individuals with secondary schooling as highest education level achieved

University studies

Dummy equals 1 for individuals with university studies

Cohabiting

Dummy equals 1 for cohabiting individuals

Number of children under 14

Number of children aged under than 14 living within the household

Relative(s) working as self-employed

Dummy equals to 1 if there are any in the household

Employment characteristics

Construction sector (reference category)

Dummy equals 1 for individuals whose codes of main activity of the local unit of the business is F (construction), by the Nomenclature of Economic Activities (NACE-93)

Industrial sector

Dummy equals 1 for individuals whose codes of main activity of the local unit of the business are C (mining and quarrying), D (manufactures) and E (electricity, gas and water supply), by the Nomenclature of Economic Activities (NACE-93)

Financial services

Dummy equals 1 for individuals whose codes of main activity of the local unit of the business are J (Financial intermediation) and K (real estate, renting and business activities), by the Nomenclature of Economic Activities (NACE-93)

Wholesale, hotels, restaurants and transport

Dummy equals 1 for individuals whose codes of main activity of the local unit of the business are G (wholesale and retail trade; repair of motor vehicles, motorcycles and personal/household goods), H (hotels and restaurants) and I (transport, storage and communication), by the Nomenclature of Economic Activities (NACE-93)

Other services

Dummy equals 1 for individuals whose codes of main activity of the local unit of the business are L (public administration and defense; compulsory social security), M (education), N (health and social work) and O-Q (other community, social and personal service activities; private households with employed persons; extra-territorial organizations and bodies), by the Nomenclature of Economic Activities (NACE-93)

Hours of work

Hours of work per week

Previous experience

Previous experience as self-employed

Dummy equals 1 for individuals with observed previous spell(s) as self-employed

Previous experience as paid-employed

Dummy equals 1 for individuals with observed previous spell(s) as paid-employed

Previous experience as inactive

Dummy equals 1 for individuals with observed previous spell(s) as inactive

Previous labour market situation

Entering self-employment from unemployment

Dummy equals 1 for individuals entering self-employment from unemployment

Incomes

Dwelling owner

Dummy equals 1 for households owning the dwelling

Receiving capital and property incomes (1 lag)

Dummy equals 1 for individuals receiving capital and property incomes or private transfers received during period t – 1

Annual incomes as self-employed (1 lag)

Incomes earned as self-employed during period t − 1, converted to average euros of 1996, being corrected by purchasing power parity (across countries) and harmonised consumer price index (across time). Variable expressed in thousands of euros

Business cycle

National unemployment rate

Harmonised annual unemployment rate (source: OECD)

Aggregated environment

Services share

Share of services sector in total employment. (source: OECD)

Rule of law

Time-dependent index for the degree of regulation enforcement (World Bank). This variable has been reclassified into a range from 0 to 6 to allow a clear comparison of the effect of this variable with other indexes included in this analysis

Labour market institutions

Start-up incentives

Expenditure on start-up incentives as one part per ten thousand of GDP (source: OECD)

Employment incentives

Expenditure on employment incentives as one part per ten thousand of GDP (source: OECD)

EPL index for employment

Time-dependent EPL index for employment (source: OECD). Variable scaled to lie between 0 and 6

Unemployment benefits index

Measure of generosity of unemployment benefits (source: Botero et al. 2004). This variable has been reclassified into a range from 0 to 6 to allow a clear comparison of the effect of this variable with other indexes included in this analysis

Statutory tax rates on dividend income

Time-dependent index for marginal statutory corporate income tax rate on distributed profits (source: OECD)

See Tables 3, 4, 5 and 6.

Table 3 Number of observations and spells across countries
Table 4 Descriptive statistics of the departure from self-employment
Table 5 Chi-squared tests for multinomial logit specifications
Table 6 Pearson correlation coefficients matrix

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Millán, J.M., Congregado, E. & Román, C. Determinants of self-employment survival in Europe. Small Bus Econ 38, 231–258 (2012). https://doi.org/10.1007/s11187-010-9260-0

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