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Life satisfaction and self-employment: a matching approach

Small Business Economics volume 40, pages 1009–1033 (2013)Cite this article

Abstract

Despite lower incomes, the self-employed consistently report higher satisfaction with their jobs. But are self-employed individuals also happier, more satisfied with their lives as a whole? High job satisfaction might cause them to neglect other important domains of life, such that the fulfilling job crowds out other pleasures, leaving the individual on the whole not happier than others. Moreover, self-employment is often chosen to escape unemployment, not for the associated autonomy that seems to account for the high job satisfaction. We apply matching estimators that allow us to better take into account the above-mentioned considerations and construct an appropriate control group (in terms of balanced covariates). Using the BHPS dataset that comprises a large nationally representative sample of the British populace, we find that individuals who move from regular employment into self-employment experience an increase in life satisfaction (up to 2 years later), while individuals moving from unemployment to self-employment are not more satisfied than their counterparts moving from unemployment to regular employment. We argue that these groups correspond to “opportunity” and “necessity” entrepreneurship, respectively. These findings are robust with regard to different measures of subjective well-being as well as choice of matching variables, and also robustness exercises involving “simulated confounders”.

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Notes

  1. Our focus on nascent entrepreneurship bears similarities to some previous work (Bradley and Roberts 2004; Schjoedt and Shaver 2007; Fuchs-Schundeln 2009); see also Andersson (2008) who focuses on changes between two cross-sections (1991 and 2000).

  2. Van Praag and Versloot (2007, pp. 375–376) provide a brief overview over some contributions entrepreneurship has on the utility levels of entrepreneurs and their employees.

  3. Cooper and Artz (1995) found that entrepreneurs with initially high expectations for their business venture performance turned out to be more satisfied than other entrepreneurs, suggesting that these more satisfied individuals have some more optimistic personality traits that influence their subsequent job satisfaction. This finding does probably only pertain to those entrepreneurs that create their business out of opportunity, not to escape unemployment.

  4. The positive effect of being self-employed on job satisfaction diminishes markedly when taking into account the heterogeneity of the control group of the employed in terms of the size of the firm they are working in (Benz and Frey 2008a, p. 374).

  5. Another source of heterogeneity might stem from distinguishing entrepreneurship from self-employment, of which we abstract here for reasons of data limitation.

  6. Note however, that this problem does not apply to randomized experiments, because treatment and control groups have no systematic differences with respect to both observed and unobserved variables.

  7. Waves before 1996 did not elicit life satisfaction measures and had to be discarded thus.

  8. We are grateful that a referee made us aware of this issue that might affect survey data.

  9. A Levene’s test for unequal variances was conducted before the t-tests, suggesting in all cases significantly differing variances.

  10. We have reversed the numerical order of the Likert scale to consistently use higher values for better outcomes. The original coding in the BHPS codes a value of one to be excellent health and five to be very poor health.

  11. To be precise, computing VIF is only possible in the context of OLS models, so that we reestimated model (1) as a simple OLS regression.

  12. We observe that 0.63% of the self-employed report a life satisfaction score of 1, compared to 0.50% of employed individuals.

  13. The rationale for model (5) lies in some econometric reservations one could have in our using an ordinal scaled life-satisfaction variable in a fixed effects OLS regression, thus implicitly treating life satisfaction as a cardinal variable. This is in part motivated by the absence of a commonly agreed-on method to account for fixed effects in an ordered probit framework. However, econometric research on happiness shows that there are no substantial differences between both approaches in terms of the results they generate (Ferrer-i-Carbonell and Frijters 2004) and a cardinal treatment of life satisfaction is common in the psychological literature on well-being. One reason for the robustness of the life satisfaction measure to being treated as cardinal could lie in the fact that individuals seem to convert ordinal response labels into similar numerical values such that these cardinal values equally divide up the response space (Van Praag 1991; Clark et al. 2008a). Nevertheless, model (5) with a 37-point scale alleviates the possible objection to using life satisfaction in an FE framework, since treating a 37-point scaled mental well-being construct as a cardinal variable seems much more uncontroversial.

  14. Cooper and Artz (1995) focus in their analysis on third year business because prospects can fluctuate and in the beginning, uncertain prospects might lower job satisfaction. This initial uncertainty offers thus an additional reason for taking into account the intertemporal structure of life satisfaction following one’s decision to go into self-employment.

  15. We also wanted to match individuals according to industry in which they are employed (or had their last employment), but since data reporting definitions changed over the sample period and were only available for the subgroup of employed individuals, we were prevented from doing this except for the robustness exercise reported below.

  16. We only present results from the “pscore” command (Becker and Ichino 2002) since these two estimators are seen to give virtually identical results.

  17. The authors will provide the detailed results of this exercise on request.

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Acknowledgments

No individuals were mistreated during our matching procedures. We are grateful to Tom Broekel, Rob Byrne, Jan Fagerberg, Steffen Künn, Ben Martin, Maria Savona, Josh Siepel, Jagannadha Pawan Tamvada, Dagmara Weckowska, Ulrich Witt and seminar participants at SPRU (University of Sussex) and Kingston University, and also to Bram Timmermans for some interesting suggestions, comments, etm. We also want to thank two anonymous referees for many invaluable comments and suggestions. The authors are grateful for having been granted access to the BHPS data set, which was made available through the ESRC Data Archive. The data were originally collected by the ESRC Research Centre on Micro-Social Change at the University of Essex (now incorporated within the Institute for Social and Economic Research). Neither the original collectors of the data nor the Archive bear any responsibility for the analyses or interpretations presented here. Any remaining errors are ours alone. We are grateful for financial support from the ESRC, TSB, BIS and NESTA on grants ES/H008705/1 and ES/J008427/1 as part of the IRC distributed projects initiative. Alex Coad also received funding from the AHRC as part of the FUSE project.

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  1. Evolutionary Economics Group, Max Planck Institute of Economics , Kahlaische Str.10, 07745, Jena, Germany

    Martin Binder & Alex Coad

  2. SPRU, University of Sussex, Falmer, Brighton, BN1 9QE, UK

    Alex Coad

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  1. Martin Binder
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Binder, M., Coad, A. Life satisfaction and self-employment: a matching approach. Small Bus Econ 40, 1009–1033 (2013). https://doi.org/10.1007/s11187-011-9413-9

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