The happy artist: an empirical application of the work-preference model

Abstract

The artistic labor market is marked by several adversities, such as low wages, above-average unemployment, and constrained underemployment. Nevertheless, it attracts many young people. The number of students exceeds the available jobs by far. A potential explanation for this puzzle is that artistic work might result in exceptionally high job satisfaction, a conjecture that has been mentioned at various times in the literature. We conduct the first direct empirical investigation into artists’ job satisfaction. The analysis is based on panel data from the German Socio-Economic Panel Survey. Artists on average are found to be considerably more satisfied with their work than non-artists, a finding that corroborates the conjectures in the literature. Differences in income, working hours, and personality cannot account for the observed difference in job satisfaction. Partially, but not fully, the higher job satisfaction can be attributed to the higher self-employment rate among artists. Suggestive evidence is found that superior “procedural” characteristics of artistic work, such as increased variety and on-the-job learning, contribute to the difference in job satisfaction.

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Fig. 1

Notes

  1. 1.

    The fact that many people turn to the arts as a leisure activity underpins the belief that artistic work yields high satisfaction. In Germany, for example, 14 % of the adult population in 2007 took part in artistic activities, such as painting, drawing, and sculpture (Eurostat 2011).

  2. 2.

    Cowen and Tabarrok (2000) emphasize that artists are not unique in deriving non-pecuniary benefits from particular forms of labor. For a more general discussion on non-pecuniary benefits form work, see also the early works on psychic income by, e.g., Thurow (1978, 1980) or Katz and Syrquin (1982).

  3. 3.

    Withers (1985) found the same result for Australian artists using data from an extensive survey specifically targeted at artists.

  4. 4.

    Haak (2005) found the same result for German artists using official data from the “Mikrozensus.”

  5. 5.

    An argument originally brought up by Santos (1976).

  6. 6.

    An argument also prominent in Frank and Cook (1995).

  7. 7.

    Influential articles from the superstar literature are Rosen (1981) and Adler (1985, 2006).

  8. 8.

    According to Menger (2006), the oversupply of artists is a phenomenon reaching far back in history.

  9. 9.

    A shortcoming of this literature is that it usually uses cross-sectional data only, so unobserved individual heterogeneity is rarely accounted for (D’Addio et al. 2007).

  10. 10.

    It is also common to combine these criteria (see, e.g., Throsby and Hollister 2003; Throsby 2001).

  11. 11.

    Karttunen (1998) notes that the degree of organization differs significantly between countries and art forms.

  12. 12.

    UNESCO adopted a definition that corresponds to a large degree with this criterion: “Artist is taken to mean any person who creates or gives expression to, or recreates works of art, who considers his artistic creation to be an essential part of his life, who contributes in this way to the development of art and culture and who is or asks to be recognized as an artist, whether or not he is bound by any relations of employment or association” (UNESCO 1980, p. 149).

  13. 13.

    If anything, our estimations would become more conservative. In the case of a positive correlation of an artistic activity with job satisfaction, those people who have an artistic job as a side occupation are counted as non-artists, thus increasing the average satisfaction of the non-artists and decreasing the probability of finding a significant effect.

  14. 14.

    Detailed descriptions are given in Table 7 in the appendix.

  15. 15.

    The regressions are estimated with an OLS model. Strictly, job satisfaction is an ordinally scaled variable, which would speak for an ordered response model. However, OLS models have the advantage that the estimated coefficients are easier to interpret, and experience shows that they are a close approximation of estimations of job and life satisfaction (Ferrer-i-Carbonell and Frijters 2004). To ascertain, we also estimated the regressions with an ordered logit model. As expected, the results remained largely unchanged.

  16. 16.

    The coefficients/standard errors without controlling for self-employment are 0.1724/0.1010 (performing or visual artist), and 0.5718/0.1768 (performing artist).

  17. 17.

    Note that the Hausman specification test favors the fixed effects over the random effects' specification. The same result was found in a Danish job satisfaction study by D’Addio et al. (2007). As such, the random effects' results should be viewed with a certain caution.

  18. 18.

    These questions were only asked in two SOEP waves, namely in 1995 and 2001.

  19. 19.

    A note on non-artists: Strictly, both groups of artists have their own “complementary set” in the labor force, that is, their own group of non-artists. However, these complementary sets are almost identical. Therefore, only one group of non-artists is depicted (complementary set of “Performing & Visual Artists”).

  20. 20.

    For the sake of simplicity, squared working hours are disregarded.

  21. 21.

    Note that the change of government did not create a natural experiment in the sense that people were randomly chosen to become artists. Rather, the term is here used to describe an exogenous change in conditions for artists. Also, note that the change of government was not completely exogenous, as the new government was elected by the individuals in the data set.

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Acknowledgments

For helpful suggestions, we are indebted to Bruno S. Frey, Reto Cueni, Christoph Engel, Margit Osterloh, and Trine Bille.

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Correspondence to Lasse Steiner.

Appendix

Appendix

See Tables 6, 7

Table 6 Occupations included in the two definitions of artists
Table 7 Variables

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Steiner, L., Schneider, L. The happy artist: an empirical application of the work-preference model. J Cult Econ 37, 225–246 (2013). https://doi.org/10.1007/s10824-012-9179-1

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Keywords

  • Job satisfaction
  • Artists
  • Work-preference
  • Cultural economics

JEL Classification

  • Z10
  • J24
  • J28
  • J31