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Artistic education matters: survival in the arts occupations

Abstract

The literature of cultural economics generally finds that an artistic education has no significant impact on artists’ income and careers in the arts. In artists’ labor markets, indefinable features such as talent and artistic creativity apparently contribute more to success or higher rates of payment than education and training. In this article, we will readdress this question by looking at the artists’ survival in the arts occupations. We find it reasonable to expect than an artistic education can have a significant impact on artists’ careers because of the importance of technical skills, networks and signaling effects. We analyze the question by using a unique longitudinal dataset for five different groups of artists in Denmark, using the Cox model to apply survival functions and semi-parametric analysis. The results show, among other things, that an artistic education has a significant impact on artists’ careers in the arts, and we find important industry differences.

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Notes

  1. For further information on the specific variables see http://www.dst.dk/TilSalg/Forskningsservice.aspx.

  2. For comparison, currently there are 5.6 mill. inhabitants in Denmark.

  3. It is worth noting that decorators and commercial designers have their own job category (ISCO code 3471) in Statistics Denmark, and they have not been included in the analysis.

  4. We can get an impression of the bias by looking at our full sample of about 45.000 individuals (before regression). We can calculate the number of individuals with an interrupted artistic career in the same year. As an example, 1300 individuals have an artistic career that start before 2002 and continue from 2003, but is interrupted in 2002, where they do not work as artists (they might have a job in another occupation). We can make the same calculation for all the years in our sample, and it turns out, that the maximum number for one year is about 4300, and the minimum number is about 1300. Based on these calculations, we can assume the number of individuals with interrupted career in 1996, who returned in 1997, is between 1300 and 4300. Therefore, we expect the bias to be small.

  5. Statistics Denmark changed the definition of the group of visual artists during the studied period, with a small impact on the number of artists in the group and therefore also on the survival function, which can be seen in the decrease in visual artists between years 4 and 5.

  6. Age is not included in quadratic form, since it does not have a quadric distribution. The career length across age is randomly distributed—with a small tendency toward shorter career length for the youngest individuals.

References

  • Abbing, H. (2002). Why are artists poor. The exceptional economy of the arts. Amsterdam: Amsterdam University Press.

    Google Scholar 

  • Allison, P. D. (1995). Survival analysis using the SAS System: A practical guide. USA: SAS Institute.

    Google Scholar 

  • Alper, N., & Wassall, G. H. (2006). Artists’ careers and their labor markets. In V. A. Ginsburgh & D. Throsby (Eds.), Handbook of the economics of the arts and culture (pp. 813–864). Amsterdam: Elsevier Science, North Holland.

    Google Scholar 

  • Bille, T. and G. Schulze (2006): Culture in urban and regional development. In: D. Throsby and V. Ginsburgh (ed.): Handbook on the economics of arts and culture, Handbook of Economics Series, general editors K. Arrow and M.D. Intriligator, Elsevier Science, North-Holland, pp 1052–1099.

  • Bille, T., Frey, B. S., Steiner, L., & Fjællegaard, C. B. (2013). Happiness in the arts—international evidence on artists’ job satisfaction. Economic Letters, 121(1), 15–18.

    Article  Google Scholar 

  • Caves, R. (2000). Creative industries: Contracts between Arts and Commerce. Cambridge, MA: Harvard University Press.

    Google Scholar 

  • Coulangeon, P., Ravet, H., & Roharik, I. (2005). Gender differentiated effect of time in performing arts professions: Musicians, actors and dancers in contemporary France. Poetics, 33, 369–387.

    Article  Google Scholar 

  • Eikhof, D. R., Haunschild, A., & Schöβler, F. (2012). Behind the scenes of boundarylessness: Careers in German theatre. In C. Mathieu (Ed.), Careers in Creative Industries (pp. 69–87). New York: Routledge.

    Google Scholar 

  • Filer, R. (1986). The “starving artist”—myth or reality? Earnings of artists in the United States. Journal of Political Economy, 49, 56–75.

    Article  Google Scholar 

  • Filer, R. (1989). The economic condition of artists in America. In D. V. Shaw, W. Hendon, & V. L. Owen (Eds.), Cultural Economics 88: An American perspective. Akron: Association for Cultural Economics.

    Google Scholar 

  • Filer, R. (1990). The arts and academe: The effect of education on earning of artists. Journal of Cultural Economics, 14(1), 15–38.

    Article  Google Scholar 

  • Heian, M. T., Løyland, K., & Mangset, P. (2012). Stability and change: Work and income conditions for Norwegian artists. Nordic Journal of Cultural Policy, 15(1), 46–76.

    Google Scholar 

  • Hosmer, D. W., & Lemeshow, Stanley. (1999). Applied survival analysis—Regression modeling of time to event data. USA: John Wiley & Sons.

    Google Scholar 

  • Mathieu, C. (Ed.). (2012). Careers in creative industries. New York: Routledge.

    Google Scholar 

  • Menger, P. M. (1999). Artistic Labor Markets and Careers. Annual Reviews, 25, 541–574.

    Article  Google Scholar 

  • Menger, P. M. (2006). Artistic labor markets: Contingent work, excess supply and occupational risk management. In V. A. Ginsburgh & D. Throsby (Eds.), Handbook of the economics of art and culture (pp. 765–811). North Holland, Amsterdam: Elsevier Science.

    Chapter  Google Scholar 

  • Murphy, E. C. (2014). Workers’ movement out of declining occupations in Great Britain, Germany and Switzerland. European Sociological Review, 30(6), 685–701.

    Article  Google Scholar 

  • Rengers, M. (2002). Economic lives of artists: Studies into careers and the labour market in the cultural sector. Utrecht: Utrecht University, Interuniversity Center for Social Science Theory and Methodology.

    Google Scholar 

  • Rosen, S. (1972). Learning and experience of the founder of self-employment duration: A comparative advantage approach. Small Business Economics, 39(1), 1–17.

    Google Scholar 

  • Rosen, S. (1981). The economics of superstars. American Economic Review, 71(5), 845–858.

    Google Scholar 

  • Steiner, L., & Schneider, L. (2013). The happy artist? An empirical application of the work-preference model. Journal of Cultural Economics, 37(2), 225–246.

    Article  Google Scholar 

  • Throsby, D. (1992): Artists as workers. Reprinted in: R. Towse (eds) (1997): Cultural economics. The arts, the heritage and the media industries, Edward Elgar, Cheltenham.

  • Throsby, D. (1994). A work-preference model of artist behavior. In A. Peacock & I. Rizzo (Eds.), Cultural economics and cultural policies (pp. 69–80). Dordrecht: Kluwer Academic Publishers.

    Chapter  Google Scholar 

  • Throsby, D. (2001). Economics and culture. Cambridge: Cambridge University Press.

    Google Scholar 

  • Throsby, D. (2006). Disaggregated earnings functions for artists. In V. Ginsburgh & P.-M. Menger (Eds.), Economics of the arts: Selected essays (pp. 331–346). Dordrecht: Kluwer Academic Publishers.

    Google Scholar 

  • Throsby, D., & Hollister, V. (2003). Don’t give up your day job yet; An economic study of professional artists in Australia. Sydney: Australia Council.

    Google Scholar 

  • Towse, R. (2006). Human capital and artists’ labour markets. In V. A. Ginsburgh & D. Throsby (Eds.), Handbook of the economics of the arts and culture (pp. 865–894). North-Holland, Amsterdam: Elsevier Science.

    Google Scholar 

  • Withers, G. (1985). Artists’ subsidy of the arts. Australian Economics Papers, 24, 290–295.

    Article  Google Scholar 

  • Woodbridge, J. (2002). Econometric analyses of cross section and panel data. Cambridge, MA: MIT Press.

    Google Scholar 

  • Wooldridge, Jeffrey M. (2010). Econometric analysis of cross section and panel data. USA: MIT Press.

    Google Scholar 

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Correspondence to Trine Bille.

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Bille, T., Jensen, S. Artistic education matters: survival in the arts occupations. J Cult Econ 42, 23–43 (2018). https://doi.org/10.1007/s10824-016-9278-5

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  • DOI: https://doi.org/10.1007/s10824-016-9278-5

Keywords

  • Artists’ careers
  • Survival functions
  • Arts education
  • Artists’ earnings