Skip to main content
SpringerLink
Log in

The efficiency of German public theaters: a stochastic frontier analysis approach

  • Original Article
  • Published:
Journal of Cultural Economics Aims and scope Submit manuscript

Abstract

In recent years the economic performance of public non-profit sectors such as cultural services has become an interesting economic issue. This is due to the high dependence of cultural institutions on public funding on the one hand and the increasing cost-pressure on public budgets on the other hand. In order to achieve an efficient, cost-minimizing resource allocation public authorities who decide on the distribution of public budgets need reliable performance indicators. Against this background, this paper analyzes the efficiency of German public theaters for the seasons 1991/1992–2005/2006. Using a stochastic frontier analysis approach, we test whether the assumption of cost-minimizing behavior is reliable in this sector. Moreover, several panel data models that differ in their ability to account for unobserved heterogeneity are applied to evaluate the impact of unobserved heterogeneity on the efficiency estimates. The results indicate that the cost-minimizing assumption cannot be maintained. Consequently, an efficiency analysis based on a cost function approach seems inappropriate in the case of German public theaters. Further, we find a considerable unobserved heterogeneity across the theaters, which causes a significant variation in the models’ efficiency estimates. This implies that failing to account for unobserved heterogeneity leads to biased efficiency values. Overall, our results suggest that there is still space for improvement in the employment of resources in the sector.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

Notes

  1. For a detailed overview, see Marco-Serrano (2006).

  2. The symmetry restrictions in Eq. 4 are imposed during estimation.

  3. Alternative model specifications for the input distance and the cost function, such as a Cobb–Douglas functional form, a translog functional form with no technical change and a translog functional form with Hicks neutral technical change, have been tested and rejected by likelihood-ratio tests.

  4. For a method to impose regularity conditions ex ante on the estimated function, see O’Donnell and Coelli (2005).

  5. Most theaters run several stages so, the number of supplied tickets is calculated for every stage and then summed.

  6. All monetary measures are adjusted for inflation using the consumer price index for Germany (Statistisches Bundesamt (Federal Statistical Office) 2009). Values are stated in year-2005 Euros.

  7. The largest theater in terms of tickets supplied is Niedersaechsisches Staatstheater Hannover, which includes the state opera house and the Schauspielhaus, resulting overall in about 2,360 seats. The smallest theater is the Schlosstheater Moers, which has about 300 seats.

  8. In short panels the so called ‘íncidental parameter’ problem arises, yielding inconsistent parameter estimates.

  9. The Mundlak terms of Model IV are not reported to conserve space. For both functions 17 out of the 20 Mundlak coefficients are statistically different from zero at the 5% level.

  10. Other possible reasons noted by Rungsuriyawiboon and Coelli (2006) are measurement errors in either the input quantities or prices or an endogenous regressor problem in the distance function model. See Rungsuriyawiboon and Coelli (2006) for a further discussion.

  11. The violation rate of the curvature condition in the distance (cost) function is 20 (94) percent in Model I, 18 (67)% in Model II, 19 (26)% in Model III, and 20 (25)% in Model IV.

  12. Since the cost function estimates are considered less reliable the estimated cost efficiency scores are not reported to conserve space. The results are available on request from the authors.

References

  • Bishop, P., & Brand, S. (2003). The efficiency of museums: A stochastic frontier production function approach. Applied Economics, 35, 1853–1858.

    Article  Google Scholar 

  • Coelli, T. J., Prasada Rao, D. S., O’Donell, C. J., & Battese, G. E. (2005). An introduction to efficiency and productivity analysis (2nd ed.). New York: Kluwer.

    Google Scholar 

  • Deutscher Bühnenverein (German Stage Association). (1993–2007). Theaterstatistik 1991/92–2005/06 (Theater Reports 1991/92–2005/06). Koblenz/Köln.

  • Deutscher Bühnenverein (German Stage Association). (2008). Theaterstatistik 2006/07 (Theater Report 2006/07). Koblenz/Köln.

  • Färe, R., & Primont, D. (1995). Multi-output production and duality: Theory and applications. New York: Kluwer.

    Google Scholar 

  • Farrell, M. J. (1957). The measurement of technical efficiency. Journal of the Royal Statistical Society Series A (General), 25, 1–19.

    Google Scholar 

  • Farsi, M., & Filippini, M. (2004). Regulation and measuring cost efficiency with panel data models: Application to electricity distribution utilities. Review of Industrial Organization, 25, 1–19.

    Article  Google Scholar 

  • Farsi, M., Filippini, M., & Greene, W. (2005). Efficiency measurement in network industries: Application to the Swiss Railway Companies. Journal of Regulatory Economics, 28(1), 69–90.

    Article  Google Scholar 

  • Farsi, M., Filippini, M., & Greene, W. (2006). Application of panel data models in benchmarking analysis of the electricity distribution sector. Annals of Public and Cooperative Economics, 77(3), 271–290.

    Article  Google Scholar 

  • Fazioli, R., & Filippini, M. (1997). Cost structure and product mix of local public theatres. Journal of Cultural Economics, 21, 77–86.

    Article  Google Scholar 

  • Globerman, S., & Book, S. H. (1974). Statistical cost functions for performing arts organizations. Southern Economic Journal, 40(4), 668–671.

    Article  Google Scholar 

  • Greene, W. (2005a). Fixed and random effects in stochastic frontier models. Journal of Productivity Analysis, 23, 7–32.

    Article  Google Scholar 

  • Greene, W. (2005b). Reconsidering heterogeneity in panel data estimators of the stochastic frontier model. Journal of Econometrics, 126, 269–303.

    Article  Google Scholar 

  • Hadi, A. S. (1992). Identifying multiple outliers in multivariate data. Journal of the Royal Statistical Society, Series B, 54(3), 761–771.

    Google Scholar 

  • Hadi, A. S. (1994). A modification of a method for the detection of outliers in multivariate samples. Journal of the Royal Statistical Society, Series B, 56(2), 393–396.

    Google Scholar 

  • Jondrow, J., Lovell, K., Materov, I., & Schmidt, P. (1982). On the estimation of technical inefficiency in the stochastic frontier production function model. Journal of Econometrics, 19, 233–238

    Article  Google Scholar 

  • Kuenzle, M. (2005). Cost efficiency in network industries: Application of stochastic frontier analysis. Dissertation ETH No. 16117. Accessed 2 August 2, 2008, from http://www.e-collection.ethbib.ethz.ch/eserv/eth:27980/eth-27980-01.pdf

  • Kumbhakar, S. C., & Lovell, C. A. K. (2000). Stochastic frontier analysis. Cambridge, UK: Cambridge University Press.

    Google Scholar 

  • Lovell, C. A. K., Richardson, S., Travers, P., & Wood, L. L. (1994). Resources and functioning: A new view of inequality in Australia. In W. Eichhhorn (Ed.), Models and measurement of welfare and inequality (pp. 787–807). Berlin: Springer Verlag.

  • Marco-Serrano, F. (2006). Monitoring managerial efficiency in the performing arts: A regional theaters network perspective. Annals of Operations Research, 145, 167–181.

    Article  Google Scholar 

  • Migué, J.-L., & Bélanger, G. (1974). Toward a general theory of managerial discretion. Public Choice, 17, 27–47.

    Article  Google Scholar 

  • Mundlak, Y. (1978). On the pooling of times series and cross section data. Econometrica, 46(1), 69–85.

    Article  Google Scholar 

  • Niskanen, W. A. (1971). Bureaucracy and representative government. Chicago/New York: Aldine Atherton.

    Google Scholar 

  • O’Donnell, C. J., & Coelli, T. J. (2005). A Bayesian approach to imposing curvature on distance functions. Journal of Econometrics, 126, 493–523.

    Article  Google Scholar 

  • Pitt, M., & Lee, L.-F. (1981). The measuement and sources of technical inefficiency in the Indonesian Weaving Industry. Journal of Development Economics, 9, 43–64.

    Article  Google Scholar 

  • Rungsuriyawiboon, S., & Coelli, T. (2006). Regulatory reform and economic performance in US Electricity generation. In T. Coelli & D. Lawrence (Eds.), Performance measurement and regulation of network utilities (pp. 267–296). Northampton, MA, USA: Edward Elgar.

    Google Scholar 

  • Sauer, J., Frohberg, K., & Hockmann, H. (2006). Stochastic efficiency measurement: The curse of theoretical consistency. Journal of Applied Economics, IX(1), 139–165.

    Google Scholar 

  • Schmidt, P., & Sickles, R. (1984). Production frontiers and panel data. Journal of Business & Economic Statistics, 2(4), 367–374.

    Article  Google Scholar 

  • Shephard, R. W. (1953). Cost and production functions. Princeton, New Jersey: Princeton University Press.

    Google Scholar 

  • Statistisches Bundesamt (Federal Statistical Office). (2009). Verbraucherpreisindizes fnr Deutschland (German Consumer Price Indexes). Accessed January 7, 2009, from, https://www-ec.destatis.de/csp/shop/sfg/bpm.html.cms.cBroker.cls?cmspat h=struktur,vollanzeige.csp&ID=1023986.

  • Taalas, M. (1997). Generalised cost functions for producers of performing arts—Allocative inefficiencies and scale economies in theatres. Journal of Cultural Economics, 21, 335–353.

    Article  Google Scholar 

  • Throsby, C. D. (1977). Production and cost relationships in the supply of performing arts. In K. A. Tucker (Ed.), Economics of the Australian service sector (pp. 414–432). London: Croom Helm.

    Google Scholar 

  • Throsby, C. D. (1994). The production and consumption of the arts: A view of cultural economics. Journal of Economic Literature, 32(1), 1–29.

    Google Scholar 

  • Tobias, S. (2003). Kosteneffizientes Theater? Deutsche Bnhnen im DEA-Vergleich [Cost-efficient performing arts? German Theatres in a DEA Comparison]. Dissertation Technische UniversitSt Dortmund. Accessed March 7, 2009, from http://www.hdl.handle.net/2003/290

Download references

Author information

Authors and Affiliations

  1. Institute of Economics, Leuphana University Lueneburg, P. O. Box 2440, 21314, Lüneburg, Germany

    Anne-Kathrin Last

  2. Institute of Energy Economics, University of Cologne, Albertus-Magnus-Platz, 50923, Köln, Germany

    Heike Wetzel

Authors
  1. Anne-Kathrin Last
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Heike Wetzel
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Anne-Kathrin Last.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Last, AK., Wetzel, H. The efficiency of German public theaters: a stochastic frontier analysis approach. J Cult Econ 34, 89–110 (2010). https://doi.org/10.1007/s10824-009-9111-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10824-009-9111-5

Keywords

JEL classification

Search

Navigation