Abstract
Theatre experts generally agree that the Flemish theatre has flourished artistically over the period 1980–2000. Attendance, on the other hand, has declined significantly. Following Lancaster’s characteristics approach, we identify several output characteristics of individual theatre productions. Using a panel of 59 Flemish theatres, we examine the impact on demand of both these output characteristics and of traditional determinants such as own price, income and the price of substitutes. Differences in the relevant geographical market for touring and non-touring theatres are considered. We find that the nature of the artistic output affects demand. Theatregoers prefer large productions (in terms of cast size), plays by Dutch-speaking playwrights and revivals of old productions. Own price and consumer income have the expected negative and positive effects on attendance. Observed trends toward a decreasing proportion of new plays, an increasing presence of plays by Dutch-speaking playwrights, and increasing consumer income had a stimulating effect on attendance. These trends have been offset, however, by trends toward smaller cast sizes and higher ticket prices as well as by unobserved factors captured by time dummies. The net result has been a considerable drop in attendance.
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Notes
Such an approach, in a way, assumes perfect foresight on the part of the theatre managers. As Krebs and Pommerehne (1995) admit, it is always possible for a ‘lowbrow’ piece to be unsuccessful and for a ‘highbrow’ piece to be successful with the lay audience.
The quality and critic ratings variables were not tested empirically (Kelejian & Lawrence, 1980).
Repertoire diversity measures—such as conformity/conventionality indices, or the number of different productions in a season—have been used in studies examining the determinants of repertoire diversity. Special focus is given to the relationship between diversity and public funding (Austen-Smith, 1980; DiMaggio & Stenberg, 1985; O’Hagan & Neligan, 2005; Pierce, 2000). It would be interesting to use such measures in demand analysis. However, the use of the conformity index in the context of the Flemish theatre is difficult because of the small scale of the sector and the large heterogeneity of the chosen plays and playwrights. For example, out of the 193 theatre productions in 2000, 122 productions involved playwrights whose work was only performed in 1 production. There was only one playwright (Thomas Bernhard) for whom (a maximum number of) five productions were staged.
The latter reflect two distinct effects on demand. First, expert opinions may be seen as an appreciation of the set of unobserved (by the empirical analyst) characteristics of a play. Second, these opinions may—given a set of characteristics—exert an effect on demand. Since a theatre performance is an experience good, consumers have the difficult task to assess the quality of a production prior to seeing the actual performance. Thus, they can rely on expert judgement to make their consumption decision.
Structural subsidies are distributed to ensure the long-run operation of a theatre company; this in contrast to project subsidies that are distributed to support individual productions during a particular theatre season.
In practice (minor) regional differences in the language persist between Flanders and the Netherlands. The actual situation is comparable with the differences between British and American English.
The distinction between touring and non-touring theatre companies is based on a categorization of subsidized theatres by the Flemish Community.
Data on theatre productions come from the ‘Vlaamse Theaterjaarboeken’ (Flemish Theatre Year Books) in the editions 1980–1981 to 1996–1997/1997–1998 and the online database (http://www.vti.be) from the Vlaams Theater Instituut (Flemish Theatre Institute). The detailed description of the theatre productions is taken to reflect which characteristics are relevant from the viewpoint of the theatre sector itself. Therefore, our own choice of output characteristics (z 1 to z 5) is based on the information provided by these data sources.
Data on theatre attendance, box office revenues and the number of visitors come from the Flemish Ministry of Culture. Data on per capita income, number of inhabitants and cinema ticket prices come from the Nationaal Instituut voor Statistiek (NIS).
As we already noted in Sect. 3, some theatres start as touring companies but end up having their own playhouse later on.
The average price of cinema tickets was calculated by dividing box office income by the number of cinema visitors. Our data on movie theatres show that they are only located in large municipalities and not in their neighbouring municipalities. Hence, the use of the spatial weighting matrix to calculate the average price of cinema tickets was not relevant.
It is standard practice for the fixed effects model (FEM) to be compared with the random effects model (REM). The REM involves rewriting the error term ɛ i,t as u i + e i,t where u i is now the random disturbance characterizing the i-th observation (constant over time) and e it a remainder component which is assumed to be uncorrelated over time. To choose between the REM and the FEM, the Hausman test statistic (Hausman, 1978) tests whether the FE and RE estimators are significantly different. The Hausman test checks the more efficient REM against the less efficient but always consistent FEM. Large values of the Hausman statistic imply a larger variance of the RE estimator relative to the FE estimator and a greater efficiency of the FE estimator. Thus a rejection of the null hypothesis confirms the preference for the FE estimator to the RE alternative. For the random effects model to be preferred to the fixed effects model the Hausman test must not be rejected (Verbeek, 2004).
To analyse subperiods, we split the sample into a 1980–1990 sample and a 1991–2000 sample. Concentrating on the significant coefficients in Table 1, we find that coefficients in the split samples have the same sign. Still, in terms of significance there is a difference. The effects found in Table 1 appear to derive mainly from the 1991–2000 period (in this subperiod, all significant variables in Table 1 except the share of Dutch-language plays are significant at 5%).
The differences in results for the different specifications of the spatial weight matrix W i are small. For example, the consumer income variable is always positively significant with t-values of 2.14 (defining the relevant market as the municipality in which a given theatre is located), 2.76 (considering the municipality where the theatre is located as well as its geographical neighbours) and 2.51 (when also considering the neighbours’ neighbours), respectively. The population variable is insignificant in all three cases with t-values of .05, .31 and .03, respectively. Finally, R² values are 83.91%, 83.99% and 83.94% for the three specifications, respectively. On the basis of these results, the second specification is preferred.
The positive relationship between cast size and attendance might indicate that theatre companies performing in playhouses with a larger capacity have the ability to stage large-scale productions as well as to attract larger audiences. However, we assume that average capacity remains the same over the studied period and is captured by theatre-specific fixed effects.
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Acknowledgements
The authors wish to thank two anonymous referees as well as Mona Grinwis and John Ashworth for their helpful and incisive comments.
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Werck, K., Heyndels, B. Programmatic choices and the demand for theatre: the case of Flemish theatres. J Cult Econ 31, 25–41 (2007). https://doi.org/10.1007/s10824-006-9026-3
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DOI: https://doi.org/10.1007/s10824-006-9026-3