the demand for creative arts in regional victoria, australia

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The demand for creative arts in regional Victoria,AustraliaTristan Masters a , Roslyn Russell a & Robert Brooks ba Department of Finance and Marketing , School of Economics, RMIT University , GPO Box2476V, Melbourne, VIC 3001, Australiab Department of Econometrics and Business Statistics , Monash University , PO Box 1071,Narre Warren, VIC 3805, AustraliaPublished online: 03 Jun 2009.

To cite this article: Tristan Masters , Roslyn Russell & Robert Brooks (2011) The demand for creative arts in regional Victoria,Australia, Applied Economics, 43:5, 619-629, DOI: 10.1080/00036840802584976

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Applied Economics, 2011, 43, 619–629

The demand for creative arts in

regional Victoria, Australia

Tristan Mastersa, Roslyn Russella,* and Robert Brooksb

aDepartment of Finance and Marketing, School of Economics,

RMIT University, GPO Box 2476V, Melbourne,

VIC 3001, AustraliabDepartment of Econometrics and Business Statistics,

Monash University, PO Box 1071, Narre Warren,

VIC 3805, Australia

A healthy creative arts industry can contribute significantly to the

economic and social fabric of a community. Unfortunately, regional

areas often suffer from a lack of supply and demand for the creative arts.

This article explores the demand for the creative arts in three regional

locations in Victoria, Australia, using three broad dimensions of demand:

attitudes towards the arts; frequency of participation in the arts and level

of expenditure on the arts. The analysis of demand patterns uses the

general modelling approach of Levy-Garboua and Montmarquette (1996)

as a basis and makes use of the ordered probit class of models for its

statistical analysis. The study confirms that individual levels of demand are

contingent on a range of demographic characteristics and also identifies

factors such as festival attendance and increased past creative arts

expenditure as being important determinants of demand for the arts.

I. Introduction

A significant volume of recent literature describes

the benefits proffered by creative industries to

towns and cities (see inter alia Landry and

Bianchini, 1995; Scott, 1997; Landry, 2000; Beyers,

2002; Florida, 2002). Throsby (2001) identifies that

such benefits can be direct or indirect in nature, and

range from increased employment (Beyers, 2002) to

urban revitalization (Throsby, 2001). Moreover,

such ‘creative cities’ are employing the arts as

a lever which promote and sustain the creative and

innovative nature of other industry sectors

(Wood, 1999). The literature suggests that creative

individuals are traditionally drawn to communities

which stimulate creativity and promote diversity

(Florida, 2002).

Markusen (2006) provides a critique of the analysis

of the creative class in Florida (2002). She argues that

many of the occupations that make up the creative

class as defined in Florida (2002) are clustered

together on the basis of educational attainment and

not creativity per se. McGranahan and Wojan (2007)

also refine the definition of the creative class used by

Florida (2002). When they focus their definition on

excluding those occupations with a low-creativity

requirement they find a stronger relationship between

the presence of the revised creative class and regional

economic growth.Markusen (2006) then focuses her analysis on

a demonstrably creative subset of the set of occupa-

tions in the creative class, specifically artists.

Markusen (2006) argues that artists provide a boost

to regional growth via providing local consumption

*Corresponding author. E-mail: [email protected]

Applied Economics ISSN 0003–6846 print/ISSN 1466–4283 online � 2011 Taylor & Francis 619http://www.informaworld.com

DOI: 10.1080/00036840802584976

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opportunities for local residents and exports ofartistic goods and services to nonresidents.Markusen and Schrock (2006) also argue that artistsprovide a significant boost to regional economicactivity. Using data on an occupational basis, theyfind evidence of a significant artistic dividend acrossa range of the US cities and regions.

Markusen (2006) discusses that the locationdecisions of artists are a function of their preferences,local efforts to facilitate artists’ livelihoods andconcentrations of artist employing industries. In theAustralian context Throsby and Hollister (2003) notethat because infrastructure is largely based in capitalcities, and that more employment opportunitiesexist in capital cities, a significantly higher concentra-tion of arts professionals live in such an urbanenvironment. A total of 73% of Australian artistslive in Australia’s capital cities, 13% live in a regionaltown or city, 9% live in a semi-rural setting andthe remaining 5% live in a rural or remote location.This represents a more significant difference whencompared to statistics regarding the labour forcemore broadly, which shows 64% of Australia’sworkforce to be living in capital cities, with theremaining 36% living in a regional, rural or remotelocation. State-based figures from Victoria suggestthat, of those employed in cultural industries 82%were from Melbourne, compared to 18% from therest of Victoria (Australian Bureau of Statistics(ABS), 1998).

This article explores the potential role of the artsin rural and regional Victoria through an analysisof the demand for the creative arts in three locationsin rural and regional Victoria. In addition todemonstrating empirical results regarding demanddrivers for creative arts in a regional Australiancontext, this article adds to the extant literature whichhas regard to understanding audience characteristicsfor creative art events and artforms. The study ofdemand for arts in this article explores three broaddimensions of demand: (i) attitudes towards the arts;(ii) frequency of participation in the arts and (iii) levelof expenditure on the arts. Our analysis of demandpatterns uses the general modelling approach ofLevy-Garboua and Montmarquette (1996) as itsbase, and makes use of the ordered probit class ofmodels for its statistical analysis. Ordered probitanalysis is seen to be a robust and versatile statisticaltest, which has had broad application from monetarypolicy (Gascoigne and Turner, 2004) and analysis ofsovereign debt ratings (Afonso et al., 2009) to analysethe characteristics of renters and buyers of videotapemovies in Spain (Collins et al., 2009).

The plan of this article is as follows. Section IIprovides details of the survey data collection.

Section III outlines the modelling approach.Section IV presents the results of empiricalanalysis. Section V concludes this article.

II. Data Collection

Data was collected using a self-complete survey sentto randomly selected households in the threetarget regions and completed by a representativefrom each household. In addition to key demographicdata, this survey instrument was designed to extractinformation relating to attitudes, frequency ofparticipation and expenditure relating to arts andculture.

Data collection took place in households acrosseach of the three target regions selected forinclusion in this study, namely the East Gippsland,Shepparton and Mildura regions of Victoria. Thesethree areas were selected to broadly represent thecurrent arts environment of regional Victoria, interms of their geographical position, size and othercharacteristics, which are presented in the summarybelow (Table 1).

In relation to attitudes towards the arts, a three-point attitudinal scale (‘agree’, ‘neutral’ or ‘disagree’)was used to measure response to eight statementsregarding general attitudes towards arts andculture, as well as more specific questionsrelating to perceived benefits of the arts to the localregional economy, and other perceived impactson the community. The measurement of attitudes isused in the analysis of cultural values by Choiet al. (2007).

Data was collected regarding frequency of partici-pation in a range of art forms and events using a five-point scale (‘never’, ‘once a year or less’, ‘every sooften’, ‘once a month’ and ‘once a week or more’).The survey included a broad range of arts andcultural products which was felt to be broadlyreflective of the arts and cultural programs of thethree selected regions.

Respondents were also asked to answer questionsregarding their average monthly expenditure on artproducts. Again, data were collected on a range ofarts and cultural products from magazines andcinema admission to visual arts and musical perfor-mances or ‘take home’ items such as craft products orpaintings. Finally, survey participants were askedwhether they had attended an arts or cultural festivalin the preceding 2 years, and if so were asked tonominate the festival which they attended.

The survey was mailed to a total of 2500 house-holds (833 in each target region). A target response

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rate of 20% was used as a guide for estimating the

total number of surveys to be administered.1 A total

of 492 completed questionnaires were returned from

across the three regional sites. As a total percentage

of the 2500 which were mailed, this represents

a response rate of 19.7%. This response rate is

comparable to the rate obtained by Choi et al. (2007)

in their survey of cultural values in Australia.

III. Modelling Approach

Our analysis of demand patterns uses the general

modelling approach of Levy-Garboua and

Montmarquette (1996) as its starting point. Levy-

Garboua and Montmarquette (1996) analyse the

demand for theatre attendance at the individual

level. They model the demand for theatre attendance

in both static (unconditional) and dynamic (condi-

tional) choice settings. Their model allows the

individual’s demand for theatre to develop over

time based on the increment (either a positive or

negative surprise) associated with each new play they

attend. This extends their analysis to a conditional

choice setting that requires an appropriate selectivity

correction to be made prior to estimation. Levy-

Garboua and Montmarquette (1996) then model the

probability of attendance using a probit model, and

the frequency of attendance using either an OLS or

Tobit specification.Prieto-Rodrıguez and Fernandez-Blanco (2000) use

the static formulation of the modelling approach

in Levy-Garboua and Montmarquette (1996) to

explore preferences for classical and popular music

in Spain. Prieto-Rodrıguez and Fernandez-Blanco

(2000) utilize a bivariate probit model in which they

simultaneously estimate the preference for popular

and classical music in separate equations. Prieto-

Rodrıguez and Fernandez-Blanco (2000) then use the

cross-equation correlation to determine if there are

common characteristics across classical and popular

music listeners. They find a significant correlation

thus indicating a taste for music of both styles.Favaro and Frateschi (2007) extend the analysis in

Prieto-Rodrıguez and Fernandez-Blanco (2000) to

study the demand for different styles of music in

Italy. Unlike the two equation framework in Prieto-

Rodrıguez and Fernandez-Blanco (2000), the empiri-

cal modelling approach adopted by Favaro and

Frateschi (2007) is to use an expanded choice set in

a multinomial logit model. Favaro and Frateschi

(2007) define the alternatives in their choice set to

allow choices with a preference for neither of the

musical styles, one of the musical styles or both of the

musical styles. This allows explicit modelling to

distinguish between individuals with a univorous

musical preference, as distinct from those individuals

Table 1. Summary statistics of target regions

City of GreaterSheppartona

Shire of EastGippslandb

Rural Cityof Mildurac

Population (2004) (#) 59 907 40 746 51 162Pop. Density (people/km2) 24.8 2.0 2.3Distance from capital (km) 180 277 550Remoteness classification Inner Regional 93.5% Outer Regional 98.3% Outer Regional

6.5% Remote 1.8% RemoteIndigenous population (%) 2.8 2.9 2.4Average income (2004) (A$) 34 006 32 566 32 503Unemployment at 30/09/2004 (%) 5.2 7.5 8.7Annual value of agriculture (A$million) 411.9 127.7 524.9Residents with post-school qualification (%) 38.1 41.7 36.3

Notes: aThe National Regional Profile data presented here refers to the Local Government Area of the City of GreaterShepparton. ABS (2006a) catalogue number 1379.0.55.001.bThe National Regional Profile data presented here refers to the Local Government Area of the East Gippsland Shire. ABS(2006b) catalogue number 1379.0.55.001.cThe National Regional Profile data presented here refers to the Local Government Area of the Mildura Rural City. ABS(2006c) catalogue number 1379.0.55.001.

1While clearly a mail-out survey creates challenges in terms of both time and financial cost, an online survey may not havereached a representative sample of the target populations, based on the fact that ABS data suggests that only 57% ofVictorian households had home Internet access in 2004–2005, and only 51% in ex-metropolitan areas of Australia(ABS, 2005).

Demand for creative arts in regional Victoria, Australia 621

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with an omnivorous musical preference. They findthat age, gender and education are significantpredictors of an omnivorous musical taste, and alsosignificantly affect the probability of attendingconcerts.

Borgonovi (2004) analyses the impacts of artseducation, prices and standard socioeconomic andsocio-demographic characteristics on both the deci-sion to participate in particular artistic events, and thelevel of attendance at such events. Borgonovi (2004)models the participation decision using a binary logitmodel, and the level of attendance using an orderedlogit model. Unlike Borgonovi (2004) we cannotmodel the impacts of price effects as we do not haveprice data in our dataset, although the findings inBorgonovi (2004) suggest that price is not a significantdeterminant of participation. Borgonovi (2004) findseducational attainment to be positively associatedwith participation and attendance. Borgonovi (2004)finds only moderate evidence of income effects.

We follow the general approach of these papers toexplore the demand for creative arts in rural andregional Victoria. The data collected as outlined inSection II is ordered response data on attitudes,frequency of participation and expenditure levels.Thus, we make use of the ordered probit modelestimated in Stata (Data analysis and statisticalsoftware) to model our data. The use of an orderedresponse model is consistent with the approachdemonstrated in other papers where our broadmodelling approach has been adopted.

An ordered probit model was used to analyse theeffects of demographic characteristics on attitudes,expenditure and the frequency of participation in thearts with the following determinants: gender, incomeand festival attendance. A number of dummyvariables were established to test the effects of age,employment status, highest level of education andplace of residence on demand for the arts: age (35–44,45–54, 55–64, 65þ years), work (full time, casual/part-time); education (partial completion of school,Technical and Further Education (TAFE), universitydegree, postgraduate degree) and location (GreaterShepparton, East Gippsland).

Each of the questions relating to attitude, fre-quency of participation and expenditure in the artsproduced an ordered dependent variable that wasanalysed using this model, and the parameterestimates, p-values and the associated marginaleffects were calculated in each case. The marginaleffects can be calculated for each category in thechoice set of the dependent variable that is beingmodelled. In the case of the data on attitudes towardsthe arts, data was coded into three responsecategories as follows: (1)¼Agree; (2)¼Neutral;

(3)¼Disagree, thus requiring the calculation ofthree marginal effects for each explanatory variable.In the case of the data describing how often surveyrespondents participate in the arts, responses werecoded into the following categories: (0)¼Never;(1)¼Once a year or less; (2)¼Every so often; and(3)¼Once a month or more, thus requiring thecalculation of three marginal effects for each expla-natory variable. Finally, regarding typical monthlyexpenditure levels on the arts, responses in eachcategory were coded into the following categories:(0)¼ $0 per month; (1)¼ $1–$10 per month;(2)¼ $11–$20 per month; (3)¼ $21–$30 per month;and (4)¼ $31 or more per month, thus requiringthe calculation of four marginal effects for eachexplanatory variable.

Consequently, the results from the ordered probitinclude parameter estimates and p-values as well asthe marginal effects in each case, and as such are vast.Rather than presenting such a large number of tables,the following section presents the analysis of theresults for a selection of dependent variables in eachcase. The aim of this analysis was to identifydemographic characteristics that generate significantresults in terms of attitude, frequency of participa-tion, or expenditure in the arts. In each case, a sampleof the results is presented which demonstrate thesignificant trends in the data.

IV. Results

In the first instance, results from three of theattitudinal questions are analysed. Table 2 presentsthe results for attitudinal responses to the statement‘attending arts events is a good way to socialize withpeople in the community’, and reports the parameterestimates and associated p-values in column 2, andthe marginal effects and associated p-values incolumns 3–5. Where significant p-values below 0.05resulted, these are shown in bold. The ordered probitresults show that gender and festival attendance aresignificant, and the variables ‘aged 45–54 years’;‘aged 65þ years’; and ‘partial completion of school’are all close to being significant. In the threeestimations of marginal effects, female respondents,those aged 65 years and older, and those whoattended a festival are significantly more likely toagree with the statement, and less likely to givea neutral response or disagree. Respondents aged45–54 years are significantly more likely to agree,and less likely to disagree.

The results in Table 3 relate to the attitudinalstatement ‘going to arts events is a waste of money’.


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Table 3 shows that the p-values of gender, festival

attendance and the variable ‘aged 55–64 years’ are

significant in the probit estimation. The marginal

effects results show that females, those who had

attended a festival, and those aged 55–64 years were

significantly more likely to disagree with the state-

ment, and significantly less likely to agree or give

a neutral response. These are similar findings to those

reported in Table 2.The final attitudinal results to be analysed relate to

the survey statement: ‘the arts should be more of

a priority for local government and the community’.

Table 4 presents these results, including parameter

estimates, marginal effects, and p-values in each case.

As was the case in the previous set of results, Table 4

shows significant results from the probit estimation

for the variables ‘gender’, ‘festival attendance’, and

‘aged 55–64 years’. In addition, those aged 65 years

and older, those with partial school completion as

their highest educational level, and the two regional

dummies ‘Greater Shepparton’ and ‘East Gippsland’

show significant p-values. Females, those who had

attended a festival, those aged 55–64 years, and

respondents from both regions are significantly more

likely to agree with the statement, and significantly

less likely to give a neutral response or disagree.

Similarly, those aged 65 years and older are

significantly more likely to agree, and less likely to

disagree, although the effects of a neutral response

are not significant. Those respondents whose highest

qualification is partial school completion are sign-

ificantly less likely to agree, and more likely to be

‘neutral’. The results also show these respondents to

be close to being significantly more likely to disagree.Results from the selected sample of attitudinal

demand responses lead to the conclusion that age,

gender and festival attendance are all variables which

lead to significant attitudinal results in the ordered

probit model and when the marginal effects in each

response category were estimated. The results show

Table 2. Attitude 1 – arts participation is a social connector – significant results

ProbitMarginal effects

Variable results Agree Neutral Disagree

Gender �0.577 (0.000) 0.203 (0.000) �0.158 (0.000) �0.045 (0.003)Aged 45–54 – 0.136 (0.048) – �0.024 (0.047)

Aged 65þ – 0.153 (0.042) �0.127 (0.049) �0.026 (0.036)

Festival attendance(y/n)

�0.615 (0.000) 0.213 (0.000) �0.168 (0.000) �0.046 (0.001)

Table 3. Attitude 2 – cultural expenditure is a waste of money – significant results



Gender 0.488 (0.002) �0.045 (0.010) �0.102 (0.003) 0.148 (0.003)

Aged 55–64 0.579 (0.034) �0.038 (0.014) �0.110 (0.017) 0.148 (0.013)

Festival attendance (y/n) 0.614 (0.000) �0.056 (0.001) �0.127 (0.000) 0.182 (0.000)

Table 4. Attitude 3 – arts should be more of a priority – significant results



Gender �0.448 (0.001) 0.171 (0.001) �0.065 (0.001) �0.106 (0.001)

Aged 45–54 – – – �0.080 (0.036)

Aged 55–64 �0.718 (0.001) 0.280 (0.001) �0.149 (0.005) �0.132 (0.000)Aged 65þ �0.470 (0.047) 0.185 (0.046) – �0.092 (0.021)

Festival attendance (y/n) �0.610 (0.000) 0.232 (0.000) �0.090 (0.000) �0.142 (0.000)

Partial school 0.318 (0.039) �0.121 (0.033) 0.043 (0.017) –Greater Shepparton �0.345 (0.015) 0.135 (0.015) �0.062 (0.029) �0.073 (0.011)

East Gippsland �0.399 (0.008) 0.156 (0.008) �0.073 (0.020) �0.083 (0.005)


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significantly positive attitudes towards the arts byfemales and festival attendees, while the generalpattern appears to be that middle aged and olderrespondents (‘45–54’, ‘55–64’ and ‘65þ’ years) viewcreative arts more positively. Bihagen and Katz-Gerro (2000) find differences in cultural consumptionbetween men and women in Sweden with womenbeing more active in highbrow cultural activities, andmen being more active in lowbrow cultural activities.Lizardo (2006) notes that this finding of greaterparticipation by women in highbrow cultural activ-ities to be one of the most consistent empiricalfindings of the literature in this area and thenproceeds to explore a number of possible theoreticalexplanations, including labour force participation,socialization and cultural norms, which are seen toinfluence engagement with highbrow activities amongmen and women. We reach a similar finding ongender effects to that of the previous literature. Thesignificance of the festival attendance variable in partsuggests the importance of previous consumptionbehaviour along the lines of the Levy-Garboua andMontmarquette (1996) model. In addition, artsfestivals are also found to play an economic devel-opment role in the work of Jackson et al. (2005) andDwyer et al. (2005), while Gapinski (1988) exploresthe volume of demand for ‘lively arts’ in Londonwhich can be attributed to tourism.

Having briefly discussed a selection of attitudinalresults from the ordered response model, this articlenow outlines the results of ordered probit estimationand the corresponding marginal effects relating tofrequency of participation in the arts in three areas.Table 5 reports the results of frequency of visitationto an art gallery. The parameter estimates and theirassociated p-values (in parentheses) are presented incolumn two, while the marginal effects and theirassociated p-values are then reported in columns 3–6for each of the four ordered response categories.Where the coefficient estimate or marginal effect issignificant below the 0.05 level the results arepresented in bold. The results in Table 5 show that

gender, the variable measuring festival attendance,those aged 45–54, 55–64 and 65 years or older, inaddition to those who reported partial completion ofschool as being their highest level of education are allstatistically significant in the ordered probit estima-tion. The marginal effects demonstrate that females,those who had attended a festival in the past twoyears, those aged 55–64 and 65 years or older were allsignificantly less likely to attend a gallery ‘never’ or‘once a year or less, and more likely to attend ‘everyso often’ or ‘once a month or more’. The resultsdemonstrate a similar effect among those respondentsaged 45–54 years, however the results in the category‘once a month or more’ (0.058), although close tobeing significant, were above the 0.05 level.In contrast, the significant results among those witha partial school qualification show that this group issignificantly more likely to either never attend an artgallery, or attend ‘once a year or less’. The negativecoefficients and significant values also show thisgroup to be significantly less likely to attend ‘every sooften’ or ‘once a month or more’.

Table 6 presents the results for attendance rates ata theatre performance. The ordered probit results forattendance at a theatre performance show gender andfestival attendance to be significant with females andfestival attendees significantly more likely to attendin the two most frequent categories ‘once a month ormore’ and ‘every so often’, while being significantlyless likely to never attend, or to attend ‘once a year orless’. The variable ‘partial school’ is significant, andshows that conversely, those who reported theirhighest qualification to be partial completion ofschool are more likely to never attend, or attend‘once a year or less’, while being less likely to attend‘every so often’ or ‘once a month or more’. ‘Aged55–64’ and ‘65þ’ years are significant variables, withrespondents in this group shown as being signifi-cantly more likely to attend the theatre ‘every sooften’. These same two groups show negativelysignificant results in the two least frequent categories,indicating that respondents in these age brackets are

Table 5. Frequency of art gallery visitation – significant results


Variable results Never 1þ year or less Every so often 1þ month or more

Gender 0.363 (0.005) �0.088 (0.007) �0.048 (0.006) 0.116 (0.005) 0.019 (0.013)Aged 45–54 0.522 (0.010) �0.107 (0.004) �0.095 (0.030) 0.164 (0.007) –Aged 55–64 0.715 (0.001) �0.137 (0.000) �0.141 (0.006) 0.217 (0.000) 0.060 (0.026)

Aged 65þ 0.794 (0.001) �0.144 (0.000) �0.163 (0.005) 0.235 (0.000) 0.073 (0.031)

Festival attendance(y/n)

0.826 (0.000) �0.198 (0.000) �0.106 (0.000) 0.256 (0.000) 0.048 (0.000)

Partial school �0.524 (0.001) 0.137 (0.002) 0.052 (0.000) �0.165 (0.000) �0.024 (0.003)


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less likely to never attend the theatre or attend ‘once

a year or less’. Similar results are observable for those

respondents aged 45–54 years also demonstrating

significant results from the probit estimations,

although in this case the marginal effects for the

category ‘once a year or less’ (0.059), although close

to being significant, were not below 0.05. Finally, the

variable ‘postgraduate’ was significant, with respon-

dents who reported a postgraduate qualification as

their highest level of education significantly more

likely to attend ‘once a year or less’, and significantly

less likely to attend ‘every so often’ or ‘once a month

or more’.The final set of results selected to demonstrate

trends in the data influencing attendance or partici-

pation behaviour in the arts relates to ballet and

opera performances. As Table 7 below shows, none

of the demographic variables generated significant

values in every case. This can be explained by no

group being significantly more likely to report

attendance at ballet or opera performances once

per month or more. The results again demonstrate

significant values in the variables ‘festival atten-

dance’, ‘aged 65þ’ years and ‘gender’, with marginal

effects indicating that festival attendees, those aged

65 and older, and females are more likely to attend

ballet or opera ‘every so often’ or ‘once a year or less’

and are significantly less likely to never attend.

The variable ‘partial school’ is again significant,

and respondents who hold this as their highest

qualification appear significantly more likely never

to attend, as well as being significantly less likely to

attend ‘once a year or less’ or ‘every so often’. The

variable ‘aged 55–64 years’ is significant in the probit

estimation, with marginal effects results reporting

a significant likelihood that respondents in this age

bracket will attend the ballet ‘once a year or less’,

while being significantly less likely to never attend.From the selected results presented in terms of

frequency of attendance, a number of demographic

variables appear consistently significant. The ordered

probit estimations of attendance and participation in

a range of arts events and practices shows that

gender, age, and highest educational level of respon-

dents, in addition to whether they have attended

a festival in the past 2 years as being consistently

significant. The most outstanding marginal effects

indicate that females and festival attendees are more

likely to attend or participate in the arts, while those

who completed partial school are consistently likely

to never or seldom attend. With the exception of the

significant results among respondents with postgrad-

uate qualifications who report infrequent attendance

at the theatre, these attendance results are consistent

with the findings in the literature regarding the

composition of arts audiences, and particularly

audiences at theatre, ballet and opera (referred to as

‘high arts’) (Baumol and Bowen, 1966; Kurabayashi

and Ito, 1992; Towse, 1994; Prieto-Rodrıguiez

and Fernandez-Blanco, 2000; Arts Victoria, 2002;

Table 6. Frequency of attendance at a theatre performance – significant results



Gender 0.687 (0.000) �0.169 (0.000) �0.093 (0.000) 0.241 (0.000) 0.020 (0.006)Aged 45–54 0.433 (0.033) �0.089 (0.019) – 0.154 (0.028) –Aged 55–64 0.649 (0.003) �0.123 (0.000) �0.132 (0.009) 0.223 (0.001) –Aged 65þ 0.661 (0.005) �0.123 (0.001) �0.137 (0.016) 0.225 (0.002) –Festival attendance (y/n) 0.797 (0.000) �0.188 (0.000) �0.115 (0.000) 0.278 (0.000) 0.026 (0.003)Partial school �0.481 (0.002) 0.123 (0.004) 0.060 (0.000) �0.171 (0.001) �0.012 (0.016)

Postgraduate �0.535 (0.035) – 0.040 (0.001) �0.185 (0.021) �0.010 (0.020)

Table 7. Frequency of attendance at ballet/opera – significant results



Gender 0.622 (0.000) �0.207 (0.000) 0.116 (0.000) 0.082 (0.000) –Aged 55–64 0.571 (0.023) �0.210 (0.028) 0.101 (0.013) – –Aged 65þ 0.815 (0.003) �0.305 (0.004) 0.130 (0.000) 0.150 (0.016) –Festival attendance (y/n) 0.614 (0.000) �0.208 (0.000) 0.114 (0.000) 0.085 (0.000) –Partial school �0.521 (0.005) 0.168 (0.002) �0.098 (0.005) �0.064 (0.002) –


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Seaman, 2006). Indeed, as Seaman (2005) notes, the

price of leisure is widely accepted by cultural

economists as being important to arts demand, the

lower levels of attendance at theatre by those with

postgraduate qualifications may be linked to

a scarcity of leisure time. Interestingly, however, the

data appears to demonstrate a slight tendency for

older respondents to have higher demand levels for

high arts, which is contrary to the finding in

Kurabayashi and Ito (1992), where younger audi-

ences were generally seen to be greater consumers of

classical music. This could be seen to support the

notion that age, as a factor which influences the level

of arts consumption, is frequently different across

studies, in addition to being an inconsistent determi-

nant of audiences over time (Seaman, 2005).The following set of results show the impact of

demographic variables on typical monthly expendi-

ture in the arts. The first table for this set of results,

Table 8, shows the results of the ordered probit

modelling on book expenditure, including the mar-

ginal effects for each of the expenditure groupings.

Firstly, the variables ‘gender’, ‘aged 55–64 years’,

‘festival attendance’, and ‘university degree’ were all

significant. Marginal effects results demonstrate

that females, festival attendees, those aged 55–64

years and those who have a university degree as

their highest qualification are significantly less

likely to spend either $0 per month or $1–$10 per

month on books, while being significantly more likely

to spend $11–$20, $21–$30 or $31 or more per month

in this category. Income was also significant, and

it can be assumed that those with higher income

levels are more likely to spend $11–$20, $21–$30 or

$31 or more per month, and less likely to spend $0 per

month. Those aged 45–54 years were seen to be

significantly less likely to report zero expenditure, but

significantly more likely to spend $11–$20 and $21–

$30 per month on books. Although not significant in

the probit estimation, those aged 35–44 years were

more likely to spend $11–$20 per month in this

category.The next set of results presented in Table 9 show

the results ordered probit modelling of reported

monthly expenditure on admission to theatre, ballet,

opera or dance performances. The results in Table 9

show that in the case of expenditure on theatre,

ballet, opera or dance among regional Victorian

respondents, the variables ‘gender’, ‘65þ years’ and

‘festival’ were all significant in the probit, as well as

each of the marginal effects. Females, those aged

65 years and older, and those who had attended

a festival were significantly less likely to report zero

expenditure, and significantly more likely to report

spending in each of the other categories. Those

aged 55–64 years, although the variable was not

Table 8. Monthly expenditure levels on books – significant results


Variable results $0/month $1–$10/month $11–$20/month $21–$30/month $31þ/month

Gender 0.313 (0.015) �0.099 (0.017) �0.018 (0.039) 0.040 (0.023) 0.035 (0.019) 0.043 (0.016)Income 0.075 (0.028) �0.023 (0.028) – 0.009 (0.037) 0.009 (0.038) 0.011 (0.032)

Aged 35–44 – – – 0.041 (0.029) – –Aged 45–54 0.436 (0.026) �0.126 (0.016) – 0.048 (0.014) 0.050 (0.032) –Aged 55–64 0.665 (0.001) �0.180 (0.000) �0.079 (0.024) 0.062 (0.000) 0.075 (0.002) 0.121 (0.011)Festival

attendance(y/n)

0.295 (0.012) �0.092 (0.013) �0.019 (0.040) 0.037 (0.018) 0.033 (0.016) 0.042 (0.015)

Uni degree 0.522 (0.002) �0.144 (0.000) �0.059 (0.031) 0.052 (0.000) 0.060 (0.004) 0.091 (0.011)

Table 9. Monthly expenditure levels on theatre, opera, ballet or dance – significant results



Gender 0.540 (0.000) �0.195 (0.000) 0.053 (0.002) 0.053 (0.001) 0.046 (0.001) 0.042 (0.002)

Aged 55–64 – – 0.036 (0.037) – – –Aged 65þ 0.838 (0.002) �0.322 (0.002) 0.051 (0.000) 0.078 (0.001) 0.085 (0.008) 0.108 (0.038)Festival

attendance(y/n)

0.712 (0.000) �0.258 (0.000) 0.067 (0.000) 0.070 (0.000) 0.062 (0.000) 0.060 (0.000)


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significant in the probit estimation, were significantlymore likely to spend $1–$10 per month in thiscategory.

Table 10 presents the final results of the orderedprobit estimation. This table shows the results ofmonthly expenditure on painting, sculpture or craft,referred to as the ‘take-home to own’ arts.In the table above, the variables ‘gender’, ‘festival’and ‘East Gippsland’ are all significant in the probitestimation. The marginal effects results show thatfemales and festival attendees are significantly lesslikely to report zero expenditure in this category,while being significantly more likely to spend $1–$10,$11–$20, $21–$30 and $31 or more per month. EastGippsland survey respondents are likewise shown tobe significantly less likely to spend nothing per monthin this category, and significantly more likely to spend$1–$10 and $11–$20 per month.

With the exception of the consistently significantgender and festival variables, the expenditure resultsappear to demonstrate far less consistent resultsbetween categories. Book expenditure results showincome levels, age, and university degrees to besignificant determinants of expenditure, while in addi-tion to gender and festival attendance, age was signi-ficant in the case of admission expenditure at theatre,ballet, opera and dance performances. Finally, unlikeany of the previous categories, in addition to genderand festival results, inter-regional differences aresignificant in the final category of expenditure onpaintings, sculpture and craft, where East Gippslandrespondents showed higher demand levels.

V. Conclusion

This article has focused upon three measures ofdemand for the arts: attitudes, participation rates andexpenditure levels, and has used a range of statisticaland econometric tests to show demographic trendswhich affect demand. Overall the results of theordered probit analysis revealed that in the case ofattitudes and participation rates, females, festival

attendees and older respondents are more likely tohave the highest demand for the arts, while at theother end of the spectrum those whose highestacademic qualification is partial school completionhave significantly lower levels of demand. The resultsalso demonstrate that expenditure levels are lessconsistent across category, with the exception offestival attendees and female respondents, whoremain the highest consumers. Moreover resultsshow that while festival attendance is seen asa significant determinant of arts demand, this articlehas also shown that the lack of a significant annualarts festival does not diminish community demand,but prompts increases in demand for other artsactivities in the community. The high level of demandfrom festival attendees and those with increasedexpenditure over the past 3 years upholds the‘learning by consuming’ model whereby presentengagement, enjoyment, and consumption in thearts is contingent on past experience (Levy-Garbouaand Montmarquette, 1996; Cameron, 1999; Sisto andZanola, 2008; Yamamura, 2009). It should be noted,however, that the data and analysis did notdetermine the causality between festival attendanceand higher arts demand. In other words, whethertypically high arts consumers are more likely toattend festivals, or whether festival attendancepromotes increased demand for other arts products.Similarly this article did not identify potentialcollinearity between other explanatory variablesincluded in the model, for example the possibleeffect of the relationship between education andincome on the results.

This article has presented an economic model ofdemand for the arts in regional Victorian commu-nities, using a range of statistical and econometricanalysis techniques. Focusing on the results of anordered probit analysis, it has been demonstratedthat residents of regional Victorian communities havegenerally high levels of demand for the arts, and thatindividual levels of demand are contingent on a rangeof demographic characteristics. In creating knowl-edge regarding demand patterns for the arts amongregional Victorians, this article has also identified

Table 10. Monthly expenditure on painting, sculpture, or craft (take home) – significant results



Gender 0.683 (0.000) �0.257 (0.000) 0.054 (0.000) 0.082 (0.000) 0.060 (0.000) 0.061 (0.000)Festival

attendance(y/n)

0.652 (0.000) �0.248 (0.000) 0.049 (0.000) 0.079 (0.000) 0.059 (0.000) 0.061 (0.000)

East Gippsland 0.326 (0.047) �0.128 (0.047) 0.022 (0.034) 0.040 (0.049) – –


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aspects such as festival attendance, increased pastcreative arts expenditure and demographics such asage and gender to be determinants of demand forthe arts. As such this article has also highlighted

circumstances, events and characteristics, whichcultivate higher levels of demand for the arts inregional Victoria, which could be useful in the contextof developing arts policy for regional communities.

In addition to presenting empirical evidence ofsocio-demographic characteristics which affectdemand for creative arts specific to the regionalVictorian context, the results from this articledemonstrate that the regional Victorian arts marketexhibits similar as well as contrasting demandpatterns to other geographically and culturallydivergent international markets.

Acknowledgements

The research in this project was funded by ARCLinkage Grant LP0453477 Demand and Supply ofCreative Arts in Rural and Regional Victoria. Theproject also received financial support from ArtsVictoria. We wish to thank Judy Morton for her

ongoing support of this research project. We alsowish to thank the editor and two anonymousreviewers for their helpful comments on a previousversion of this article.

References

Afonso, A., Gomes, P. and Rother, P. (2009) Orderedresponse models for sovereign debt ratings, AppliedEconomics Letters, 16, 769–73.

Arts Victoria (2002) Small to Medium Performing ArtsAudiences Fact Sheet, Arts Victoria, Melbourne.

Australian Bureau of Statistics (ABS) (1998) The ArtsIndustry in Victoria: A Statistical Overview, ArtsVictoria, Melbourne.

Australian Bureau of Statistics (ABS) (2005)Household Useof Information Technology 2004–05, Australian Bureauof Statistics, Canberra.

Australian Bureau of Statistics (ABS) (2006a) NationalRegional Profile: Greater Shepparton (C) (LocalGovernment Area), Australian Bureau of Statistics,Canberra.

Australian Bureau of Statistics (ABS) (2006b) NationalRegional Profile: East Gippsland (S) (LocalGovernment Area), Australian Bureau of Statistics,Canberra.

Australian Bureau of Statistics (ABS) (2006c) NationalRegional Profile: Mildura (RC) (Local GovernmentArea), Australian Bureau of Statistics, Canberra.

Baumol, W. and Bowen, W. (1966) Performing Arts: TheEconomic Dilemma, Twentieth Century Fund,New York.

Beyers, W. B. (2002) Culture, services and regionaldevelopment, The Service Industries Journal, 22, 4–34.

Bihagen, E. and Katz-Gerro, T. (2000) Culture consump-tion in Sweden: the stability of gender differences,Poetics, 27, 327–49.

Borgonovi, F. (2004) Performing arts attendance: aneconomic approach, Applied Economics, 36, 1871–85.

Cameron, S. (1999) Rational addiction and the demand forcinema, Applied Economics Letters, 6, 617–20.

Choi, A., Papandrea, F. and Bennett, J. (2007) Assessingcultural values: developing an attitudinal scale, Journalof Cultural Economics, 31, 311–35.

Collins, A., Fernandez-Blanco, V. and Prieto-Rodrıguez, J.(2009) Characteristics of buyers and renters of culturalgoods: the case of movies, Applied Economics, 41,195–210.

Dwyer, L., Forsyth, P. and Spurr, R. (2005) Estimating theimpacts of special events on an economy, Journal ofTravel Research, 43, 351–9.

Favaro, D. and Frateschi, C. (2007) A discrete choicemodel of consumption of cultural goods: the case ofmusic, Journal of Cultural Economics, 31, 205–34.

Florida, R. (2002) The Rise of the Creative Class, BasicBooks, New York.

Gapinski, J. H. (1988) Tourism’s contribution to London’slively arts, Applied Economics, 20, 957–68.

Gascoigne, J. and Turner, P. (2004) Asymmetries in bankof England monetary policy, Applied EconomicsLetters, 11, 615–18.

Jackson, J., Houghton, M., Russell, R. and Triandos, P.(2005) Innovations in measuring economic impacts ofregional festivals: a do-it-yourself kit, Journal of TravelResearch, 43, 360–7.

Kurabayashi, Y. and Ito, T. (1992) Socio-economiccharacteristics of audiences for western classicalmusic in Japan: a statistical analysis, in CulturalEconomics (Eds) R. Towse and A. Khakee, SpringerVerlag, Berlin, pp. 257–87.

Landry, C. (2000) The Creative City: A Toolkit for UrbanInnovators, Earthscan, London.

Landry, C. and Bianchini, F. (1995) The Creative City,Demos, London.

Levy-Garboua, L. and Montmarquette, C. (1996)A microeconometric study of theatre demand,Journal of Cultural Economics, 20, 25–50.

Lizardo, O. (2006) The puzzle of women’s ‘highbrow’culture consumption: integrating gender and workinto Bourdieu’s class theory of taste, Poetics, 34,1–23.

Markusen, A. (2006) Urban development and the politicsof a creative class: evidence from a study of artists,Environment and Planning A, 38, 1921–40.

Markusen, A. and Schrock, G. (2006) The artistic dividend:urban artistic specialisation and economic develop-ment implications, Urban Studies, 43, 1661–86.

McGranahan, D. and Wojan, T. (2007) Recasting thecreative class to examine growth processes in rural andurban counties, Regional Studies, 41, 197–216.

Prieto-Rodrıguez, J. and Fernandez-Blanco, V. (2000) Arepopular and classical music listeners the same people?,Journal of Cultural Economics, 24, 147–64.

Scott, A. (1997) The cultural economy of cities,International Journal of Urban and Regional Research,21, 323–39.

Seaman, B. (2005) Attendance and public participation inthe performing arts: a review of the empirical


Dow

nloa

ded

by [

The

Aga

Kha

n U

nive

rsity

] at

01:

49 1

0 O

ctob

er 2

014

literature, Nonprofit Studies Program Working PaperNo. 05-03, Andrew Young School of Policy Studies,Georgia State University.

Seaman, B. (2006) Empirical studies of demand for theperforming arts, in Handbook of the Economics of Artand Culture (Eds) V. Ginsburgh and D. Throsby,Elsevier, North Holland, Amsterdam, pp. 415–72.

Sisto, A. and Zanola, R. (2008) Cinema attendance inEurope, Applied Economics Letters, iFirst, 1–3.

Throsby, D. (2001) Economics and Culture, CambridgeUniversity Press, Cambridge.

Throsby, D. and Hollister, V. (2003) Don’t Give Up YourDay Job: An Economic Study of Professional Artists inAustralia, The Australia Council, Sydney.

Towse, R. (1994) Achieving public policy objectives in thearts and heritage, in Cultural Economics and CulturalPolicies (Eds) A. Peacock and I. Rizzo, KluwerAcademic Publishers, The Netherlands, pp. 143–65.

Wood, P. (1999) Think global act local: lookingforward to the creative region, in paper presentedat The Role of the Creative Industries in Localand Regional Development Conference, GovernmentOffice for Yorkshire and the Humber and theForum on Creative Industries, Manchester.

Yamamura, E. (2009) Rethinking rational addictivebehaviour and demand for cinema: a study usingJapanese panel data, Applied Economics Letters, 16,693–7.


Dow

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by [

The

Aga

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] at

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the demand for creative arts in regional victoria, australia

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