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The efficiency of theatres in Finland Seppo Suominen, Haaga-Helia University of Applied Sciences, Helsinki, Finland.

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Presentation on theme: "The efficiency of theatres in Finland Seppo Suominen, Haaga-Helia University of Applied Sciences, Helsinki, Finland."— Presentation transcript:

1 The efficiency of theatres in Finland Seppo Suominen, Haaga-Helia University of Applied Sciences, Helsinki, Finland

2 State subsidy system The state subsidy to the dramatic art had been discretionary until 1993 and mainly financed by profit funds of the pools and money lotteries Since the beginning of 1993 the Ministry of Education has made theatre- specific decisions on state subsidies. The basic principle in the state subsidy system (VOS) is that a theatre receives subsidies on the grounds of unit cost based on full time equivalent (FTE) person years. In 1993 the number of theatres in this state subsidy system was 53 in Finland. ACEI Montreal 2014 n 2

3  Also the municipalities support the above mentioned institutions  According to the ownership, the theatres can be classified into full municipal theatres (11) and private theatres.  In practice this means that the income share of state and municipal subsidies was 25 % and 43 % for theatres excluding the National Theatre and the National Opera  The state subsidy system can be justified by the Baumol’s cost disease  Since the share of public subsidies is so big, it is important that these cultural institutions and groups should pursue efficiency and respect high quality and cultural diversity. ACEI Montreal 2014 3

4 The measurement of the achievement  The measurement of the achievement of the cultural institutions is complicated by the presence of goals of different nature.  The principal objectives and obligations set to the VOS-theatres are related to regular presentation activity, to spectator number and to the number of premieres or performances  Two approaches have been used.  A non-parametric technique data envelopment analysis (DEA) is useful since there is no need to explicitly specify a mathematical form for the production function.  The statistical approach has two main routes both assuming some functional form for the production relationship: Cobb-Douglas or translog ACEI Montreal 2014 4

5  5

6  6

7 Data  ACEI Montreal 2014 7

8  The dependent variable, -lnx Kit is the logarithm of the number of the actors with negative sign ACEI Montreal 2014 n 8

9 Variable (all in logarithmic) / parameter Fixed effects Random effects True random effects; 50 Halton draws Fixed effects Random effects (with two restrictions) y1 = Tickets sold / β y1 -2.11 (0.194)*** -1.65 (0.446)*** -1.62 (0.242)*** -1.99 (0.197)*** -1.57 (0.475)*** y1 2 / β y1y1 0.0855 (0.0135)*** 0.0644 (0.0205)** 0.0639 (0.0118)*** 0.101 (0.0141)*** 0.0801 (0.0220)*** x2 = Other staff/actors / β 2 0.321 (0.152)* 0.242 (0.188) 0.248 (0.115)* 0.391 (0.154)* 0.311 x2 2 / β 22 -0.0366 (0.00222)*** -0.0364 (0.00440)*** -0.0329 (0.00198)*** -0.0406 (0.00269)*** -0.0400 x3 = seat capacity/actors / β 3 -0.135 (0.270) -0.0403 (0.609) -0.0683 (0.300) 0.717 (0.289)* 0.689 (0.258)*** x3 2 / β 33 -0.0557 (0.0320) (*) -0.0465 (0.0419) -0.0556 (0.0203)** 0.0222 (0.0357) 0.0328 (0.0218) x2x3 / β 23 -0.0484 (0.0133)*** -0.0436 (0.0241) (*) -0.0129 (0.0176) 0.00695 (0.0141) 0.00722 (0.0238) y1x2 / γ 12 -0.0341 (0.0145)* -0.0275 (0.0196) -0.0331 (0.0108)** -0.0560 (0.0150)*** -0.0478 (0.0221)* y1x3 / γ 13 0.0931 (0.0302)** 0.0761 (0.0510) 0.0727 (0.0271)** -0.0510 (0.0227) -0.0550 (0.0217)* average ticket price / µ 1 -0.160 (0.0282)*** -0.155 (0.0621)* -0.215 (0.0220)*** -0.183 (0.0292)*** -0.180 (0.0609)** net incomes / µ 2 -0.0500 (0.0813) -0.00874 (0.205) -0.100 (0.0779) -0.151 (0.0813) (*) -0.0969 (0.211) constant 7.15 (3.72) (*) 7.54 (1.661)*** 6.72 (3.66) (*) 7.784 (1.405)*** 6.306 (2.921)* 1.486 (0.456)** 6.986 (1.122)*** 5.743 (2.792)* Wald test: β 2 + β 3 = 1χ 2 =18.93***χ 2 =1.40 Wald test: β 2 + β 3 = 1 & β 22 + β 33 + β 23 = 0; χ 2 =2.17 Restricted: β 2 + β 3 = 1 Wald test: β 22 + β 33 + β 23 = 0 χ 2 =14.37***χ 2 =7.39** Restricted: β 22 + β 33 + β 23 = 0 Wald test: γ 12 + γ 13 = 0χ 2 =2.63χ 2 =0.67 ACEI Montreal 2014 9

10 Variable (all in logarithmic) / parameter Fixed effects Random effects True random effects; 50 Halton draws Random effects (with restrictions) y2 = Repertoire/ β y1 -0.618 (0.183)*** -0.700 (0.379) (*) -0.540 (0.244)* 0.522 (0.448) y2 2 / β y1y1 0.0506 (0.0291) (*) 0.0718 (0.0664) 0.0745 (0.0348)* 0.112 (0.0991) x2 = Other staff/actors / β 2 0.0394 (0.0529) 0.0486 (0.0957) 0.0593 (0.0681) -0.0524 (0.0993) x2 2 / β 22 -0.0495 (0.00231)*** -0.0490 (0.00661)*** -0.0404 (0.00311)*** -0.0445 (0.00783)*** x3 = seat capacity/actors / β 3 0.272 (0.209) 0.188 (0.451) 0.340 (0.245) 1.052 (0.00994)*** x3 2 / β 33 -0.0276 (0.0297) -0.0180 (0.0556) -0.0377 (0.0280) -0.0634 (0.0109)*** x2x3 / β 23 -0.0192 (0.0108) (*) -0.0184 (0.0220) -0.00297 (0.0180) 0.108 (0.0133)*** y2x2 / γ 22 -0.0821 (0.0136)*** -0.0891 (0.0410)* -0.0899 (0.0177)*** -0.0162 (0.0500)*** y2x3 / γ 23 0.159 (0.0375)*** 0.170 (0.0912) (*) 0.115 (0.00559)* -0.237 (0.0499)*** average ticket price / µ 1 -0.175 (0.0307)*** -0.175 (0.0744)* -0.232 (0.0239)*** -0.116 (0.101) net incomes / µ 2 0.196 (0.043)*** 0.115 (0.229) 0.0529 (0.0877) -0.0586 (0.257) constant -2.55 (2.58) -2.76 (1.02)** -3.04 (2.57) 7.976 (1.423)*** 6.398 (2.398)** 1.085 (0.528)* 10.695 (16.23) Wald test: β 2 + β 3 = 1χ 2 =13.95***χ 2 =3.53 (*) Restricted: β 2 + β 3 = 1 Wald test: β 22 + β 33 + β 23 = 0χ 2 =12.46***χ 2 =2.27 Restricted: β 22 + β 33 + β 23 = 0 Wald test: γ 12 + γ 13 = 0χ 2 =0.17χ 2 =1.08 ACEI Montreal 2014 10

11 Variable (all in logarithmic) / parameter Fixed effects Random effects True random effects; 50 Halton draws y1 = Tickets sold / β y1 -1.987 (0.235)*** -1.428 (0.703)* -1.480 (0.325)*** y1 2 / β y1y1 0.294 (0.354) 0.0341 (0.700) 0.0612 (0.0173)*** y2 = Repertoire/ β y1 0.0761 (0.0177)** * 0.0515 (0.0413) 0.405 (0.298) y2 2 / β y1y1 0.0401 (0.0450) 0.0676 (0.0945) 0.0680 (0.0374) (*) y1y2 / β y1y2 -0.0457 (0.0474) -0.0426 (0.0801) -0.0667 (0.0345) (*) x2 = Other staff/actors / β 2 0.0900 (0.146) -0.0208 (0.499) -0.0380 (0.137) x2 2 / β 22 -0.0411 (0.00295)* ** -0.0410 (0.00665)*** -0.0367 (0.00304)*** x3 = seat capacity/acto rs / β 3 -0.686 (0.284)* -0.576 (0.889) 0.0145 (0.317) x3 2 / β 33 -0.0243 (0.0343) -0.0131 (0.0750) -0.0516 (0.0266) (*) x2x3 / β 23 -0.0451 (0.0123)** * -0.0378 (0.0273) -0.0180 (0.0172) y1x2 / γ 12 0.0102 (0.0174) 0.0212 (0.0552) 0.0171 (0.0144) y1x3 / γ 13 0.117 (0.0333)** * 0.0893 (0.0670) 0.0541 (0.0344) y2x2 / γ 22 -0.103 (0.0217)** * -0.111 (0.0554)* -0.0960 (0.0185)*** y2x3 / γ 23 0.0494 (0.0505) 0.0964 (0.118) 0.0419 (0.0573) average ticket price / µ 1 -0.183 (0.0313)** * -0.189 (0.0810)* -0.285 (0.0248)*** net incomes / µ 2 0.0343 (0.0908) 0.0280 (0.219) -0.0269 (0.0839) constant 6.714 (4.602) 6.218 (1.827)*** 7.412 (1.548)*** 6.023 (2.522)* 1.533 (0.526)** ACEI Montreal 2014 11

12 random, yfixed, ytrue r, yrandom, y2fixed, y2true r, y2random yy2fixed, yy2true r, yy2 random, y1-0.0300.1620.878**0.0350.2110.961**-0.1030.193 fixed, y 10.616**0.1170.938**0.852**0.0760.921**0.746** true r, y 10.2240.616**0.678**0.2420.610**0.646** random, y2 10.1770.318*0.945**-0.1030.193 fixed, y2 10.919**0.1370.929**0.786** true r, y2 10.314*0.878**0.863** random yy2 1-0.0080.320* fixed, yy2 10.784** true r, yy2 1 ACEI Montreal 2014 12

13 DEA input and output oriented variable, constant and nonconstant returns to scale output = y and y2 VRS, i VRS, o CRS, i CRS, o NRS, i NRS, o Minimum 0.778 0.270 0.258 0.267 Maximum 1 1 1 1 1 1 Mean 0.945 0.823 0.755 0.761 ACEI Montreal 2014 13

14 Conclusion  The results indicate that theatre attendance measured by tickets sold and the versatility of the programme measured by the number of different plays give similar efficiency ranking among the speech theatres in Finland during a five year period 2006/07 – 2010/11.  Municipalities and state are subsidizing theatres but the financial aid does not have any effect on the efficiency. The results are not shown here.  The number of administrative and technical staff in relation to the number of actors does not seem to be significant in explaining efficiency. An important finding is that the average ticket price has an impact on efficiency.  One of the findings here is that Finnish speech theatres are on average not technically efficient since the mean efficiency score is ranging from 60 to 70 per cent depending on the SFA model used ACEI Montreal 2014 14

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