Economic Estimation of Value of Culture

7/30/2019 Economic Estimation of Value of Culture

1/25

ECONOMIC ESTIMATION OF

VALUE OF CULTURE

Andrej SrakarFaculty of Economics

University of Ljubljana


2/25

Plan of presentation

Economic effects of cultural events Methods to estimate economic effects of

culture and their critiques

Ex-post econometric estimation how it isdesigned, what it shows, first results

Value of culture and arguments for public

support to the arts Economic model of non-use values and results

Summary


3/25

Economic effects of cultural events Seaman (2003):

Total impact = Short-run spending impact (SRS) + Long-run growthimpact (LRG) + Consumption impact (C)

SRS: short-run net increases in economic activity, related to the net

injections of new spending into the region as a direct consequenceof the cultural asset Economic Impact Studies (EIM)

LRG: long-run increases in productivity and economic development

linked to the cultural asset Travel-cost method; Hedonic pricing

C: consumer attributed value of the event Contingent valuation

(CVM); Conjoint analysis & Choice experiments

(Big) problem (Seaman 2006): can these effects just be added up?

Arent they overlapping to some extent especially C and SRS?


4/25

Economic impact studies

Key question: 'How much wouldshort-run economic activity decline

in a specific region if X were no

longer to exist?' (Seaman, 2003)

Economic impact studies of art use

economic indicators such asoutput, income, employment,

revenue to local and state

government, to assess the amount

of direct, indirect and inducedimpacts of an art activity

Main method: Keynesian

multipliers (production, value-

added, employment) + ex-ante

analysis


5/25

Economic impact studies EIM gained influence in 1970s as an answer to different after-WW2 problems

(Radich 1993): 1) art as new domain of state support (especially in the US); 2)growth of non-profit art sector; 3) public sector problems; 4) growing

influence of private business sector

Most influential studies - USA: 1977 report, Economic Impacts of Arts and

Cultural Institutions: A Model for Assessment and a Case Study in Baltimore

(Cwi and Lyall); 1983 study, The Arts as an Industry: Their EconomicImportance to the New YorkNew Jersey Metropolitan Region (Port Authority

of New York and New Jersey); Arts and Economic Prosperity I, II, III, IV (2002-

2011, Americans for the Arts)

EIM in Europe: Economy of Culture in Europe (KEA European Affairs 2006),

regional studies (e.g. Denmark, Netherlands, UK, Finland, Latvia, Sweden,Lithuania, Poland, Slovenia); regular studies still being made (e.g. WIPO

national studies)

EIM in Slovenia: Economics of culture (CIC & Peace Institute 2003); Percent for

art (Slovenian Sculpture Association & UMAR 2008); WIPO Slovenian study

(URSIL & Faculty of Economics 2011)


6/25

Economic impact studies number of

problems and critiques Seaman 2003:

1) Spending diversion error: failure to subtract local sources and non-local uses of funds

2) Induced (ancillary spending) base error: attribution of all spending to cultural event

3) Multiplier (indirect impact) error: adapting multipliers to specific regions

4) Supply constraint (crowding-out) error

5) Ex post verification error

6) Policy interpretation (partial vs. general equilibrium) error

Snowball & Antrobus 2006:

7) Defining the area of study

8) Including time switchers and casuals

9) Determining the size of the multiplier

10) Non - including non-market costs and benefits

+ 2 common problems of any input-output study:

11) Homogeneity of products

12) Linear structure of input-output coefficients


7/25

Economic impact studies

final consideration

Seaman (2012): If the marginal value (MV) of

another EIM study was $0 in 1987 (as noted by

Seaman 1987), imagine how negative it must be nowafter thousands of additional studies!

(Of course, even if the social MV is low, the private MV is perceived as

high, so since after the next global extinction event only roaches and EIM willsurvive (and probably CVM too), it is imperative to do such studies well. That

will also increase the SMV above $0 again and can make it a useful policy tool

in conjunction with others.)


8/25

The answer so far:

contingent valuation methodology CVM: A method of estimating the value that individuals attribute to non-

tradable goods or to some characteristics of tradable goods not revealed by

the market mechanism

Consists of asking directly selected samples of population in survey or

experimental settings, what is their willingness-to-pay (WTP) / willingness-to-

accept (WTA) for qualitative and quantitative increments / decreases in non-

marketed goods

CVA (compensating variation): V (p, y CVA, z1) = V (p, y, z0)

EVA (equivalent variation): V (p, y + EVA, z0) = V (p, y, z1)

Turning points for CVM: Exxon Valdez 1989 oil spill, NOAA panel

NOAAs conclusion: that CV studies can produce estimates reliable enough to

be the starting point of a judicial process of damage assessment, including lost

passive-use values. To be acceptable for this purpose, such studies should

follow the proposed guidelines. (Arrow et al., 1993)


9/25

But:

severe problems of contingent valuation methodology

Number of biases and critiques (some of them from Venkatachalam

2004):

- Disparity between WTP and WTA (willingness to accept)

- Embedding or scope effect

- Sequencing

- Information effect

- Elicitation effects

- Hypothetical bias

- Strategic bias

- Benefit transfer

- Microeconomic nature, not addressing the macro economic effects

- Extremely expensive and difficult to perform (they are mostly infeasible

in practice for any cultural organization)


10/25

Contingent valuation

final consideration

Dilemma:

Epstein (2003): The Regrettable Necessity of

Contingent Valuation, Journal of Cultural

Economics

vs.

Diamond & Hausman (1994): Is Some

Number better than No Number?, The

Journal of Economic Perspectives


11/25

Methods to estimate value of culture and their

critiques - CVM vs. EIM in cultural economics

Seaman (2006): CVM and EIM as substitutes /complements

Ibid: sometimes nave, overblown EIM can be bestestimators of true value of the event!

Frey (2005): cultural advocates vs. cultural academics

Stutzer, Luechinger & Frey (2010), Frey (2012): lifesatisfaction approach

Seaman (2012): The existential threat from ex postverification econometric analysis


12/25

A simple solution

ex-post econometric analysis A somewhat different question: How much did the macro-

economic indicators change because of the event?

It is done ex-post, after the event

It uses methodology which suffers from no additionaleconomic problems (overblown results, hypothetical bias,

micro vs. macro focus)

It uses statistical data, measured under common methodology

Results can be compared across events, regions, states It is not expensive and methodologically over-complex

It can be used to study the characteristics that influence the

economic effects of cultural events the most (in positive and

negative manner)

h d i l f l d h i


13/25


critiques - ex-post econometric analysis

A flourishing method in sports economics

Starts: Baade & Dye (1988): Sports Stadiums and Area Development: ACritical View

Some findings Baade & Matheson (2004): Bidding for the Olympics: Fools

Gold?

The increase in economic activity attributable to the 1984 Los AngelesOlympic games, as represented by job growth, an estimated 5,043 full-time

and part-time jobs using our model, appears to have been entirely transitory,

however. There is no economic residue that can be identified once the Games

left town

The job implications for the Los Angeles and Atlanta Summer Olympic Gameswere fundamentally different

Atlanta Olympics created between 3.467 and 21.767 full and part time jobs

Humphreys and Plummer (1995) projected that the Olympics would create

approximately 77,000 new jobs in the State of Georgia with 37,000 of those

materializing in Atlanta.


14/25


critiques - ex-post econometric analysis

Main methods used (and possible to use): Panel data analysis;Treatment/Response analysis (Difference-in-differences;

Instrumental variables); Dynamic Panel, GMM and Time Series

analysis

Seaman (2012): There is a virtual explosion of efforts to identify

empirical tracks in the sand in local employment and tax

revenue data following an event. A similar task might be tried in

Maribor after the year ends to see if econometric equations that

attempt to isolate the unique effect of being a Cultural Capitalreveal both economically and statistically significant unique

effects of this honor. In the sports literature, they almost NEVER

find such effects.


15/25

Ex-post econometric estimation of effects of ECoC

Maribor 2012, first results, tourism visits, all cities pooled

Coefficient t Coefficient t Coefficient t Coefficient t

const 48015,1 4,3292 *** 30369,4 3,5552 *** 144723 4,4548 *** 83410 3,8673 ***

EPK_dummy -14153,1 -0,8476 -7569,06 -0,5865 -65843,1 -1,5112 -32715,5 -1,1006

time_of_treat_ 2853,32 1,9602 * 3263,71 2,2768 ** 3712,62 1,3103 8077,58 3,0317 ***

epk_time_dummy 2212,1 0,448 2407,74 0,5064 7690,63 0,8055 5863,67 0,584

R-squared 0,002832 0,001648 0,006901 0,004102

Adjusted R-square -0,007106 -0,008303 -0,002997 -0,005824

F (3, 301) 0,284998 0,165596 0,697175 0,413226

p value of F 0,836224 0,919506 0,554396 0,743623

Log-Likelihood -3876,75 -3802,062 -4199,57 -4080,577

Akaike 7761,501 7612,124 8407,14 8169,154

Schwartz 7776,382 7627,005 8422,022 8184,035

Hannan-Quinn 7767,453 7618,076 8413,092 8175,106

dependent variable: tevilo

skupnih obiskov


obiskov tujih obiskovalcev


skupnih noitev


noitev tujih turistov


16/25


Maribor 2012, first results, tourism visits, only Maribor

Coefficient t Coefficient t Coefficient t Coefficient t

const 48015,1 4,3292 *** 30369,4 3,5552 *** 144723 4,4548 *** 83410 3,8673 ***

EPK_dummy 43537,2 3,9255 *** 41354,1 4,8411 *** 60504,5 1,8624 * 69842,5 3,2382 ***

time_of_treat_ 2853,32 1,9602 * 3263,71 2,2768 ** 3712,62 1,3103 8077,58 3,0317 ***

epk_time_dummy 27944,4 19,1979 *** 27136,8 18,9308 *** 57388,9 20,255 *** 58201,9 21,8444 ***

R-squared 0,006685 0,010028 0,0018 0,005266

Adjusted R-square -0,004112 -0,000732 -0,00905 -0,005547

F (3, 276) 0,619118 0,931952 0,165894 0,487006

p value of F 0,603152 0,425674 0,919301 0,691579

Log-Likelihood -3568,616 -3499,969 -3865,841 -3756,329

Akaike 7145,233 7007,937 7739,681 7520,657

Schwartz 7159,772 7022,477 7754,221 7535,196

Hannan-Quinn 7151,065 7013,769 7745,513 7526,489


skupnih obiskov


obiskov tujih obiskovalcev


skupnih noitev


noitev tujih turistov


17/25


Maribor 2012, first results

Positive and significant effects on visitors to culturalevents approx. 15.000 new visitors to each public

theatre in the region, approx. 30 new visitors per show

Positive results on incomes on firms, yet only in the city

of Maribor

No effects on monthly wages in any city considered

No (or even possibly negative) effects on new

employment

Strong warning: so far only preliminary results!!

Yet: the results are significantly different from

multiplier/EIM results


18/25

Value of culture Total Economic Value (Peterson & Sorg, 1987):

use + non-use values

Non-use values (Snowball, 2008): values to

people who, for whatever reason, might be

non-users, but who are still willing to pay to

preserve or support the public good

Typology of values of culture:USE VALUE: price + part of buyers consumer

surplus

NON-USE VALUES: option, bequest, existence,

prestige, educational (Frey & Pommerehne,

1989) + altruistic value, vicarious consumption(Bille Hansen 1997; Throsby 2001)

CULTURAL VALUES: symbolic, historical, aesthetic,

authenticity, spiritual, social (Throsby, 2001)

+ Cultural inherent values (Hutter & Shusterman,

2006)


19/25

Arguments for public support to the arts

Public goods argument: non-excludability + non-

rivalry

Externalities argument: Positive/beneficial vs.

negative externalities

Asymmetric information

Market power argument (monopolies + similar

arguments)

Inequality in income Productivity lag / Baumols disease argument

Meritgoods argument

Supply-side vs. demand-side arguments


20/25

Economics of donations Samuelson (1954; 1955): Pareto inefficiency of

private provision of public goods

Warr (1982; 1983) + Bergstrom, Blume & Varian

(1986): crowding-out in relationship 1:1 no help in

direct fiscal redistributions in hope of achieving thePareto equilibrium

Andreoni (1989; 1990); Sugden (1984): other

explanations for donors motives warm-glow

altruism

Brooks (2003): crowding-in can be possible under

certain conditions (low level of public good provided)


21/25

BASIC MODEL Samuelsons model:

Our model each user solves:

Each non-user solves:

: use value of the user

: non-use value of the user

: non-use value of the non-user

),0,(),,(max GxUGGxU iiii GGgts ii ..

iii wgx

),0,(max GxU niniGGgts nini ..ninini wgx

),,( GGxU ii

),0,( GxU ii

),0,( GxU nini

),(max GxU


22/25

MODIFIED MODEL An added fourth, warm-glow component U(gi)

Modified model each user solves:

Each non-user solves:

: use value of the user

: non-use value of the user

: non-use value of the non-user

),,0,(),,,(maxi

iii

ii gGxUgGGxU

GGgts ii ..

iii wgx

),,0,(maxni

nini gGxU

GGgts nini ..ninini wgx

),,,(i

ii gGGxU

),,0,(i

ii gGxU

),,0,(ni

nini gGxU


23/25

Results Non-use values act in two different directions: they cause

inefficiency of the model (less donations, externality effect) andat the same time they cause more efficiency in the model (more

donations, altruism effect)

Yet always the externality effect predominates, therefore non-

use values always denote externalities in private provision ofpublic goods

Comparative statics: 1) users donations will almost always be

higher than non-users donations; 2) if present, the crowding-

out effect will be higher for the party with the higher level ofdonations; 3) crowding-in effect is possible under certain

circumstances; 4) relationship of non-use values of the user and

non-user has to be determined empirically

Econometric results using previous contingent valuation study

dataset confirmed the theoretical findings


24/25

Conclusion what was gained? New method to estimate economics effects of cultural events:

solution to decades of futile metodological discussions onEIM vs. CVM method

Many new and open questions for research in the future: 1) Docultural events really have the proclaimed economic effects?;2) How large are they?; 3) On what do they depend upon?

One of the first sensible economic models of non-use values, astep ahead in exploring this public economics concept

New argument for public support / market failure in provisionof a certain good: values argument if one finds existence ofsignificant non-use values in the estimation of a value of acertain good, this is the proof of beneficial externalities andtherefore necessary condition to consider (not to ensure!!)public support to provision of this good


25/25

THANK YOU FOR LISTENING!

Economic Estimation of Value of Culture

Documents

Transcript of Economic Estimation of Value of Culture