The Economic Impact of the Arts in Watauga County, North Carolina


where v(y, z) is the respondent’s indirect utility function and y is income. The probability that an amount A is at least as high as the respondent’s WTP is



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where v(y, z) is the respondent’s indirect utility function and y is income. The probability that an amount A is at least as high as the respondent’s WTP is:

where is a continuous nondecreasing function. The functional form of WTP is assumed to be:



where and is a continuous and increasing function such that and

Second, the respondent was asked whether she was willing to pay anything at all to ensure the baseline level of community art activity, that is:



Ti indicates whether the respondent was willing to pay the suggested price:

The log likelihood for the sample is then equal to:



Following Hanemann (1984), assuming a linear utility function:



where  and  are coefficients, y denotes income,  is a vector of coefficients, and s denotes a vector of socio-economic and demographic characteristics gives:



where denotes an approximation of the utility change. Using a logistic distribution Gwtp we have:




Maximizing the log likelihood function, Kriström (1997) finds mean WTP:

The variance was computed using a Gauss approximation.

Four dichotomous choice bids X ($5, 10, 25 and 50) were randomly distributed among the sampled residents. The bids were chosen to provide sufficient information about the tails of the empirical survival distribution. In our survey, 57 percent of the respondents were willing to pay a positive amount to sustain current levels of community art activity. The large number of respondents unwilling to pay a positive amount shows the importance of using a distribution that allows for a zero WTP. Popular distributional assumptions such as log-logistic, lognormal or Weibull imply that all respondents have a positive WTP. Use of such an assumption may, therefore, result in a biased benefit estimate. The resulting estimated value function is provided in Table A1.



Table A1

Results from Probabilistic Spike Model


Variable

Coefficient

Standard Error

p-value

Constant

0.3523

0.2321

0.1290

Bid

-0.2944

0.1056

0.0055

Income

0.4579•10-4

0.2754•10-4

0.0962

Gender

4.3818

2.3498

0.0622

Age

0.7754•10-7

0.3067•10-7

0.0115

Events

0.2887

0.1565

0.0650













WTP

3.0052

1.1367

0.0082


SECTION III
TABLES


Table III-1

Household Interest in the Arts


Category

% of Respondents

Not Very Interested

21.40%

Not Interested

12.09%

Neutral

9.77%

Interested

21.86%

Very Interested

33.95%


Table III-2

Household Familiarity with the Arts


Category

% of Respondents

Not Very Familiar

18.60%

Not Familiar

11.16%

Neutral

28.84%

Familiar

24.65%

Very Familiar

15.81%


Table III-3

Number of Events Attended and Expenditures per Event during last 12 Months


Category

Median

Mean

Individual Events Attended

3

4.48

Household Events Attended

4

4.94

Household Spending per Event

20

$31.60



Table III-4

Likelihood of Attending Arts Events in the next 12 Months


Category

% of Respondents

Definitely Will Not

12.09%

Probably Not

18.60%

Neutral

15.35%

Probably Will

19.54%

Definitely Will

37.67%


Table III-5

Areas of Watauga County Residents Attend Events


Location

% of respondents*

Boone

59.07%

Blowing Rock

46.98%

Valle Crucis

26.51%

Cove Creek/Sugar Grove

26.05%

Todd

19.07%

Foscoe/Seven Devils

12.56%

Other

5.12%

*Multiple response question



Table III-6

Types of Arts Activities, Festivals or Events Preferred


Category

% of Respondents*

Music**

57.67%

Crafts

29.30%

Folk Arts

27.91%

Dance

25.12%

Theater

19.53%

Furniture Making

18.14%

Film

17.67%

Pottery

17.21%

Ceramics

16.74%

Photography

12.56%

Drawing

11.63%

Quilting

9.77%

Jewelry

9.30%

Storytelling

8.84%

Painting

8.84%

Weaving

7.91%

Sculpture

6.51%

Poetry/Readings

5.58%

Other

1.86%

*Multiple response question

**Includes a broad spectrum of events


Table III-7

Places Visited to Experience Arts Events/Activities


Category

% of Respondents*

Outdoor Performing Arts Facilities

47.91%

Indoor Performing Arts Facilities

45.12%

Galleries

42.36%

Museums

28.84%

Restaurants

28.84%

Street Fair/Festivals

26.05%

Classes/Workshops

13.02%

Craft Trails

7.91%

Studio Hops

5.12%

*Multiple response question



Table III-8

How Residents Learn of Art Activities/Events


Category

% of Respondents*

Newspapers

46.51%

Friends/Family

43.26%

Previous Visit

21.86%

Radio

20.93%

Brochures

19.54%

Television

17.67%

Internet

11.16%

Billboards

7.44%

Retail Shop

5.58%

Other

4.19%

Welcome Center

1.40%

Hotel/Motel

0.47%

*Multiple response question



Table III-9

Community Value Estimates for Local Art Sector


Value Category

Estimate

*WTP for Marginal 20% of Arts Events




Individual Resident

$3.01

Community

$107,931.80







*WTP for Total Art Events




Individual

$15.03

Community

$539,658.80

*WTP = Willingness to Pay



Table III-10

Reason for Indicated Support or Non-Support


Category

% of Respondents

Support* (57%)

Important to Local Economy

25.12%

Important to Local Culture

42.79%

Frequently Attend

17.21%

Provider of Arts

6.98%

Non–Support (43%)

Cannot Afford

13.95%

Not My Responsibility

17.67%

Suitable Substitutes

8.37%

Need More Information

2.33%

Not Sure

0.00%

Other

1.40%

*Willingness to pay a positive amount


Section III

References
Carson, R.T., Wright, J., Carson, N., Alberini, A., and Flores, N. (1996) A Bibliography of Contingent Valuation Studies and Papers. Natural Resource Damage Assessment, Inc.
Kriström, B. (1997). Spike Models in Contingent Valuation. American Journal of Agricultural Economics 79: 1013-1023.
Mitchell, R.C. and Carson, R.T. (1989) Using Surveys to Value Public Goods: The Contingent Valuation Method. Baltimore: Johns Hopkins University, Resources for the Future.
Thompson, E., Berger, M., Blomquist, G., and Allen, S. (2002) Valuing the Arts: The Contingent Valuation Approach. Journal of Cultural Economics 26: 87-113.

Conclusion

The final section of this research report discusses the total economic impact of the arts in Watauga County as well as the study's limitations and factors not considered in the computation of the total economic impact of the arts.



Total Economic Impact of the Arts in Watauga County, North Carolina

This research project was designed to assess the economic impact of the arts in Watauga County, North Carolina. The project consisted of three sections. In the first section arts patrons were surveyed and their economic impact was estimated as the sum of arts patronage spending (both residential and visitor) and additional spending by visiting arts patrons. The second section surveyed artists and arts organizations in Watauga County. The economic impact of artists and arts organizations was estimated as the sum of the sales revenue they derived in Watauga County, their employee payroll expenses, and subcontracting expenses. The final section of the study involved a survey of Watauga County residents. This survey assessed their willingness to support arts events.

The total economic impact of the arts in Watauga County, North Carolina was computed to be the sum of the economic impact of arts patrons in Watauga County, $11,089,275, plus the economic impact of artists and arts organizations operating in Watauga County, $14,840,703, plus an additional amount representing the willingness of Watauga County residents to support the arts in the county, $539,658. Therefore, the total economic impact of the arts in Watauga County was estimated to be $26,469,636.

Discussion

Although a random sampling procedure would have been preferable for surveying arts patrons and tourists, practical limitations precluded this procedure. In addition, it is possible that a very small amount of double counting of arts patrons may have occurred since about ten percent of Appalachian-related arts patrons purchased season tickets.

However, the $26,469,636 economic impact estimated reported herein is expected to be to be low. There are several reasons for this expectation. First, the marginal effect of property taxes paid by resident art patrons, artists and art organizations were not accounted for. Second, not all arts events in Watauga County were sampled, leading to an underestimate of number of attendees and their resultant spending. Third, no attempt was made to account for arts events occurring in restaurants and bars in Watauga County. Finally, the study ignores the multiplier effect - additional spending on items such as additional supplies or any other good or service needed to supply a business, the amount of money arts employees spend as part of their daily lives in grocery stores and malls, and the additional jobs that result from this spending.

The $26,469,636 economic impact estimate seems to compare well with other estimates of economic activity in Watauga County. For example, the Boone Chamber of Commerce reported 2001 retail sales of $670 million. Further, the North Carolina Department of Commerce estimated tourism spending in Watauga County for the year 2001 to be $147.32 million. Overall, the results of this study suggest that the arts are one of the major industries in Watauga County, North Carolina.




1 See Carson et. al (1996) for an extensive review of contingent valuation studies, and see Mitchell and Carson (1989) for the theoretical foundations of the contingent valuation method.

2 Locations were selected to obtain a proportionate sample of the county population. Test confirm no statistical difference exists between the two elicitation methods.

3 The Census estimates the total population of Watauga County as 42,909 in 2001 and the proportion of that population that is under 18 as 16.3 percent. The adult (18 or older) population is therefore 35,915.

We respectfully request that no part of this document be reproduced without express written permission of

Drs. Stoddard, Davé and Cherry, John A. Walker College of Business, Appalachian State University, Boone, NC.




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