Resources
Economic Development
The Economic Impact of Montana Artists
Table of Contents
Methodology
Primary data were collected by means of a mail survey which was sent to over 3,000 artists across the state. The categories of artists surveyed included visual artists, performing artists, photographers, writers, designers, traditional artists and crafts artists. Primary survey data was collected on gross sales of art, estimates of the percentage of those sales to out-of-state purchases, estimates of total household and individual income, and the percentage of that income which originates from artist sales. Within the survey, artists were queried regarding their full-time occupation, numbers of full-time or part-time employees of the business, the wage and benefit levels of those employees, and the location of those employees.
Artists were surveyed regarding their production expenses. These expenses were disaggregated into materials and supplies, marketing expenses and all other expenses. Additionally, survey participants were questioned on the percentage of the dollar value of the purchases that were made in-state versus out-of-state. This data provides a better picture of the number of Montana businesses that are supported partially or in total by artists.
An input-output model (IMPLAN) was used to identify direct, indirect and induced effects associated with the production and sale of art. The direct effects are those which fall on artists and art production-related businesses. The indirect effects accrue to businesses that the artists utilize. An example would be that as the artist has higher sales, he/she now purchases accounting services to assist in the record keeping for the business. The third type of effect is referred to as the induced effect. As businesses generate more profits, their workers and owners earn higher incomes which are spent in the economy on other types of goods and services. This additional spending generated by the higher incomes is called the induced effect. The linkages between sectors provide the mechanism necessary to capture the full effect that spending in one industry has on the other sectors of the economy. The model captures the direct effects on businesses within that industry, the indirect effects on businesses outside of the target industry and the induced effects of increased spending resulting from higher consumer and business incomes. Model results can be used to examine the relative importance of artists on different counties within the state. The value of the impacts is discussed in detail at the beginning of page 25. (Click here for that section of the report.)
Survey results were compiled to provide information on the rationale for artists choosing Montana as a residence and their expectations about remaining in the state. Available information was assessed to determine migration patterns for artists, both into the state and out of the state
The primary survey utilized the database of artists compiled by the Montana Arts Council and the Billings Arts Association to identify and provide contact information for the artists. The number of surveyed artists is approximately 3,099, across all disciplines of artists. The 2000 Census report indicates that there are at least 5,840 artists in the state of Montana. Contact information was not available for all of these 5,840 artists or artists who were identified under other census categories. The survey required 398 responses to provide a 95% confidence level (with a sampling error of 2% and expected true error rate of 5%), slightly more than a 10% response rate. Of these 3,099, we received 795 completed responses (a response rate of 26%). It should be noted that despite the high response rate, the possibility of non-response bias exists. Non-response bias occurs when a portion of the surveyed population that has particular characteristics chooses not to respond.
Once the primary data was received, it was compiled into a database that allowed for analysis of the data by artistic category, location, length of time in business, and other variables of interest. Income and expense data were divided into in-state and out-of-state categories and totaled.
