Colby College Digital Commons @ Colby
Undergraduate Research Symposium (UGRS) Student Research
2006
The Economic Effects of Ski Resorts on Communities in the State of Maine
Rachel Freierman Colby College
Follow this and additional works at: https://digitalcommons.colby.edu/ugrs
Part of the Other Life Sciences Commons, and the Systems Biology Commons
Recommended Citation Freierman, Rachel, "The Economic Effects of Ski Resorts on Communities in the State of Maine" (2006). Undergraduate Research Symposium (UGRS). 12. https://digitalcommons.colby.edu/ugrs/12
This Article is brought to you for free and open access by the Student Research at Digital Commons @ Colby. It has been accepted for inclusion in Undergraduate Research Symposium (UGRS) by an authorized administrator of Digital Commons @ Colby. The Economic Effects of Ski Resorts on Communities in the State of Maine Rachel Freierman ’09 Colby College Department of Environmental Studies
Introduction Statistical Analysis
Skiing and snowboarding is a fairly expensive activity for participant and one in which the industry as a whole makes handsome Average Annual Income in Relation to Percent of Population in Poverty in Relation to Relative Distance from Ski Area profits. In the 2005/06 season, resorts in the Northeast reported an average gross revenue of $18.5 million. (NSAA) With the 120000 The Relative Distance from a Ski Area current weather phenomenon of El Nino, however, resorts in New England especially, have been suffering economically. The 120 100000 gross revenue in New England in the ’05/’06 season was down 4% from the previous year, likely due to the fact the total snowfall 100 e declined by 16%. (NSAA) Much of this loss in revenue came during the Christmas to New Years vacation period. In the 2007 80000 season, most mountains were less than half-opened during this peak week and the number of skiers and riders was especially low. 80
60000 With such a large decrease in profits, it is likely that many people will soon be affected (if they have not already been), including 60 local employees. This project, therefore, seeks to analyze the impact that the resorts have on the local economies in order to 40000 40 determine the potential problems the changing snowfall patterns could have on locals’ well-being. It is hypothesized that there Incom Average Annual
Percent of Population in Poverty 20 will be a strong correlation between the proximity of a community to a resort and the relative economic prosperity of that 20000 community; meaning that the ski industry is a pivotal part of their income and livelihood. 0 0 0 5000 10000 15000 20000 25000 30000 35000 0 5000 10000 15000 20000 25000 30000 35000 Relative Distance from Ski Area Relative Distance from Ski Area Methods Income of Census Blocks Within the Proximity of Poverty Status of Census Blocks Within the This project uses GIS to map the fourteen ski areas in the state of Maine and the economies of the surrounding census blocks. Sugarloaf USA Proximity of Sugarloaf USA 45000
20 The main relationship analyzed is between the proximity of a census block to a ski area and the relative economic success of that 40000 18 35000 census block. The measures of economic success are: average annual household income and the percentage of the population 16 30000 14 that is living in poverty, as determined from the US Census Bureau data. Other comparisons are made between the ski areas and 25000 12 the effective communities based on the size of the ski area – measured by their vertical drop. An initial map was created (below, 20000 10 8 15000
6
left), which shows how far away a census block is from any ski area as a relative distance. The distance is computed in a Income Annual Average 10000 4
5000
Euclidean format that is presented in a relative index. A lengthy attempt was made to calculate the distance using the road Percentof Population in Poverty 2
0 0 coverage and speed limit as a measure of driving time from a census block to a ski area, but due to time constraints and feasibility 0.00 10000.00 20000.00 30000.00 40000.00 50000.00 60000.00 0.00 10000.00 20000.00 30000.00 40000.00 50000.00 60000.00 Relative Distance Relative Distance issues, this more accurate and complex model was abandoned. A second map was created (below, right), showing the allocation of ski areas from any census block – essentially, which ski area is the closest. With this statewide data, more specific and Income of Census Blocks Within the Proximity of Poverty Status of Census Blocks Within the individual relationship were made by looking at the distance as is correlates to the size of ski areas, which were divided up into Big Rock Ski Area Proximity of Big Rock Ski Area three categories of small, medium, and large. 60000 35 The categories were formed on the basis of vertical Proximity to Ski Areas Allocation of Ski Areas 50000 30 25 drop on the mountain as there is typically a direct 40000 20 30000 relationship between vertical drop and other size aspects 15 I# I# 20000 such as the number of runs and lifts. Both average 10 Average Annual Income Annual Average 10000
5 annual household income and the percent of households Percentof Population in Poverty
0 0.00 10000.00 20000.00 30000.00 40000.00 50000.00 60000.00 70000.00 80000.00 90000.00 0 0.00 10000.00 20000.00 30000.00 40000.00 50000.00 60000.00 70000.00 80000.00 90000.00 in poverty were graphed in relationship to the relative Relative Distance Relative Distance distance for the entire state. Then Sugarloaf, Big Rock I# #I I# #I Ski Area, and Lost Valley were selected (one to I# I# I# I# Income of Census Blocks Within the Proximity of Poverty Status of Census Blocks Within the I# #I I# #I represent each of the three size categories and to #I #I Lost Valley Proximity of Lost Valley #I #I 120000 60 provide data from a wider range of state locals) and the I#I# I#I# 100000 50 #I I# #I I# economic factors for the census blocks allocated to I# Ski Area Vertical Drop (ft) I# 40 I# 240 - 800 80000 these mountains were mapped against the distance. I# 801 - 2000 Ski Area Vertical Drop (ft) 60000 30 I# 2001 - 2820 #I 240 - 800 Proximity to Ski Area 801 - 2000 40000 20 Far I# 2001 - 2820 I# Income Annual Average 20000 10
Close Percent of Population inPoverty
0 0 0.00 10000.00 20000.00 30000.00 40000.00 50000.00 60000.00 70000.00 0.00 10000.00 20000.00 30000.00 40000.00 50000.00 60000.00 70000.00 Relative Distance Relative Distance Results
Maine Census: Average Annual Household Income Maine Census: Percent of Households in Poverty Analysis None of the graphs above produced a relationship between the distance from the ski resort and either the income level or the percent of population in poverty. Both of the graphs that display the data from the whole state show a very constant level of income and poverty across all distances. The individual graphs also do not show a clear correlation between the distance and
I# Big Rock Ski Area I# Big Rock Ski Area economic well being. There are some possible sources of error to explain why the hypothesis was proved false. The first is that the Euclidian distance analysis that was done is not the most accurate tool for measuring distance traveled. Because it takes the distance as a straight line from one point to another, it does not incorporate the fact that most roads in Maine do not go in straight lines and that it would take longer to get somewhere in reality. It also does not take into account that there are varying speed limits on roads that will affect the rate of travel. Secondly, only two forms of economic criteria were looked at, which is likely not a
Big Squaw Mountain Big Squaw Mountain I# #I Mt Jefferson I# #I Mt Jefferson broad enough field to make an accurate conclusion. There are many potential measurements for economic success, and having a greater range of these determinants would prove more accurate. Finally, the allocation method used was also not as accurate as I# Sugarloaf USA I# Sugarloaf USA I# Saddleback I# Saddleback possible, because like the Euclidian distance analysis, it operates on a purely geometric scheme where it simply draws a line I# New Hermon Mountain I# New Hermon Mountain I# Eaton Mountain Ski Area I# Eaton Mountain Ski Area across the land in the middle of two ski areas as opposed to calculating the middle distance of travel on the roads. A future attempt I# Titcomb Mountain I# Titcomb Mountain #I Black Mountain Ski Area #I Black Mountain Ski Area I# Sunday River I# Sunday River to reevaluate this issue would certainly take into account the complications that the distances posed and would incorporate the I# Mount Abram I# Mount Abram I# Camden Snow Bowl I# Camden Snow Bowl non-Euclidian analysis. Additionally, the second attempt would make try to create relationships using more variables of economic #I Lost Valley Ski Area Vertical Drop (ft) #I Lost Valley I# Shawnee Peak I# Shawnee Peak Ski Area Vertical Drop (ft) I# 240 - 800 success in the hopes of better answering the questions of how greatly, if at all, ski areas effect local economies. I# 240 - 800 801 - 2000 I# I# 801 - 2000 I# 2001 - 2820 I# 2001 - 2820 Average Annual Household Income Percent of Households in Poverty 0.000 - 31914.683 0.000 - 6.182 Works Cited & Acknowledgements 31914.684 - 41282.895 6.183 - 11.436 41282.896 - 51621.622 11.437 - 16.760 National Ski Areas Association (NSAA). 2005/06 Ski Resort Industry Research Compendium. RRC Associates, Inc. 2006. 51621.623 - 66561.876 16.761 - 26.310 66561.877 - 106704.019 26.311 - 100.000 Data from: US Census Bureau, New England Ski Resorts by SkiTown.com, Maine Geographic Information System Pictures: Title Picture – Roger Medlin, 2003; http://www.oregonicons.com/elkhornmountainssunrize.jpg, Roger Medlin 2003 Results Picture - Zwieselalm sight; Results: http://auto.pege.org/2003-dachstein-west/zwieselalm-ausblick.jpg Much thanks to Curtis Bohlen and Manny Gimond for their continuous GIS help throughout the project, and Liza Benson for her assistance with the graphic design.