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THE 2000 ECONOMIC IMPACT OF EXPENDITURES
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Hotels/Motels/ |
Cabins/ |
Campgrounds | |
| Number of properties |
1,945 |
1,116 |
733 |
| Number of rooms/units/sites |
76,492 |
9,282 |
58,380 |
| Total available
roomnights/ site-nights (millions) |
25.61 |
2.14 |
8.21 |
| Total occupied
roomnights/ site-nights (millions) |
15.66 |
1.21 |
3.56 |
| Average occupancy rate |
61% |
56% |
43% |
| Average double rate |
$81.80 |
||
| Average unit rate |
$99.07 |
||
| Average site rate |
$17.79 | ||
| Management's Estimate: | |||
| Average party size |
2.07 |
4.24 |
3.54 |
| Average length of stay |
2.15 |
4.80 |
2.47 |
| Guest Origin | |||
| Out of State |
50% |
53% |
38% |
| U.S. |
47% |
53% |
38% |
| Canada |
2% |
* |
* |
| Other foreign |
1% |
* |
* |
| Wisconsin |
50% |
47% |
62% |
| Trip Purpose1 | |||
| Pleasure |
48% |
94% |
N/A |
| Business |
36% |
5% |
N/A |
| Meetings/conventions |
16% |
1% |
N/A |
Note: Length of stay as noted throughout this document represents the average number of nights spent in a hotel/motel/resort. It does not necessarily reflect the total number of nights spent in Wisconsin. Columns of figures may not add to totals shown due to rounding. * Less than 0.5%
WISCONSIN COMPARISON SUMMARY
1999
(Revised) vs. 2000
|
1999 (Revised) |
2000 |
Change | |
| Estimated Traveler Expenditures (billions) |
$9.081 |
$9.972 |
+9.8% |
| Estimated Economic Impact: | |||
| Total full-time job equivalents supported |
258,138 |
282,960 |
+9.6% |
| Total resident income (millions) |
$5,026.14 |
$5,565.72 |
+10.7% |
| Total government revenues generated: | |||
| State (millions) |
$848.78 |
$894.99 |
+5.4% |
| Local (millions) |
$583.30 |
$647.98 |
+11.1 % |
WISCONSIN TOTAL ESTIMATED TRAVELER
EXPENDITURES BY SEASON
1999 (Revised) vs. 2000
|
1999 (Revised) |
2000 |
% Change | |
| December - April |
$2,653,071,725 |
$2,900,557,805 |
+9.3% |
| May - August |
$4,352,791,507 |
$4,793,915,638 |
+10.1% |
| September - November |
$2,074,810,397 |
$2,277,232,204 |
+9.8% |
| Total |
$9,080,673,629 |
$9,971,705,647 |
+9.8% |
THE 2000 ESTIMATES OF TRAVELER EXPENDITURES
By Accommodation Type
More than half of the total estimated traveler expenditures, $5.66 billion (57%), were spent by travelers staying in Wisconsin overnight at hotels/motels/resorts.
Those camping in Wisconsin spent $628 million (6%), and those staying in cabins/cottages/condominiums spent $513 million (5%) while traveling in Wisconsin.
Visitors with no lodging expenses spent 32% of Wisconsin's 2000 traveler expenditures ($3.18 billion). Travelers who stayed at the homes of family and/or friends spent $2.45 billion (25%) while visiting Wisconsin, and those visiting just for the day or passing through Wisconsin spent nearly $722 million (7%).
By Category of Expenditure
More than half of Wisconsin's total estimated travel expenditures came from shopping and food expenditures ($3.0 billion and $2.4 billion, respectively).
Recreation expenditures represent 24% of traveler expenditures ($2.4 billion), and lodging expenses represent 15% of the total estimated traveler expenditures ($1.5 billion). Six percent of Wisconsin traveler expenditures ($583 million) were spent on transportation.
Seasonal Differences in Traveler Expenditures
Half of all traveler expenditures in Wisconsin ($4.8 billion or 48%) were spent in the summer season (May through August). The winter season (December through April) represents 29% of Wisconsin's total traveler expenditures ($2.9 billion), and the fall season (September through November) accounts for 23% of these expenditures ($2.3 billion).
Fall and summer traveler expenditures increased by 10%, compared to 1999 (revised) while the winter season saw a 9% increase.
2000 County by County Traveler Expenditures and Economic Impact
|
COUNTY |
EXPENDITURES $ |
|
|
JOBS* |
RESIDENT INCOME $ |
STATE REVENUE $ |
LOCAL REVENUE $ |
|
|
2000 |
1999 REV. |
%CHG |
2000 |
2000 |
2000 |
2000 |
|
ADAMS |
86,268,150 |
86,042,916 |
0.26% |
2,402 |
50,316,911 |
6,750,011 |
6,179,378 |
|
ASHLAND |
47,317,959 |
43,052,109 |
9.91% |
1,324 |
27,738,809 |
3,721,159 |
3,406,580 |
|
BARRON |
86,440,383 |
80,424,806 |
7.48% |
2,670 |
34,333,000 |
7,878,000 |
4,292,000 |
|
BAYFIELD |
106,217,094 |
103,037,036 |
3.09% |
3,057 |
36,762,000 |
8,995,000 |
4,900,000 |
|
BROWN |
412,253,639 |
358,753,108 |
14.91% |
11,163 |
218,523,000 |
41,876,000 |
22,815,000 |
|
BUFFALO |
16,538,682 |
16,212,036 |
2.01% |
478 |
9,998,874 |
1,341,349 |
1,227,954 |
|
BURNETT |
34,542,346 |
33,533,523 |
3.01% |
956 |
19,997,746 |
2,682,696 |
2,455,908 |
|
CALUMET |
25,038,089 |
22,543,600 |
11.07% |
693 |
14,514,493 |
1,947,118 |
1,782,513 |
|
CHIPPEWA |
70,674,265 |
63,620,405 |
11.09% |
1,971 |
41,285,671 |
5,538,471 |
5,070,259 |
|
CLARK |
27,411,025 |
25,240,721 |
8.60% |
754 |
15,804,671 |
2,120,196 |
1,940,958 |
|
COLUMBIA |
138,024,002 |
129,451,299 |
6.62% |
3,835 |
80,313,531 |
10,774,056 |
9,863,239 |
|
CRAWFORD |
35,302,013 |
32,151,899 |
9.80% |
985 |
20,642,835 |
2,769,235 |
2,535,129 |
|
DANE |
882,760,398 |
795,185,467 |
11.01% |
29,720 |
484,587,000 |
91,504,000 |
49,853,000 |
|
DODGE |
63,875,020 |
55,864,623 |
14.34% |
1,771 |
37,092,595 |
4,975,970 |
4,555,311 |
|
DOOR |
415,538,496 |
405,175,579 |
2.56% |
13,596 |
164,880,000 |
38,122,000 |
20,770,000 |
|
DOUGLAS |
99,605,860 |
89,270,183 |
11.58% |
2,772 |
58,057,975 |
7,788,475 |
7,130,052 |
|
DUNN |
42,258,716 |
40,110,735 |
5.36% |
1,186 |
24,835,911 |
3,331,736 |
3,050,078 |
|
EAUCLAIRE |
171,004,817 |
155,894,155 |
9.69% |
4,742 |
99,343,645 |
13,326,945 |
12,200,311 |
|
FLORENCE |
8,076,755 |
7,757,654 |
4.11% |
215 |
4,515,620 |
605,770 |
554,559 |
|
FONDDULAC |
126,750,878 |
115,623,722 |
9.62% |
3,511 |
73,540,100 |
9,865,400 |
9,031,399 |
|
FOREST |
17,280,727 |
16,942,976 |
1.99% |
493 |
10,321,418 |
1,384,618 |
1,267,565 |
|
GRANT |
61,144,063 |
55,023,581 |
11.12% |
1,708 |
35,802,417 |
4,802,892 |
4,396,865 |
|
GREEN |
38,870,681 |
36,394,691 |
6.80% |
1,157 |
16,114,000 |
3,472,000 |
1,892,000 |
|
GREENLAKE |
48,331,419 |
45,410,143 |
6.43% |
1,340 |
28,061,354 |
3,764,429 |
3,446,192 |
|
IOWA |
45,488,780 |
42,896,948 |
6.04% |
1,263 |
26,448,633 |
3,548,083 |
3,248,135 |
|
IRON |
49,042,232 |
48,619,199 |
0.87% |
1,371 |
28,706,443 |
3,850,968 |
3,525,415 |
|
JACKSON |
56,670,311 |
53,709,988 |
5.51% |
1,571 |
32,899,519 |
4,413,469 |
4,040,363 |
|
JEFFERSON |
94,065,693 |
84,302,680 |
11.58% |
2,633 |
55,155,076 |
7,399,051 |
6,773,549 |
|
JUNEAU |
83,941,102 |
81,175,351 |
3.41% |
2,340 |
49,026,733 |
6,576,933 |
6,020,933 |
|
KENOSHA |
179,368,589 |
165,996,487 |
8.06% |
4,216 |
70,699,000 |
16,524,000 |
9,002,000 |
|
KEWAUNEE |
33,972,242 |
33,334,568 |
1.91% |
939 |
19,675,202 |
2,639,427 |
2,416,295 |
|
LACROSSE |
200,831,324 |
208,847,272 |
-3.84% |
5,574 |
116,761,036 |
15,663,486 |
14,339,326 |
|
LAFAYETTE |
14,662,061 |
14,258,736 |
2.83% |
415 |
8,708,697 |
1,168,272 |
1,069,507 |
|
LANGLADE |
34,577,678 |
32,229,943 |
7.28% |
970 |
20,320,291 |
2,725,966 |
2,495,518 |
|
LINCOLN |
45,156,744 |
43,483,000 |
3.85% |
1,247 |
26,126,089 |
3,504,814 |
3,208,523 |
|
MANITOWOC |
114,609,305 |
100,708,186 |
13.80% |
3,187 |
66,766,670 |
8,956,745 |
8,199,559 |
|
MARATHON |
182,966,715 |
167,143,617 |
9.47% |
5,081 |
106,439,619 |
14,278,869 |
13,071,762 |
|
MARINETTE |
69,758,029 |
65,090,686 |
7.17% |
1,925 |
40,318,037 |
5,408,662 |
4,951,425 |
|
MARQUETTE |
35,547,384 |
35,073,960 |
1.35% |
986 |
20,642,836 |
2,769,236 |
2,535,130 |
|
MENOMINEE |
8,437,794 |
7,583,786 |
11.26% |
246 |
5,160,709 |
692,309 |
633,782 |
|
MILWAUKEE |
1,479,177,496 |
1,260,631,028 |
17.34% |
40,466 |
851,895,723 |
163,529,738 |
89,093,831 |
|
MONROE |
100,059,852 |
97,396,633 |
2.73% |
2,787 |
58,380,519 |
7,831,744 |
7,169,663 |
|
OCONTO |
48,672,093 |
45,620,727 |
6.69% |
1,355 |
28,383,899 |
3,807,699 |
3,485,804 |
|
ONEIDA |
164,573,860 |
164,000,002 |
0.35% |
4,573 |
95,795,658 |
12,850,983 |
11,764,586 |
|
OUTAGAMIE |
271,700,719 |
240,805,301 |
12.83% |
7,545 |
158,046,707 |
21,201,957 |
19,409,586 |
|
OZAUKEE |
79,532,462 |
74,107,014 |
7.32% |
2,181 |
45,910,548 |
8,812,980 |
4,801,465 |
|
PEPIN |
8,467,320 |
8,188,686 |
3.40% |
231 |
4,838,165 |
649,040 |
594,171 |
|
PIERCE |
29,694,790 |
26,857,818 |
10.56% |
816 |
17,094,849 |
2,293,274 |
2,099,404 |
|
POLK |
48,853,306 |
43,460,847 |
12.41% |
1,355 |
28,383,898 |
3,807,698 |
3,485,803 |
|
PORTAGE |
135,897,654 |
124,911,386 |
8.80% |
3,772 |
79,023,354 |
10,600,979 |
9,704,793 |
|
PRICE |
29,437,545 |
30,926,399 |
-4.81% |
695 |
10,744,000 |
2,817,000 |
1,534,000 |
|
RACINE |
202,745,158 |
184,114,336 |
10.12% |
5,635 |
118,051,213 |
15,836,563 |
14,497,772 |
|
RICHLAND |
21,928,998 |
20,928,343 |
4.78% |
616 |
12,901,772 |
1,730,772 |
1,584,456 |
|
ROCK |
215,723,144 |
197,350,784 |
9.31% |
5,989 |
125,469,733 |
16,831,758 |
15,408,835 |
|
RUSK |
30,328,817 |
28,774,713 |
5.40% |
831 |
17,417,392 |
2,336,542 |
2,139,015 |
|
ST.CROIX |
86,104,857 |
78,442,530 |
9.77% |
2,387 |
49,994,367 |
6,706,742 |
6,139,767 |
|
SAUK |
683,393,970 |
616,458,592 |
10.86% |
19,060 |
399,309,833 |
53,567,383 |
49,038,916 |
|
SAWYER |
99,961,768 |
99,525,210 |
0.44% |
2,771 |
58,057,974 |
7,788,474 |
7,130,052 |
|
SHAWANO |
62,075,003 |
58,125,422 |
6.79% |
1,740 |
36,447,505 |
4,889,430 |
4,476,088 |
|
SHEBOYGAN |
219,683,112 |
202,111,924 |
8.69% |
6,112 |
128,050,088 |
17,177,913 |
15,725,726 |
|
TAYLOR |
17,989,010 |
16,523,531 |
8.87% |
493 |
10,321,418 |
1,384,618 |
1,267,565 |
|
TREMPEALEAU |
31,412,195 |
30,379,877 |
3.40% |
863 |
18,062,481 |
2,423,081 |
2,218,239 |
|
VERNON |
30,234,127 |
28,674,000 |
5.44% |
832 |
17,417,392 |
2,336,542 |
2,139,016 |
|
VILAS |
185,720,336 |
187,280,119 |
-0.83% |
5,158 |
108,052,341 |
14,495,216 |
13,269,819 |
|
WALWORTH |
296,407,991 |
264,198,404 |
12.19% |
8,237 |
172,561,201 |
23,149,076 |
21,192,099 |
|
WASHBURN |
36,821,817 |
35,871,624 |
2.65% |
1,031 |
21,610,469 |
2,899,044 |
2,653,964 |
|
WASHINGTON |
113,169,419 |
98,184,911 |
15.26% |
3,102 |
65,295,002 |
12,534,017 |
6,828,749 |
|
WAUKESHA |
541,781,927 |
451,421,849 |
20.02% |
14,830 |
312,191,727 |
59,928,265 |
32,649,955 |
|
WAUPACA |
69,250,226 |
67,331,924 |
2.85% |
2,135 |
28,342,000 |
6,300,000 |
3,433,000 |
|
WAUSHARA |
38,864,172 |
37,741,696 |
2.97% |
1,078 |
22,578,102 |
3,028,852 |
2,772,798 |
|
WINNEBAGO |
175,617,133 |
161,444,525 |
8.78% |
4,881 |
102,246,543 |
13,716,368 |
12,556,813 |
|
WOOD |
105,803,906 |
101,712,104 |
4.02% |
2,940 |
61,605,961 |
8,264,436 |
7,565,778 |
|
TOTALS |
9,971,705,643 |
9,080,673,633 |
9.81% |
282,960 |
5,565,720,000 |
894,986,000 |
647,979,000 |
Introduction
The basic procedure employed in this project is the T-MAP-I economic impact model. This procedure was first employed by Davidson-Peterson Associates in 1985 for the State of Georgia. Since then, it has been employed on behalf of states and local areas throughout the United States. This Technical Appendix provides a brief outline of the procedure.
A. What is Economic Impact?
Economic impact begins when a visitor to an area spends money in that area -- no matter what the reason. But the benefits to local economy go beyond the basic impact of these dollars spent in the area; these visitor expenditures create a chain effect. The direct effects or impacts of these expenditures are evident as the "direct" recipients of these expenditures in turn pay wages, earn income and pay taxes. Further, these direct recipients spend their income and thereby create indirect impact: more jobs, wages, salaries, proprietary income and tax revenues. These direct and indirect effects together equal the total economic impact of traveler expenditures in the area being visited.
B. What is a Traveler?
For purposes of this study, a traveler is anyone who visits an area traveling outside of their normal routine and spends money. They may be motivated to travel by pleasure, personal, or business reasons or some combination of reasons. If they remain in the area being visited for more than thirty (30) days, they cease being a traveler or if they are staying in accommodations contracted for more than a thirty (30) day period (construction workers or truck drivers, for example), they are also not classified as travelers.
C. What is Being Measured?
It should be underscored that this report and the T-MAP-I procedure are based on the premise that economic impact begins with the expenditures of dollars by travelers (bottom-up measurement) rather than receipts of selected businesses, (top-down measurement).
Because of the problems and errors associated with it, Davidson-Peterson Associates does not use this traditional top-down or industry receipts-based measurement.
Let's explain a little further.
Our procedure for assessing economic impact allows us to estimate current numbers as well as measure change from year to year accurately. We are constantly reviewing and revising methods and numbers to generate the most accurate measures of change over time.
D. The Basic Research Steps for the 2000 Wisconsin Effort
What follows is a brief description of the procedures for estimating economic impact as they were completed in 2000.
1. Inventory Update
2. Seasonal Surveys of lodging business activity (HMR)
| Season | # Called |
| December - April | 1,370 |
| May - August | 1,330 |
| September - November | 1,301 |
3. Resident (VFR) Survey
4. Visitor Expenditure Survey/Modeling
5. Economic Impact Data Calculations
6. Input/Output (I/O) Modeling
Definition of Economic Impact Terminology
First, the dollars spent by travelers.
Total Estimated Traveler Expenditures
These figures represent the total estimated expenditures made by all travelers to the State, as calculated by the Davidson-Peterson Associates, Inc. proprietary economic impact model, based on survey data.
Next, the two degrees of economic impact
Economic impact begins when a visitor spends money in the state -- no matter what the reason. But the benefits to local economy go beyond the basic impact of these dollars spent in the state; these visitor expenditures create a chain effect.
Direct Impacts
The direct effects or impacts of these expenditures are evident as the "direct" recipients of these expenditures in turn pay wages, earn income and pay taxes. These figures represent the economic impacts that are created by the initial circulation of the total estimated traveler expenditures. For example, a server at a resort frequented by travelers is directly supported by the expenditures made by those travelers.
Indirect Impacts
Further, these direct recipients spend their income and thereby create indirect impact: more jobs, wages, salaries, proprietary income and tax revenues. These figures represent the economic impacts that are created as the total estimated traveler expenditures are re-circulated throughout the economy. For example, the above server's landlord is indirectly supported by the traveler expenditures that paid the waitress's salary.
These direct and indirect effects together equal the total economic impact of traveler expenditures in the area being visited.
Finally, the four categories of economic impact.
Full-time Equivalent Jobs
These figures represent the estimated number of full-time job equivalents that are supported by the total estimated traveler expenditures. A full-time job equivalent could be one full-time employment position, such as a hotel manager.
However, the Davidson-Peterson Associates, Inc. input/output model created specifically for each area by Dr. William Schaffer of the Georgia Institute of Technology also account for part-time employment. Therefore, the input/output model combines all part-time jobs supported by the area's tourism and calculates its estimated equivalent full-time employment. For instance, three part-time waitress positions may be the equivalent of one full-time position.
Resident Wages & Proprietary Income
These figures represent the estimated dollar amount of resident income which is generated by these full-time equivalent jobs that are supported by total estimated traveler expenditures. These income figures include resident wages, resident salaries and resident proprietary income.
State Government Revenues
These figures represent the estimated dollar amount of state government revenues that are collected as a result of the total estimated traveler expenditures. State government revenues collected include lodging, sales and meals taxes as well as any other sources of government income collected as a result of the total estimated traveler expenditures throughout the state.
Local Government Revenues
These figures represent the estimated dollar amount of local government revenues which are collected as a result of the total estimated traveler expenditures. Local government revenues collected include property taxes as well as any additional sources of county or city government income (additional regional sales taxes, lodging taxes, etc. that are collected at or returned to the local level).