Economic Analysis
Question One:
Suppose that the sales manager of a large automotive parts distributor wants to estimates as early
as April the total annual sales of a region. On the basis of regional sales, the total sales for the
company can also be estimated. If, based on past experience, it is found that the April estimates
of annual sales are reasonable accurate, then in future years the April forecast could be used to
revise production schedules and maintain the correct inventory at the retail outlets.
Several factors appear to be related to sales, including the number of retail outlets in the region
stocking the company’s parts, the number of automobiles in the region registered as of April 1,
and the total personal income for the first quarter of the year. Five independent variables were
finally selected as being the most important (according to the sales manager). Then the data were
gathered for a recent year. The total annual sales for that year for each region were also recorded.
Note in the Exam Data One that for region 1 there were 1,739 retail outlets stocking the
company’s automotive parts, there were 9,270,000 registered automobiles in the region as of
April 1 and so on. The sales for that year were $37,702,000.
Please check the Exam Data One on Moodle, and answer the following questions:
1. What percent of the variation is explained by the regression equation?
7.8% +0.58%+10.89%+9.02%=28.29%/4=7.07%
2. Compute the elasticity for each variable. On this basis, discuss the relative impact that
each variable has on demand. (For computing elasticity, you can use the first row of the
data from Exam Data One. Which are: Number of retail outlets=1739, Number of
automobiles registered(Millions)=9.27, Personal income($billions)=85.4, Average age of
automobiles(years)=3.5, Number of supervisors=9
12316/1739= 7.8% retail outlet percentages, 83.61 million/9.27 million=9.02% number
of automobiles, 498.9 billion/85.4 billion = 0.58%, 98/9= 10.89% (All first row stats used
as example)
3. Conduct a t-test for the statistical significance of each variable. Discuss the results of the
t-tests in lights of the policy implications.
Question Two:
Teton Village, Wyoming, near Grand Teton Park and Yellowstone Park, contains shops,
restaurants, and motels. The village has two peak seasons---winter, for skiing on the 10,000-foot
slopes, and summer, for tourists visiting the parks. The number of visitors(in thousands) by
quarter for five years can be found in Exam Data Two on Moodle.
a) Develop the typical seasonal pattern for Teton Village
The most people or visitors come into the thousands in the Teton Village in the winter and
summer from the highest number of people in the Summer and second highest in the
winter. The least number of people in thousands is in the Spring to Fall from the third
lowest to the lowest number of people in the thousands.
b) Determine the seasonally adjusted number of visitors for winter 2011.
76.1+77+75+72=300/4=75 for Fall of 2011