The forecasting staff for the Prizer Corporation has developed a model to predict sales of its air-cushioned ride snowmobiles. The model specifies that the S vary jointly with disposable personal income Y and the population between ages 15 and 40,Z, and inversely with the price of the snowmobiles P. Based on the past data, the best estimate of this relationship is S= K *YZ/P where k has been estimated (with the pst data) to equal 100. If Y=$11,000, Z= $1,200, and P=$20,000 c)how would you go about developing a value for k?
a). Fill in the table by preparing forecasts based on a five-year moving average, a three-year moving average, and exponential smoothing (with a w = 0.9 and a w = 0.3). Note: The exponential smoothing forecasts may be begun by assuming ?t+1 = Yt.
|YearActual5yr move 3yr exponential exponential|
|demand avg.avg.smoothing smoothing|
|2000 800 xxxxx xxxxx xxxxx xxxxx|
|2001 925 xxxxx xxxxx — —|
|2002 900 xxxxx xxxxx — —|
|2003 1025 xxxxx — — —|
|2004 1150 xxxxx — — —|
|2005 1160 — — — —|
|2006 1200 — — — —|
|2007 1150 — — — —|
|2008 1270 — — — —|
|2009 1290 — — — —|
|2010 * — — — —|
The economic analysis division of Mapco Enterprises has estimated the demand function for its line of weed trimmers as Qd = 18,000 + 0.4N – 350Pm + 90Ps where N = number of new homes completed in the primary market area Pm = price of the Mapco trimmer Ps = price of its competitor’s Surefire trimmer In 2010, 15,000 new homes are expected to be completed in the primary market area. Mapco plans to charge $50 for its trimmer. The Surefire trimmer is expected to sell for $55.
a. What sales are forecast for 2010 under these conditions?
b. If its competitor cuts the price of the Surefire trimmer to $50, what effect will this have on Mapco’s sales?
- c. What effect would a 30 percent reduction in the number of new homes completed have on Mapco’s sales ( ignore the impact of the price cut of the Surefire trimmer)?
Savings-Mart (a chain of discount department stores) sells patio and lawn furniture. Sales are seasonal, with higher sales during the spring and summer quarters and lower sales during the fall and winter quarters. The company developed the following quarterly sales forecasting model:
Yt= 8.25 + 0.125t 2.75D1t + 2.25D2t + 3.50D3t
Where Yt = predicted sales ($ million) in quarter t
8.25 = quarterly sales ($ million) when t = 0
t = time period (quarter) where the fourth quarter of 2002 = 0 First quarter of 2003 = 1, second quarter of 2003 = 2,. . .
D1t = 1 for first-quarter observations 0 otherwise
D2t = 1 for second quarter observations 0 otherwise
D3t = 1 for third-quarter observations 0 otherwise
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