30 Apr Question: 1. Exercise 5.1 The forecasting staff for the Prizer Corporation has developed a model to predict…
1. Exercise 5.1 The forecasting staff for the Prizer Corporation has developed a model to predict sales of its air-cushioned-ride snowmobiles. The model specifies that sales, 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 past data, the best estimate of this relationship is: where k has been estimated (from past data) to equal 100 If Y $13,000, Z- $1,200, and P $20,000, what value would you predict for S? $78,000 $74,286 $184,615 S91,000 If P is reduced to $17,500, S to Note: Assume Y and Z remain constant at $13,000 and S1.200, respectively) $161,538 Which of the following is a potential weaknes 1? $84,324 It uses time-series data $104,000 It does not account for seasonal $89,143 It assumes that price and sales are uuveisery Telated
Fred’s Hardware and Hobby House expects its sales to increase at a constant rate of 6 percent per year over the next three years. Current sales are $300,000 Complete the following table by forecasting sales for each of the next three years Forecasted Sales Year (Dollars) If sales in 2003 were $180,000 and they grew to S300,000 by 2007 (a four-year period), the actual annual compound growth rate was: 18.56% 13.62% 10.76% Which of the following are some of the hazards of employing a constant rate of growth forecasting model? Check all that apply. It is ill-suited to estimate secular trends It ignores seasonal trends. It assumes that there are no cyclical variations.
Year Forecast Actual 2007 2006 2005 2004 2003 2002 1,045 937 829 721 613 505 1,076 974 870 764 656 545 What seasonal adjustment factor would you recommend be used in making future June forecasts? -0.2% 2.7% 55%
Stowe Automotive is considering an offer from the country of Indula to build a plant making automotive parts for use there. In preparation for a final decision, Stowe’s economists have been hard at work constructing a basic econometric model for Indula to aid the company in predicting future levels of economic activity. Because of the cyclical nature of the automotive parts industry, forecasts of future economic activity are quite important in Stowe’s decision process. Corporate profits (Pfor all firms in Indula were about $110.00 billion. GDP for the nation is composed of consumption, C, investmentI, and government spending, G. It is anticipated that Induļa’s federal, state and local governments will spend in the range of $220 billion next year. On the basis of an analysis of recent economic activity in Indula, consumption expenditures are assumed to be $1540 billion plus 80% of national income. National income, Ý, s equal to GDPminus taxes xes aree timated Oheata ateoft ut i Finally, corporate investments have historically equaled S33 billion plus 90% of last year’s corporate profits P Construct a five-equation econometric model of the state of Induļa A Simple Model of the National Economy of Indula C+I+G GDP T GDP-
A firm experienced the demand shown in the following table Fill in the table by preparing forecasts based on a five-year moving average, a three-year moving average, and exponential smoothing (w -0.9 and w – 0.3 ). (Note: The exponential smoothing forecasts may be begun by assuming Y +1-Yt ) Moving Average Exponential Smoothing (W 0.9) (3-year) (W 0.3) Year Actual Demand(5-year) 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 1,500 1,545 1,585 1,620 1,650 1,675 1,695 1,710 1,720 1,725 The following table shows the square errors, (Y, – Yt. /), for forecasts from 2005 through 2009 Fill the table by calculating the root mean square error (RMSE) for each of the methods
Fill the table by calculating the root mean square error (RMSE) for each of the methods. Square Error Moving Average Exponential Smoothing Year 2005 2006 2007 2008 2009 RMSE (5-year) 9,025 6,400 4,225 2,500 1,225 (3-year) 3,249 2,209 1,369 729 289 (W- 0.9) 784 529 289 144 36 (W- 0.3) 7,569 6,561 5,184 3,600 2,209 Based on the RMSE criterion, which of the forecasting methods is the most accurate? Exponential smoothing (w -0.3) Five-year moving average Exponential smoothing (w -0.9) Three-year moving average
The Questor Corporation has experienced the following sales pattern over a 10-year period Complete the table using a first-order exponential smoothing model with a w = 09 to forecast sales in 2017. Sales (Y,) Exponential Smoothing (Yt) ear(000) 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 (w-0.9) 139 162 158 168 192 189 200 225 223 235 139
Bell Greenhouses has estimated its monthly demand for potting soil to be the following N-400 +9X where N is the monthly demand for bags of potting soil and X is the time period in months (March 2016 0) Assume this trend factor is expected to remain stable in the foreseeable future. The following table contains the monthly seasonal adjustment factors, which have been estimated using actual sales data from the past five years: Complete the following table by forecasting Bell Greenhouses’ demand for potting soil in March, June, August, and December 2017. Month March June August December Adjustment Factor (%) Forecast +15 +10 12 The following table shows the forecasted and actual potting soil sales by Bell Greenhouses for April in five different years YearForecast Actual 2017 2016 2015 2014 2013 517 409 301 193 85 538 442 310 207 87
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: Y, 6.00+0.600r -2.75Dl, +025D2, +3.5D where predicted sales (in in millions of dolars) in quarter 6.00quly sales (in millions of dollars) whent0 time period (quarter) where the fourth quarter of 2012 -0 first quarter of 2013-1, secon Di1 for first-quarter observations; 0 otherwise D21 for second-quarter observations; 0 otherwise Dit1 for third-quarter observations; 0otherwise Forecast Savings-Mart’s sales of patio and lawn furniture for each quarter of 2020 Sales Forecast Quarter 2020 First Quarter 2020 Second Quarter 2020 Third Quarter 2020 Fourth Quarter (Millions of dollars)
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