5. Exercise 5.5A 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 movingaverage, and exponential smoothing (w = 0.9forecasts may be begun by assuming Y t+ F Yt •)and w = 0.3 ). (Note: The exponential smoothingMoving AverageActual Demand (5-year) (3-year)Exponential Smoothing(W = 0.9)Year(W = 0.3)2000900200188590090020028752003870887 ▼2004870877 ▼2005875880872 Y200688587587220079008758772008920880887 -2009945890902 Y2010905922The following table shows the square errors,(Y; - T1-) , for forecasts from 2005 through2009.Fill the table by calculating the root mean square error (RMSE) for each of the methods.Square ErrorExponential SmoothingMoving AverageYear (5-year) (3-year) (W = 0.9)(W = 0.3)20052592525200610016910036200762552925636120081,6001,0894841,08920093,0251,8497292,304RMSEBased on the RMSE criterion, which of the forecasting methods is the most accurate?Exponential smoothing (w = 0.3)Five-year moving averageThree-year moving averageExponential smoothing (w = 0.9)

Compute 5-year moving average demand forecast using Fy = (Dy-1 + Dy-2 + Dy-3 + Dy-4 + Dy-5) / 5…

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 Yt+ F Y; •)

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 Yt+ F Y; •)

Managerial Economics: Applications, Strategies and Tactics (MindTap Course List)

14th Edition

ISBN:9781305506381

Author:James R. McGuigan, R. Charles Moyer, Frederick H.deB. Harris

Publisher:James R. McGuigan, R. Charles Moyer, Frederick H.deB. Harris

Chapter5: Business And Economic Forecasting

Section: Chapter Questions

Problem 5E: A firm experienced the demand shown in the following table. *Unkown future value to be forecast Fill...

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A firm experienced the demand shown in the following table. *Unkown future value to be forecast 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 Y t+1=Yt. Using the forecasts from 2005 through 2009, compare the accuracy of each of the forecasting methods based on the RMSE criterion. Which forecast would you have used for 2010? Why?
Bell Greenhouses has estimated its monthly demand for potting soil to be the following: N=400+4X where N=monthlydemandforbagsofpottingsoil X=timeperiodsinmonths(March2006=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: Forecast Bell Greenhouses demand for potting soil in March, June, August, and December 2007. If the following table shows the forecasted and actual potting soil sales by Bell Greenhouses for April in five different years, determine the seasonal adjustment factor to be used in making an April 2008 forecast.
A firm keeps a record of sales and prices over the past seven months, resulting in the following table: Price (ZMW/ton) Sales (tons) Nov. 1985 7.5 84.5 Dec. 8.0 82.0 Jan. 1986 8.0 84.0 Feb. 7.2 92.0 March 7.0 95.0 April 8.0 92.0 May 8.5 91.5 Use these observations to estimate demand as a linear function of both price and time. Further, utilise this function to estimate demand for the following month, on the assumption that: (a) price remains unchanged, (b) price increases to ZMW9/ton. Hence estimate the price elasticity of demand between these prices and find the price which would maximise sales revenue. Given the nature of the observations, comment on any difficulties in interpreting your results for decision-making purposes.
AD has estimated the following demand relationship for its product over the last four years, using monthly observations: ln Qt = 4.932- 1.238 ln Pt + 1.524 ln Yt-1 + 0.4865lnQt-1(2.54) (1.38) (3.65) (2.87)R2= 0.8738where Q = sales in units, P = price in Rs., Y is income in Rs,000, and the numbers in brackets are t-statistics.a. Interpret the above model.b. Make a sales forecast if price is Rs. 9, income last month was Rs. 25,000 and sales last month were 2,981 units.c. Make a sales forecast for the following month if there is no change in price or income.d. If price is increased by 5 per cent in general terms, estimate the effect on sales, stating any assumptions.
21. Consider a firm subject to quarter-to-quarter variation in its sales. Suppose that the following equation was estimated using quarterly data for the period 2011–2018 (the time variable goes from 1 to 32). The variables D1, D2, and D3 are, respectively, dummy variables for the first, second, and third quarters (e.g., D1 is equal to 1 in the first quarter and 0 otherwise). Qt =a+bt+c1D1+c2D2+c3D3 The results of the estimation are presented here: a. Calculate the intercept in each of the four quarters. What do these values imply? b. Use this estimated equation to forecast sales in the fourth quarter of 2019.
As a manager of a small software retailing company, you are concerned with projected profit next year. While profit can be determined as the difference between sales and maintenance cost, or in symbols, P = S - M, where P is profit, S is sales, and M is maintenance cost including technical support. It is argues that when sales goes up so does maintenance cost because the cost of technical support will go up. Further, it is measured that the correlation between S and M is 0.8. Now given the figure that sales next year is expected to be $300 thousand with standard deviation of $4 thousand and maintenance cost is expected to be $150 thousand with standard deviation of $6 thousand, what would be the expected profit and its standard deviation you will include in your report?
part a b and c solved Suppose that a coffee producing firm estimated the following regression of thedemand for its brand of coffee:Qc = 1.5 − 3.0Pc + 0.8Y + 2.0Pb − 0.6PS +1.2 Awhere Qc = sales of coffee brand C, in dollarsper pound Pc = price of coffee brand C,in dollars per poundY = personal disposable income, in millions of dollars per yearPb = price of the competitive brand of coffee, in dollarsper pound Ps = price of sugar, in dollars per poundA = advertising expenditures for coffee brand C, in hundreds of thousands ofdollars per year.Suppose also that this year, Pc = $2, Y = $2.5, Pb = $1.80,Ps = $1 and A =$1.a. Interpret the results of the estimated demand.b. Compute point price elasticity of demand for the firm’s brand of coffeewith respect to its price.c. Compute the cross-price elasticity of demand for coffee with respect to theprice of competitive coffee brand b.d. At the current price level, would it be viable for the firm to increase the pricelevel of its brand of coffee?…
kad has estimated the following demand relationship for its product over the last four years, using monthly observations: ln qt = 4.932- 1.238 ln pt + 1.524 ln yt-1 + 0.4865ln qt-1 (2.54) (1.38) (3.65) (2.87) r 2= 0.8738 where q = sales in units, p = price in rs., y is income in rs,000, and the numbers in brackets are t-statistics. a. interpret the above model. b. make a sales forecast if price is rs. 9, income last month was rs. 25,000 and sales last month were 2,981 units. c. make a sales forecast for the following month if there is no change in price or income. d. if price is increased by 5 per cent in general terms, estimate the effect on sales, stating any assumptions.
19. Suppose Q is related to L and K in the following nonlinear way: Q = aLbK c a. How well does this nonlinear model fit the data? b. Write the estimated equation in either the log-linear form or the nonlinear way. c. What is the estimated elasticity of L? Of K?
Demand for Orange Juice is given asQd = 5000 – 2500 P + 1200 I + 650 E – 255 PsSuppose Income is I = Rs.500, Expectations E = 55, and Price of Ps = Rs 25.a. Find the Demand Equation.b. Using the demand function from part a.,Calculate Elasticity of Demand for price range of Rs.125 and Rs.155.c. What will be the ‘Price Elasticity of Demand’ at P = Rs.125?d. Interpret the Elasticity of Demand calculated in (C) above.
A printer manufacturer estimates that the average purchaser of a printer will also purchase six ink refills over the lifetime of the printer. The relevant data are: Printer: price: $400, margin: $100 Refills: price: $40, margin: $30 The manufacturer is considering increasing the price of printers by 10% to $440. What volume decrease in the sales of printers is the stay-even sales change for the firm? (Ignore the issue of discounting the value of future ink refill sales. Imagine, for example, that all six are purchased upfront with the printer). A. 11.5% B. 12.5% C. 13.5% D. 14.5% Use = % Q = (Pold - Cold)/(Pnew - Cold) - 1
FORCASTING Month Time QJan 1 46Feb 2 56Mar 3 72Apr 4 67May 5 77Jun 6 66Jul 7 69Aug 8 79Sep 9 88Oct 10 91Nov 11 94Dec 12 104Jan ?Feb ? Make a forecast of the demand for the month of January and February