Q1: KSU Products has just carried out a survey of the demand for their guidebooks to spoken Arabic. They have found the following results over the last six months. Sales revenue 356 398 372 360 365 35O Price ($) 4.5 4.0 4.2 4.5 4.3 4.8 a. Estimate an appropriate demand relationship; Q=apb b. Make a forecast of sales revenue for a price of $5, stating any assumptions. c. Éstimate the price elasticity of demand for the data as a whole. d. If price is raised 10 per cent in general terms, what will happen to revenue?
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- Metropolitan Hospital has estimated its average monthly bed needs as N=1,000+9X where X=timeperiod(months);January2002=0 N=monthlybedneeds Assume that no new hospital additions are expected in the area in the foreseeable future. The following monthly seasonal adjustment factors have been estimated, using data from the past five years: Forecast Metropolitans bed demand for January, April, July, November, and December 2007. If the following actual and forecast values for June bed demands have been recorded, what seasonal adjustment factor would you recommend be used in making future June forecasts?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?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.
- 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.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.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
- is the world heading for a recession? explain the conditons under which the world can be classified as being in a recession as COVID-19 persists. explain linking the pandemic to the various stages of a recessionb. Is the World heading for a recession? Explain the conditions under which the world can be classified as being in a recession as COVID-19 persists. Explain linking the pandemic to the various stages of a recession.A manufacturer of entertainment centers uses the completion of new homes as part of their demand forecast. They consider that for every five homes that cost over $300,000 in the city, they make one sale. For every 20 new homes that cost over $150,000 but less than $300,000 in the city, they make one sale. Their projected demand for the future period, before they consider home sales, is for six entertainment centers. They now receive home figures of ten new homes of over $300,000 and 40 new homes of $150,000-$300,000. What should their new forecast be?
- Raul is the marketing manager for a line of skin care products targeted to males between 16 and 35 who have active outdoor lifestyles. He has found through market research the the price elasticity for his most popular sunscreen, which is priced at $22.00 for a 6 oz. tube, is -1.20. Last year Raul sold 125,000 units of the sunscreen. Raul is considering a price reduction on the sunscreen to $18.00. His manager has asked Raul for a forecast of the units he should expect to sell at the reduced price. What forecast should Raul provide to his manager? Group of answer choices about 145.000 units about 130,000 units about 152,000 units about 27,000 unitsSuppose that you work for a U.S. senator who is contemplating writing a bill that would put a national sales tax in place. Because the tax would be levied on the sales revenue of retail stores, the senator has asked you to prepare a forecast of retail store sales for year 8, based on data from year 1 through year 7. The data are: (c1p2) Year Retail Store Sales 1 $1,225 2 1,285 3 1,359 4 1,392 5 1,443 6 1,474 7 1,467 54 Chapter One a. Use the first naive forecasting model presented in this chapter to prepare a forecast of retail store sales for each year from 2 through 8. b. Prepare a time-series graph of the actual and forecast values of retail store sales for the entire period. (You will not have a forecast for year 1 or an actual value for year 8.) c. Calculate the root-mean-squared error for your forecast series using the values for year 2 through year 7. 3. Use the second naive forecasting model presented in this chapter to answer parts (a) through (c) of Exercise 2. Use P 0.2 in…An analyst for FoodMax estimates that the demand for its Brand X potato chips is given by ln QdX = 12.14 – 2.8 ln PX + 3.4PY + 0.7 ln AX, where Qx and PX are the respective quantity and price of a four-ounce bag of Brand X potato chips, PY is the price of a six-ounce bag sold by its only competitor, and AX is FoodMax’s level of advertising on Brand X potato chips. Last year, FoodMax sold 7 million bags of Brand X chips and spent $0.42 million on advertising. Its plant lease is $2.1 million (this annual contract includes utilities) and its depreciation charge for capital equipment was $2.8 million; payments to employees (all of whom earn annual salaries) were $0.8 million. The only other costs associated with manufacturing and distributing Brand X chips are the costs of raw potatoes, peanut oil, and bags; last year FoodMax spent $2.8 million on these items, which were purchased in competitive input markets. Based on this information, what is the profit-maximizing price for a bag of…