eneral Cereals is using a regression model to estimate the demand for Tweetie Sweeties, a whistle-shaped, sugar-coated breakfast cereal for children. The following (multiplicative exponential) demand function is being used: QD=6,280 P(−1.85)A2.05N2.70QD=6,280 P−1.85A2.05N2.70 where QDQD = quantity demanded, in 10-oz boxes PP = price per box, in dollars AA = advertising expenditures on daytime television, in dollars NN = proportion of the population under 12 years old, in percent What is the point price elasticity of demand for Tweetie Sweeties? 2.05 2.70 -0.90 -1.85 What is the advertising elasticity of demand? 0.76 -1.85 2.70 2.05

eneral Cereals is using a regression model to estimate the demand for Tweetie Sweeties, a whistle-shaped, sugar-coated breakfast cereal for children. The following (multiplicative exponential) demand function is being used: QD=6,280 P(−1.85)A2.05N2.70QD=6,280 P−1.85A2.05N2.70 where QDQD = quantity demanded, in 10-oz boxes PP = price per box, in dollars AA = advertising expenditures on daytime television, in dollars NN = proportion of the population under 12 years old, in percent What is the point price elasticity of demand for Tweetie Sweeties? 2.05 2.70 -0.90 -1.85 What is the advertising elasticity of demand? 0.76 -1.85 2.70 2.05

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

Chapter4: Estimating Demand

Section: Chapter Questions

Problem 5E

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Q. Wilpen Company, a price-setting firm, produces nearly 80 percent of all tennis balls purchased in the United States. Wilpen estimates the U.S. demand for its tennis balls by using the following linear specification: Q = a + bP + cM + dPR. Where Q is the number of cans of tennis balls sold quarterly, P is the wholesale price Wilpen charges for a can of tennis balls, M is the consumers’ average household income, and PR is the average price of tennis rackets. The regression results are as follows: a- Discuss the statistical significance of the parameter estimates a^, b^, c^, and d^ using the p-values. Are the signs of b^, c^, and d^ consistent with the theory of demand? Wilpen plans to charge a wholesale price of $1.65 per can. The average price of a tennis racket is $110, and consumers’ average household income is $24,600. b. What is the estimated number of cans of tennis balls demanded? c) At the values of P, M, and Pr given, what are the estimated values of the price (E^), income…
Q. Wilpen Company, a price-setting firm, produces nearly 80 percent of all tennis balls purchased in the United States. Wilpen estimates the U.S. demand for its tennis balls by using the following linear specification: Q = a + bP + cM + dPR. Where Q is the number of cans of tennis balls sold quarterly, P is the wholesale price Wilpen charges for a can of tennis balls, M is the consumers’ average household income, and PR is the average price of tennis rackets. The regression results are as follows: a. Discuss the statistical significance of the parameter estimates a^, b^, c^, and d^ using the p-values. Are the signs of b^, c^, and d^ consistent with the theory of demand? Wilpen plans to charge a wholesale price of $1.65 per can. The average price of a tennis racket is $110, and consumers’ average household income is $24,600. b. What is the estimated number of cans of tennis balls demanded? c) At the values of P, M, and Pr given, what are the estimated values of the price (E^), income…
Please no written by hand and no emage Your company, which specializes in running shoes for men who are growing increasingly follicly-challenged (BalderDash®), has the following demand function: Q = a + bP + cM + dR where Q is the quantity demanded of BalderDash’s most popular shoes, P is the price of that product, M is consumer income, and R is the price of a related product. The regression results are: Adjusted R Square 0.7796 Independent Variables Coefficients Standard Error t Stat P-value Intercept 21,055.04 1428.27 14.74 8.1E-16 P -83.912 19.079 -4.398 0.000 M 0.0266 0.013 2.064 0.047 R -16.6 10.664 -1.556 0.129 Discuss whether you think these regression results will generate good sales estimates for BalderDash. Now assume that the income is $69,100, the price of the related good is $39, and BalderDash chooses to set the price of its product at $54. b. What is the estimated number of units sold given the data above? (round to nearest unit; no decimals) c.…
The multivariate demand function below will be needed for questions 12-18. Setting: Grapple, Inc. is a leading seller of laptop personal computers. However, they want to become a leading tablet seller, too. Your marketing department, aided by your economics staff, has estimated a function to help you in the quest for market leader in tablets. The variables are defined after the function. Qg = the number of Grapple tablet computers demanded per week. Pg = the price of each new Grapple tablet (in $). Ph = the price of each Hewpaq tablet (in $). Pr = the price of each Ronova tablet. Pdv = the price to equip a tablet with Holographic digital video (in $, this is an upgrade option that enables three-dimensional graphics on a tablet. Two-dimensional graphics is standard equipment). Psc = the price of various screen sizes (in $, a 8 inch is standard, but upgrade options are 10 inch extra sharp, 12 inch, 12 inch extra sharp, Each also has a touch-screen option. The upgrades…
Demand for Magnum Ice Cream is given by an equation Q = - 5,000 – 40P + 20Px + 5I + 0.2A Where, Q = Quantity of Magnum demanded, P = Price of Magnum Ice Cream, Px = Price of Walls Ice Cream, I = Per Capita Income and A = advertisement expenditure. State and elaborate the key steps for analyzing regression results of demand. Assume P = Rs 500, Px = Rs 600, I = Rs 5,000 and A = 10,000 (Rs in thousands). Calculate elasticities for each of the variables: Price Elasticity of Demand Cross Price Elasticity of Demand Income Elasticity of Demand Advertisement Elasticity 3. How does each of the elasticities help in managerial decision making? Given these estimates should Magnum consider reducing its price to increase market share? Explain.
Imagine that you work for the maker of a leading brand of low-calorie, frozen microwavable food that estimates the following demand equation for its product using data from 26 supermarkets around the country for the month of April. Note: The following is a regression equation. Standard errors are in parentheses for the demand for widgets. QD = - 5200 - 42P + 20PX + 5.2I + 0.20A + 0.25M (2.002) (17.5) (6.2) (2.5) (0.09) (0.21) R2 = 0.55 n = 26 F = 4.88 Your supervisor has asked you to compute the elasticities for each independent variable. Assume the following values for the independent variables: Q = Quantity demanded of 3-pack units P (in cents) = Price of the product = 500 cents per 3-pack unit PX (in cents) = Price of leading competitor's product = 600 cents per 3-pack unit I (in dollars) = Per capita income of the standard metropolitan statistical area (SMSA) in…
Using regression analysis on data from a field experiment, the demand curve for a product is estimated to be QXd = 1,200 − 3PX − 0.1PZ where Pz = $300. a. What is the own price elasticity of demand when Px = $140? Is demand elastic or inelastic at this price? b. What is the own price elasticity of demand when Px = $240? Is demand elastic or inelastic at this price? c. What is the cross-price elasticity of demand between good X and good Z when Px = $140?
Suppose that an economist has been able to gather data on the relationship between demand and price for a particular product. After analyzing scatterplots and using economic theory, the economist decides to estimate an equation of the form Q= aPb, where Q is quantity demanded and P is price. An appropriate regression analysis is then performed, and the estimated parameters turn out to be a = 1000 and b = - 1.3. Now consider two scenarios: (1) the price increases from $10 to $12.50; (2) the price increases from $20 to $25. a. Do you predict the percentage decrease in demand to be the same in scenario 1 as in scenario 2? Why or why not? b. What is the predicted percentage decrease in demand in scenario 1? What about scenario 2? Be as exact as possible.
Consider the file demand.xlsx which contains the demand observed for different levels of pricing for a product. Produce a scatter plot of demand vs price. Use trendline to fit a linear and a power function to estimate demand as a function of price. price demand 18.05 1490 13.17 4094 15.17 2784 16.83 2888 18.64 1334 11.95 3573 14.88 2961 17.04 1790 14.15 3664 17.56 1632 20.1 1564 10.21 5583 14.1 2767 13.64 3686 11 3002 20.16 1316 13.47 3661 15.77 479 17.7 1612 15.58 3287 14.33 3750 18.91 1245 20.77 1415 11.83 4643 12.32 3942 20.13 1558 12.71 4045 16.04 2843 13.99 3332 17.97 2373 12.61 3357 13.66 2884
The following regression is the demand for free-range chicken, which was estimated from (actual) nationwide data provided by a large UK retailer over a two-year period Qx= 229,821 - 38,121 Px + 28,826 Py, where: Qx = quantity of free-range chicken sold (number of units), Px = average price of free-range chicken ; and Py = average price of standard non-free-range chicken(f). The average for these variables in these two years are: Qx= 117,735, Px= f 5.56 and Py = 3.46. Question: Calculate the values of the two price elasticities (own-price elasticity, and cross-price elasticity) and interpret them, also critically justifying whether they make intuitive sense. Note:- Do not provide handwritten solution. Maintain accuracy and quality in your answer. Take care of plagiarism. Answer completely. You will get up vote for sure.
The demand function for good X is ln Qdx= a + b ln Px + c ln M + e, where Px is the price of good X and M is income. Least squares regression reveals that â = 7.42, b ˆ = −2.18, and ĉ = 0.34. a. If M = 55,000 and Px = 4.39, compute the own price elasticity of demand based on these estimates. Determine whether demand is elastic or inelastic. b. If M = 55,000 and Px = 4.39, compute the income elasticity of demand based on these estimates. Determine whether X is a normal or inferior good.
Using the data below, what is the slope coefficient from a regression of Quantity on Price? It is probably easiest to use either Gretl or Jamovi as in the powerpoint example. (round your answer to the nearest 0.1, and it can be either positive or negative.) Quantity 17 24 23 39 55 54 60 76 71 80 Price 93 77 62 64 47 35 38 12 29 2