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Running head: 640 WEEK 2 ASIGNMENT 2 Consumer Demand Analysis and Estimation Applied Problems Name Ashford University Managerial economics BUS 640 Dr. Sayim January 14, 2013 1 640 WEEK 2 ASIGNMENT 2 2 640 Week 2 Assignment 2 Please, complete the following 3 applied problems in a Word or Excel document. Show all your calculations and explain your results. Submit your assignment in the drop box by using the Assignment Submission button. 1. Roshima is researching universities where she could study for her MBA degree. She is considering 3 major attributes that she considers important in her choice: ranking, price, and location. The value she places on each attribute, however, differs according to whether she remains full-time employed during her studies or quits her job and focuses on her degree. If she continues to work full time and takes all her courses online, then ranking is the most important attribute, twice as important as price and three times as important as location. If she quits her job and attends school full time, then location becomes three times as important as ranking and twice as important as price. She is considering two universities, respectively, the MBA program at Arizona State University (ASU) and the MBA program at University of Phoenix (UOP), both of which are priced at approximately $25,000. She has rated each attribute on a scale of 1 to 100 for each of the two schools. Attribute Ranking ASU 80 UOP 70 Location 50 70 Price 45 45 Problem 1 Attribute Ranking = r Location = l Price = p Keeps job (EU) Quits job (EU) ASU 80 50 45 119.17 51.17 UOP 70 70 45 115.83 115.83 Keeps job = Quits job = r=2p r=3l l=3r l=2p ASU 9533.333333 2558.333333 UOP 8108.33 8108.33 640 WEEK 2 ASIGNMENT 2 3 a. Which of the two options should Roshima pursue of she wants to keep her full-time job? (Calculate the total expected utility from each school option and compare. Graph is not required) She should go to ASU its EU is 119.17 which is an EU that is better than the UOP EU by 3.36. UOP = 115.83 for UE b. Which of the two options should she pick if she plans to quit her job and dedicate to her studies? She should pick UOP with an EU of115.83 verses an ASU EU of 51.17 c. Which option should she pursue if the probability of being laid off and unable to find a new job is estimated as 0.6? Show your calculations and explain your reasoning. EU keep job with .6 probability of layoff and no job. EU= .6*119.17*r+.6*297.5*r = .6*119.17*90+.6*297.5*90= 172,318,009.50 EU Quit job. EU=.6*115.83*90+.6*347.5*90= 195,638,260.50 She should quit and go to the university of Phoenix 2. The demand function for Einstein Bagels has been estimated as follows: Qx = -15.87 – 40.73Px + 84.17Py + 0.55Ax where Qx represents thousands of bagels; Px is the price per bagel; Py is the average price per bagel of other brands of bagels; and Ax represents thousands of dollars spent advertising Einstein Bagels. The current values of the independent variables are Ax=216, Px=0.85, and Py=0.79. 640 WEEK 2 ASIGNMENT 2 4 Problem 2 original Qx = bagels Px = price per Einstein brand Py = price per other brand Ax = advertising dollars (a) Price elasticity variable -15.87 40.73 84.17 0.55 Einstein Brand change in demand = = = 134.8038 0.256821395 26% = 128.6943 32% (b) Price elasticity change in price ( c) Profit maximizing total revenue total cost total profit 114.58323 13.48038 $ 101.10 (d) advertising 88% a. Calculate the price elasticity of demand for Einstein’s Bagels and explain what it means. % change Qdx/ % change Px = Price elasticity of demand new 0.85 0.79 216 34. 66. 1 640 WEEK 2 ASIGNMENT 2 .2486 = .2925 5 Price elasticity of demand=.2925 .85 This is an inelastic price item. Any number < than 1 the price of demand is inelastic. b. Derive an expression for the (inverse) demand curve for Einsteins’s Bagels. As price for bagels rises, demand remains constant c. If the cost of producing Einstein’s Bagels is constant at $0.10 per bagel, should they reduce price and thereafter, sell more bagels (assume profit maximization is the company’s goal)? No, this is an inelastic product the return would not justify the reduction. d. Should Einstein Bagels spend more on advertising? No, their Budget is adequate. 3. The consulting firm that you work for has been hired by the US Government to provide an independent analysis of the demand-side effects of a contemplated increase in the tax on gasoline. They provide you with a data set relating to the period 1962-1987, which they say contains valuable historic lessons relating to the impact of volatile pump prices due to the supply restrictions imposed by the Organization of Petroleum Exporting Countries (OPEC), and the Corporate Average Fuel Economy (CAFE) regulations that required car manufacturers to increase the fuel efficiency of the cars they sold, while at the same time Real Disposable Income (RDI) per capita was rising, the number of passenger cars (NPC) almost doubled, and inflation was pushing up the Consumer Price Index (CPI). a. Reconcile the fact that while the quantity demanded of gasoline and pump prices both rise over this period generally, they are inversely related along a demand curve. `It is true that normally the quantity demanded of gasoline is inversely proportional to pump prices. The reason that this is not true during this period is that there were external variances that were so large that they could all be considered outliers compared to a normal demand curve. Curves and graphs in economics show probability due to the collection and analyst rational of data and portray the continuance of the norm. The numbers during this timeframe were just not normal. 640 WEEK 2 ASIGNMENT 2 6 b.Conduct a multiple regression analysis to explain the quantity demanded of gasoline in terms of the other data provided. (Transpose this data into an Excel spread-sheet and use the Excel regression tool, if loaded, or alternatively download an ‘add-in’ regression program such as ‘Statpro’ to find the regression statistics). SUMMARY OUTPUT Regression Statistics Multiple R 0.991823 R Square 0.983713 Adjusted R Square 0.979426 Standard Error 1544.571 Observations 25 ANOVA df Regression Residual Total Intercept X Variable 1 X Variable 2 X Variable 3 5 19 24 Coefficients 82547.14 -142.647 0.638322 -6224.56 SS 2.74E+09 45328310 2.78E+09 Significance MS F F 5.48E+08 229.5094 2.67E-16 2385701 Standard Error t Stat P-value 26132.28 3.158819 0.00517 46.47614 -3.06926 0.006313 0.243492 2.621533 0.016795 1743.79 -3.56956 0.002045 Upper Lower Upper Lower 95% 95% 95.0% 95.0% 27851.65 137242.6 27851.65 137242.6 -239.923 -45.3716 -239.923 -45.3716 0.128688 1.147956 0.128688 1.147956 -9874.35 -2574.76 -9874.35 -2574.76 640 WEEK 2 ASIGNMENT 2 X Variable 4 X Variable 5 0.778334 53.13485 7 2.598568 0.299524 0.767792 76.26494 0.696714 0.494418 -4.66053 6.2172 -106.49 212.7592 -4.66053 6.2172 -106.49 212.7592 Upper 95% #N/A 44.19799 1.603837 176.3975 5.504301 -143.256 Lower 95.0% #N/A -84.7854 0.678775 -1933.4 -7.27438 -221.996 640 WEEK 2 ASIGNMENT 2 8 c What proportion of the variance in Qx is explained by these other variables? What missing variables might account for the remainder of the variance in the quantity demanded of gasoline? 5%, extra miles driven or not driven due to price of gas rising and inflation d. Use the regression equation to predict the quantity demanded of gasoline in 1988 for the values Px = 68.5; NPC = 145,885; MPG = 20.36; RDI = 11,192; and CPI = 354.6. 1988 Qx= 83,245.14 e. What is the 95% confidence interval for your prediction? The equation covers 95 % of variance the other 5% is mostly located in the x variables.