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Suppose that an economist has been able to gather data on the relationship between
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.
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- You are the owner of a restaurant located in a beach resort in Hawaii and want to use regression analysis to estimate the demand for your fresh seafood dinners. You have collected data on the daily quantity of seafood dinners sold over the last summer season. In order to correctly specify your regression equation, which of the following variables should be considered? Select one: A. the prices charged for souvenirs in local stores B. the prices charged for scuba diving excursions at the resort C. the wages paid to your chef and servers D. the daily number of vacationers at the resortGeneral 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 2.05If we suppose that the weekly price of milk is $3.40 per gallon and MPEP changes the weekly advertising to $300, the best-fitting regression model to estimate the weekly quantity of milk consumed would be Q = 6.52 - 1.614 (3.40) + .005 (300) = 2.533 gallons of milk. What is the elasticity between $5 and $4? Should you lower or raise price to maximize revenue?
- Imagine you are trying to explain the effect of square footage on home sale prices in the United States. You collect a random sample of 100,000 homes that recently sold. a) Homes can be one of three types: single-family houses, townhomes, or condos. How would you control for a home’s type in a regression model? b) Write down a regression model that includes controls for home type, square footage, and number of bedrooms. c) How would you interpret the es3mated coefficients for each of the variables from part b? Be specific.General 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 1.35) 42.05 N 2.70 where QD quantity demanded, in 10-oz boxes P = price per box, in dollars A = advertising expenditures on daytime television, in dollars N = proportion of the population under 12 years old, in percent What is the point price elasticity of demand for Tweetie Sweeties? O 2.70 O 2.05 -0.66 -1.35 What is the advertising elasticity of demand? -1.35 O 2.70 O 0.76 O 2.05 According to the estimated model, a percent increase in the proportion of the population under 12 years old by percent. the quantity demandedGeneral 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(-2.15) A1.75N2.70 where QD = quantity demanded, in 10-oz boxes P = price per box, in dollars A = advertising expenditures on daytime television, in dollars N = proportion of the population under 12 years old, in percent What is the point price elasticity of demand for Tweetie Sweeties? 1.75 -1.23 2.70 -2.15 What is the advertising elasticity of demand? 0.65 1.75 -2.15 2.70 According to the estimated model, a percent increase in the proportion of the population under 12 years old by percent. the quantity demanded
- Consider the following estimated regression model relating annual salary to years of education and work experience. Estimated Salary=11,681.31+3418.97(Education)+1194.78(Experience) Suppose two employees at the company have been working there for five years. One has a bachelor's degree (8 years of education) and one has a master's degree (10 years of education). How much more money would we expect the employee with a master's degree to make?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, Pis 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 Intercept P Coefficients Standard Error t Stat 21,055.04 1428.27 14.74 8.1E-16 -4.398 0.000 2.064 0.047 -1.556 0.129 Discuss whether you think these regression results will generate good sales estimates for Balder Dash. 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 $54. b. What is the estimated number of units sold given the data above? (round to nearest unit; no decimals) c. What are the values for the own-price, income, and cross-price elasticities? d. If Pincreases by 6%, what would…Refrigerator prices are affected by characteristics such as whether or not the refrigerator is on sale, whether or not it is listed as a Sub- Zero brand, the number of doors (one door or two doors), and the placement of the freezer compartment (top, side, or bottom). The table below shows the regression output from a regression model using the natural log of price as the dependent variable. The model was developed by the Bureau of Labor Statistics. Variable Coefficient Standard Error t Statistic 5.4841 Intercept 0.13081 41.92 Sale price -0.0733 0.0234 -3.13 Sub-Zero brand 1.1196 0.1462 7.66 0.06956 0.005351 13.00 Total capacity (in cubic feet) Two-door, freezer on bottom Two-door, side freezer 0.04657 0.08085 0.58 Two-door, freezer on top 0.03596 -9.55 Base -0.3432 -0.7096 -0.8820 One door with freezer 0.1310 -5.42 -5.92 One door, no freezer 0.1491 (a) Write the regression model, being careful to exclude the base indicator variable. (Negative amounts should be indicated by a minus…
- The Ipod Touch has been out for several years now and a lot of data has been collected. There is a functional relationship between the Price of an IPod Touch and Weekly Demand. Below is a table of data that have been collected Price P ($) Weekly Demand S (1,000s) 150 207 170 208 190 192 210 190 230 185 250 169 A.. Find the linear model that best fits this data using regression and enter the model below (for entry round the slope value to nearest 0.01 and constant parameter to nearest 1) T(p) = Now answer these two questions: B.. What does the model predict will be the weekly demand if the price of an ipod touch is $191 ? (nearest 100) C.. According to the model at what should the price be set in order to have a weekly demand of 194,800 ipod Touches? $ (nearest $1) Note: In the "real" world Apple sold about 20 million Ipod Touch's from Sept. 2007-Sept. 20093. To explain what determine the price of air conditioners, B.T. Ratchford, obtained the following regression results based on a sample of 19 air conditioners: R²=0.84 y=-68.236 +0.023x, +19.729x3, +7.653x (0.005) (8.992) (3.082) se= Where y the price, in dollars x2= the BTU rating of air conditioner x3 the energy efficiency ratio x, the number of settings se standard errors a) Interpret the regression results. b) Do the results make economic sense? c) At 5% significance level, test the hypothesis that the BTU rating has no effect on the price of an air conditioner vs. that it has a positive effect. d) Would you accept the null hypothesis that the three explanatory variables explain a substantial variation in the prices of air conditioners? Show clearly all your calculations.The Physics Club sells E = mc2 T-shirts at the local flea market. Unfortunately, the club's previous administration has been losing money for years, so you decide to do an analysis of the sales. A quadratic regression based on old sales data reveals the following demand equation for the T-shirts. q = −2p2 + 30p (9 ≤ p ≤ 15) Here, p is the price the club charges per T-shirt, and q is the number it can sell each day at the flea market. (a) Obtain a formula for the price elasticity of demand for E = mc2 T-shirts. E = (b) Compute the elasticity of demand if the price is set at $9 per shirt. (Round your answer to two decimal places.) Interpret the result. The demand for E = mc2 T-shirts is going down by about ____% per 1% increase in the price. (c) How much should the Physics Club charge for the T-shirts to obtain the maximum daily revenue? $ What will the revenue be? $