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: Cengage Learning
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Chapter 4, Problem 1.3CE
To determine
To observe: The biased data in the parameter
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An analyst working for your firm provided an estimated log-linear demand function based on the
natural logarithm of the quantity sold, price, and the average income of consumers. Results are
summarized in the following table:
SUMMARY OUTPUT
Regression Statistics
Multiple R
R Square
Adjusted R Square
Standard Error
Observations
ANOVA
Regression
Residual
Total
Intercept
LN Price
LN Income
df
0.968
0.937
0.933
0.003
30
SS
MS
F
2 0.003637484 0.001818742 202.48598
0.000242516 8.98206E-06
27
29
0.00388
Coefficients Standard Error
0.57
0.00
0.13
0.51
-0.08
0.15
t Stat
0.90
-19.50
1.13
P-value
0.37
0.00
0.27
Significance F
5.55598E-17
Lower 95%
-0.65
-0.09
-0.12
How would a 4 percent increase in income impact the demand for your product?
Demand would increase by 60 percent.
Demand would increase by 0.6 percent.
Demand would decrease by 60 percent.
Demand would decrease by 0.6 percent.
Upper 95%
1.68
-0.07
0.41
10. Residual analysis
Consider a regression of y on several independent variables, and the resulting predicted values of the dependent variable.
The residual for the ith observation
Consider a data set for a large sample of professional basketball players. Each observation contains the salary, as well as various performance
statistics such as points, rebounds, and assists for each player.
Suppose a regression of salary on all performance statistics is run, and the residuals are obtained. The player with the lowest (most negative) resid
represents which of the following? (Assume the regression reasonably predicts salaries in most cases.)
The most fairly paid player relative to her on-court performance
The most overpaid player relative to her on-court performance
The highest-paid player, regardless of her on-court performance
The most underpaid player relative to her on-court performance
The demand equation for a popular brand of fruit drink is given by the equation
Qx=10-5Px+0.00I +10Py
where Qx=monthly consumption per family in gallons
Px=price per gallon of the fruit drink=GHC2.00
I=median annual family income=GHC20,000
Py=price per gallon of a competing brand of fruit drink=GHC2.5
a.Interpret the parameter estimates
b.At the stated values of the explanatory variables,calculate the monthly consumption(gallons)of the fruit drink
c.suppose that median annual family income increased to GHC30,000.How does this change your answer to part b?
Chapter 4 Solutions
Managerial Economics: Applications, Strategies and Tactics (MindTap Course List)
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- 1. An analyst from your firm used a linear demand specification to estimate the demand for its product and sent you a hard copy of the results: SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations ANOVA Regression Residual Total Intercept Price of X Income 0.38 0.14 0.13 20.77 150 df 2 147 149 SS 58.87 -1.64 1.11 10398.87 63408.62 73807.49 Coefficients Standard Error 15.33 0.85 0.24 MS 5199.43 431.35 t Stat 3.84 -1.93 4.63 F 12.05 P-value 0.00 0.06 0.00 Significance F 0 Lower 95% 28.59 -3.31 0.63 Upper 95% b. Which regression coefficients are statistically significant at the 5 percent level? a. Based on these estimates, write an equation that summarizes the demand for the firm's product. 89.15 0.04 1.56 C. When price is $10, what is the income elasticity for this product for an income level of 35?arrow_forwardThe best way to interpret polynomial regressions is to: A. look at the t-statistics for the relevant coefficients. B. analyze the standard error of estimated effect. C. plot the estimated regression function and to calculate the estimated effect on Y associated with a change in X for one or more values of X. D. take a derivative of Y with respect to the relevant X.arrow_forwardSally Sells Sea Shells by the Sea Shore and collects all sales dataNow she is curious to find out what the elasticity of demand is for her shells Assume they are all the same type and quantity She scatter plots the data and finds there is a linear relationship that looks ripe for a regression estimation of the price response function for her shells The slope of her regression line is 61. Currently, her average daily price is 11.74 and she sells 95 quantity at that priceCalculate the point elasticity of demand for her sea shellsarrow_forward
- Using a sample of recent university graduates, you estimate a simple linear regression using initial annual salary as the dependent variable and the graduate's weighted average mark (WAM) as the explanatory variable. If the regression model has an estimated intercept of 3200 and an estimated slope coefficient of 550, what is the predicted starting salary of a student with a WAM of 69? Answer:arrow_forwardSuppose you are the manager of a firm that produces good X in Ghana. In order to make informed decision, you engaged an economist to estimate the demand equation for your product. Using data from 30 supermarkets around the country for the month of April, 2021, the estimated linear regression result for your product is shown in the table below: Variable Parameter Estimates Standard error Constant -164.0 20.24 Price of good X (P,) Price of good Y (P,) -3.50 1.55 2.50 0.28 Per capita Income (/) 0.45 0.52 R-squared 0.8672 Adjusted R-squared 0.8132 F-statistic 15.6893 a) Suppose the average price of 3 units of good X is GH¢12, price of 2 units of goodY is GH¢60, the per capita income of Ghana is GH¢420. 1. Write down the estimated demand equation for your firm's product and interpret the parameter estimates. Determine the quantity of good X sold. Estimate the own price elasticity of demand and state the type of demand curve 11. 111. your firm has?arrow_forwardYour 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…arrow_forward
- TRUE OR FALSE? If a plot of the actual data points falls along a convex (bowed inward) curve, specifying the demand function as Q^d= a - b x P makes it impossible to estimate a regression.arrow_forwardDefine coefficients of the Linear Regression Model?arrow_forwardYou are the manager of a firm that produces a vegetable cooking oil in Ghana. In order to make informed decision, you engaged an economist to estimate the demand equation for your product. Using data from 25 supermarkets around the country for the month of February, 2021, the estimated linear regression result for your product is shown in the table below: Variable Constant Parameter Estimates Standard error -164.0 20.24 Price of vegetable cooking oil (P,) Price of palm oil (P,) Per capita Income () -3.50 1.55 2,50 0.28 0.45 0.52 R-squared 0.8672 Adjusted R-squared 0.8132 F-statistic 15.6893 a) Suppose the average price of 3 gallons of vegetable cooking oil is GH¢12, price of 2 gallons of palm oil is GH¢60, the per capita income of Ghana is GH¢420. i. Write down the estimated demand equation for your firm's product and interpret the parameter estimates. ii. Detemine the quantity of vegetable cooking oil sold. Estimate the own price elasticity of demand and state the type of demand curve…arrow_forward
- 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.…arrow_forwardQuantile regression (QR) is different from OLS in that: a. QR estimates marginal effects at the mean values of the dependent variables. b. QR does not estimate marginal effects at the mean values of the dependent and independent variables. c. QR minimizes the sum of squared residuals to obtain the coefficient estimates. d. QR only uses the data below the quantile where the quantile regression is being estimated.arrow_forwardIf we run a regression where y (bankruptcy) = f (factors potentially predicting bankruptcy), what is the dependent variable?arrow_forward
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