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Managerial Economics and Business Strategy - Regression Questions

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Problem # 10
You are the manager of a firm that sells a leading brand of alkaline batteries. The accompanying Excel file contains data on the demand for your product. Specifically, the file contains data on the natural logarithm of your quantity sold, price, and the average income of consumers in various regions around the world. Use this information to perform a log-linear regression, and then determine the likely impact of a 3 percent decline in global income on the overall demand for your product.

Problem # 15
As a newly appointed "Energy Czar," your goal is to reduce the total demand for residential heating fuel in your state. You must choose one of three legislative proposals designed to accomplish this goal: (a) a tax that would effectively increase the price of residential heating fuel by $2; (b) a subsidy that would effectively reduce the price of natural gas by $1; or (c) a tax that would effectively increase the price of electricity (produced by hydroelectric facilities) by $5. To assist you in your decision, an economist in your office has estimated the demand for residential heating fuel using a linear demand specification. The regression results are presented below. Based on this information, which proposal would you favor? Explain.

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The solutions answers 2 questions on regression from Managerial Economics and Business Strategy, Fourth Edition by Michael R. Baye.

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Problem # 15
As a newly appointed "Energy Czar," your goal is to reduce the total demand for residential heating fuel in your state. You must choose one of three legislative proposals designed to accomplish this goal: (a) a tax that would effectively increase the price of residential heating fuel by $2; (b) a subsidy that would effectively reduce the price of natural gas by $1; or (c) a tax that would effectively increase the price of electricity (produced by hydroelectric facilities) by $5. To assist you in your decision, an economist in your office has estimated the demand for residential heating fuel using a linear demand specification. The regression results are presented below. Based on this information, which proposal would you favor? Explain.

SUMMARY OUTPUT

Regression statistics
Multiple R 0.76
R-Square 0.57
Adjusted R-Square 0.49
Standard Error 47.13
Observations 25

Analysis of Variance
Degrees of freedom Sum of Squares Mean Square F Significance F
Regression 4 60936.56 15234.14 6.86 0.03
Residual 20 44431.27 2221.56
Total 24 105367.84

Coefficients Standard Error t-Statistic P-Value Lower 95% Upper 95%
Intercept 136.96 43.46 3.15 0.01 50.6 223.32
Price of residential heating fuel -91.69 29.09 -3.15 0.01 -149.49 -33.89
Price of natural ...

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