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 2 27 29 Coefficients 0.51 -0.08 0.15 SS MS F Significance F 0.003637484 0.001818742 202.48598 5.55598E-17 0.000242516 8.98206E-06 0.00388 Standard Error 0.57 0.00 0.13 t Stat 0.90 -19.50 1.13 P-value 0.37 0.00 0.27 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
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 2 27 29 Coefficients 0.51 -0.08 0.15 SS MS F Significance F 0.003637484 0.001818742 202.48598 5.55598E-17 0.000242516 8.98206E-06 0.00388 Standard Error 0.57 0.00 0.13 t Stat 0.90 -19.50 1.13 P-value 0.37 0.00 0.27 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
Chapter1: Introducing The Economic Way Of Thinking
Section1.A: Applying Graphs To Economics
Problem 2SQP
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