1. Suppose demand for a product is determined by its price, consumers' income, and the price of a related good. Use Q for demand, P for price, M for income, and PR for price of related good. The demand function is estimated using regression analysis. The results are reported below:
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SUMMARY OUTPUT
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Regression Statistics
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Multiple R
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0.814752135
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R Square
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0.663821042
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Adjusted R Square
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0.159552605
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Standard Error
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530.2842631
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Observations
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66
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Coefficients
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Standard Error
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t Stat
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P-value
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Intercept
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125.56
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15.87
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P
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-5.39
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2.19
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7.1001
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M
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0.069
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0.046
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PR
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-10.98
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2.73
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1) What is the of this regression? R² is how statistically close by measure the data is to the regression line.
2) What is the degrees of freedom of this regression?
66-2 = 64 degrees at .05 = 1.669
3) What is the effect of a one-dollar increase in price (P) on demand (Q)?
4) What is the effect of a one-dollar increase in income (M) on demand (Q)?
5) What is the effect of a one-dollar increase in price of related good (PR) on demand (Q)?
6) Calculate the t Stat (or t ratio marked with "???" in the table) for the coefficient on P?t= 7.1007992
7) Test whether the effect of P on Q is significant at the 5% significance level. Show your work.
8) Using the p-value 0.046 in the table, test if the effect of M on Q is significant at the 5% significance level.
9) Using the values P=100, M=35,000, and PR=40, predict the demand (Q)?
10) Using the value of predicted Q you just calculated for part 9), calculate the estimates of
The price elasticity of demand. Show your work.
The income elasticity of demand. Show your work.
The cross-price elasticity of demand. Show your work.
2. Suppose the following is an estimated log-linear demand function:
ln Q = 8.99 - 3.78 ln P - 1.77 ln M - 2.03 ln PR
All parameter estimates are significant.
1) Is this good a normal or an inferior good?
2) Is this good a complement of or substitute for the related good?
3) What is the price elasticity of demand for this good?
4) What is the income elasticity of demand for this good?