3. (20 points) An MBA student has proposed the following demand equation for good Y. QdY = a + b PY + c M where: QdY = quantity demanded of good Y in millions of tons per year PY = price of good Y in dollars per ton M = average consumer income in thousands of dollars. The regression output from the computer is as follows: Dependent Variable: QdY R-Square F-ratio p-value on; F Observations: 90 .4 12.84 0.015 Variable Parameter Estimate Standard Error T-ratio P-Value Intercept 60.00 5468.32 3.12 0.0082 PY -1.00 0.65 -1.27 0.2145 M 0.02 3.29 5.12 0.0121. This economist is comfortable using parameter estimates that are statistically significant at the 10 percent level or better.
iv.
What fraction of the total variation in the quantity demanded of good Y remains unexplained?
What can the student do to increase the explanatory power of his demand equation?
What other variables might he add to his demand equation?
3. (20 points) An MBA student has proposed the following demand equation for good Y. QdY = a + b PY + c M where: QdY = quantity demanded of good Y in millions of tons per year PY = price of good Y in dollars per ton M = average consumer income in thousands of dollars. The regression output from the computer is as follows: Dependent Variable: QdY R-Square F-ratio p-value on; F Observations: 90 .4 12.84 0.015 Variable Parameter Estimate Standard Error T-ratio P-Value Intercept 60.00 5468.32 3.12 0.0082 PY -1.00 0.65 -1.27 0.2145 M 0.02 3.29 5.12 0.0121. This economist is comfortable using parameter estimates that are statistically significant at the 10 percent level or better.
iv.
What fraction of the total variation in the quantity demanded of good Y remains unexplained?
What can the student do to increase the explanatory power of his demand equation?
What other variables might he add to his demand equation?
