Homework SourseThe regression output from the computer is as follows This e
The regression output from the computer is as follows.
This economist is comfortable using parameter estimated that are statistically significant at the 10 percent level or better.
i) Does PY have a statistically significant effect on the quantity demanded of good Y? Explain, using the appropriate p-value.
ii) Does M have a statistically significant effect on the quantity demanded of good Y? Explain, using the appropriate p-value.
iii) 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?
iv) What is the expected quantity demanded of good Y when PY=50 and M=20,000?
| Dependent Variable | QdY | R-Square | F-ratio | p-value on F |
| Observations | 90 | .6 | 12.84 | 0.015 |
| Variable | Parameter Estimate | Standard Error | T-ratio | P-value |
| Intercept | 60.00 | 5468.32 | 3.12 | 0.0082 |
| PY | -2.00 | 0.65 | -2.86 | 0.0145 |
| M | 0.01 | 3.29 | 4.12 | 0.0831 |
Solution
A variable is significant when the p-value is less than the level of significance.
i. The p-value for coefficient of PY variable is 0.0145. This value is less than 0.05, so it is siginficant, even at 5% significance level.
ii. The p-value for coefficient of M variable is 0.0831. This value is less than 0.10, so it is siginficant at 10% significance level.
iii. Fraction of the total variation in the quantity demanded of good Y remains unexplained = 1 - R square
= 1 - 0.6 = 0.4
= 2/5
To increase the explanatory power of his demand equation, the student should involve more independent variables that explain the variation in the quantity demanded.
Other variables that can be added: Price of substitute good, taste of consumers.
iv. When PY=50 and M=20,000, we use the parameter estimates.
Q = 60 - 2*PY + 0.01*M
= 60 - 2*50 + 0.01*20,000
= 160
