Dependent Variable: WHY Method: Least Squares Sample(adjusted): 19652006 Included observations: 30 atter adjusting endpoints $\begin{array}{lllll} \hline \text { Variable } & \text { Coefficient } & \text { Std. Error } & \text { t-Statistic } & \text { Prob. } \ \hline \hline \text { C } & -19.60486 & 123.5064 & -0.158736 & 0.8747 \ \text { EX1 } & 20.04112 & 12.56987 & 1.594377 & 0.1189 \ \text { EX2 } & 0.517140 & 0.007738 & 66.83540 & 0.0000 \ \hline \text { R-squared } & 0.991948 &\text { Mean dependent var } && 2775.633 \ \text { Adjusted R-squared } & 0.991536 & \text { S.D. dependent var } && 1915.813 \ \text { S.E. of regression } & 176.2591 & \text { Akaike info criterion }&& 13.25054 \ \text { Sum squared resid } & 1211624 . & \text { Schwarz criterion } && 13.37466 \ \text { Log likelihood } & -275.2613 & \text { F-statistic }&& 2402.403 \ \text { Durbin-Watson stat } & 0.289425 &\text { Prob(F-statistic) } && 0.000000 \end{array}$ Use the Eviews output above to help with A) through I) below. A) Interpret the coefficient on EX1. B) Interpret R² for this regression. C) Replace the "?"'s with the appropriate values. An 80% confidence interval around the coefficient on EX1 is: 20.04112 +/- (?)(?) D) Perform a positive sign test on the coefficient attached to EX2. Show the 5-step procedure. E) IF you performed a test of significance on the constant term at the 87 percent critical level, would you reject the null hypothesis or not? Explain. F) Perform a test to determine if the coefficient attached to EX2 is greater than 7.47. Show the 5-step procedure. G) Based on the information in the table above (and ignoring Ramsey's Reset test which we will perform in a moment) do you think the regression above is under or over specified? Explain. H)1.Perform Ramsey's Reset Test on the regression above using the Eviews printout below. Show the 5-step procedure. 2. What is the difference between "FITTED^2" and "FITTED^3" in the Eviews printout above? Do the two terms appear in the restricted or unrestricted regression?

Question

Quizplus · Accepted Answer

The Answer is A) If EX1 increases 1 unit, then WHY is expected to increase 20.04 units holding EX2 constant.
B) 99% of the variation in WHY is explained by EX1 and EX2.
C) 12.57 and 1.314
D) 1) Ho:

B _ { 2 }

= 0 Ha:

B _ { 2 }

> 0 (minus 2 for messing up step 1)
2) 5%
3) If t-ratio > t^c, then reject Ho
4) 66.84 > 1.703 (d.f. = n- k = 30 - 3 =27)
5) Reject Ho

\rightarrow

\beta _ { 1 }

is not significantly positive
E) Not reject because the P-value > .87
F) 1. Ho:

\beta _ { 2 } = 7.47 \quad

Ha:

\beta _ { 2 } > 7.47

2.5 \%

3. If t-ratio

> t

, then reject

\mathrm { Ho }

4.

( 20.04 - 7.47 ) / 12.57 = 1 < 1.703

(d.f.

= \mathbf { n } - \mathbf { k } = 30 - 3 = 27

)
5. Do not reject Ho;

\beta _ { 2 }

is not statistically greater than 7.47 . G) All we have to go on is significance and EX1 is insignificant at the 5% critical level. So the equation may be over specified.
H) 1) $A) If EX1 increases 1 unit, then WHY is expected to increase 20.04 units holding EX2 constant. B) 99% of the variation in WHY is explained by EX1 and EX2. C) 12.57 and 1.314 D) 1) Ho: B _ { 2 } = 0 Ha: B _ { 2 } > 0 (minus 2 for messing up step 1) 2) 5% 3) If t-ratio > t<sup>c</sup>, then reject Ho 4) 66.84 > 1.703 (d.f. = n- k = 30 - 3 =27) 5) Reject Ho \rightarrow \beta _ { 1 } is not significantly positive E) Not reject because the P-value > .87 F) 1. Ho: \beta _ { 2 } = 7.47 \quad Ha: \beta _ { 2 } > 7.47 2.5 \% 3. If t-ratio > t , then reject \mathrm { Ho } 4. ( 20.04 - 7.47 ) / 12.57 = 1 < 1.703 (d.f. = \mathbf { n } - \mathbf { k } = 30 - 3 = 27 ) 5. Do not reject Ho; \beta _ { 2 } is not statistically greater than 7.47 . G) All we have to go on is significance and EX1 is insignificant at the 5% critical level. So the equation may be over specified. H) 1)$

Dependent Variable: WHY Method: Least Squares Sample(adjusted): 19652006 Included Observations

Dependent Variable: WHY
Method: Least Squares
Sample(adjusted): 19652006
Included Observations