Ecomat Exam
Essay by Papus • November 23, 2017 • Exam • 420 Words (2 Pages) • 839 Views
- Multiple Regression Japanese asset price bubble (1986–1992)
Dependent Variable: INFLATION | ||||
Method: Least Squares | ||||
Date: 11/09/17 Time: 13:43 | ||||
Sample: 1981 2016 | ||||
Included observations: 36 | ||||
Variable | Coefficient | Std. Error | t-Statistic | Prob. |
C | 38.38802 | 13.95053 | 2.751724 | 0.0097 |
CRISIS | -3.707653 | 3.681568 | -1.007085 | 0.3214 |
GDPR | -0.010202 | 0.005344 | -1.909158 | 0.0652 |
MS2 | 0.005148 | 0.003557 | 1.447207 | 0.1576 |
R-squared | 0.268566 | Mean dependent var | 8.359497 | |
Adjusted R-squared | 0.199995 | S.D. dependent var | 8.549961 | |
S.E. of regression | 7.647343 | Akaike info criterion | 7.011033 | |
Sum squared resid | 1871.420 | Schwarz criterion | 7.186979 | |
Log likelihood | -122.1986 | Hannan-Quinn criter. | 7.072443 | |
F-statistic | 3.916567 | Durbin-Watson stat | 1.702047 | |
Prob(F-statistic) | 0.017268 | |||
It is indicated that the following Japanese asset price bubble crisis from 1986-1992 has no significant value except from the constant. We can conclude that the following dummy variable does not significantly affect inflation rate.
Breusch-Godfrey Serial Correlation LM Test: | ||||
F-statistic | 2.117052 | Prob. F(2,30) | 0.1380 | |
Obs*R-squared | 4.452511 | Prob. Chi-Square(2) | 0.1079 | |
Serial correlation LM test indicated that there are no serial correlation since prob chi-square is more than 5%.
Heteroskedasticity Test: Breusch-Pagan-Godfrey | ||||
F-statistic | 1.426565 | Prob. F(3,32) | 0.2532 | |
Obs*R-squared | 4.246700 | Prob. Chi-Square(3) | 0.2360 | |
Scaled explained SS | 23.82189 | Prob. Chi-Square(3) | 0.0000 | |
The following results indicated that there are no heteroscedasticity since the corresponding prob chi square of the obs r squared is more than 5%. Therefore, it’s homoscedastic.
PAM
Dependent Variable: FDI | ||||
Method: Least Squares | ||||
Date: 11/09/17 Time: 14:13 | ||||
Sample (adjusted): 1982 2016 | ||||
Included observations: 35 after adjustments | ||||
Variable | Coefficient | Std. Error | t-Statistic | Prob. |
C | 1327.489 | 746.4426 | 1.778421 | 0.0851 |
GDPRGR | -71.36587 | 79.15186 | -0.901632 | 0.3742 |
TBILL90 | -65.61530 | 39.44720 | -1.663370 | 0.1063 |
FDI(-1) | 0.885527 | 0.155083 | 5.710039 | 0.0000 |
R-squared | 0.668061 | Mean dependent var | 1584.543 | |
Adjusted R-squared | 0.635938 | S.D. dependent var | 1802.614 | |
S.E. of regression | 1087.653 | Akaike info criterion | 16.92864 | |
Sum squared resid | 36672656 | Schwarz criterion | 17.10640 | |
Log likelihood | -292.2512 | Hannan-Quinn criter. | 16.99000 | |
F-statistic | 20.79692 | Durbin-Watson stat | 2.472433 | |
Prob(F-statistic) | 0.000000 | |||
Fdi(-1) is the only significant variable that affects fdi.
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