You estimate the following model. Dependent Variable: DRATE Method: ARMA Conditional Least Squares (Gauss-Newton / Marquardt steps) Date: 02/24/20 Time: 20:21 Sample (adjusted): 1962M02 2019M07 Included observations: 690 after adjustments Failure to Improve likelihood (non-zero gradients) after 11 iterations Coefficient covariance computed using outer product of gradients MA Backcast: 1962M01 Variable C MA(1) R-squared Adjusted R-squared S.E. of regression Sum squared resid Log likelihood F-statistic Prob(F-statistic) Inverted MA Roots O-0.002872 O-0.002933 O.0.439867 Coefficient Std. Error O 0.261752 -0.002872 0.439867 0.133801 0.132542 0.261752 47.13757 -53.21823 106.2748 0.000000 -44 t-Statistic 0.014344 -0.200229 0.034251 12.84247 Mean dependent var S.D. dependent var Akaike Info criterion Schwarz criterion Hannan-Quinn criter. Durbin-Watson stat Prob. 0.8414 0.0000 The unconditional mean of the above process (from Eviews output above) is -0.002933 0.281038 0.160053 0.173203 0.165139 2.088358

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You estimate the following model.
Dependent Variable: DRATE
Method: ARMA Conditional Least Squares (Gauss-Newton / Marquardt
steps)
Date: 02/24/20 Time: 20:21
Sample (adjusted): 1962M02 2019M07
Included observations: 690 after adjustments
Failure to Improve likelihood (non-zero gradients) after 11 iterations
Coefficient covariance computed using outer product of gradients
MA Backcast: 1962M01
Variable
C
MA(1)
R-squared
Adjusted R-squared
S.E. of regression
Sum squared resid
Log likelihood
F-statistic
Prob(F-statistic)
Inverted MA Roots
O-0.002872
O-0.002933
O.0.439867
Coefficient Std. Error t-Statistic
O 0.261752
-0.002872
0.439867
0.133801
0.132542
0.261752
47.13757
-53.21823
106.2748
0.000000
-44
0.014344
-0.200229
0.034251 12.84247
Mean dependent var
S.D. dependent var
Akaike Info criterion
Schwarz criterion
Hannan-Quinn criter.
Durbin-Watson stat
Prob.
0.8414
0.0000
The unconditional mean of the above process (from Eviews output above) is
-0.002933
0.281038
0.160053
0.173203
0.165139
2.088358
Transcribed Image Text:You estimate the following model. Dependent Variable: DRATE Method: ARMA Conditional Least Squares (Gauss-Newton / Marquardt steps) Date: 02/24/20 Time: 20:21 Sample (adjusted): 1962M02 2019M07 Included observations: 690 after adjustments Failure to Improve likelihood (non-zero gradients) after 11 iterations Coefficient covariance computed using outer product of gradients MA Backcast: 1962M01 Variable C MA(1) R-squared Adjusted R-squared S.E. of regression Sum squared resid Log likelihood F-statistic Prob(F-statistic) Inverted MA Roots O-0.002872 O-0.002933 O.0.439867 Coefficient Std. Error t-Statistic O 0.261752 -0.002872 0.439867 0.133801 0.132542 0.261752 47.13757 -53.21823 106.2748 0.000000 -44 0.014344 -0.200229 0.034251 12.84247 Mean dependent var S.D. dependent var Akaike Info criterion Schwarz criterion Hannan-Quinn criter. Durbin-Watson stat Prob. 0.8414 0.0000 The unconditional mean of the above process (from Eviews output above) is -0.002933 0.281038 0.160053 0.173203 0.165139 2.088358
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