| OLS Regression Results |
| ============================================================================== |
| Dep. Variable: GDP R-squared: 0.971 |
| Model: OLS Adj. R-squared: 0.970 |
| Method: Least Squares F-statistic: 839.9 |
| Date: Thu, 10 Jul 2025 Prob (F-statistic): 5.55e-76 |
| Time: 22:30:42 Log-Likelihood: -903.30 |
| No. Observations: 105 AIC: 1817. |
| Df Residuals: 100 BIC: 1830. |
| Df Model: 4 |
| Covariance Type: nonrobust |
| ============================================================================== |
| coef std err t P>|t| [0.025 0.975] |
| ------------------------------------------------------------------------------ |
| const -328.8855 630.799 -0.521 0.603 -1580.374 922.603 |
| UNRATE -21.7142 79.789 -0.272 0.786 -180.013 136.584 |
| CPIAUCSL 85.7935 2.036 42.144 0.000 81.755 89.832 |
| FEDFUNDS 492.3433 92.591 5.317 0.000 308.646 676.041 |
| DGS10 -883.8622 122.881 -7.193 0.000 -1127.655 -640.070 |
| ============================================================================== |
| Omnibus: 12.409 Durbin-Watson: 2.138 |
| Prob(Omnibus): 0.002 Jarque-Bera (JB): 13.297 |
| Skew: 0.746 Prob(JB): 0.00130 |
| Kurtosis: 3.902 Cond. No. 812. |
| ============================================================================== |
|
|
| Notes: |
| [1] Standard Errors assume that the covariance matrix of the errors is correctly specified. |
