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z=list(r~m2+yt, yt~r+inv)

fms=systemfit(z,method="SUR")

summary(fms)

systemfit results

method: SUR

N DF SSR detRCov OLS-R2 McElroy-R2

system 46 40 876932684 1935792727 0.80107 0.957149

N DF SSR MSE RMSE R2 Adj R2

eq1 23 20 3.0322e+03 151.61 12.313 0.68255 0.650807

eq2 23 20 8.7693e+08 43846482.57 6621.668 0.80107 0.781177

The covariance matrix of the residuals used for estimation

eq1 eq2

eq1 141.348 35512.7

eq2 35512.731 38099658.2

The covariance matrix of the residuals

eq1 eq2

eq1 151.61 68642.4

eq2 68642.41 43846482.6

The correlations of the residuals

eq1 eq2

eq1 1.000000 0.841901

eq2 0.841901 1.000000

 

SUR estimates for 'eq1' (equation 1)

Model Formula: r ~ m2 + yt

Estimate Std. Error t value Pr(>|t|)

(Intercept) 82.200705295 8.978289497 9.1555 1.3653e-08 ***

m2 -0.000223850 0.000202598 -1.1049 0.2823197

yt -0.001036269 0.000317699 -3.2618 0.0039037 **

---

Signif. codes: 0 *** 0.001 ** 0.01 * 0.05 . 0.1 1

Residual standard error: 12.313008 on 20 degrees of freedom

Number of observations: 23 Degrees of Freedom: 20

SSR: 3032.203552 MSE: 151.610178 Root MSE: 12.313008

Multiple R-Squared: 0.682552 Adjusted R-Squared: 0.650807

SUR estimates for 'eq2' (equation 2)

Model Formula: yt ~ r + inv

Estimate Std. Error t value Pr(>|t|)

(Intercept) 50064.399982 3799.527571 13.17648 2.5600e-11 ***

r -495.453785 66.932776 -7.40226 3.7868e-07 ***

inv 1.218453 0.360274 3.38202 0.0029616 **

---

Signif. codes: 0 *** 0.001 ** 0.01 * 0.05 . 0.1 1

Residual standard error: 6621.667658 on 20 degrees of freedom

Number of observations: 23 Degrees of Freedom: 20

SSR: 876929651.445334 MSE: 43846482.572267 Root MSE: 6621.667658

Multiple R-Squared: 0.80107 Adjusted R-Squared: 0.781177

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