In all models we reject the hypothesis of homoscedastic
variation in both the noise term and the conduct term.
Table 6 shows the sum of squared residuals considering the adjustment of homoscedastic
and heteroscedastic models.
One can also clearly see that the errors in the intensity axis are not homoscedastic
(see unequal, i.e., heteroscedastic uncertainties for any element in different GRMs in Table S2).
Table 3 shows the results for the balanced design under normal homoscedastic
We tested whether the homoscedastic
and heteroscedastic models could be assumed equivalent with a likelihood ratio test and reported the simpler model if we were able to accept the equivalence of the two models.
Thus, based on the RMSE criterion, the [A.sub.0](3) model is the best model, which implies that, out of the models taken into account, a three-factor homoscedastic
structure best describes the evolution of the yield curve in Colombia.
Having estimated them, the homoscedastic
inefficiency can be obtained as follows:
In all these considerations, the error component model commonly assumes that the regression disturbances are homoscedastic
in terms of common variance across time and cross sections.
The p-value rejected the hypothesis that model residuals are homoscedastic
, and there was evidence of heteroscedasticity.
Cluster robust standard errors are used because the assumptions that the error terms are serially uncorrelated and homoscedastic
are rarely met for bilateral trade data sets and initial tests confirm this.
distribution of the residuals varianceof the model is very important for the model to give good results.
As this was not the case, it was confirmed that the error term was homoscedastic
. Further details on this can be found in appendix I.