<![CDATA[GSTAR is a special form of the VAR model and is one of the commonly used models for modeling and forecasting time series data and location. At GSTAR modeling, estimation method used is OLS, the method is considered to have a weakness, which will result in an inefficient estimator. Thus, one appropriate method is GLS. In this study, conducted modeling GSTARX two levels by adding a predictor of calendar variation model. Parameter estimation of the first level models made of predictors with a linear regression model, while the second level models using error models which is done on first level with GSTAR model. Calendar variation model discussed is the impact of Ramadhan effect. Results of the simulation study showed that GSTAR-GLS models produces a more efficient estimator than GSTAR-OLS, seen from the obtained standard error smaller.]]>
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