An Estimator For Simultaneous Equation Model Using Two Stage Ridge Method (Case Study On Farmer Exchange Rate Data In Indonesia)

The concept of simultaneity is undoubtedly the most influential idea in econometrics, such as the relationship
in farmer exchange rate. A simultaneous equations model is model with two or more equations is defined as
one in which a variable explained in one equation appears as an explanatory in another. In the simultaneous
equation model, the variables used are known as endogenous variables and exogenous variables. As a result,the
model's endogenous variables are determined at the same time. Moreover, in these simultaneous equations,
there is a correlation between the error terms of the structural equations of the model, the two stage least square method was selected to estimate. Under the issues of multicollinearity two stage least squares estimation in a
simultaneous equations model has several desirable properties. Futhermore, we use a two Stages least square
estimator for the simultaneous equations model, which su൵ers from autocorrelation issues and then we
combined with ridge regression estimator which su൵ers from multicollinearity issues. After adjusting this with
the ordinary ridge regression estimator, we use a mixed method to apply the two stages least squares procedure.
From the this study, it was found that the two stage ridge is better than two stage least square. This is influenced
by the simultaneous relationship and multicollinearity in each equation.