EViews being the #1 best software for Econometric, leaves no feature behind in enhancing your analysis. EViews 12 has come up with many econometric advancements making your analysis more accurate and less time-taking.
Regression Variable Selection in Eviews
Selecting variables, among a large set of all variables, that are to be included in models is a very important step in analysis. EViews is best at automatically determining the variables to be used as regressors in a least squares regression. EViews includes three such techniques: Stepwise, and (new to EViews 12) Lasso and Auto-Search/GETS.
Each of these techniques are implemented in EViews as a pre-estimation step before performing a standard least squares regression. Before estimation, you must specify a dependent variable together with a list of always-included variable, and a list of selection variables, from which the selection algorithm will choose the most appropriate. Following the variable selection process, EViews reports the results of the final regression.
Indicator Saturation in Eviews
EViews 12 have added regression tools for testing outliers and structural breaks in a regression specification based on the indicator saturation approach.
The indicator saturation approach is an extension of least squares regression for testing for outliers and structural breaks in a regression specification. The indicator saturation approach works by including indicator variables for outliers or structural breaks at every observation in the regression, and then employing the GETS algorithms to select which of the included variables should be retained in a final regression model.
To instruct EViews to detect indicators in your least squares regression, open the equation estimation dialog, enter your least squares specification in the Equation specification edit field, and select LS – Least Squares (NLS and ARMA) in the Method dialog. Next, click on the Options tab to display the dialog:
