This article therefore explains the step by step methods of using ARDL bounds test to estimate the model if some of the variables are stationary at level I(0) while some are stationary at first difference I(1).
Ramsey reset test eviews pdf#
You can download the PDF where FMOLS was explained here.
If all the variables are stationary at first difference I(1), then Fully Modified Ordinary Least Square (FMOLS) is the appropriate method of analysis.
If some of the variables are stationary at level I(0) and some are stationary at first difference I(1), then the researcher will have to proceed to using ARDL bounds test to estimate the model.In this case, the researcher can proceed to using the normal Ordinary Least Squares (OLS) to estimate the model and the result will be valid. If all the variables are stationary at level, it means the mean and variance are equal without doing anything to them.The following constitute the methods of analysis based on the stationarity test: It is based on the result of the stationarity test, that we will know which method of analysis to go for. As such, the Augmented Dickey-Fuller test (ADF) is used to test for stationarity and make the variables to be stationary. Usually, a variable that is trending tends to have its mean and variance not equal (non-stationary).
Ramsey reset test eviews series#
The characteristics of time series data make them not suitable for OLS directly, as such, the variables must be tested for stationarity that is, make their mean and variance equal in case they are not. Please refer to the previous article on using Co-integration test and Fully Modified Ordinary Least Squares (FMOLS) here.