To interpret the results of a unit root test in EViews, you should consider the test statistic, p-value, and critical values. If the test statistic is less than the critical value, you may reject the null hypothesis of a unit root and conclude that the series is stationary.

The p-value indicates the probability of obtaining a test statistic as extreme as the one observed, assuming the null hypothesis is true. If the p-value is less than the significance level, typically 0.05, you may reject the null hypothesis. EViews provides a variety of unit root testing tools, including the Augmented Dickey-Fuller (ADF) test, HEGY test, Canova and Hansen test, and Variance Ratio tests.

You can run a unit root test by specifying the series and the test type in EViews, such as the ADF test, Phillips-Perron test, or other relevant tests. It’s important to ensure that the series is stationary before performing further analysis, such as time series modeling or forecasting.

You can refer to EViews tutorials and resources available on platforms like YouTube and EViews forums for step-by-step guidance on conducting unit root tests and checking for stationarity in EViews