Augmented Dickey-Fuller Test

The Augmented Dickey-Fuller test is used to estimate the stability of a time series. It is a part of a group of the tests for unit roots.

To execute the test

Test parameters:

Calculation Start. Specify calculation start point.
Calculation End. Specify calculation end point.
Missing Data Treatment. Select missing data treatment method. The Casewise method is used by default, that is, empty values are excluded. Calculations are executed without considering them. For details about missing data treatment methods see the Missing Data Treatment section.
Model Type. The test enables the user to work with three types of models. Select the required type in the drop-down list:
- Without Constant and Trend. It is used to test random processes.
- With Constant. It is used to test random processes with offset.
- With Constant and Trend. It is used to test random processes with offset and linear deterministic trend.
Series Differentiation. Specify differentiation order:
- Source Series. Differentiation is not used.
- Differentiated Series.
- Twice Differentiated Series.
Autoregression Order. Specify variable autoregression order.

The test is executed consecutively for each selected variable. The ADF statistics is calculated and compared with the N percent (N = 1%, 5%, 10%) significance level. Based on this comparison, the conclusion is formed about stationarity or non-stationarity of the series. The results are displayed as a table, for example: