What is MacKinnon approximate p value?

Z(t) -1.318 -4.069 -3.463 -3.158 MacKinnon approximate p-value for Z(t) = 0.8834. As we might expect from economic theory, here we cannot reject the null hypothesis that log consumption exhibits a unit root.

How do you check stationarity in R?

To check if a time series is stationary, we can use Dickey-Fuller test using adf. test function of tseries package. For example, if we have a time series object say TimeData then to check whether this time series is stationary or not we can use the command adf. test(TimeData).

What does the Dickey Fuller test for?

Augmented Dickey Fuller test (ADF Test) is a common statistical test used to test whether a given Time series is stationary or not. It is one of the most commonly used statistical test when it comes to analyzing the stationary of a series.

How do you read Dickey Fuller results?

Augmented Dickey-Fuller test

1. p-value > 0.05: Fail to reject the null hypothesis (H0), the data has a unit root and is non-stationary.
2. p-value <= 0.05: Reject the null hypothesis (H0), the data does not have a unit root and is stationary.

What is the test statistic of the ADF test?

The augmented Dickey–Fuller (ADF) statistic, used in the test, is a negative number. The more negative it is, the stronger the rejection of the hypothesis that there is a unit root at some level of confidence.

What library is ADF test in R?

the tseries library
What is this? To perform an augmented Dickey-Fuller test, we can use the adf. test() function from the tseries library.

How would you test for stationarity?

Two tests for checking the stationarity of a time series are used, namely the ADF test and the KPSS test. Detrending is carried out by using differencing technique and the same will be covered in future articles on Statistical tests to check stationarity in Time Series.

How do you read an ADF test?