Contents
What is economic stationarity?
Statistical stationarity: A stationary time series is one whose statistical properties such as mean, variance, autocorrelation, etc. are all constant over time. Such statistics are useful as descriptors of future behavior only if the series is stationary.
What is the test of stationarity?
The KPSS test, short for, Kwiatkowski-Phillips-Schmidt-Shin (KPSS), is a type of Unit root test that tests for the stationarity of a given series around a deterministic trend. In other words, the test is somewhat similar in spirit with the ADF test.
What do you need to know about stationarity?
1 Concepts. Basically stationarity means that a time series has a constant mean and constant variance over time. 2 Tests. When working with the Box-Jenkins approach it is common to check the stationarity of a time series by visual inspection of the correlogram, i.e. 3 Literature.
Which is the best model for nonstationary series?
For this it is useful to know that there are two popular models for nonstationary series, trend- and difference-stationary models. 1 Trend-stationary: A series is trend-stationary, if it fluctuates around a deterministic trend, to which it reverts in the long run. Subtracting this trend from the original series yields a stationary series.
What are the results of non stationary data?
Non-stationary data, as a rule, are unpredictable and cannot be modeled or forecasted. The results obtained by using non-stationary time series may be spurious in that they may indicate a relationship between two variables where one does not exist.
How to check the stationarity of a time series?
When working with the Box-Jenkins approach it is common to check the stationarity of a time series by visual inspection of the correlogram, i.e. a plot containing the k th-order normalised autocorrelations. If the estimated autocorrelations die out rather quickly, the series is likely to be stationary.