100. STATIONARY AND NON-STATIONARY SERIES | Time Series | Econometrics | By Sumita Biswas

#timeseries #econometrics #economics
Stationarity and nonstationarity are terms you may have encountered previously if you've taken water or climate related courses and are important for understanding changes in the Earth System. But what do these terms actually mean? A stationary time series has statistical properties or moments (e.g., mean and variance) that do not vary in time. Stationarity, then, is the status of a stationary time series. Conversely, nonstationarity is the status of a time series whose statistical properties are changing through time. This step explores examples of stationarity and nonstationarity.
A non-stationary process with a deterministic trend becomes stationary after removing the trend, or detrending. For example, Yt = α + βt + εt is transformed into a stationary process by subtracting the trend βt: Yt - βt = α + εt, as shown in the figure below. No observation is lost when detrending is used to transform a non-stationary process to a stationary one.

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