One of the most fundamental concepts in time series econometrics is stationarity. A stationary time series is one whose statistical properties—such as mean, variance, and autocorrelation—remain constant over time. This concept may appear technical, but it is central to the validity of econometric inference. Much of modern applied econometrics, from forecasting inflation to modelling asset prices, rests on the assumption of stationarity. When this condition is violated, standard results collapse, leading to spurious regressions, misleading inferences, and flawed policy conclusions.
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