Causality analysis

The use of the series lags to forecast the future value of the series is beneficial whenever the series has stable repeated patterns over time. An excellent example of this type of series is the US natural gas consumption, as it has a strong seasonal pattern along with a consistent trend (or growth) pattern. Yet, the main pitfall of this method is that it will fail whenever the changes in the series derive from exogenous factors. In these cases, using only past lags could potentially lead to misleading results, as the lags do not necessarily drive the changes in the series. The goal of causality analysis, in the context of time series analysis, is to identify whether a causality relationship exists between the series we wish to forecast and other potential exogenous factors. The use of those external factors as drivers of the forecasting model (whenever exists...