Causal Models and Leading Indicators
8.1 Leading Indicators
The time series forecasting methods discussed in the previous two chapters have one key advantage: the only data they require are the time series data themselves; no additional data are needed to estimate a smoothing parameter, or the parameters of an ARIMA model, and use it for forecasting. However, firms often have a range of additional information available that could be used to create demand forecasts as well, such as consumer confidence indices, advertising projections, reservations made or orders already placed, and so forth. Using such information falls into the domain of causal modeling and leading indicators.
A useful leading indicator is given by additional data ...
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