To reduce the size of an effect, as in “to damp the trend” (as contrasted to dampening, which would imply some type of moisturizing and thus be senseless, or worse, for forecasters). Damped estimates are useful in the presence of uncertainty. Thus, in making extrapolations over long horizons, one should damp. Seasonal factors can also be damped if there is uncertainty. In addition, the effects in an econometric model can be damped in light of uncertainty about the forecasts of the explanatory variables. See mitigation and Armstrong (2001c).
- Armstrong, J. S. (2001c), “Extrapolation for time-series
and cross-sectional data,” in J. S. Armstrong (ed.), Principles of
Forecasting. Norwell, MA: Kluwer Academic Press.