The full effect that a change in a causal variable has on the dependent variable. In a regression model, where Y = *a* + *bX*, a shift in *X* has an instantaneous effect (of *b*) on *Y*. In dynamic regression, there are lags in either *X* or *Y* in the model. A shift in *X* also has a long-run effect, which may either amplify or damp the short-run effect. When using causal variables in a forecasting model, one is typically concerned with long-run effects. Thus, it is inadvisable to formulate a model on first differences.