When to Use Lagged Variables?

Lagged dependent variables (LDVs) have been used in regression analysis to provide robust estimates of the effects of independent variables, but some research argues that using LDVs in regressions produces negatively biased coefficient estimates, even if the LDV is part of the data-generating process.

What is a lagged variable in regression?

A dependent variable that is lagged in time. For example, if Yt is the dependent variable, then Yt-1 will be a lagged dependent variable with a lag of one period. Lagged values are used in Dynamic Regression modeling.

Why lags are used in time series?

Lags are very useful in time series analysis because of a phenomenon called autocorrelation, which is a tendency for the values within a time series to be correlated with previous copies of itself.