In statistics and econometrics, a distributed lag model is a model for time series data in which a regression equation is used to predict current values of a dependent variable based on both the current values of an explanatory variable and the lagged (past period) values of this explanatory variable. The starting point for a distributed lag model is an assumed structure of the form y t = a + w 0 x t + w 1 x t − 1 + w 2 x t − 2 + .
In statistics and econometrics, a distributed lag model is a model for time series data in which a regression equation is used to predict current values of a dependent variable based on both the current values of an explanatory variable and the lagged (past period) values of this explanatory variable. The starting point for a distributed lag model is an assumed structure of the form y t = a + w 0 x t + w 1 x t − 1 + w 2 x t − 2 + .
Source: Wikipedia "Distributed lag" · CC BY-SA 4.0
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