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 …

In summary, the finite distributed lag model is most suitable to estimating dynamic rela-tionships when lag weights decline to zero relatively quickly, when the regressor is not highly …

We will focus on the discrete version of the model here as we will be working with discrete data. In that case the collection {βj} {β j} as a function of the lag j j will be referred to as the distributed …

Here we develop the family of distributed lag non-linear models (DLNM), a modelling framework that can simultaneously represent non-linear exposure–response dependencies and delayed …

Explore how distributed lag models help analyze delayed relationships between variables over time. Learn how these models capture the gradual impact of economic shocks and policies, …

The relationship between income and consumption is used to introduce distributed lag models. Assume the following relationship between income and consumption: \ [C_t=\alpha+\beta_0 …

Mar 8, 2024 · This chapter deals with a particular class of such dynamic models, namely, distributed lag models, which include present and lagged values of explanatory variables. It …

Mar 8, 2025 · One important class of dynamic models is the distributed lag model (DLM), which explicitly accounts for how past values affect the present over multiple time steps.

Instead of only using the dependent variable’s lags as predictors, an autoregressive distributed lag (ADL) model also uses lags of other variables for forecasting. The general ADL model is …

Apr 17, 2025 · In this article, we provide an in-depth guide to distributed lag models by outlining their theoretical foundations, practical applications, estimation techniques, critical case studies, …