Bootstrap Liu estimator for Almon Distributed Lag Model

The Almon distributed lag model is used to study how an explanatory variable affects a dependent variable spread out over a number of time periods, as opposed to an influence that happens instantly. Most of the time, Almon technique is used to estimate the parameters in the distributed lag model (DLM). Still, this estimator becomes very unstable if the explanatory variables and their delays are highly correlated. A new bootstrapped Liu shrinkage estimator is suggested in this research to deal with multicollinear challenges in the DLM. It was achieved by gradually narrowing the selection of the biasing parameters. According to the findings of the Monte Carlo study, the new methods lead to lesser MSE in all the cases compared to the standard methods. The use of the tested methods in real-world situations supports the assumption that they are better than the other ones.