An Introduction to time-varying lag autoregression
This paper introduces a new autoregressive model, with the specific feature that the lag structure can vary over time. More precise, and to keep matters simple, the autoregressive model sometimes has lag 1, and sometimes lag 2. Representation, autocorrelation, specification, inference, and the creation of forecasts are presented. A detailed illustration for annual inflation rates for eight countries in Africa shows the empirical relevance of the new model. Various potential extensions are discussed.
|Keywords||Autoregression, Time-varying lags, Forecasting|
|JEL||Time-Series Models; Dynamic Quantile Regressions (jel C22), Forecasting and Other Model Applications (jel C53)|
Franses, Ph.H.B.F. (2020). An Introduction to time-varying lag autoregression. Retrieved from http://hdl.handle.net/1765/126723