The vector autoregressive model has long been used for portfolio analysis, while a recent extension (VARX) incorporates exogenous factors. Despite its increased forecasting precision, the ...

An autoregressive model is a category of machine learning models in which algorithms predict future data based on a series of their own past data. The core ideas date back to the early 1900s when an ...

This paper proposes a new high-frequency structural vector autoregression model that can disentangle the drivers of oil and natural gas prices in real time. In particular, it separately identifies ...

After computing the sample autocovariance matrices, PROC STATESPACE fits a sequence of vector autoregressive models. These preliminary autoregressive models are used to estimate the autoregressive ...

This paper investigates spillovers between electricity supply shocks and US growth, using monthly data from forty-eight US states from January 2001 to September 2016, and employs a novel strategy for ...

A model with first-order autoregressive errors, AR(1), has the form while an AR(2) error process has the form and so forth for higher-order processes. Note that the ...

This Selected Issues paper analyzes the main determinants of inflation in Mongolia using empirical tests based on a structural model approach and vector autoregression model, with a view to assessing ...