Large Vector Auto Regressions

Understand

One popular approach for nonstructural economic and financial forecasting is to include a large number of economic and financial variables, which has been shown to lead to significant improvements for forecasting, for example, by the dynamic factor models.

• A challenging issue is to determine which variables and (their) lags are relevant, especially when there is a mixture of serial correlation (temporal dynamics), high dimensional (spatial) dependence structure and moderate sample size (relative to dimensionality and lags).
• To this end, an \textit{integrated} solution that addresses these three challenges simultaneously is appealing.
• We study the large vector auto regressions here with three types of estimates.