notably with the pandemic. In a VAR, allowing the errors to have a distribution with fatter tails than the Gaussian one equips … the model to better deal with the COVID-19 shock. A standard Gaussian VAR can still be used for producing conditional …

-used probit approach, but the dynamics of regressors are endogenized using a VAR. The combined model is called a ‘ProbVAR’. At any … short-term interest rate, stock returns or corporate bond spreads. The forecasting performance is very good for the United …

euro area as a whole and in its five largest countries. In a Bayesian VAR framework, the two credit supply shocks are …

the implications of the model through a Structural Vector Auto Regression (VAR) that separates non-OPEC and OPEC …

include disaggregate information or disaggregate variables in the aggregate model as opposed to first forecasting the … in forecasting the aggregate. We show theoretically that the first method of forecasting the aggregate should outperform … findings and analyse why forecasting the aggregate using information on its disaggregate components improves forecast accuracy …

This paper estimates the effects of exogenous fiscal policy shocks in Spain in a VAR framework. Government expenditure …

(2005) and a large scale model, introducing the sign restrictions approach to the global VAR (GVAR) literature, that allows …