We incorporate external information extracted from the European Central Bank’s Survey of Professional Forecasters into predictions a Bayesian VAR using entropic tilting and soft conditioning. The resulting conditional forecasts significantly improve plain BVAR point density forecasts. Importantly, we do not restrict at specific quarterly horizon but their possible paths over several horizons jo...

Large Bayesian VARs with stochastic volatility are increasingly used in empirical macroeconomics. The key to making these highly parameterized useful is the use of shrinkage priors. We develop a family priors that captures best features two prominent classes priors: adaptive hierarchical and Minnesota Like priors, new ensure only ‘small’ coefficients strongly shrunk zero, while ‘large’ remain i...

Nowcasting can play a key role in giving policymakers timelier insight to data published with significant time lag, such as final GDP figures. Currently, there are plethora of methodologies and approaches for practitioners choose from. However, lacks comprehensive comparison these disparate terms predictive performance characteristics. This paper addresses that deficiency by examining the 12 di...

Large Bayesian VARs are now widely used in empirical macroeconomics. One popular shrinkage prior this setting is the natural conjugate as it facilitates posterior simulation and leads to a range of useful analytical results. This is, however, at expense modeling flexibility, rules out cross?variable shrinkage, that shrinking coefficients on lags other variables more aggressively than those own ...

This paper studies how to combine real-time forecasts from a broad range of Bayesian vector autoregression (BVAR) specifications and survey by optimally exploiting their properties. To do that, it compares the forecasting performance optimal pooling tilting techniques, including for predicting euro area inflation GDP growth at medium-term forecast horizons using both univariate multivariate met...

This paper employs a large BVAR model with common stochastic volatility to examine the effects of oil supply shocks, global demand shocks and precautionary on 17 U.S. macroeconomic financial market variables from 1986Q1 2019Q2. Generalized impulse response functions calculated using provide time-varying account impacts occurring in each quarter. We also compute standard for sizes evident 2019Q2...

This study analyses the impact of fiscal policy on South African economy during period 1972Q1-2020Q2. The adopted quarterly time series data to estimate a Bayesian Vector Autoregression (BVAR) model with selection hierarchical priors. variables employed for empirical investigation included GDP, government expenditure, public debt, and gross fixed-capital formation. results show that an unexpect...