VARs are a popular tool for forecasting and structural analysis, but ill-suited to handle occasionally binding …

comparably to quantile regression for estimating and forecasting tail risks, complementing BVARs' established performance for … forecasting and structural analysis …

Small or medium-scale VARs are commonly used in applied macroeconomics for forecasting and evaluating the shock … instability in a forecasting context. While none of the methods clearly emerges as best, some techniques turn out to be useful to … improve the forecasting performance …

Small or medium-scale VARs are commonly used in applied macroeconomics for forecasting and evaluating the shock … instability in a forecasting context. While none of the methods clearly emerges as best, some techniques turn out to be useful to … improve the forecasting performance …

the pandemic period, as well as for earlier subsamples of relatively high volatility. In historical forecasting, outlier …

VARs are a popular tool for forecasting and structural analysis, but ill-suited to handle occasionally binding …

Interest rate data are an important element of macroeconomic forecasting. Projections of future interest rates are not … only an important product themselves, but also typically matter for forecasting other macroeconomic and financial variables …. A popular class of forecasting models is linear vector autoregressions (VARs) that include shorter- and longer …

Models based on economic theory have serious problems at forecasting exchange rates better than simple univariate … forecasting. In addition, we adopt a driftless random walk prior, so that cross-dynamics matter for forecasting only if there is …

The paper addresses the issue of forecasting a large set of variables using multivariate models. In particular, we … propose three alternative reduced rank forecasting models and compare their predictive performance with the most promising …