Path forecasts, defined as sequences of individual forecasts, generated by vector autoregressions are widely used in applied work. It has been recognized that a profound econometric analysis requires, besides the path forecast, a joint prediction region that contains the whole future path with a...

This paper investigates the finite sample properties of confidence intervals for structural vector error correction models (SVECMs) with long-run identifying restrictions on the impulse response functions. The simulation study compares methods that are frequently used in applied SVECM studies...

This paper considers the problem of forecasting real and financial macroeconomic variables across a large number of countries in the global economy. To this end, a global vector autoregressive (GVAR) model previously estimated over the 1979:Q1–2003:Q4 period by Dees, de Mauro, Pesaran, and...

We consider forecast combination and, indirectly, model selection for VAR models when there is uncertainty about which variables to include in the model in addition to the forecast variables. The key difference from traditional Bayesian variable selection is that we also allow for uncertainty...

In this note, we use multivariate models estimated with Bayesian techniques and an out-ofsample approach to investigate whether money growth Granger-causes output growth in the United States. We find surprisingly strong evidence for a money-output link over the 1960-2005 period. However, further...

Poor identification of individual impulse response coefficients does not necessarily mean that an impulse response is imprecisely estimated. This paper introduces a three-pronged approach on how to communicate uncertainty of impulse response estimates: (1) withWald tests of joint significance; (2)...

This study uses a Bayesian VAR to demonstrate that the recent house price boom in Germany can be explained by falling interest rates and that higher interest rates are likely suciffient to stop the increase of German house prices. The latter suggests a potential drawback of the current monetary...

Mixed frequency Bayesian vector autoregressions (MF-BVARs) allow forecasters to incorporate a large number of mixed frequency indicators into forecasts of economic activity. This paper evaluates the forecast performance of MF-BVARs relative to surveys of professional forecasters and investigates...

This paper provides an empirical comparison of various selection and penalized regression approaches for forecasting with vector autoregressive systems. In particular, we investigate the effect of the system size as well as the effect of various prior specification choices on the relative and...

We extend the analysis of Christoffersen and Diebold (1998) on long-run forecasting in cointegrated systems to multicointegrated systems. For the forecast evaluation we consider several loss functions, each of which has a particular interpretation in the context of stock-flow models where...