This paper shows that Vector Autoregression with Bayesian shrinkage is an appropriate tool for large dynamic models. We build on the results by De Mol, Giannone, and Reichlin (2008) and show that, when the degree of shrinkage is set in relation to the cross-sectional dimension, the forecasting...

We construct and explore a new quarterly dataset covering crisis episodes in 40 developed countries over 1970–2010. First, we examine stylized facts of banking, debt, and currency crises. Banking turmoil was most frequent in developed economies. Using panel vector autoregression, we confirm...

This paper aims to illustrate how weight matrices that are needed to construct foreign variable vectors in Global Vector Autoregressive (GVAR) models can be estimated jointly with the GVAR's parameters. An application to real GDP and consumption expenditure price inflation as well as a...

This paper extends the analysis of infinite dimensional vector autoregressive models (IVAR) proposed in Chudik and Pesaran (2010) to the case where one of the variables or the cross section units in the IVAR model is dominant or pervasive. This extension is not straightforward and involves...

We develop a Mixed-Cross-Section Global Vector Autoregressive (MCS-GVAR) model for the 28 EU economies and a sample of individual banking groups to study the propagation of bank capital shocks to the economy. We conduct various simulations with the model to assess how capital ratio shocks...

This paper considers Bayesian regression with normal and double-exponential priors as forecasting methods based on large panels of time series. We show that, empirically, these forecasts are highly correlated with principal component forecasts and that they perform equally well for a wide range...

This paper asks two questions. First, can we detect empirically whether the shocks recovered from the estimates of a structural VAR are truly structural? Second, can the problem of nonfundamentalness be solved by considering additional information? The answer to the first question is "yes" and...

We investigate the interactions across current account misalignments, Real Effective Exchange Rate misalignments and financial (or output) gaps within EU countries. We apply panel techniques, including a Bayesian panel VAR, to 27 EU members over the period 1994-2012. We find that, for the euro...

This paper describes an algorithm to compute the distribution of conditional forecasts, i.e. projections of a set of variables of interest on future paths of some other variables, in dynamic systems. The algorithm is based on Kalman filtering methods and is computationally viable for large...

This paper uses a panel VAR (PVAR) approach to estimating, analysing, and forecasting price dynamics in four different sectors – industry, services, construction, and agriculture – across the four largest euro area economies – Germany, France, Italy and Spain – and the euro area as a...