We extend the work done in our “Redux” paper from Oct 2011 to find a weighted composite U.S coincident economic index (CEI) that includes non-zero weightings from all 50 states and when used in a standard Probit model, produces a perfect correlation (R2 of 1) to NBER recession dating. We...

This article re-examines the findings of Stock and Watson (2012b) who assessed the predictive performance of dynamic factor models (DFM) over autoregressive (AR) bench-marks for hundreds of target variables by focusing on possible business cycle performance asymmetries in the spirit of Chauvet...

We introduce a multivariate multiplicative error model which is driven by componentspecific observation driven dynamics as well as a common latent autoregressive factor. The model is designed to explicitly account for (information driven) common factor dynamics as well as idiosyncratic effects...

We propose a new model for volatility forecasting which combines the Generalized Dynamic Factor Model (GDFM) and the GARCH model. The GDFM, applied to a large number of series, captures the multivariate information and disentangles the common and the idiosyncratic part of each series of returns....

The appropriate design of monetary policy in integrated financial markets is one of the most challenging areas for central banks. One hot topic is whether the rise in liquidity in recent years has contributed to the formation of price bubbles in asset markets. If strong linkages exist, the...

We use a vector error correction model to study the long-term relationship between aggregate expected default frequency and the macroeconomic development, i.e. CPI, industry production and short-term interest rate. The model is used to forecast the median expected default frequency of the...

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...

World power and gas markets have a natural relationship with global tradable carbon permits markets, including the U.S. Clean Air Act Amendments and the EU Emissions Trading Scheme, the latter officially launched in January 2005. Electric utilities operate their power plants based in part on the...

Measuring and displaying uncertainty around path-forecasts, i.e. forecasts made in period T about the expected trajectory of a random variable in periods T+1 to T+H is a key ingredient for decision making under uncertainty. The probabilistic assessment about the set of possible trajectories that...

Structural vector-autoregressive models are potentially very useful tools for guiding both macro- and microeconomic policy. In this paper, we present a recently developed method for exploiting non-Gaussianity in the data for estimating such models, with the aim of capturing the causal structure...