We propose to use the attractiveness of pooling relatively short time series that display similar dynamics, but without restricting to pooling all into one group. We suggest estimating the appropriate grouping of time series simultaneously along with the group-specific model parameters. We cast...

The present Paper investigates the effects of incorporating illiquidity in a standard dynamic portfolio choice problem. Lack of liquidity means that an asset cannot be immediately traded at any point in time. We find the portfolio share of financial wealth invested in illiquid assets given the...

We propose regression based estimators for beta representations of dynamic asset pricing models with an affine pricing kernel specification. We allow for state variables that are cross sectional pricing factors, forecasting variables for the price of risk, and factors that are both. The...

We develop a novel Bayesian pooling technique to estimate aggregate production functions for the previously centrally planned economies (PCPEs) of Eastern Europe and for Western economies, as well as for a group of developing countries. This technique adjusts for the low quality of the PCPE data...

The estimation of large Vector Autoregressions with stochastic volatility using standard methods is computationally very demanding. In this paper we propose to model conditional volatilities as driven by a single common unobserved factor. This is justified by the observation that the pattern of...

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 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 assesses the performance of Bayesian Vector Autoregression (BVAR) for models of different size. We consider standard specifications in the macroeconomic literature based on, respectively, three and eight variables and compare results with those obtained by larger models containing...

This Paper studies empirically the transmission mechanism of European monetary policy by means of time-varying, heterogenous coefficient models estimated in a numerical Bayesian fashion. Based on pre-EMU evidence from Germany, France, Italy, and Spain, we find that (i) the long-run cumulative...

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 for US time series with the most promising existing alternatives, namely, factor...