We propose a new algorithm which allows easy estimation of Vector Autoregressions (VARs) featuring asymmetric priors and time varying volatilities, even when the cross sectional dimension of the system N is particularly large. The algorithm is based on a simple triangularisation which allows to...

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 existing alternatives, namely, factor models, large scale...

Models based on economic theory have serious problems at forecasting exchange rates better than simple univariate driftless random walk models, especially at short horizons. Multivariate time series models suffer from the same problem. In this paper, we propose to forecast exchange rates with a...

We propose a new approach to forecasting the term structure of interest rates, which allows to efficiently extract the information contained in a large panel of yields. In particular, we use a large Bayesian Vector Autoregression (BVAR) with an optimal amount of shrinkage towards univariate AR...

Small or medium-scale VARs are commonly used in applied macroeconomics for forecasting and evaluating the shock transmission mechanism. This requires the VAR parameters to be stable over the evaluation and forecast sample, or to explicitly consider parameter time variation. The earlier...

This paper is a general investigation of temporal aggregation in time series analysis. It encompasses traditional research on time aggregation as a particular case and extends the analysis to irregular intervals of aggregation. The Data Generating Process is allowed to evolve at regular,...

The paper provides a proof of consistency of the ridge estimator for regressions where the number of regressors tends to infinity. Such result is obtained without assuming a factor structure. A Monte Carlo study suggests that shrinkage autoregressive models can lead to very substantial...

Instrumental variable estimation is central to econometric analysis and has justifiably been receiving considerable and consistent attention in the literature in the past. Recent developments have focused on cases where instruments are either weak, in terms of correlations with the endogenous...

This paper proposes and discusses an instrumental variable estimator that can be of particular relevance when many instruments are available. Intuition and recent work (see, e.g., Hahn (2002)) suggest that parsimonious devices used in the construction of the final instruments, may provide...

This paper analyses the use of factor analysis for instrumental variable estimation when the number of instruments tends to infinity. We consider cases where the unobserved factors are the optimal instruments but also cases where the factors are not necessarily the optimal instruments but can...