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Forecasting Large Datasets with Bayesian Reduced Rank Multivariate Models

Carriero, Andrea; Kapetanios, George; Marcellino, … - C.E.P.R. Discussion Papers - 2009

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 …

Persistent link: https://www.econbiz.de/10008528528

Common Drifting Volatility in Large Bayesian VARs

Carriero, Andrea; Clark, Todd; Marcellino, Massimiliano - C.E.P.R. Discussion Papers - 2012

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...

Persistent link: https://www.econbiz.de/10011083279

Real-Time Nowcasting with a Bayesian Mixed Frequency Model with Stochastic Volatility

Carriero, Andrea; Clark, Todd; Marcellino, Massimiliano - C.E.P.R. Discussion Papers - 2013

This paper develops a method for producing current-quarter forecasts of GDP growth with a (possibly large) range of available within-the-quarter monthly observations of economic indicators, such as employment and industrial production, and financial indicators, such as stock prices and interest...

Persistent link: https://www.econbiz.de/10011084707

Bayesian VARs: Specification Choices and Forecast Accuracy

Carriero, Andrea; Clark, Todd; Marcellino, Massimiliano - C.E.P.R. Discussion Papers - 2011

In this paper we discuss how the forecasting performance of Bayesian VARs is affected by a number of specification … lag length and of both; compare alternative approaches to h-step ahead forecasting (direct, iterated and pseudo …

Persistent link: https://www.econbiz.de/10008854551