Selecting predictors by using Bayesian model averaging in bridge models

Lorenzo Bencivelli, Massimiliano Marcellino and Gianluca Moretti ()
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Gianluca Moretti: UBS Global asset management

No 872, Temi di discussione (Economic working papers) from Bank of Italy, Economic Research and International Relations Area

Abstract: This paper proposes the use of Bayesian model averaging (BMA) as a tool to select the predictors' set for bridge models. BMA is a computationally feasible method that allows us to explore the model space even in the presence of a large set of candidate predictors. We test the performance of BMA in now-casting by means of a recursive experiment for the euro area and the three largest countries. This method allows flexibility in selecting the information set month by month. We find that BMA based bridge models produce smaller forecast error than fixed composition bridges. In an application to the euro area they perform at least as well as medium-scale factor models.

Keywords: business cycle analysis; forecasting; Bayesian model averaging; bridge models. (search for similar items in EconPapers)
JEL-codes: C22 C52 C53 (search for similar items in EconPapers)
Date: 2012-07
New Economics Papers: this item is included in nep-ecm and nep-for
References: View complete reference list from CitEc
Citations: View citations in EconPapers (11)

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Persistent link: https://EconPapers.repec.org/RePEc:bdi:wptemi:td_872_12

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