Multivariate Bayesian Predictive Synthesis in Macroeconomic Forecasting

59 Pages Posted: 15 Feb 2019

See all articles by Ken McAlinn

Ken McAlinn

Temple University, Fox School of Business

Knut Are Aastveit

Norges Bank

Jouchi Nakajima

Bank for International Settlements (BIS)

Mike West

Duke University - Department of Statistical Science

Date Written: January 16, 2019

Abstract

We present new methodology and a case study in use of a class of Bayesian predictive synthesis (BPS) models for multivariate time series forecasting. This extends the foundational BPS framework to the multivariate setting, with detailed application in the topical and challenging context of multi-step macroeconomic forecasting in a monetary policy setting. BPS evaluates – sequentially and adaptively over time – varying forecast biases and facets of miscalibration of individual forecast densities for multiple time series, and – critically – their time-varying interdependencies. We define BPS methodology for a new class of dynamic multivariate latent factor models implied by BPS theory. Structured dynamic latent factor BPS is here motivated by the application context – sequential forecasting of multiple US macroeconomic time series with forecasts generated from several traditional econometric time series models. The case study highlights the potential of BPS to improve of forecasts of multiple series at multiple forecast horizons, and its use in learning dynamic relationships among forecasting models or agents.

Keywords: Agent opinion analysis, Bayesian forecasting, Dynamic latent factors models, Dynamic SURE models, Macroeconomic forecasting, Multivariate density forecast combination

JEL Classification: C11, C15, C53, E37

Suggested Citation

McAlinn, Kenichiro and Aastveit, Knut Are and Nakajima, Jouchi and West, Mike, Multivariate Bayesian Predictive Synthesis in Macroeconomic Forecasting (January 16, 2019). Norges Bank Working Paper 2/2019; ISBN 978-82-8379-068-9, Available at SSRN: https://ssrn.com/abstract=3334958 or http://dx.doi.org/10.2139/ssrn.3334958

Kenichiro McAlinn (Contact Author)

Temple University, Fox School of Business ( email )

Philadelphia, PA 19122
United States

Knut Are Aastveit

Norges Bank ( email )

P.O. Box 1179
Oslo, N-0107
Norway

Jouchi Nakajima

Bank for International Settlements (BIS) ( email )

Centralbahnplatz 2
Basel, Basel-Stadt 4002
Switzerland

Mike West

Duke University - Department of Statistical Science ( email )

Box 90251
Durham, NC 27708-0251
United States

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