Macroeconomic forecasting using BVARs

Niko Hauzenberger; Florian Huber; Gary Koop

Macroeconomic forecasting using BVARs

Niko Hauzenberger, Florian Huber, Gary Koop

Research output: Chapter in Book/Report/Conference proceeding › Chapter

Abstract

Bayesian Vector Autoregressions (BVARs) have come a long way since the classic early work of Chris Sims and his co-authors, e.g., Sims (1980) and Doan et al. (1984), and have developed into one of the most popular tools for macroeconomic forecasting. The original Minnesota prior used in early work is still very popular, but a range of alternative priors have been proposed with various properties. In this chapter, we will discuss some of the many new VAR priors that have been proposed over the last decades and discuss their properties.

Original language	English
Title of host publication	Handbook of Research Methods and Applications on Macroeconomic Forecasting
Editors	Michael P. Clements, Ana Beatriz Galvao
Place of Publication	Cheltenham, UK
Chapter	2
Pages	15-42
Number of pages	31
ISBN (Electronic)	978 1 03531 005 0
Publication status	Published - 26 Nov 2024

Publication series

Name	Handbooks of Research Methods and Applications
Publisher	Edward Elgar

Keywords

Bayesian Vector Autoregression
macroeconomic forecasting
forecasting performance models

Cite this

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title = "Macroeconomic forecasting using BVARs",

abstract = "Bayesian Vector Autoregressions (BVARs) have come a long way since the classic early work of Chris Sims and his co-authors, e.g., Sims (1980) and Doan et al. (1984), and have developed into one of the most popular tools for macroeconomic forecasting. The original Minnesota prior used in early work is still very popular, but a range of alternative priors have been proposed with various properties. In this chapter, we will discuss some of the many new VAR priors that have been proposed over the last decades and discuss their properties.",

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AU - Hauzenberger, Niko

AU - Huber, Florian

AU - Koop, Gary

N1 - This is a draft chapter/article. The final version is available in Handbook of Research Methods and Applications in Macroeconomic Forecasting edited by Michael P. Clements and Ana Beatriz Galvão, published in 2024, Edward Elgar Publishing Ltd https://doi.org/10.4337/9781035310050. It is deposited under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way.

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N2 - Bayesian Vector Autoregressions (BVARs) have come a long way since the classic early work of Chris Sims and his co-authors, e.g., Sims (1980) and Doan et al. (1984), and have developed into one of the most popular tools for macroeconomic forecasting. The original Minnesota prior used in early work is still very popular, but a range of alternative priors have been proposed with various properties. In this chapter, we will discuss some of the many new VAR priors that have been proposed over the last decades and discuss their properties.

AB - Bayesian Vector Autoregressions (BVARs) have come a long way since the classic early work of Chris Sims and his co-authors, e.g., Sims (1980) and Doan et al. (1984), and have developed into one of the most popular tools for macroeconomic forecasting. The original Minnesota prior used in early work is still very popular, but a range of alternative priors have been proposed with various properties. In this chapter, we will discuss some of the many new VAR priors that have been proposed over the last decades and discuss their properties.

KW - Bayesian Vector Autoregression

KW - macroeconomic forecasting

KW - forecasting performance models

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M3 - Chapter

SN - 9781035310043

T3 - Handbooks of Research Methods and Applications

SP - 15

EP - 42

BT - Handbook of Research Methods and Applications on Macroeconomic Forecasting

A2 - Clements, Michael P.

A2 - Galvao, Ana Beatriz

CY - Cheltenham, UK

ER -

Macroeconomic forecasting using BVARs

Abstract

Publication series

Keywords

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Embargoed Document

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Statistical software for macroeconomic forecasting using BVARs: Open source code package in R on GitHub

Cite this