Revealing priors from posteriors with an application to inflation forecasting in the UK

Masako Ikefuji; Jan Magnus; Takashi Yamagata

doi:10.1093/ectj/utad021

Revealing priors from posteriors with an application to inflation forecasting in the UK

Masako Ikefuji, Jan Magnus, Takashi Yamagata

Economics

Research output: Contribution to journal › Article › peer-review

Abstract

A Bayesian typically uses data and a prior to produce a posterior.
We shall follow the opposite route, using data and the posterior information to reveal the prior. We then apply this theory to inflation forecasts by the Bank of England and the National Institute of Economic and Social Research in an attempt to get some insight into the prior beliefs of the policy makers in these two institutions, especially under the uncertainties about the Brexit referendum, the Covid-19 lockdown, and the Russian invasion of Ukraine.

Original language	English
Pages (from-to)	151-170
Number of pages	20
Journal	Econometrics Journal
Volume	27
Issue number	1
Early online date	3 Oct 2023
DOIs	https://doi.org/10.1093/ectj/utad021
Publication status	Published - 1 Jan 2024

Bibliographical note

Access to Document

10.1093/ectj/utad021Licence: CC BY

Revealing priors from posteriors with an application to inflation forecasting in the UK
© The Author(s) 2023
Final published version, 832 KBLicence: CC BY

Cite this

@article{e792e4c6e3af4a729242ab8e3e778371,

title = "Revealing priors from posteriors with an application to inflation forecasting in the UK",

abstract = "A Bayesian typically uses data and a prior to produce a posterior.We shall follow the opposite route, using data and the posterior information to reveal the prior. We then apply this theory to inflation forecasts by the Bank of England and the National Institute of Economic and Social Research in an attempt to get some insight into the prior beliefs of the policy makers in these two institutions, especially under the uncertainties about the Brexit referendum, the Covid-19 lockdown, and the Russian invasion of Ukraine.",

author = "Masako Ikefuji and Jan Magnus and Takashi Yamagata",

note = "{\textcopyright} The Author(s) 2023",

year = "2024",

month = jan,

day = "1",

doi = "10.1093/ectj/utad021",

language = "English",

volume = "27",

pages = "151--170",

journal = "Econometrics Journal",

issn = "1368-4221",

publisher = "Wiley-Blackwell",

number = "1",

}

TY - JOUR

T1 - Revealing priors from posteriors with an application to inflation forecasting in the UK

AU - Ikefuji, Masako

AU - Magnus, Jan

AU - Yamagata, Takashi

PY - 2024/1/1

Y1 - 2024/1/1

N2 - A Bayesian typically uses data and a prior to produce a posterior.We shall follow the opposite route, using data and the posterior information to reveal the prior. We then apply this theory to inflation forecasts by the Bank of England and the National Institute of Economic and Social Research in an attempt to get some insight into the prior beliefs of the policy makers in these two institutions, especially under the uncertainties about the Brexit referendum, the Covid-19 lockdown, and the Russian invasion of Ukraine.

AB - A Bayesian typically uses data and a prior to produce a posterior.We shall follow the opposite route, using data and the posterior information to reveal the prior. We then apply this theory to inflation forecasts by the Bank of England and the National Institute of Economic and Social Research in an attempt to get some insight into the prior beliefs of the policy makers in these two institutions, especially under the uncertainties about the Brexit referendum, the Covid-19 lockdown, and the Russian invasion of Ukraine.

U2 - 10.1093/ectj/utad021

DO - 10.1093/ectj/utad021

M3 - Article

SN - 1368-4221

VL - 27

SP - 151

EP - 170

JO - Econometrics Journal

JF - Econometrics Journal

IS - 1

ER -