Predictable non-linearities in U.S. inflation

Jane M. Binner; C. Thomas Elger; Birger Nilsson; Jonathan A. Tepper

doi:10.1016/j.econlet.2006.06.001

Predictable non-linearities in U.S. inflation

Jane M. Binner^*, C. Thomas Elger, Birger Nilsson, Jonathan A. Tepper

^*Corresponding author for this work

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

Abstract

This paper compares the out-of-sample inflation forecasting performance of two non-linear models; a neural network and a Markov switching autoregressive (MS-AR) model. We find that predictable non-linearities in inflation are best accounted for by the MS-AR model.

Original language	English
Pages (from-to)	323-328
Number of pages	6
Journal	Economics Letters
Volume	93
Issue number	3
DOIs	https://doi.org/10.1016/j.econlet.2006.06.001
Publication status	Published - 1 Dec 2006

Bibliographical note

Keywords

Inflation forecasting
Markov switching models
Recurrent neural networks

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10.1016/j.econlet.2006.06.001

Predictable non-linearities in U.S. inflation
© 2006, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/
Accepted author manuscript, 94.6 KBLicence: CC BY-NC-ND 3.0

Cite this

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title = "Predictable non-linearities in U.S. inflation",

abstract = "This paper compares the out-of-sample inflation forecasting performance of two non-linear models; a neural network and a Markov switching autoregressive (MS-AR) model. We find that predictable non-linearities in inflation are best accounted for by the MS-AR model.",

keywords = "Inflation forecasting, Markov switching models, Recurrent neural networks",

author = "Binner, {Jane M.} and Elger, {C. Thomas} and Birger Nilsson and Tepper, {Jonathan A.}",

note = "{\textcopyright} 2006, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/",

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AU - Binner, Jane M.

AU - Elger, C. Thomas

AU - Nilsson, Birger

AU - Tepper, Jonathan A.

PY - 2006/12/1

Y1 - 2006/12/1

N2 - This paper compares the out-of-sample inflation forecasting performance of two non-linear models; a neural network and a Markov switching autoregressive (MS-AR) model. We find that predictable non-linearities in inflation are best accounted for by the MS-AR model.

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KW - Inflation forecasting

KW - Markov switching models

KW - Recurrent neural networks

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UR - https://www.sciencedirect.com/science/article/pii/S0165176506001972?via%3Dihub

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SP - 323

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JO - Economics Letters

JF - Economics Letters

IS - 3

ER -

Predictable non-linearities in U.S. inflation

Abstract

Bibliographical note

Keywords

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