Constructing a Coincident Index of Business Cycles without Assuming a One-Factor Model

The Stock–Watson coincident index and its subsequent extensions assume a static linear one-factor structure for the component indicators. Such assumption is restrictive in practice, however, with as few as four indicators. In fact, such assumption is unnecessary if one defines a coincident index as...

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Main Authors: Mariano, Roberto S., Murasawa, Yasutomo
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2004
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Online Access:https://ink.library.smu.edu.sg/soe_research/985
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spelling sg-smu-ink.soe_research-19842010-09-23T05:48:03Z Constructing a Coincident Index of Business Cycles without Assuming a One-Factor Model Mariano, Roberto S. Murasawa, Yasutomo The Stock–Watson coincident index and its subsequent extensions assume a static linear one-factor structure for the component indicators. Such assumption is restrictive in practice, however, with as few as four indicators. In fact, such assumption is unnecessary if one defines a coincident index as an estimate of latent monthly real GDP. This paper considers VAR and factor models for latent monthly real GDP and other coincident indicators, and estimates the models using the observable mixed-frequency series. For US data, Schwartz’s Bayesian information criterion selects a two-factor model. The smoothed estimate of latent monthly real GDP is the proposed index. 2004-09-01T07:00:00Z text https://ink.library.smu.edu.sg/soe_research/985 Research Collection School Of Economics eng Institutional Knowledge at Singapore Management University Econometrics
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Econometrics
spellingShingle Econometrics
Mariano, Roberto S.
Murasawa, Yasutomo
Constructing a Coincident Index of Business Cycles without Assuming a One-Factor Model
description The Stock–Watson coincident index and its subsequent extensions assume a static linear one-factor structure for the component indicators. Such assumption is restrictive in practice, however, with as few as four indicators. In fact, such assumption is unnecessary if one defines a coincident index as an estimate of latent monthly real GDP. This paper considers VAR and factor models for latent monthly real GDP and other coincident indicators, and estimates the models using the observable mixed-frequency series. For US data, Schwartz’s Bayesian information criterion selects a two-factor model. The smoothed estimate of latent monthly real GDP is the proposed index.
format text
author Mariano, Roberto S.
Murasawa, Yasutomo
author_facet Mariano, Roberto S.
Murasawa, Yasutomo
author_sort Mariano, Roberto S.
title Constructing a Coincident Index of Business Cycles without Assuming a One-Factor Model
title_short Constructing a Coincident Index of Business Cycles without Assuming a One-Factor Model
title_full Constructing a Coincident Index of Business Cycles without Assuming a One-Factor Model
title_fullStr Constructing a Coincident Index of Business Cycles without Assuming a One-Factor Model
title_full_unstemmed Constructing a Coincident Index of Business Cycles without Assuming a One-Factor Model
title_sort constructing a coincident index of business cycles without assuming a one-factor model
publisher Institutional Knowledge at Singapore Management University
publishDate 2004
url https://ink.library.smu.edu.sg/soe_research/985
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