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

Author

Roberto S. MARIANO, Singapore Management UniversityFollow
Yasutomo MURASAWA, Osaka Prefecture University

Publication Type

Working Paper

Version

publishedVersion

Publication Date

10-2004

Abstract

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.

Discipline

Econometrics | Macroeconomics

Research Areas

Econometrics

Volume

22-2004

First Page

1

Last Page

24

Publisher

SMU Economics and Statistics Working Paper Series, No. 22-2004

City or Country

Singapore

Citation

MARIANO, Roberto S. and MURASAWA, Yasutomo. Constructing a Coincident Index of Business Cycles without Assuming a One-Factor Model. (2004). 22-2004, 1-24.
Available at: https://ink.library.smu.edu.sg/soe_research/795

Copyright Owner and License

Authors

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.