Publication Type
Journal Article
Version
submittedVersion
Publication Date
7-2003
Abstract
Popular monthly coincident indices of business cycles, e.g. the composite index and the Stock-Watson coincident index, have two shortcomings. First, they ignore information contained in quarterly indicators such as real GDP. Second, they lack economic interpretation; hence the heights of peaks and the depths of troughs depend on the choice of an index. This paper extends the Stock-Watson coincident index by applying maximum likelihood factor analysis to a mixed-frequency series of quarterly real GDP and monthly coincident business cycle indicators. The resulting index is related to latent monthly real GDP. [PUBLICATION ABSTRACT]
Keywords
Factor analysis, Time series, Missing observation, State-space model, Kalman filter, Stock-Watson index
Discipline
Econometrics | Finance
Research Areas
Econometrics
Publication
Journal of Applied Econometrics
Volume
18
Issue
4
First Page
427
Last Page
443
ISSN
0883-7252
Identifier
10.1002/jae.695
Publisher
Wiley
Citation
Mariano, Roberto S. and Murasawa, Yasutomo.
A new coincident index of business cycles based on monthly and quarterly series. (2003). Journal of Applied Econometrics. 18, (4), 427-443.
Available at: https://ink.library.smu.edu.sg/soe_research/374
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.
Additional URL
https://doi.org/10.1002/jae.695