A Coincident Index, Common Factors, and Monthly Real GDP

20 Pages Posted: 21 Dec 2009

See all articles by Roberto S. Mariano

Roberto S. Mariano

Singapore Management University

Yasutomo Murasawa

Konan University

Date Written: 0000

Abstract

The Stock–Watson coincident index and its subsequent extensions assume a static linear one-factor model for the component indicators. This restrictive assumption is unnecessary if one defines a coincident index as an estimate of monthly real gross domestic products (GDP). This paper estimates Gaussian vector autoregression (VAR) and factor models for latent monthly real GDP and other coincident indicators using the observable mixed-frequency series. For maximum likelihood estimation of a VAR model, the expectation-maximization (EM) algorithm helps in finding a good starting value for a quasi-Newton method. The smoothed estimate of latent monthly real GDP is a natural extension of the Stock–Watson coincident index.

Suggested Citation

Mariano, Roberto S. and Murasawa, Yasutomo, A Coincident Index, Common Factors, and Monthly Real GDP (0000). Oxford Bulletin of Economics and Statistics, Vol. 72, Issue 1, pp. 27-46, February 2010, Available at SSRN: https://ssrn.com/abstract=1524528 or http://dx.doi.org/10.1111/j.1468-0084.2009.00567.x

Roberto S. Mariano (Contact Author)

Singapore Management University ( email )

50 Stamford Rd.
Singapore 912409, 178899
Singapore

Yasutomo Murasawa

Konan University ( email )

8-9-1 Okamoto Higashinadaku
Kobe 658-8501
Japan

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