Title

A Coincident Index, Common Factors, and Monthly Real Gdp

Publication Type

Journal Article

Publication Date

2-2010

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.

Discipline

Econometrics

Research Areas

Econometrics

Publication

Oxford Bulletin of Economics and Statistics

Volume

72

Issue

1

First Page

27-46

ISSN

0305-9049

Identifier

10.1111/j.1468-0084.2009.00567.x