Abstract
The Stock–Watson coincident index of business cycles and its extensions assume a static linear one-factor model for the component indicators. This paper tests that assumption. Since the factor structure restricts the autocovariance matrices of the component indicators, a distance test, or the Hansen–Sargan test of over-identifying restrictions, is applicable. This also gives a GMM counterpart of the Stock–Watson coincident index, or a new composite index (CI) of coincident indicators, as a by-product. For the four US coincident indicators that currently make up the CI, the test strongly rejects the null hypothesis of static linear one-factor structure.
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