Mixed-Frequency Macro–Finance Factor Models: Theory and Applications*

Elena Andreou, Patrick Gagliardini, Eric Ghysels and Mirco Rubin

Journal of Financial Econometrics, vol. 18, issue 3, 585-628

Abstract: This article presents tests for the existence of common factors spanning two large panels/groups of macroeconomic and financial variables, and the estimation of common and group-specific factors. New analytical results are derived regarding (i) the difference in the asymptotic distribution of the test statistics when aggregating the data first and then extracting the principal components (PCs), or vice versa, as well as (ii) the estimation of the common factor and its asymptotic distribution, extending the work of Andreou et al. (2019). We find that although there is no empirical evidence for one common factor, with constant loadings, in the United States during the period 1963–2017, there is evidence of one common macro–finance factor during the pre- and post-Great Moderation regimes. The aforementioned approaches of estimating PCs yield almost identical common and group-specific (financial and macro) factors which turn out to be significant in predicting key economic indicators, such as real Gross Domestic Product (GDP) growth and the CBOE Volatility Index, among others.

Keywords: large panel; unobservable pervasive factors; mixed frequency; canonical correlations; forecasting models (search for similar items in EconPapers)
JEL-codes: C22 C38 C53 C55 (search for similar items in EconPapers)
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