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Silos, Pedro
Vilán, Diego
Year of Publication: 
[Journal:] Economic Review [ISSN:] 0732-1813 [Volume:] 94 [Year:] 2009 [No.:] 3
Assessing the state of an economy is not an easy task and generally involves interpreting myriad and sometimes contradictory indicators. In 2007 the authors unveiled a dynamic common factor model, dubbed the D6 Factor, for the economy of the Sixth Federal Reserve District. This model combined disaggregated information for each of the six states in the Southeast and provided an estimate of an unobserved common component that would account for major shifts in the region's economic activity. The D6 Factor proved superior to the traditional practice of averaging state-level factors because it was able to filter out idiosyncratic shocks that could disproportionately affect one state in the sample.This article presents an updated version of the D6 Factor that improves upon the original model in several ways. While the original D6 based its estimation on twenty-five distinct data series, the new version uses forty-eight. In addition, the revised model expands the sample estimation period by a decade. These changes provide the updated model with substantially more information while reducing the incidence that certain key series (like housing) had in the original common factor movement. The longer data set also allows for historical comparisons across several business cycles.Another feature of the new D6 enables it to handle data at both monthly and quarterly frequencies, a feature that greatly increases researchers' options. The authors find that, when compared to the original D6, the updated model does a better job of describing contemporary economic activity because it significantly reduces noise in the estimation.
coincident index
dynamic factor model
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