Nowcasting Business Cycles: a Bayesian Approach to Dynamic Heterogeneous Factor Models

Antonello D'Agostino, Domenico Giannone, Michele Lenza and Michele Modugno

No 2015-66, Finance and Economics Discussion Series from Board of Governors of the Federal Reserve System (U.S.)

Abstract: We develop a framework for measuring and monitoring business cycles in real time. Following a long tradition in macroeconometrics, inference is based on a variety of indicators of economic activity, treated as imperfect measures of an underlying index of business cycle conditions. We extend existing approaches by permitting for heterogenous lead-lag patterns of the various indicators along the business cycles. The framework is well suited for high-frequency monitoring of current economic conditions in real time - nowcasting - since inference can be conducted in presence of mixed frequency data and irregular patterns of data availability. Our assessment of the underlying index of business cycle conditions is accurate and more timely than popular alternatives, including the Chicago Fed National Activity Index (CFNAI). A formal real-time forecasting evaluation shows that the framework produces well-calibrated probability nowcasts that resemble the consensus assessment of t he Survey of Professional Forecasters.

Keywords: Current Economic Conditions; Dynamic Factor Models; Dynamic Heterogeneity; Business Cycles; Real Time; nowcasting (search for similar items in EconPapers)
JEL-codes: C11 C32 C38 E32 (search for similar items in EconPapers)
Pages: 24 pages
Date: 2015-08-06
New Economics Papers: this item is included in nep-ecm, nep-for and nep-mac
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Citations: View citations in EconPapers (11)

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http://www.federalreserve.gov/econresdata/feds/2015/files/2015066pap.pdf Full text (application/pdf)
http://dx.doi.org/10.17016/FEDS.2015.066 http://dx.doi.org/10.17016/FEDS.2015.066 (application/pdf)

Related works:
Chapter: Nowcasting Business Cycles: A Bayesian Approach to Dynamic Heterogeneous Factor Models (2016)
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