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Board of Governors of the Federal Reserve System (US)
Finance and Economics Discussion Series
Nowcasting Business Cycles: a Bayesian Approach to Dynamic Heterogeneous Factor Models
Antonello D'Agostino
Domenico Giannone
Michele Lenza
Michele Modugno
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.


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Download http://dx.doi.org/10.17016/FEDS.2015.066
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Antonello D'Agostino & Domenico Giannone & Michele Lenza & Michele Modugno, Nowcasting Business Cycles: a Bayesian Approach to Dynamic Heterogeneous Factor Models, Board of Governors of the Federal Reserve System (US), Finance and Economics Discussion Series 2015-66, 06 Aug 2015.
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Keywords: Current Economic Conditions; Dynamic Factor Models; Dynamic Heterogeneity; Business Cycles; Real Time; Nowcasting.
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