Macroeconomic Nowcasting and Forecasting with Big Data

Domenico Giannone, Andrea Tambalotti, Argia Sbordone, Brandyn Bok and Daniele Caratelli

No 12589, CEPR Discussion Papers from C.E.P.R. Discussion Papers

Abstract: Data, data, data ... Economists know their importance well, especially when it comes to monitoring macroeconomic conditions -- the basis for making informed economic and policy decisions. Handling large and complex data sets was a challenge that macroeconomists engaged in real-time analysis faced long before "big data" became pervasive in other disciplines. We review how methods for tracking economic conditions using big data have evolved over time and explain how econometric techniques have advanced to mimic and automate best practices of forecasters on trading desks, at central banks, and in other market-monitoring roles. We present in detail the methodology underlying the New York Fed Staff Nowcast, which employs these innovative techniques to produce early estimates of GDP growth, synthesizing a wide range of macroeconomic data as they become available.

Keywords: Monitoring economic conditions; Business cycle analysis; High-dimensional data; Real-time data flow (search for similar items in EconPapers)
JEL-codes: C32 C53 C55 E3 (search for similar items in EconPapers)
Date: 2018-01
New Economics Papers: this item is included in nep-big, nep-for, nep-hpe and nep-mac
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Citations: View citations in EconPapers (97)

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Journal Article: Macroeconomic Nowcasting and Forecasting with Big Data (2018)
Working Paper: Macroeconomic nowcasting and forecasting with big data (2017)
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