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Discussion Paper Details

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Title: Macroeconomic Nowcasting and Forecasting with Big Data

Author(s): Brandyn Bok, Daniele Caratelli, Domenico Giannone, Argia Sbordone and Andrea Tambalotti

Publication Date: January 2018

Keyword(s): business cycle analysis, high-dimensional data, monitoring economic conditions and real-time data flow

Programme Area(s): Monetary Economics and Fluctuations

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.

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Bibliographic Reference

Bok, B, Caratelli, D, Giannone, D, Sbordone, A and Tambalotti, A. 2018. 'Macroeconomic Nowcasting and Forecasting with Big Data'. London, Centre for Economic Policy Research. https://cepr.org/active/publications/discussion_papers/dp.php?dpno=12589