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A New “Big Data” Index of U.S. Economic Activity

Author

Listed:
  • Scott A. Brave
  • R. Andrew Butters
  • David Kelley

Abstract

The authors present a new ?big data? index of U.S. economic activity that can be used to track business and inflation cycles in real time and estimate monthly real gross domestic product growth.

Suggested Citation

  • Scott A. Brave & R. Andrew Butters & David Kelley, 2019. "A New “Big Data” Index of U.S. Economic Activity," Economic Perspectives, Federal Reserve Bank of Chicago, issue 1, pages 1-30.
    • Handle: RePEc:fip:fedhep:00034
    DOI: 10.21033/ep-2019-1
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    References listed on IDEAS

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    1. Giannone, Domenico & Reichlin, Lucrezia & Small, David, 2008. "Nowcasting: The real-time informational content of macroeconomic data," Journal of Monetary Economics, Elsevier, vol. 55(4), pages 665-676, May.
    2. Groen, Jan J.J. & Kapetanios, George, 2016. "Revisiting useful approaches to data-rich macroeconomic forecasting," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 221-239.
    3. Stock, James H. & Watson, Mark, 2011. "Dynamic Factor Models," Scholarly Articles 28469541, Harvard University Department of Economics.
    4. Patrick C. Higgins, 2014. "GDPNow: A Model for GDP \"Nowcasting\"," FRB Atlanta Working Paper 2014-7, Federal Reserve Bank of Atlanta.
    5. Catherine Doz & Domenico Giannone & Lucrezia Reichlin, 2012. "A Quasi–Maximum Likelihood Approach for Large, Approximate Dynamic Factor Models," The Review of Economics and Statistics, MIT Press, vol. 94(4), pages 1014-1024, November.
    6. Durbin, James & Koopman, Siem Jan, 2012. "Time Series Analysis by State Space Methods," OUP Catalogue, Oxford University Press, edition 2, number 9780199641178.
    7. Antonello D’Agostino & Domenico Giannone & Michele Lenza & Michele Modugno, 2016. "Nowcasting Business Cycles: A Bayesian Approach to Dynamic Heterogeneous Factor Models," Advances in Econometrics, in: Dynamic Factor Models, volume 35, pages 569-594, Emerald Group Publishing Limited.
    8. Peter Exterkate & Dick Van Dijk & Christiaan Heij & Patrick J. F. Groenen, 2013. "Forecasting the Yield Curve in a Data‐Rich Environment Using the Factor‐Augmented Nelson–Siegel Model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 32(3), pages 193-214, April.
    9. Clements, Michael P. & Hendry, David F. (ed.), 2011. "The Oxford Handbook of Economic Forecasting," OUP Catalogue, Oxford University Press, number 9780195398649.
    10. Domenico Giannone & Lucrezia Reichlin & David Small, 2008. "Nowcasting: the real time informational content of macroeconomic data releases," ULB Institutional Repository 2013/6409, ULB -- Universite Libre de Bruxelles.
    11. Chamberlain, Gary & Rothschild, Michael, 1983. "Arbitrage, Factor Structure, and Mean-Variance Analysis on Large Asset Markets," Econometrica, Econometric Society, vol. 51(5), pages 1281-1304, September.
    12. Scott Brave & Max Lichtenstein, 2012. "A different way to review the Chicago Fed National Activity Index," Chicago Fed Letter, Federal Reserve Bank of Chicago, issue May.
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    Cited by:

    1. Bu, Chunya & Rogers, John & Wu, Wenbin, 2021. "A unified measure of Fed monetary policy shocks," Journal of Monetary Economics, Elsevier, vol. 118(C), pages 331-349.
    2. Meyer, Brent H. & Prescott, Brian & Sheng, Xuguang Simon, 2022. "The impact of the COVID-19 pandemic on business expectations," International Journal of Forecasting, Elsevier, vol. 38(2), pages 529-544.
    3. Michael T. Kiley, 2020. "Financial Conditions and Economic Activity: Insights from Machine Learning," Finance and Economics Discussion Series 2020-095, Board of Governors of the Federal Reserve System (U.S.).
    4. James Mitchell & Gary Koop & Stuart McIntyre & Aubrey Poon, 2020. "Reconciled Estimates of Monthly GDP in the US," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2020-16, Economic Statistics Centre of Excellence (ESCoE).
    5. Michael D. Bauer & Eric T. Swanson, 2020. "The Fed's Response to Economic News Explains the “Fed Information Effect”," Working Paper Series 2020-06, Federal Reserve Bank of San Francisco.

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