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Macroeconomic Uncertainty Through the Lens of Professional Forecasters

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  • Soojin Jo

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  • Rodrigo Sekkel

Abstract

We analyze the evolution of macroeconomic uncertainty in the United States, based on the forecast errors of consensus survey forecasts of various economic indicators. Comprehensive information contained in the survey forecasts enables us to capture a real-time subjective measure of uncertainty in a simple framework. We jointly model and estimate macroeconomic (common) and indicator-specific uncertainties of four indicators, using a factor stochastic volatility model. Our macroeconomic uncertainty has three major spikes aligned with the 1973?75, 1980, and 2007?09 recessions, while other recessions were characterized by increases in indicator-specific uncertainties. We also show that the selection of data vintages affects the estimates and relative size of jumps in estimated uncertainty series. Finally, our macroeconomic uncertainty has a persistent negative impact on real economic activity, rather than producing ?wait-and-see? dynamics.

Suggested Citation

  • Soojin Jo & Rodrigo Sekkel, 2017. "Macroeconomic Uncertainty Through the Lens of Professional Forecasters," Working Papers 1702, Federal Reserve Bank of Dallas.
  • Handle: RePEc:fip:feddwp:1702
    DOI: 10.24149/wp1702
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    Cited by:

    1. Richard K. Crump & Stefano Eusepi & Emanuel Moench, 2016. "The term structure of expectations and bond yields," Staff Reports 775, Federal Reserve Bank of New York.
    2. Laurent Ferrara & Pierre Guérin, 2018. "What are the macroeconomic effects of high‐frequency uncertainty shocks?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(5), pages 662-679, August.
    3. Takeshi Shinohara & Tatsushi Okuda & Jouchi Nakajima, 2020. "Characteristics of Uncertainty Indices in the Macroeconomy," Bank of Japan Working Paper Series 20-E-6, Bank of Japan.
    4. Ambrocio, Gene, 2017. "The real effects of overconfidence and fundamental uncertainty shocks," Research Discussion Papers 37/2017, Bank of Finland.
    5. Kajal Lahiri & Huaming Peng & Xuguang Sheng, 2015. "Measuring Uncertainty of a Combined Forecast and Some Tests for Forecaster Heterogeneity," CESifo Working Paper Series 5468, CESifo.
    6. Ozturk, Ezgi O. & Sheng, Xuguang Simon, 2018. "Measuring global and country-specific uncertainty," Journal of International Money and Finance, Elsevier, vol. 88(C), pages 276-295.
    7. Todd E. Clark & Michael W. McCracken & Elmar Mertens, 2020. "Modeling Time-Varying Uncertainty of Multiple-Horizon Forecast Errors," The Review of Economics and Statistics, MIT Press, vol. 102(1), pages 17-33, March.
    8. Galvao, Ana Beatriz & Garratt, Anthony & Mitchell, James, 2020. "Does Judgment Improve Macroeconomic Density Forecasts?," EMF Research Papers 33, Economic Modelling and Forecasting Group.
    9. Lucy Greig & Amy Rice & Tugrul Vehbi & Benjamin Wong, 2018. "Measuring Uncertainty and Its Impact on a Small Open Economy," Australian Economic Review, The University of Melbourne, Melbourne Institute of Applied Economic and Social Research, vol. 51(1), pages 87-98, March.
    10. Glas, Alexander, 2020. "Five dimensions of the uncertainty–disagreement linkage," International Journal of Forecasting, Elsevier, vol. 36(2), pages 607-627.
    11. Liu, Yang & Sheng, Xuguang Simon, 2019. "The measurement and transmission of macroeconomic uncertainty: Evidence from the U.S. and BRIC countries," International Journal of Forecasting, Elsevier, vol. 35(3), pages 967-979.
    12. Danilo Cascaldi-Garcia & Deepa Dhume Datta & Thiago Revil T. Ferreira & Olesya V. Grishchenko & Mohammad R. Jahan-Parvar & Juan M. Londono & Francesca Loria & Sai Ma & Marius del Giudice Rodriguez & J, 2020. "What is Certain about Uncertainty?," International Finance Discussion Papers 1294, Board of Governors of the Federal Reserve System (U.S.).
    13. MORIKAWA Masayuki, 2018. "Measuring Firm-level Uncertainty: New evidence from a business outlook survey," Discussion papers 18030, Research Institute of Economy, Trade and Industry (RIETI).
    14. Buesa, Alejandro & Población García, Francisco Javier & Tarancón, Javier, 2019. "Measuring the procyclicality of impairment accounting regimes: a comparison between IFRS 9 and US GAAP," Working Paper Series 2347, European Central Bank.
    15. Martina Hengge, 2019. "Uncertainty as a Predictor of Economic Activity," IHEID Working Papers 19-2019, Economics Section, The Graduate Institute of International Studies.
    16. Travis J. Berge, 2020. "Time-varying Uncertainty of the Federal Reserve’s Output Gap Estimate," Finance and Economics Discussion Series 2020-012, Board of Governors of the Federal Reserve System (U.S.).
    17. Krüger, Steffen & Rösch, Daniel & Scheule, Harald, 2018. "The impact of loan loss provisioning on bank capital requirements," Journal of Financial Stability, Elsevier, vol. 36(C), pages 114-129.
    18. Joshy Easaw & Christian Grimme, 2021. "The Impact of Aggregate Uncertainty on Firm-Level Uncertainty," CESifo Working Paper Series 8934, CESifo.
    19. Guglielmo Maria Caporale & Menelaos Karanasos & Stavroula Yfanti, 2019. "Macro-Financial Linkages in the High-Frequency Domain: The Effects of Uncertainty on Realized Volatility," CESifo Working Paper Series 8000, CESifo.
    20. Tatjana Dahlhaus & Tatevik Sekhposyan, 2018. "Monetary Policy Uncertainty: A Tale of Two Tails," Staff Working Papers 18-50, Bank of Canada.

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    More about this item

    Keywords

    Factor stochastic volatility model; survey forecasts; Uncertainty;
    All these keywords.

    JEL classification:

    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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