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Macroeconomic Uncertainty Indices Based on Nowcast and Forecast Error Distributions

Listed author(s):
  • Barbara Rossi
  • Tatevik Sekhposyan

We propose new indices to measure macroeconomic uncertainty. The indices measure how unexpected a realization of a representative macroeconomic variable is relative to the unconditional forecast error distribution. We use forecast error distributions based on the nowcasts and forecasts of the Survey of Professional Forecasters. We further compare the new indices with those proposed in the literature and assess their macroeconomic impact.

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File URL: http://www.aeaweb.org/articles.php?doi=10.1257/aer.p20151124
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File URL: https://www.aeaweb.org/aer/app/10505/P2015_1124_app.pdf
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File URL: https://www.aeaweb.org/aer/ds/10505/P2015_1124_ds.zip
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Article provided by American Economic Association in its journal American Economic Review.

Volume (Year): 105 (2015)
Issue (Month): 5 (May)
Pages: 650-655

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Handle: RePEc:aea:aecrev:v:105:y:2015:i:5:p:650-55
Note: DOI: 10.1257/aer.p20151124
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References listed on IDEAS
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  1. Gill Segal & Ivan Shaliastovich & Amir Yaron, 2014. "Good and Bad Uncertainty: Macroeconomic and Financial Market Implications," 2014 Meeting Papers 488, Society for Economic Dynamics.
  2. Nicholas Bloom, 2009. "The Impact of Uncertainty Shocks," Econometrica, Econometric Society, vol. 77(3), pages 623-685, 05.
  3. Rossi, Barbara & Sekhposyan, Tatevik, 2014. "Evaluating predictive densities of US output growth and inflation in a large macroeconomic data set," International Journal of Forecasting, Elsevier, vol. 30(3), pages 662-682.
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