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The world uncertainty index and GDP growth rate

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  • Liu, Na
  • Gao, Fumin

Abstract

Based on the content of the novel World Uncertainty Index (WUI), this paper examines whether the World Uncertainty Index has the predictability for the U.S. gross domestic product growth rate. Empirical results show that the information of WUI indices is able to predict GDP growth rate, especially the U.S. WUI indices such as USA WUI (frequency) and USA WUI (total number) indices. During the COVID-19 period, we find that all the WUI models can generate stronger forecasting ability for the GDP growth rate. Our paper tries to provide new evidence for predicting the GDP growth rate.

Suggested Citation

  • Liu, Na & Gao, Fumin, 2022. "The world uncertainty index and GDP growth rate," Finance Research Letters, Elsevier, vol. 49(C).
    • Handle: RePEc:eee:finlet:v:49:y:2022:i:c:s1544612322003609
    DOI: 10.1016/j.frl.2022.103137
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    1. Oguzhan Cepni & I. Ethem Guney & Norman R. Swanson, 2020. "Forecasting and nowcasting emerging market GDP growth rates: The role of latent global economic policy uncertainty and macroeconomic data surprise factors," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(1), pages 18-36, January.
    2. Nicholas Bloom, 2009. "The Impact of Uncertainty Shocks," Econometrica, Econometric Society, vol. 77(3), pages 623-685, May.
    3. Charlotte Christiansen & Maik Schmeling & Andreas Schrimpf, 2012. "A comprehensive look at financial volatility prediction by economic variables," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 27(6), pages 956-977, September.
    4. Ferderer, J Peter, 1993. "The Impact of Uncertainty on Aggregate Investment Spending: An Empirical Analysis," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 25(1), pages 30-48, February.
    5. Scott R. Baker & Nicholas Bloom & Steven J. Davis, 2016. "Measuring Economic Policy Uncertainty," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 131(4), pages 1593-1636.
    6. Clark, Todd E. & West, Kenneth D., 2007. "Approximately normal tests for equal predictive accuracy in nested models," Journal of Econometrics, Elsevier, vol. 138(1), pages 291-311, May.
    7. Chao Liang & Feng Ma & Lu Wang & Qing Zeng, 2021. "The information content of uncertainty indices for natural gas futures volatility forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(7), pages 1310-1324, November.
    8. Wen, Fenghua & Li, Cui & Sha, Han & Shao, Liuguo, 2021. "How does economic policy uncertainty affect corporate risk-taking? Evidence from China," Finance Research Letters, Elsevier, vol. 41(C).
    9. John Y. Campbell & Samuel B. Thompson, 2008. "Predicting Excess Stock Returns Out of Sample: Can Anything Beat the Historical Average?," Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1509-1531, July.
    10. Zeng, Qing & Ma, Feng & Lu, Xinjie & Xu, Weiju, 2022. "Policy uncertainty and carbon neutrality: Evidence from China," Finance Research Letters, Elsevier, vol. 47(PB).
    11. Pär Stockhammar & Pär Österholm, 2016. "Effects of US policy uncertainty on Swedish GDP growth," Empirical Economics, Springer, vol. 50(2), pages 443-462, March.
    12. He, Feng & Ma, Yaming & Zhang, Xiaojie, 2020. "How does economic policy uncertainty affect corporate Innovation?–Evidence from China listed companies," International Review of Economics & Finance, Elsevier, vol. 67(C), pages 225-239.
    13. David E. Rapach & Jack K. Strauss & Guofu Zhou, 2013. "International Stock Return Predictability: What Is the Role of the United States?," Journal of Finance, American Finance Association, vol. 68(4), pages 1633-1662, August.
    14. David E. Rapach & Jack K. Strauss & Guofu Zhou, 2010. "Out-of-Sample Equity Premium Prediction: Combination Forecasts and Links to the Real Economy," Review of Financial Studies, Society for Financial Studies, vol. 23(2), pages 821-862, February.
    15. Kilian, Lutz & Inoue, Atsushi, 2004. "Bagging Time Series Models," CEPR Discussion Papers 4333, C.E.P.R. Discussion Papers.
    16. Feng Ma & Xinjie Lu & Lu Wang & Julien Chevallier, 2021. "Global economic policy uncertainty and gold futures market volatility: Evidence from Markov regime‐switching GARCH‐MIDAS models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(6), pages 1070-1085, September.
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    Cited by:

    1. Giorgiana Roxana Ene, 2023. "A Snapshot of Where We Are. A Gross Domestic Product Analysis Related to Household Energy Price Index in the European Union," Ovidius University Annals, Economic Sciences Series, Ovidius University of Constantza, Faculty of Economic Sciences, vol. 0(1), pages 360-367, August.

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