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Forecasting European Economic Policy Uncertainty

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  • Stavros Degiannakis

    (Department of Economics and Regional Development, Panteion University of Social and Political Sciences)

  • George Filis

    (Department of Accounting, Finance and Economics, Bournemouth University)

Abstract

Forecasting the economic policy uncertainty in Europe is of paramount importance given the on-going debt crisis and the Brexit vote. This paper evaluates monthly out-of-sample economic policy uncertainty index forecasts and examines whether ultra-high frequency information from asset market volatilities and global economic policy uncertainty can improve the forecasts relatively to the no-change forecast. The results show that the global economic policy uncertainty provides the highest predictive gains, followed by the European and US stock market volatilities. The results hold true even when we consider the directional accuracy.

Suggested Citation

  • Stavros Degiannakis & George Filis, 2018. "Forecasting European Economic Policy Uncertainty," BAFES Working Papers BAFES15, Department of Accounting, Finance & Economic, Bournemouth University.
  • Handle: RePEc:bam:wpaper:bafes15
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    1. N. Bloom, 2016. "Fluctuations in uncertainty," Voprosy Ekonomiki, NP Voprosy Ekonomiki, issue 4.
    2. Beckmann, Joscha & Czudaj, Robert, 2017. "The impact of uncertainty on professional exchange rate forecasts," Journal of International Money and Finance, Elsevier, vol. 73(PB), pages 296-316.
    3. Antonakakis, Nikolaos & Chatziantoniou, Ioannis & Filis, George, 2014. "Dynamic Spillovers of Oil Price Shocks and Policy Uncertainty," Department of Economics Working Paper Series 166, WU Vienna University of Economics and Business.
    4. Caggiano, Giovanni & Castelnuovo, Efrem & Figueres, Juan Manuel, 2017. "Economic policy uncertainty and unemployment in the United States: A nonlinear approach," Economics Letters, Elsevier, vol. 151(C), pages 31-34.
    5. Nicholas Bloom & Max Floetotto & Nir Jaimovich & Itay Saporta†Eksten & Stephen J. Terry, 2018. "Really Uncertain Business Cycles," Econometrica, Econometric Society, vol. 86(3), pages 1031-1065, May.
    6. Hansen, Peter Reinhard, 2005. "A Test for Superior Predictive Ability," Journal of Business & Economic Statistics, American Statistical Association, vol. 23, pages 365-380, October.
    7. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold, 2007. "Roughing It Up: Including Jump Components in the Measurement, Modeling, and Forecasting of Return Volatility," The Review of Economics and Statistics, MIT Press, vol. 89(4), pages 701-720, November.
    8. Emmanuel Sirimal Silva & Hossein Hassani, 2015. "On the use of singular spectrum analysis for forecasting U.S. trade before, during and after the 2008 recession," International Economics, CEPII research center, issue 141, pages 34-49.
    9. Kyle Jurado & Sydney C. Ludvigson & Serena Ng, 2015. "Measuring Uncertainty," American Economic Review, American Economic Association, vol. 105(3), pages 1177-1216, March.
    10. Wang, Yudong & Zhang, Bing & Diao, Xundi & Wu, Chongfeng, 2015. "Commodity price changes and the predictability of economic policy uncertainty," Economics Letters, Elsevier, vol. 127(C), pages 39-42.
    11. Nicholas Bloom, 2009. "The Impact of Uncertainty Shocks," Econometrica, Econometric Society, vol. 77(3), pages 623-685, May.
    12. Kang, Wensheng & Ratti, Ronald A., 2013. "Structural oil price shocks and policy uncertainty," Economic Modelling, Elsevier, vol. 35(C), pages 314-319.
    13. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    14. repec:cii:cepiie:2015-q1-141-30 is not listed on IDEAS
    15. Degiannakis, Stavros & Filis, George, 2017. "Forecasting oil price realized volatility using information channels from other asset classes," Journal of International Money and Finance, Elsevier, vol. 76(C), pages 28-49.
    16. Colombo, Valentina, 2013. "Economic policy uncertainty in the US: Does it matter for the Euro area?," Economics Letters, Elsevier, vol. 121(1), pages 39-42.
    17. Peter R. Hansen & Asger Lunde & James M. Nason, 2011. "The Model Confidence Set," Econometrica, Econometric Society, vol. 79(2), pages 453-497, March.
    18. Pindyck, Robert S, 1991. "Irreversibility, Uncertainty, and Investment," Journal of Economic Literature, American Economic Association, vol. 29(3), pages 1110-1148, September.
    19. Ko, Jun-Hyung & Lee, Chang-Min, 2015. "International economic policy uncertainty and stock prices: Wavelet approach," Economics Letters, Elsevier, vol. 134(C), pages 118-122.
    20. Kang, Wensheng & Ratti, Ronald A., 2013. "Oil shocks, policy uncertainty and stock market return," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 26(C), pages 305-318.
    21. Fulvio Corsi, 2009. "A Simple Approximate Long-Memory Model of Realized Volatility," Journal of Financial Econometrics, Oxford University Press, vol. 7(2), pages 174-196, Spring.
    22. 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.
    23. Marcellino, Massimiliano & Stock, James H. & Watson, Mark W., 2003. "Macroeconomic forecasting in the Euro area: Country specific versus area-wide information," European Economic Review, Elsevier, vol. 47(1), pages 1-18, February.
    24. 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.
    25. Antonakakis, Nikolaos & Chatziantoniou, Ioannis & Filis, George, 2013. "Dynamic co-movements of stock market returns, implied volatility and policy uncertainty," Economics Letters, Elsevier, vol. 120(1), pages 87-92.
    26. Kang, Wensheng & Lee, Kiseok & Ratti, Ronald A., 2014. "Economic policy uncertainty and firm-level investment," Journal of Macroeconomics, Elsevier, vol. 39(PA), pages 42-53.
    27. Ben S. Bernanke, 1983. "Irreversibility, Uncertainty, and Cyclical Investment," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 98(1), pages 85-106.
    28. Stelios Bekiros & Gazi Salah Uddin, 2017. "Extreme Dependence under Uncertainty: an application to Stock, Currency and Oil Markets," International Review of Finance, International Review of Finance Ltd., vol. 17(1), pages 155-162, March.
    29. Beckmann, Joscha & Czudaj, Robert, 2017. "Exchange rate expectations and economic policy uncertainty," European Journal of Political Economy, Elsevier, vol. 47(C), pages 148-162.
    30. Scotti, Chiara, 2016. "Surprise and uncertainty indexes: Real-time aggregation of real-activity macro-surprises," Journal of Monetary Economics, Elsevier, vol. 82(C), pages 1-19.
    31. Karnizova, Lilia & Li, Jiaxiong (Chris), 2014. "Economic policy uncertainty, financial markets and probability of US recessions," Economics Letters, Elsevier, vol. 125(2), pages 261-265.
    32. Leduc, Sylvain & Liu, Zheng, 2016. "Uncertainty shocks are aggregate demand shocks," Journal of Monetary Economics, Elsevier, vol. 82(C), pages 20-35.
    33. repec:cii:cepiei:2015-q1-141-3 is not listed on IDEAS
    34. Berger, Theo & Uddin, Gazi Salah, 2016. "On the dynamic dependence between equity markets, commodity futures and economic uncertainty indexes," Energy Economics, Elsevier, vol. 56(C), pages 374-383.
    35. Liu, Li & Zhang, Tao, 2015. "Economic policy uncertainty and stock market volatility," Finance Research Letters, Elsevier, vol. 15(C), pages 99-105.
    36. Strobel, Johannes, 2015. "On the different approaches of measuring uncertainty shocks," Economics Letters, Elsevier, vol. 134(C), pages 69-72.
    37. Antonakakis, Nikolaos & Chatziantoniou, Ioannis & Filis, George, 2014. "Dynamic spillovers of oil price shocks and economic policy uncertainty," Energy Economics, Elsevier, vol. 44(C), pages 433-447.
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    Cited by:

    1. Chatziantoniou, Ioannis & Degiannakis, Stavros & Delis, Panagiotis & Filis, George, 2021. "Forecasting oil price volatility using spillover effects from uncertainty indices," Finance Research Letters, Elsevier, vol. 42(C).
    2. Chatziantoniou, Ioannis & Degiannakis, Stavros & Delis, Panagiotis & Filis, George, 2019. "Can spillover effects provide forecasting gains? The case of oil price volatility," MPRA Paper 96266, University Library of Munich, Germany.
    3. Brandt, Richard, 2021. "Economic Policy Uncertainty Index: Extension and optimization of Scott R. Baker, Nicholas Bloom and Steven J. Davis's search term," DoCMA Working Papers 5, TU Dortmund University, Dortmund Center for Data-based Media Analysis (DoCMA).
    4. Afees A. Salisu & Rangan Gupta & Ahamuefula E. Ogbonna, 2021. "Point and density forecasting of macroeconomic and financial uncertainties of the USA," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(4), pages 700-707, July.
    5. Degiannakis, Stavros & Filis, George, 2023. "Oil price assumptions for macroeconomic policy," Energy Economics, Elsevier, vol. 117(C).
    6. Bonato, Matteo & Çepni, Oğuzhan & Gupta, Rangan & Pierdzioch, Christian, 2021. "Do oil-price shocks predict the realized variance of U.S. REITs?," Energy Economics, Elsevier, vol. 104(C).
    7. Gupta, Rangan & Sun, Xiaojin, 2020. "Forecasting economic policy uncertainty of BRIC countries using Bayesian VARs," Economics Letters, Elsevier, vol. 186(C).
    8. Alqahtani, Abdullah & Klein, Tony & Khalid, Ali, 2019. "The impact of oil price uncertainty on GCC stock markets," Resources Policy, Elsevier, vol. 64(C).
    9. Orlowski, Lucjan T., 2023. "How susceptible is the European financial stability to economic policy uncertainty?," Journal of Policy Modeling, Elsevier, vol. 45(4), pages 864-875.
    10. Afees A. Salisu & Rangan Gupta & Ahamuefula E. Ogbonna, 2020. "Point and Density Forecasting of Macroeconomic and Financial Uncertainties of the United States," Working Papers 202058, University of Pretoria, Department of Economics.
    11. Joscha Beckmann & Robert L. Czudaj & Gary Koop, 2019. "An empirical assessment of recent challenges in today's financial markets," Scottish Journal of Political Economy, Scottish Economic Society, vol. 66(1), pages 1-4, February.
    12. Syed Jawad Hussain Shahzad & Rangan Gupta & Riza Demirer & Christian Pierdzioch, 2022. "Oil shocks and directional predictability of macroeconomic uncertainties of developed economies: Evidence from high‐frequency data†," Scottish Journal of Political Economy, Scottish Economic Society, vol. 69(2), pages 169-185, May.

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    More about this item

    Keywords

    Economic policy uncertainty; forecasting; financial markets; commodities markets; HAR; ultra-high frequency information;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E60 - Macroeconomics and Monetary Economics - - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook - - - General
    • E66 - Macroeconomics and Monetary Economics - - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook - - - General Outlook and Conditions
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)

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