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The Role of Economic Policy Uncertainty in Forecasting US Inflation Using a VARFIMA Model

Author

Listed:
  • Mehmet Balcilar

    (Department of Economics, Eastern Mediterranean University, Famagusta, Northern Cyprus , via Mersin 10, Turkey; Department of Economics, University of Pretoria, Pretoria, 0002, South Africa)

  • Rangan Gupta

    (Department of Economics, University of Pretoria)

  • Charl Jooste

    (Department of Economics, University of Pretoria)

Abstract

We compare inflation forecasts of a vector fractionally integrated autoregressive moving average (VARFIMA) model against standard forecasting models. U.S. inflation forecasts improve when controlling for persistence and economic policy uncertainty (EPU). Importantly, the VARFIMA model, comprising of inflation and EPU, outperforms commonly used inflation forecast models.

Suggested Citation

  • Mehmet Balcilar & Rangan Gupta & Charl Jooste, 2014. "The Role of Economic Policy Uncertainty in Forecasting US Inflation Using a VARFIMA Model," Working Papers 201460, University of Pretoria, Department of Economics.
  • Handle: RePEc:pre:wpaper:201460
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    References listed on IDEAS

    as
    1. Jones, Paul M. & Olson, Eric, 2013. "The time-varying correlation between uncertainty, output, and inflation: Evidence from a DCC-GARCH model," Economics Letters, Elsevier, vol. 118(1), pages 33-37.
    2. Lovcha, Yuliya & Pérez Laborda, Àlex, 2013. "A fractionally integrated approach to monetary policy and inflation dynamics," Working Papers 2072/211795, Universitat Rovira i Virgili, Department of Economics.
    3. 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.
    4. Dick van Dijk & Philip Hans Franses, 2003. "Selecting a Nonlinear Time Series Model using Weighted Tests of Equal Forecast Accuracy," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 65(s1), pages 727-744, December.
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    Cited by:

    1. Wael Hemrit, 2022. "Does insurance demand react to economic policy uncertainty and geopolitical risk? Evidence from Saudi Arabia," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 47(2), pages 460-492, April.
    2. Kazutaka Kurasawa, 2016. "Policy Uncertainty and Foreign Exchange Rates: The DCC-GARCH Model of the US / Japanese Foreign Exchange Rate," International Journal of Economic Sciences, International Institute of Social and Economic Sciences, vol. 5(4), pages 1-19, December.
    3. Mehmet Balcilar & Rangan Gupta & Clement Kyei & Mark E. Wohar, 2016. "Does Economic Policy Uncertainty Predict Exchange Rate Returns and Volatility? Evidence from a Nonparametric Causality-in-Quantiles Test," Open Economies Review, Springer, vol. 27(2), pages 229-250, April.
    4. López Noria Gabriela & Bush Georgia, 2019. "Uncertainty and Exchange Rate Volatility: the Case of Mexico," Working Papers 2019-12, Banco de México.
    5. Christina Anderl & Guglielmo Maria Caporale, 2023. "The Asymmetric Impact of Economic Policy and Oil Price Uncertainty on Inflation: Evidence from Developed and Emerging Economies," CESifo Working Paper Series 10276, CESifo.
    6. Lei, Adrian C.H. & Song, Chen, 2022. "Economic policy uncertainty and stock market activity: Evidence from China," Global Finance Journal, Elsevier, vol. 52(C).
    7. Yin DAI & Jing-wen ZHANG & Xiu-zhen YU & Xin LI, 2017. "Causality between economic policy uncertainty and exchange rate in China with considering quantile differences," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania - AGER, vol. 0(3(612), A), pages 29-38, Autumn.
    8. Kisswani, Khalid M. & Elian, Mohammad I., 2021. "Analyzing the (a)symmetric impacts of oil price, economic policy uncertainty, and global geopolitical risk on exchange rate," The Journal of Economic Asymmetries, Elsevier, vol. 24(C).

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    More about this item

    Keywords

    Inflation; long-range dependency; economic policy uncertainty;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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