IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/82343.html
   My bibliography  Save this paper

Performance of Markov-Switching GARCH Model Forecasting Inflation Uncertainty

Author

Listed:
  • Raihan, Tasneem

Abstract

This paper seeks to uncover the non-linear characteristics of uncertainty underlying the US inflation rates over the period 1971-2015 within a regime-switching framework. Accordingly, we employ two variants of a Markov regime-switching GARCH model, one with normally distributed errors (MS-GARCH-N) and another with t-distributed errors (MS-GARCH-t), and compare their relative in-sample as well as out-of-sample performances with those of their standard single-regime counterparts. Consistent with the findings in existing studies, both of our regime-switching models are successful in identifying the year 1984 as the breakpoint in inflation volatility. Among other interesting results is a new finding that the process of switching to the low volatility regime started around April, 1979 and continued until mid 1983. This time frame is matched with the period of aggressive monetary policy changes implemented by the then Fed chairman Paul Volcker. As regards the performance in forecasting uncertainty, for shorter horizons spanning 1 to 5 months, MS-GARCH-N forecasts are found to outperform all other models whereas for 8 to 12-month ahead forecasts MS-GARCH-t appears superior.

Suggested Citation

  • Raihan, Tasneem, 2017. "Performance of Markov-Switching GARCH Model Forecasting Inflation Uncertainty," MPRA Paper 82343, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:82343
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/82343/1/MPRA_paper_82343.pdf
    File Function: original version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. David E. Lindsey & Athanasios Orphanides & Robert H. Rasche, 2013. "The Reform of October 1979: How It Happened and Why," Review, Federal Reserve Bank of St. Louis, issue Nov, pages 487-542.
    2. Pesaran, M Hashem & Timmermann, Allan, 1992. "A Simple Nonparametric Test of Predictive Performance," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(4), pages 561-565, October.
    3. Kevin B. Grier & Ólan T. Henry & Nilss Olekalns & Kalvinder Shields, 2004. "The asymmetric effects of uncertainty on inflation and output growth," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 19(5), pages 551-565.
    4. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-384, March.
    5. Pagan, Adrian R. & Schwert, G. William, 1990. "Alternative models for conditional stock volatility," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 267-290.
    6. Stanley Fischer & Franco Modigliani, 1978. "Towards an understanding of the real effects and costs of inflation," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 114(4), pages 810-833, December.
    7. Marcucci Juri, 2005. "Forecasting Stock Market Volatility with Regime-Switching GARCH Models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 9(4), pages 1-55, December.
    8. Holland, A Steven, 1995. "Inflation and Uncertainty: Tests for Temporal Ordering," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 27(3), pages 827-837, August.
    9. Engle, Robert F, 1983. "Estimates of the Variance of U.S. Inflation Based upon the ARCH Model," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 15(3), pages 286-301, August.
    10. James H. Stock & Mark W. Watson, 2003. "Has the Business Cycle Changed and Why?," NBER Chapters, in: NBER Macroeconomics Annual 2002, Volume 17, pages 159-230, National Bureau of Economic Research, Inc.
    11. Giordani, Paolo & Soderlind, Paul, 2003. "Inflation forecast uncertainty," European Economic Review, Elsevier, vol. 47(6), pages 1037-1059, December.
    12. Kajal Lahiri & Xuguang Sheng, 2010. "Measuring forecast uncertainty by disagreement: The missing link," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(4), pages 514-538.
    13. Kontonikas, A., 2004. "Inflation and inflation uncertainty in the United Kingdom, evidence from GARCH modelling," Economic Modelling, Elsevier, vol. 21(3), pages 525-543, May.
    14. Lamoureux, Christopher G & Lastrapes, William D, 1990. "Persistence in Variance, Structural Change, and the GARCH Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(2), pages 225-234, April.
    15. Stilianos Fountas & Menelaos Karanasos & Jinki Kim, 2006. "Inflation Uncertainty, Output Growth Uncertainty and Macroeconomic Performance," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 68(3), pages 319-343, June.
    16. Melvin, Michael, 1982. "Expected Inflation, Taxation, and Interest Rates: The Delusion of Fiscal Illusion," American Economic Review, American Economic Association, vol. 72(4), pages 841-845, September.
    17. Marianne Sensier & Dick van Dijk, 2004. "Testing for Volatility Changes in U.S. Macroeconomic Time Series," The Review of Economics and Statistics, MIT Press, vol. 86(3), pages 833-839, August.
    18. Fischer, Stanley, 1981. "Towards an understanding of the costs of inflation: II," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 15(1), pages 5-41, January.
    19. Hansen, Bruce E, 1992. "The Likelihood Ratio Test under Nonstandard Conditions: Testing the Markov Switching Model of GNP," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 7(S), pages 61-82, Suppl. De.
    20. Evans, Martin, 1991. "Discovering the Link between Inflation Rates and Inflation Uncertainty," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 23(2), pages 169-184, May.
    21. Friedman, Milton, 1977. "Nobel Lecture: Inflation and Unemployment," Journal of Political Economy, University of Chicago Press, vol. 85(3), pages 451-472, June.
    22. Grier, Kevin B. & Perry, Mark J., 1998. "On inflation and inflation uncertainty in the G7 countries," Journal of International Money and Finance, Elsevier, vol. 17(4), pages 671-689, August.
    23. Kim, Chang-Jin, 1994. "Dynamic linear models with Markov-switching," Journal of Econometrics, Elsevier, vol. 60(1-2), pages 1-22.
    24. Hamilton, James D. & Susmel, Raul, 1994. "Autoregressive conditional heteroskedasticity and changes in regime," Journal of Econometrics, Elsevier, vol. 64(1-2), pages 307-333.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jassim Aladwani, 2024. "Oil Volatility Uncertainty: Impact on Fundamental Macroeconomics and the Stock Index," Economies, MDPI, vol. 12(6), pages 1-24, June.
    2. Katleho Makatjane & Ntebogang Moroke, 2021. "Predicting Extreme Daily Regime Shifts in Financial Time Series Exchange/Johannesburg Stock Exchange—All Share Index," IJFS, MDPI, vol. 9(2), pages 1-18, March.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Kuang‐Liang Chang & Chi‐Wei He, 2010. "Does The Magnitude Of The Effect Of Inflation Uncertainty On Output Growth Depend On The Level Of Inflation?," Manchester School, University of Manchester, vol. 78(2), pages 126-148, March.
    2. Chang, Kuang-Liang, 2012. "The impacts of regime-switching structures and fat-tailed characteristics on the relationship between inflation and inflation uncertainty," Journal of Macroeconomics, Elsevier, vol. 34(2), pages 523-536.
    3. Kushal Banik Chowdhury & Kaustav Kanti Sarkar & Srikanta Kundu, 2021. "Nonlinear relationships between inflation, output growth and uncertainty in India: New evidence from a bivariate threshold model," Bulletin of Economic Research, Wiley Blackwell, vol. 73(3), pages 469-493, July.
    4. Conrad, Christian & Hartmann, Matthias, 2014. "Cross-sectional evidence on the relation between monetary policy, macroeconomic conditions and low-frequency inflation uncertainty," Working Papers 0574, University of Heidelberg, Department of Economics.
    5. Mustafa Caglayan & Ozge Kandemir & Kostas Mouratidis, 2011. "Real effects of inflation uncertainty in the US," Working Papers 2011002, The University of Sheffield, Department of Economics, revised Feb 2015.
    6. Kushal Banik Chowdhury & Nityananda Sarkar, 2019. "Regime Dependent Effect Of Output Growth On Output Growth Uncertainty: Evidence From Oecd Countries," Bulletin of Economic Research, Wiley Blackwell, vol. 71(3), pages 257-282, July.
    7. Mustafa Caglayan & Ozge Kandemir Kocaaslan & Kostas Mouratidis, 2016. "Regime Dependent Effects of Inflation Uncertainty on Real Growth: A Markov Switching Approach," Scottish Journal of Political Economy, Scottish Economic Society, vol. 63(2), pages 135-155, May.
    8. LeBaron, Blake, 2003. "Non-Linear Time Series Models in Empirical Finance,: Philip Hans Franses and Dick van Dijk, Cambridge University Press, Cambridge, 2000, 296 pp., Paperback, ISBN 0-521-77965-0, $33, [UK pound]22.95, [," International Journal of Forecasting, Elsevier, vol. 19(4), pages 751-752.
    9. Chih-Chuan Yeh & Kuan-Min Wang & Yu-Bo Suen, 2011. "A quantile framework for analysing the links between inflation uncertainty and inflation dynamics across countries," Applied Economics, Taylor & Francis Journals, vol. 43(20), pages 2593-2602.
    10. Mendy, David & Widodo, Tri, 2018. "On the Inflation-Uncertainty Hypothesis in The Gambia: A Multi-Sample View on Causality Linkages," MPRA Paper 86743, University Library of Munich, Germany.
    11. Yue-Jun Zhang & Ting Yao & Ling-Yun He, 2015. "Forecasting crude oil market volatility: can the Regime Switching GARCH model beat the single-regime GARCH models?," Papers 1512.01676, arXiv.org.
    12. Nima Nonejad, 2019. "Has the 2008 financial crisis and its aftermath changed the impact of inflation on inflation uncertainty in member states of the european monetary union?," Scottish Journal of Political Economy, Scottish Economic Society, vol. 66(2), pages 246-276, May.
    13. Conrad, Christian & Hartmann, Matthias, 2019. "On the determinants of long-run inflation uncertainty: Evidence from a panel of 17 developed economies," European Journal of Political Economy, Elsevier, vol. 56(C), pages 233-250.
    14. Christian Grimme & Steffen Henzel & Elisabeth Wieland, 2014. "Inflation uncertainty revisited: a proposal for robust measurement," Empirical Economics, Springer, vol. 47(4), pages 1497-1523, December.
    15. Kushal Banik Chowdhury & Srikanta Kundu & Nityananda Sarkar, 2018. "Regime‐dependent effects of uncertainty on inflation and output growth: evidence from the United Kingdom and the United States," Scottish Journal of Political Economy, Scottish Economic Society, vol. 65(4), pages 390-413, September.
    16. Zeynel Abidin Ozdemir, 2010. "Dynamics Of Inflation, Output Growth And Their Uncertainty In The Uk: An Empirical Analysis," Manchester School, University of Manchester, vol. 78(6), pages 511-537, December.
    17. Mehmet Balcilar & Zeynel Abidin Ozdemir, 2013. "Asymmetric and Time-Varying Causality between Inflation and Inflation Uncertainty in G-7 Countries," Scottish Journal of Political Economy, Scottish Economic Society, vol. 60(1), pages 1-42, February.
    18. Mustafa Caglayan & Ozge Kandemir & Kostas Mouratidis, 2012. "The Impact of Inflation Uncertainty on Economic Growth: A MRS-IV Approach," Working Papers 2012025, The University of Sheffield, Department of Economics.
    19. B. Balaji & S. Raja Sethu Durai & M. Ramachandran, 2016. "The Dynamics Between Inflation and Inflation Uncertainty: Evidence from India," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 14(1), pages 1-14, June.
    20. Broto Carmen & Ruiz Esther, 2009. "Testing for Conditional Heteroscedasticity in the Components of Inflation," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 13(2), pages 1-30, May.

    More about this item

    Keywords

    Markov switching; GARCH; inflation uncertainty;
    All these keywords.

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pra:mprapa:82343. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Joachim Winter (email available below). General contact details of provider: https://edirc.repec.org/data/vfmunde.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.