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Is the Quantity Theory of Money Useful in Forecasting U.S. Inflation?

Author

Listed:
  • Markku Lanne

    (University of Helsinki and CREATES)

  • Jani Luoto

    (University of Helsinki)

  • Henri Nyberg

    (University of Helsinki)

Abstract

We propose a new simple model incorporating the implication of the quantity theory of money that money growth and inflation should move one for one in the long run, and, hence, inflation should be predictable by money growth. The model fits postwar U.S. data well, and beats common univariate benchmark models in forecasting inflation. Moreover, this evidence is quite robust, and predictability is found also in the Great moderation period. The detected predictability of inflation by money growth lends support to the quantity theory.

Suggested Citation

  • Markku Lanne & Jani Luoto & Henri Nyberg, 2014. "Is the Quantity Theory of Money Useful in Forecasting U.S. Inflation?," CREATES Research Papers 2014-26, Department of Economics and Business Economics, Aarhus University.
    • Handle: RePEc:aah:create:2014-26
    as

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    File URL: https://repec.econ.au.dk/repec/creates/rp/14/rp14_26.pdf
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    References listed on IDEAS

    as
    1. Pedro Teles & Harald Uhlig & João Valle e Azevedo, 2016. "Is Quantity Theory Still Alive?," Economic Journal, Royal Economic Society, vol. 126(591), pages 442-464, March.
    2. Raffaella Giacomini & Halbert White, 2006. "Tests of Conditional Predictive Ability," Econometrica, Econometric Society, vol. 74(6), pages 1545-1578, November.
    3. Joshua C. C. Chan & Gary Koop & Simon M. Potter, 2013. "A New Model of Trend Inflation," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 31(1), pages 94-106, January.
    4. Robert J. Gordon, 1986. "The American Business Cycle: Continuity and Change," NBER Books, National Bureau of Economic Research, Inc, number gord86-1, March.
    5. Antonello D'Agostino & Paolo Surico, 2009. "Does Global Liquidity Help to Forecast U.S. Inflation?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 41(2-3), pages 479-489, March.
    6. Katrin Assenmacher-Wesche & Stefan Gerlach, 2007. "Money at Low Frequencies," Journal of the European Economic Association, MIT Press, vol. 5(2-3), pages 534-542, 04-05.
    7. West, Kenneth D, 1996. "Asymptotic Inference about Predictive Ability," Econometrica, Econometric Society, vol. 64(5), pages 1067-1084, September.
    8. Helge Berger & Pär Österholm, 2011. "Does Money matter for U.S. Inflation? Evidence from Bayesian VARs," CESifo Economic Studies, CESifo Group, vol. 57(3), pages 531-550, September.
    9. 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.
    10. Gianni Amisano & Roberta Colavecchio, 2013. "Money Growth and Inflation: evidence from a Markov Switching Bayesian VAR," Macroeconomics and Finance Series 201304, University of Hamburg, Department of Socioeconomics.
    11. Nathan Balke & Robert J. Gordon, 1986. "Appendix B: Historical Data," NBER Chapters, in: The American Business Cycle: Continuity and Change, pages 781-850, National Bureau of Economic Research, Inc.
    12. Liu, Jun M. & Chen, Rong & Yao, Qiwei, 2010. "Nonparametric transfer function models," LSE Research Online Documents on Economics 28868, London School of Economics and Political Science, LSE Library.
    13. Liu, Jun M. & Chen, Rong & Yao, Qiwei, 2010. "Nonparametric transfer function models," Journal of Econometrics, Elsevier, vol. 157(1), pages 151-164, July.
    14. Antonello D'Agostino & Paolo Surico, 2012. "A Century of Inflation Forecasts," The Review of Economics and Statistics, MIT Press, vol. 94(4), pages 1097-1106, November.
    15. Lucas, Robert E, Jr, 1980. "Two Illustrations of the Quantity Theory of Money," American Economic Review, American Economic Association, vol. 70(5), pages 1005-1014, December.
    16. Andrew Atkeson & Lee E. Ohanian, 2001. "Are Phillips curves useful for forecasting inflation?," Quarterly Review, Federal Reserve Bank of Minneapolis, vol. 25(Win), pages 2-11.
    17. Thomas J. Sargent & Paolo Surico, 2011. "Two Illustrations of the Quantity Theory of Money: Breakdowns and Revivals," American Economic Review, American Economic Association, vol. 101(1), pages 109-128, February.
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    More about this item

    Keywords

    Money growth; transfer function model; low-pass filter;
    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
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • E40 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - General
    • E51 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Money Supply; Credit; Money Multipliers

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