IDEAS home Printed from https://ideas.repec.org/p/hep/macppr/201304.html
   My bibliography  Save this paper

Money Growth and Inflation: evidence from a Markov Switching Bayesian VAR

Author

Listed:
  • Gianni Amisano

    (DG Research, European Central Bank and University of Brescia, Italy)

  • Roberta Colavecchio

    (Universitaet Hamburg (University of Hamburg))

Abstract

We contribute to the empirical debate on the role of money in monetary policy by analysing the features of the relationship between money growth and inflation in a Bayesian Markov Switching framework for a set of four countries, the US, the UK, the Euro area and Japan, over an estimation period spanning from 1960 to 2012. We find that the relationship between money growth and inflation appears to be nonlinear, as our estimation results identify multiple inflation regimes displaying clear and diversified features; moreover, as part of the model's information set, money growth plays a determinant role in the allocation of regimes. We show that observing monetary developments does (slightly) improve the signal of entering a high inflation regime but the influence of money on such signal seems to be relevant mainly in the 70s and the early 80s, i.e. in periods featuring exceptionally high rates of inflation. Our evidence confi?rms that the relationship between money and inflation appears to be relatively weak during periods featuring low and stable inflation.

Suggested Citation

  • 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.
    • Handle: RePEc:hep:macppr:201304
    as

    Download full text from publisher

    File URL: https://www.wiso.uni-hamburg.de/repec/hepdoc/macppr_4_2013.pdf
    File Function: First version, 2013
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. De Santis, Roberto A., 2012. "Quantity theory is alive: the role of international portfolio shifts," Working Paper Series 1435, European Central Bank.
    2. Ralf Brüggemann & Helmut Lütkepohl & Massimiliano Marcellino, 2008. "Forecasting euro area variables with German pre-EMU data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(6), pages 465-481.
    3. Sylvia Kaufmann & Peter Kugler, 2008. "Does Money Matter For Inflation In The Euro Area?," Contemporary Economic Policy, Western Economic Association International, vol. 26(4), pages 590-606, October.
    4. 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.
    5. Andreas Beyer & Jurgen A. Doornik & David F. Hendry, 2000. "Reconstructing Aggregate Euro‐zone Data," Journal of Common Market Studies, Wiley Blackwell, vol. 38(4), pages 613-624, November.
    6. 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.
    7. John Geweke & Gianni Amisano, 2011. "Hierarchical Markov normal mixture models with applications to financial asset returns," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 26(1), pages 1-29, January/F.
    8. Amisano, Gianni & Giacomini, Raffaella, 2007. "Comparing Density Forecasts via Weighted Likelihood Ratio Tests," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 177-190, April.
    9. 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.
    10. 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.
    11. James H. Stock & Mark W. Watson, 2007. "Why Has U.S. Inflation Become Harder to Forecast?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(s1), pages 3-33, February.
    12. Emil Stavrev & Helge Berger, 2012. "The information content of money in forecasting euro area inflation," Applied Economics, Taylor & Francis Journals, vol. 44(31), pages 4055-4072, November.
    13. Chang-Jin Kim & Charles R. Nelson, 1999. "State-Space Models with Regime Switching: Classical and Gibbs-Sampling Approaches with Applications," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262112388, April.
    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. Colavecchio, Roberta & Amisano, Gianni & Fagan, Gabriel, 2014. "A money-based indicator for deflation risk," VfS Annual Conference 2014 (Hamburg): Evidence-based Economic Policy 100595, Verein für Socialpolitik / German Economic Association.
    2. Cuneyt Dumrul & Yasemin Dumrul, 2015. "Price-Money Relationship after Infl ation Targeting: Co-integration Test with Structural Breaks for Turkey and Brazil," International Journal of Economics and Financial Issues, Econjournals, vol. 5(3), pages 701-708.
    3. Eltejaei , Ebrahim & Montazeri Shoorekchali , Jalal, 2021. "Investigating the Relationship between Money Growth and Inflation in Turkey: A Nonlinear Causality Approach," Journal of Money and Economy, Monetary and Banking Research Institute, Central Bank of the Islamic Republic of Iran, vol. 16(3), pages 305-322, September.
    4. 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.
    5. Claudio Borio & Marco Jacopo Lombardi & James Yetman & Egon Zakrajsek, 2023. "The two-regime view of inflation," BIS Papers, Bank for International Settlements, number 133.

    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. Amisano, Gianni & Fagan, Gabriel, 2013. "Money growth and inflation: A regime switching approach," Journal of International Money and Finance, Elsevier, vol. 33(C), pages 118-145.
    2. Del Boca, Alessandra & Fratianni, Michele & Spinelli, Franco & Trecroci, Carmine, 2010. "The Phillips curve and the Italian lira, 1861-1998," The North American Journal of Economics and Finance, Elsevier, vol. 21(2), pages 182-197, August.
    3. 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.
    4. Roberto Santis, 2015. "Quantity theory is alive: the role of international portfolio shifts," Empirical Economics, Springer, vol. 49(4), pages 1401-1430, December.
    5. Ayse Kabukcuoglu & Enrique Martínez-García, 2016. "What Helps Forecast U.S. Inflation?—Mind the Gap!," Koç University-TUSIAD Economic Research Forum Working Papers 1615, Koc University-TUSIAD Economic Research Forum.
    6. Scharnagl, Michael & Mandler, Martin, 2015. "The relationship of simple sum and Divisia monetary aggregates with real GDP and inflation: a wavelet analysis for the US," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 112879, Verein für Socialpolitik / German Economic Association.
    7. Roberto Leon-Gonzalez & Blessings Majoni, 2023. "Exact Likelihood for Inverse Gamma Stochastic Volatility Models," GRIPS Discussion Papers 23-07, National Graduate Institute for Policy Studies.
    8. Avouyi-Dovi, Sanvi & Sahuc, Jean-Guillaume, 2016. "On the sources of macroeconomic stability in the euro area," European Economic Review, Elsevier, vol. 83(C), pages 40-63.
    9. Atanas Christev & Yue Kang, 2015. "Money and Inflation: Is Monetary Policy Useful?," Manchester School, University of Manchester, vol. 83, pages 30-50, September.
    10. Han Gao & Mariano Kulish & Juan Pablo Nicolini, 2020. "Two Illustrations of the Quantity Theory of Money Reloaded," Working Papers 774, Federal Reserve Bank of Minneapolis.
    11. Joshua C. C. Chan, 2017. "The Stochastic Volatility in Mean Model With Time-Varying Parameters: An Application to Inflation Modeling," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(1), pages 17-28, January.
    12. Janice Boucher Breuer & John Mcdermott & Warren E. Weber, 2018. "Time Aggregation and the Relationship between Inflation and Money Growth," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 50(2-3), pages 351-375, March.
    13. João Valle e Azevedo, 2010. "Forecasting Inflation (and the Business Cycle?) with Monetary Aggregates," Working Papers w201024, Banco de Portugal, Economics and Research Department.
    14. Assenmacher-Wesche, Katrin & Gerlach, Stefan, 2008. "Interpreting euro area inflation at high and low frequencies," European Economic Review, Elsevier, vol. 52(6), pages 964-986, August.
    15. Qureshi, Irfan, 2016. "Monetarism, Indeterminacy and the Great Inflation," The Warwick Economics Research Paper Series (TWERPS) 1123, University of Warwick, Department of Economics.
    16. Maciej Ryczkowski, 2021. "Money and inflation in inflation-targeting regimes – new evidence from time–frequency analysis," Journal of Applied Economics, Taylor & Francis Journals, vol. 24(1), pages 17-44, January.
    17. Jung, Alexander, 2024. "The quantity theory of money, 1870-2020," Working Paper Series 2940, European Central Bank.
    18. Matheron, J. & Mojon, B. & Sahuc, J.G., 2012. "The sovereign debt crisis and monetary policy," Financial Stability Review, Banque de France, issue 16, pages 155-167, April.
    19. Drew Creal & Siem Jan Koopman & Eric Zivot, 2008. "The Effect of the Great Moderation on the U.S. Business Cycle in a Time-varying Multivariate Trend-cycle Model," Tinbergen Institute Discussion Papers 08-069/4, Tinbergen Institute.
    20. Raggi, Davide & Bordignon, Silvano, 2012. "Long memory and nonlinearities in realized volatility: A Markov switching approach," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3730-3742.

    More about this item

    Keywords

    Money growth; infl?ation regimes; Markov Switching model; Bayesian inference;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • 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:hep:macppr:201304. 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: Ulrich Fritsche (email available below). General contact details of provider: https://edirc.repec.org/data/dwuhhde.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.