Skip to main content

The role of monetary aggregates in the policy analysis of the swiss national bank


Using Swiss data from 1983 to 2008, this paper investigates whether growth rates of the different measures of the quantity of money and or excess money can be used to forecast inflation. After a preliminary data analysis, money demand relations are specified, estimated and tested. Then, employing error correction models, measures of excess money are derived. Using recursive estimates, indicator properties of monetary aggregates for inflation are assessed for the period from 2000 onwards, with time horizons of one, two, and three years. In these calculations, M2 and M3 clearly outperform M1, and excess money is generally a better predictor than the quantity of money. Taking into account also the most (available) recent observations that represent the first three quarters of the economic crisis, the money demand function of M3 remains stable while the one for M2 is strongly influenced by these three observations. While in both cases forecasts for 2010 show inflation rates inside the target zone between zero and two percent, and the same holds for forecasts based on M3 for 2011, forecasts based on M2 provide evidence that the upper limit of this zone might be violated in 2011.


  • Assenmacher-Wesche, Katrin (2008), “Modeling Monetary Transmission in Switzerland with a Structural Cointegrated VAR Model”, Swiss Journal of Economics and Statistics, 144, pp. 197–246.

    Article  Google Scholar 

  • Assenmacher, Katrin, and Katarina Juselius (2008), “Modeling Monetary Transmission in Switzerland”, mimeo, Swiss National Bank, Zürich 2008.

  • Baltensperger, Ernst, Thomas J. Jordan and Marcel R. Savioz (2001), “The Demand for M3 and Inflation Forecasts: An Empirical Analysis for Switzerland”, Weltwirtschaftliches Archiv, 137, pp. 244–272.

    Article  Google Scholar 

  • Banerjee, Anindya, Juan J. Dolado and Ricardo Mestre (1998), “Error-Correction Mechanism Tests for Cointegration in a Single-Equation Framework”, Journal of Time Series Analysis, 19, pp. 267–284.

    Article  Google Scholar 

  • Baumol, William J. (1952), “The Transaction Demand for Cash: An Inventory Theoretic Approach”, Quarterly Journal of Economics, 66, pp. 545–556.

    Article  Google Scholar 

  • Brüggemann, Ralf, and Helmut Lütkepohl (2005), “Practical Problems with Reduced Rank ML Estimators for Cointegration Parameters and a Simple Alternative”, Oxford Bulletin of Economics and Statistics, 67, pp. 673–690.

    Article  Google Scholar 

  • Carstensen, Kai, Jan Hagen, Oliver Hossfeld and Abelardo S. Neaves (2009), “Money Demand Stability and Inflation Prediction in the Four Largest EMU Countries”, Scottish Journal of Political Economy, 56, pp. 73–93.

    Article  Google Scholar 

  • Ericsson, Neil R. (1998), “Empirical Modeling of Money Demand”, Empirical Economics, 23, pp. 295–315, reprinted in: H. Lütkepohl and J. Wolters (eds), Money Demand in Europe, Heidelberg 1999, pp. 29–49.

  • Estrella, Arturo, and Frederic S. Mishkin (1997), “Is There a Role for Monetary Aggregates in the Conduct of Monetary Policy?”, Journal of Monetary Economics, 40, pp. 279–304, reprinted in: F.S. Mishkin (ed.), Monetary Policy Strategy, Cambridge (Mass.) 2007, pp. 109–132.

  • Friedman, Milton (1963), Inflation: Causes and Consequences, New York.

  • Gerlach, Stefan and Lars E.O. Svensson (2003), “Money and Inflation in the Euro Area: A Case for Monetary Indicators?”, Journal of Monetary Economics, 50, pp. 1649–1672.

    Article  Google Scholar 

  • Gerlach-Kristen, Petra (2001), “The Demand for Money in Switzerland”, Swiss Journal of Economics and Statistics, 137, pp. 535–554.

    Google Scholar 

  • Hannan, Edward J., and Barry G. Quinn (1979), “The Determination of the Order of an Autoregression”, Journal of the Royal Statistical Society B, 41, pp. 190–195.

    Google Scholar 

  • Hofmann, Boris (2006), “Do Monetary Indicators (Still) Predict Euro Area Inflation”, Deutsche Bundesbank, Discussion Paper, Series 1, No 18.

  • Hylleberg, Svend, Robert Engel, Clive W.J. Granger and Byung S. Yoo (1990), “Seasonal Integration and Cointegration”, Journal of Econometrics, 44, pp. 215–238.

    Article  Google Scholar 

  • Johansen, Søren (1995), Likelihood-Based Inference in Cointegrated Vector Autoregressive Models, Oxford.

  • Jordan, Thomas J., Michel Peytrignet and Georg Rich (2001), “The Role of M3 in the Policy Analysis of the Swiss National Bank”, in: H.J. Klöckers and C. Willeke (eds), Monetary Analysis: Tools and Applications, Frankfurt, pp. 47–62.

  • Jordan, Thomas J., Michel Peytrignet and Enzo Rossi (2010), “Ten Years’ Experience with the Swiss National Bank’s Monetary Policy Strategy”, Swiss Journal of Economics and Statistics, 146, 1, pp. 9–90.

    Article  Google Scholar 

  • Juselius, Katarina (1999), “Models and Relations in Economics and Econometrics”, Journal of Economic Methodology, 6, pp. 259–290.

    Article  Google Scholar 

  • Kaufmann, Sylvia and Peter Kugler (2008), “Does Money Matter for Inflation in the Euro-Area?”, Contemporary Economic Policy, 26, pp. 590–606.

    Article  Google Scholar 

  • Kirchgässner, Gebhard, and Jürgen Wolters (1992), “Implications of Temporal Aggregation on the Relation Between Two Time Series”, Statistische Hefte/Statistical Papers, 33, pp. 1–19.

    Article  Google Scholar 

  • Kirchgässner, Gebhard, and Jürgen Wolters (2007), Introduction to Modern Time Series Analysis, Berlin/Heidelberg/New York 2007.

  • MacKinnon, James G. (1996), “Numerical Distribution Functions for Unit Root and Cointegration Tests”, Journal of Applied Econometrics, 11, pp. 601–618.

    Article  Google Scholar 

  • Nelson, Edward (2003), “The Future of Monetary Aggregates in Monetary Policy Analysis”, Journal of Monetary Economics, 50, pp. 1029–1059.

    Article  Google Scholar 

  • Newey, Whitney K., and Kenneth D. West (1987), “A Simple Positive Definite Heteroscedasticity and Autocorrelation Consistent Covariance Matrix”, Econometrica, 55, pp. 703–708.

    Article  Google Scholar 

  • Peytrignet, Michel and Christof Stahel (1998), “Stability of Money Demand in Switzerland: A Comparison of the M2 and M3 Cases”, Empirical Economics, 23, pp. 437–454, reprinted in: H. Lütkepohl and J. Wolters (eds), Money Demand in Europe, Heidelberg 1999, pp. 171–188.

  • Rajaguru, Gulasekaran, and Tilak Abeysinghe (2008), “Temporal Aggregation, Cointegration and Causality Inference”, Economics Letters, 101, pp. 223–226.

    Article  Google Scholar 

  • Reynard, Samuel (2007), “Maintaining Low Inflation: Money, Interest Rates, and Policy Stance”, Journal of Monetary Economics, 54, pp. 1441–1471.

    Article  Google Scholar 

  • Schwarz, Gideon (1978), “Estimating the Dimension of a Model”, Annals of Statistics, 6 (1978), pp. 461–464.

    Article  Google Scholar 

  • Stock, James H. (1987), “Asymptotic Properties of Least-Squares Estimators of Cointegrating Vectors”, Econometrica, 55, pp. 1035–1056.

    Article  Google Scholar 

  • Tobin, James (1956), “The Interest Elasticity of Transactions Demand for Cash”, Review of Economics and Statistics, 38, pp. 241–247.

    Article  Google Scholar 

  • Trecroci, Carmine, and Juan L. Vega (2002), “The Information Content of M3 for Future Inflation in the Euro Area”, Weltwirtschaftliches Archiv, 138, pp. 22–53.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations


Corresponding author

Correspondence to Gebhard Kirchgässner.

Additional information

We thank the Swiss National Bank for providing the data, and Sylvia Kaufmann (Austrian National Bank) as well as Samuel Reynard (Swiss National Bank) for helpful comments and suggestions.

Rights and permissions

Open Access This article is distributed under the terms of the Creative Commons Attribution 2.0 International License ( ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Reprints and permissions

About this article

Cite this article

Kirchgässner, G., Wolters, J. The role of monetary aggregates in the policy analysis of the swiss national bank. Swiss J Economics Statistics 146, 221–253 (2010).

Download citation

  • Published:

  • Issue Date:

  • DOI: