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Predicting Inflation: Does The Quantity Theory Help?

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Author Info
Lance J. Bachmeier () (East Carolina University)
Norman R. Swanson () (Rutgers University)

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Abstract

Various inflation forecasting models are compared using a simulated out-of-sample forecasting framework. We focus on the question of whether monetary aggregates are useful for forecasting inflation, but unlike previous work we examine a wide range of forecast horizons and allow for estimated as well as theoretically specified cointegrating relationships in some of our models. Our findings indicate that there are forecasting gains from allowing monetary aggregates to enter into prediction models via cointegrating restrictions among money, prices, and output derived from a simple version of the quantity theory, but only when the cointegrating relations are specified a priori based on economic theory. When estimated cointegrating relations are used in a vector error correction (VEC) model, a vector autoregression (VAR) model in differences predicts better. These results hold, even during the 1990s, and evidence is presented suggesting that previous findings of a breakdown in the cointegrating relationship among prices, money, and output is the result of a failure of M2 as a measure of the money stock, and is not due to money demand instabilities. Two Monte Carlo experiments that lend credence to our findings are also reported on. The first shows that cointegration vector parameter estimation error is crucial when using VEC models for forecasting, and helps to explain previous findings of the failure of VEC models to forecast better than VAR models. The second shows that random walk and other atheoretical models routinely forecast better than correctly specified alternative models, due to parameter estimation error, indicating that caution needs to be exercised when interpreting the results of such comparisons, particularly when making statements concerning the usefulness of empirical models for use in policy-setting.

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Paper provided by Rutgers University, Department of Economics in its series Departmental Working Papers with number 200317.

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Date of creation: 27 Oct 2003
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Handle: RePEc:rut:rutres:200317

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Related research
Keywords: Inflation; Phillips curve; Forecast evaluation; cointegration;

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Find related papers by JEL classification:
E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions

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Full references

Cited by:
(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

  1. Joao Miguel Sousa & Andrea Zaghini, 2007. "Global Monetary Policy Shocks in the G5: a SVAR Approach," CEIS Research Paper 89, Tor Vergata University, CEIS. [Downloadable!]
    Other versions:
  2. Michael Graff, 2008. "The Quantity Theory of Money in Historical Perspective," KOF Working papers 08-196, KOF Swiss Economic Institute, ETH Zurich. [Downloadable!]
  3. Anthony Garratt & Gary Koop & Emi Mise & Shaun Vahey, 2008. "Real-time Prediction with UK Monetary Aggregates in the Presence of Model Uncertainty," Reserve Bank of New Zealand Discussion Paper Series DP2008/13, Reserve Bank of New Zealand. [Downloadable!]
    Other versions:
  4. Berger, Helge & Österholm, Pär, 2007. "Does Money Growth Granger-Cause Inflation in the Euro Area? Evidence from Out-of-Sample Forecasts Using Bayesian VARs," Working Paper Series 2007:30, Uppsala University, Department of Economics. [Downloadable!]
    Other versions:
  5. Doyle, Matthew, 2006. "Empirical Phillips Curves in OECD Countries: Has There Been A Common Breakdown?," Staff General Research Papers 12684, Iowa State University, Department of Economics. [Downloadable!]
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