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Does global liquidity help to forecast US inflation?

Author

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  • D'Agostino, Antonello

    (Central Bank and Financial Services Authority of Ireland)

  • Surico, Paolo

    (Bank of England and University of Bari)

Abstract

We construct a measure of global liquidity using the growth rates of broad money for the G7 economies. Global liquidity produces forecasts of US inflation that are significantly more accurate than the forecasts based on US money growth, Phillips curve, autoregressive and moving average models. The marginal predictive power of global liquidity is strong at three years horizons. Results are robust to alternative measures of inflation.

Suggested Citation

  • D'Agostino, Antonello & Surico, Paolo, 2007. "Does global liquidity help to forecast US inflation?," Research Technical Papers 10/RT/07, Central Bank of Ireland.
  • Handle: RePEc:cbi:wpaper:10/rt/07
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    References listed on IDEAS

    as
    1. Domenico Giannone & Lucrezia Reichlin & Luca Sala, 2005. "Monetary Policy in Real Time," NBER Chapters,in: NBER Macroeconomics Annual 2004, Volume 19, pages 161-224 National Bureau of Economic Research, Inc.
    2. Nicoletti-Altimari, Sergio, 2001. "Does money lead inflation in the euro area?," Working Paper Series 0063, European Central Bank.
    3. Kenneth S. Rogoff, 2003. "Globalization and global disinflation," Proceedings - Economic Policy Symposium - Jackson Hole, Federal Reserve Bank of Kansas City, pages 77-112.
    4. Catherine Doz & Domenico Giannone & Lucrezia Reichlin, 2012. "A Quasi–Maximum Likelihood Approach for Large, Approximate Dynamic Factor Models," The Review of Economics and Statistics, MIT Press, vol. 94(4), pages 1014-1024, November.
    5. Gerlach, Stefan & Svensson, Lars E. O., 2003. "Money and inflation in the euro area: A case for monetary indicators?," Journal of Monetary Economics, Elsevier, vol. 50(8), pages 1649-1672, November.
    6. Todd Clark & Michael McCracken, 2005. "Evaluating Direct Multistep Forecasts," Econometric Reviews, Taylor & Francis Journals, vol. 24(4), pages 369-404.
    7. 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.
    8. Benati, Luca, 2009. "Long run evidence on money growth and inflation," Working Paper Series 1027, European Central Bank.
    9. Robert B. Barsky & Lutz Kilian, 2002. "Do We Really Know that Oil Caused the Great Stagflation? A Monetary Alternative," NBER Chapters,in: NBER Macroeconomics Annual 2001, Volume 16, pages 137-198 National Bureau of Economic Research, Inc.
    10. 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.
    11. Sergio Rossi, 2001. "Money and Inflation," Books, Edward Elgar Publishing, number 2571.
    12. George T. McCandless & Warren E. Weber, 1995. "Some monetary facts," Quarterly Review, Federal Reserve Bank of Minneapolis, issue Sum, pages 2-11.
    13. Milton Friedman & Anna J. Schwartz, 1982. "Monetary Trends in the United States and United Kingdom: Their Relation to Income, Prices, and Interest Rates, 1867–1975," NBER Books, National Bureau of Economic Research, Inc, number frie82-2.
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    More about this item

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • E47 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Forecasting and Simulation: Models and Applications

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