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The low-frequency impact of daily monetary policy shocks

Author

Listed:
  • Neville Francis
  • Eric Ghysels
  • Michael T. Owyang

Abstract

With rare exception, studies of monetary policy tend to neglect the timing of the innovations to the monetary policy instrument. Models which do take timing seriously are often difficult to compare to standard VAR models of monetary policy because of the differences in the frequency that they use. We propose an alternative model using MIDAS regressions which nests both ideas: Accurate (daily) timing of innovations to the monetary policy instrument are embedded in a monthly frequency VAR to determine the macroeconomic effects of high frequency changes to policy. We find that taking into account the timing of the shocks is important and can alleviate some of the puzzles in standard monthly VARs [e.g., the price puzzle]. We find that policy shocks are most important to variables thought of as being heavily expectations-oriented and that, contrary to some VAR studies, the effects of FOMC shocks on real variables are small.>

Suggested Citation

  • Neville Francis & Eric Ghysels & Michael T. Owyang, 2011. "The low-frequency impact of daily monetary policy shocks," Working Papers 2011-009, Federal Reserve Bank of St. Louis.
  • Handle: RePEc:fip:fedlwp:2011-009
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    References listed on IDEAS

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    1. Roberto S. Mariano & Yasutomo Murasawa, 2003. "A new coincident index of business cycles based on monthly and quarterly series," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(4), pages 427-443.
    2. Giannone, Domenico & Reichlin, Lucrezia & Small, David, 2008. "Nowcasting: The real-time informational content of macroeconomic data," Journal of Monetary Economics, Elsevier, vol. 55(4), pages 665-676, May.
    3. Peter A. Zadrozny, 1990. "Forecasting U.S. GNP at monthly intervals with an estimated bivariate time series model," Economic Review, Federal Reserve Bank of Atlanta, issue Nov, pages 2-15.
    4. Neville Francis & Michael T. Owyang, 2004. "Monetary policy in a Markov-switching VECM: implications for the cost of disinflation and the price puzzle," Working Papers 2003-001, Federal Reserve Bank of St. Louis.
    5. Gurkaynak, Refet S. & Sack, Brian T. & Swanson, Eric P., 2007. "Market-Based Measures of Monetary Policy Expectations," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 201-212, April.
    6. Doz, Catherine & Giannone, Domenico & Reichlin, Lucrezia, 2011. "A two-step estimator for large approximate dynamic factor models based on Kalman filtering," Journal of Econometrics, Elsevier, vol. 164(1), pages 188-205, September.
    7. Andreou, Elena & Ghysels, Eric & Kourtellos, Andros, 2010. "Regression models with mixed sampling frequencies," Journal of Econometrics, Elsevier, vol. 158(2), pages 246-261, October.
    8. Emanuel Moench & Serena Ng & Simon Potter, 2013. "Dynamic Hierarchical Factor Model," The Review of Economics and Statistics, MIT Press, vol. 95(5), pages 1811-1817, December.
    9. Domenico Giannone & Lucrezia Reichlin & David H. Small, 2005. "Nowcasting GDP and inflation: the real-time informational content of macroeconomic data releases," Finance and Economics Discussion Series 2005-42, Board of Governors of the Federal Reserve System (U.S.).
    10. Ghysels, Eric & Santa-Clara, Pedro & Valkanov, Rossen, 2006. "Predicting volatility: getting the most out of return data sampled at different frequencies," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 59-95.
    11. Kuzin, Vladimir N. & Marcellino, Massimiliano & Schumacher, Christian, 2009. "MIDAS versus mixed-frequency VAR: nowcasting GDP in the euro area," Discussion Paper Series 1: Economic Studies 2009,07, Deutsche Bundesbank.
    12. Hanson, Michael S., 2004. "The "price puzzle" reconsidered," Journal of Monetary Economics, Elsevier, vol. 51(7), pages 1385-1413, October.
    13. Stefan Mittnik & Peter A. Zadrozny, 2004. "Forecasting Quarterly German GDP at Monthly Intervals Using Monthly IFO Business Conditions Data," CESifo Working Paper Series 1203, CESifo Group Munich.
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    Cited by:

    1. Bjørn Eraker & Ching Wai (Jeremy) Chiu & Andrew T. Foerster & Tae Bong Kim & Hernán D. Seoane, 2015. "Bayesian Mixed Frequency VARs," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 13(3), pages 698-721.
    2. Foroni, Claudia & Guérin, Pierre & Marcellino, Massimiliano, 2015. "Markov-switching mixed-frequency VAR models," International Journal of Forecasting, Elsevier, vol. 31(3), pages 692-711.

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    Keywords

    Monetary policy ; Econometric models ; Prices;

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