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Monetary policy and data uncertainty

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  • Jarkko Jääskelä
  • Tony Yates

Abstract

One of the problems facing policymakers is that recent releases of data are liable to subsequent revisions. This paper discusses how to deal with this, and is in two parts. In the normative part of the paper, we study the design of monetary policy rules in a model that has the feature that data uncertainty varies according to the vintage. We show how coefficients on lagged variables in optimised simple rules for monetary policy increase as the relative measurement error in early vintages of data increases. We also explore scenarios when policymakers are uncertain by how much measurement error in new data exceeds that in old data. An optimal policy can then be one in which it is better to assume that the ratio of measurement error in new compared to old data is larger, rather than smaller. In the positive part of the paper, we show that the response of monetary policy to vintage varying data uncertainty may generate evidence of apparent interest rate smoothing in interest rate reaction functions: but we suggest that it may not generate enough to account for what has been observed in the data.

Suggested Citation

  • Jarkko Jääskelä & Tony Yates, 2005. "Monetary policy and data uncertainty," Bank of England working papers 281, Bank of England.
    • Handle: RePEc:boe:boeewp:281
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    Cited by:

    1. Alastair Cunningham & Jana Eklund & Chris Jeffery & George Kapetanios & Vincent Labhard, 2009. "A State Space Approach to Extracting the Signal From Uncertain Data," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(2), pages 173-180, March.
    2. Alastair Cunningham & Jana Eklund & Chris Jeffery & George Kapetanios & Vincent Labhard, 2009. "A State Space Approach to Extracting the Signal From Uncertain Data," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(2), pages 173-180, March.
    3. Robert J. Tetlow, 2015. "Real-Time Model Uncertainty in the United States: "Robust" Policies Put to the Test," International Journal of Central Banking, International Journal of Central Banking, vol. 11(2), pages 113-155, March.
    4. Xueting Yu & Yuhan Zhu & Guangming Lv, 2020. "Analysis of the Impact of China’s GDP Data Revision on Monetary Policy from the Perspective of Uncertainty," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 56(6), pages 1251-1274, May.
    5. Paul Downward & Andrew Mearman, 2008. "Decision-making at the Bank of England: a critical appraisal," Oxford Economic Papers, Oxford University Press, vol. 60(3), pages 385-409, July.
    6. Carlo Altavilla & Matteo Ciccarelli, 2008. "Inflation models, optimal monetary policy and uncertain unemployment dynamics: Evidence from the US and the euro area," Discussion Papers 8_2008, D.E.S. (Department of Economic Studies), University of Naples "Parthenope", Italy.

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