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Inflation uncertainty revisited: A proposal for robust measurement

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  • Christian Grimme

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  • Steffen Henzel
  • Elisabeth Wieland

Abstract

Any measure of unobserved inflation uncertainty relies on specific assumptions which are most likely not fulfilled completely. This calls into question whether an individual measure delivers a reliable signal. To reduce idiosyncratic measurement error, we propose using common information contained in different measures derived from survey data, a variety of forecast models, and volatility models. We show that all measures are driven by a common component which constitutes an indicator for inflation uncertainty. Moreover, the idiosyncratic component of survey disagreement contains systematic measurement error during economic downturns. Finally, we study the Friedman-Ball hypothesis. Using the indicator, it turns out that higher inflation is followed by higher uncertainty. By contrast, we obtain contradictory results for the individual measures. We also document that, after an inflationary shock, uncertainty decreases in the first two months which is traceable to the energy component in CPI inflation.

Suggested Citation

  • Christian Grimme & Steffen Henzel & Elisabeth Wieland, 2011. "Inflation uncertainty revisited: A proposal for robust measurement," ifo Working Paper Series 111, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
  • Handle: RePEc:ces:ifowps:_111
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    Cited by:

    1. Steffen Henzel & Elisabeth Wieland, 2013. "Synchronization and Changes in International Inflation Uncertainty," CESifo Working Paper Series 4194, CESifo Group Munich.
    2. Claudiu T. Albulescu & Aviral Kumar Twari & Stephen M. Miller & Rangan Gupta, 2015. "Time-Frequency Relationship between Inflation and Inflation Uncertainty for the U.S.: Evidence from Historical Data," Working Papers 201591, University of Pretoria, Department of Economics.
    3. Tino Berger & Sibylle Grabert & Bernd Kempa, 2016. "Global and Country-Specific Output Growth Uncertainty and Macroeconomic Performance," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 78(5), pages 694-716, October.
    4. Steffen R. Henzel & Malte Rengel, 2017. "Dimensions Of Macroeconomic Uncertainty: A Common Factor Analysis," Economic Inquiry, Western Economic Association International, vol. 55(2), pages 843-877, April.
    5. Knüppel, Malte & Vladu, Andreea L., 2016. "Approximating fixed-horizon forecasts using fixed-event forecasts," Discussion Papers 28/2016, Deutsche Bundesbank.

    More about this item

    Keywords

    Inflation uncertainty; inflation; survey data; stochastic volatility; GARCH; principal component analysis;

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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