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The New York Fed Staff Underlying Inflation Gauge (UIG)

Author

Listed:
  • Marlene Amstad
  • Simon M. Potter
  • Robert W. Rich

Abstract

A measure of underlying inflation that uses all relevant information, is available in real time, and forecasts inflation better than traditional underlying inflation measures?such as core inflation measures?would greatly benefit monetary policymakers, market participants, and the public. This article presents the New York Fed Staff Underlying Inflation Gauge (UIG) for the consumer price index and the personal consumption expenditures deflator. Using a dynamic factor model approach, the UIG is derived from a broad data set that extends beyond price series to include a wide range of nominal, real, and financial variables. This modeling approach also makes it possible to combine information simultaneously from the cross-sectional and time dimensions of the sample in a unified framework. In addition, the UIG can be updated on a daily basis to closely monitor changes in underlying inflation?a feature that is especially useful when sudden and large economic fluctuations occur, as was the case during the 2008 global financial crisis. Lastly, the UIG displays greater forecast accuracy than many measures of core inflation. Editor?s note: This article?s data appendix has been updated to reflect the removal of a duplicate price series (CPI-U: Other fresh vegetables). The article?s conclusions remain the same. (December 2017)

Suggested Citation

  • Marlene Amstad & Simon M. Potter & Robert W. Rich, 2017. "The New York Fed Staff Underlying Inflation Gauge (UIG)," Economic Policy Review, Federal Reserve Bank of New York, issue 23-2, pages 1-32.
    • Handle: RePEc:fip:fednep:00042
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    2. Oguz Atuk & Mustafa Utku Ozmen, 2009. "Design and Evaluation of Core Inflation Measures for Turkey," Working Papers 0903, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
    3. Matteo Luciani, 2020. "Common and Idiosyncratic Inflation," FEDS Notes 2020-03-05, Board of Governors of the Federal Reserve System (U.S.).
    4. Barigozzi, Matteo & Hallin, Marc & Luciani, Matteo & Zaffaroni, Paolo, 2024. "Inferential theory for generalized dynamic factor models," Journal of Econometrics, Elsevier, vol. 239(2).
    5. Sara Serra & João Quelhas, 2023. "The inflation process in Portugal: the role of price spillovers," Economic Bulletin and Financial Stability Report Articles and Banco de Portugal Economic Studies, Banco de Portugal, Economics and Research Department.
    6. Marlene Amstad & Simon M. Potter & Robert W. Rich, 2014. "The FRBNY staff underlying inflation gauge: UIG," Staff Reports 672, Federal Reserve Bank of New York.
    7. Schoenle, Raphael & L'Huillier, Jean-Paul, 2019. "Raising the Inflation Target: How Much Extra Room Does It Really Give?," CEPR Discussion Papers 14142, C.E.P.R. Discussion Papers.

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    More about this item

    Keywords

    inflation; core inflation; monetary policy; dynamic factor models; forecasting;
    All these keywords.

    JEL classification:

    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General

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