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The FRBNY Staff Underlying Inflation Gauge: UIG

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  • Marlene Amstad
  • Simon Potter
  • Robert Rich

Abstract

Monetary policymakers and long-term investors would benefit greatly from 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. This paper presents the "Federal Reserve Bank of New York (FRBNY) Staff Underlying Inflation Gauge (UIG)" for CPI and PCE. 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. It also considers the specific and time-varying persistence of individual subcomponents of an inflation series. An attractive feature of the UIG is that it can be updated on a daily basis, which allows for a close monitoring of changes in underlying inflation. This capability can be very useful when large and sudden economic fluctuations occur, as at the end of 2008. In addition, the UIG displays greater forecast accuracy than traditional measures of core inflation.

Suggested Citation

  • Marlene Amstad & Simon Potter & Robert Rich, 2014. "The FRBNY Staff Underlying Inflation Gauge: UIG," BIS Working Papers 453, Bank for International Settlements.
  • Handle: RePEc:bis:biswps:453
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    1. Balke, Nathan S. & Wynne, Mark A., 2000. "An equilibrium analysis of relative price changes and aggregate inflation," Journal of Monetary Economics, Elsevier, vol. 45(2), pages 269-292, April.
    2. Altissimo, Filippo & Mojon, Benoit & Zaffaroni, Paolo, 2009. "Can aggregation explain the persistence of inflation?," Journal of Monetary Economics, Elsevier, vol. 56(2), pages 231-241, March.
    3. Stock, James H. & Watson, Mark W., 1999. "Forecasting inflation," Journal of Monetary Economics, Elsevier, vol. 44(2), pages 293-335, October.
    4. Reichlin, Lucrezia & Forni, Mario & Cristadoro, Riccardo & Veronese, Giovanni, 2001. "A Core Inflation Index for the Euro Area," CEPR Discussion Papers 3097, C.E.P.R. Discussion Papers.
    5. Amstad, Marlene & Fischer, Andreas M., 2010. "Monthly pass-through ratios," Journal of Economic Dynamics and Control, Elsevier, vol. 34(7), pages 1202-1213, July.
    6. William T. Gavin & Kevin L. Kliesen, 2008. "Forecasting inflation and output: comparing data-rich models with simple rules," Review, Federal Reserve Bank of St. Louis, vol. 90(May), pages 175-192.
    7. 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.
    8. Vining, Daniel R, Jr & Elwertowski, Thomas C, 1976. "The Relationship between Relative Prices and the General Price Level," American Economic Review, American Economic Association, vol. 66(4), pages 699-708, September.
    9. Ang, Andrew & Bekaert, Geert & Wei, Min, 2007. "Do macro variables, asset markets, or surveys forecast inflation better?," Journal of Monetary Economics, Elsevier, vol. 54(4), pages 1163-1212, May.
    10. Fischer, Andreas & Amstad, Marlene, 2004. "Sequential Information Flow and Real-Time Diagnosis of Swiss Inflation: Intra-Monthly DCF Estimates for a Low-Inflation Environ," CEPR Discussion Papers 4627, C.E.P.R. Discussion Papers.
    11. Quah, Danny & Vahey, Shaun P, 1995. "Measuring Core Inflation?," Economic Journal, Royal Economic Society, vol. 105(432), pages 1130-1144, September.
    12. Castelnuovo, Efrem & Rodriguez-Palenzuela, Diego & Nicoletti Altimari, Sergio, 2003. "Definition of price stability, range and point inflation targets: the anchoring of long-term inflation expectations," Working Paper Series 273, European Central Bank.
    13. Marlene Amstad & Andreas M. Fischer, 2009. "Are Weekly Inflation Forecasts Informative?," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 71(2), pages 237-252, April.
    14. Bernanke, Ben S. & Boivin, Jean, 2003. "Monetary policy in a data-rich environment," Journal of Monetary Economics, Elsevier, vol. 50(3), pages 525-546, April.
    15. James H. Stock & Mark W. Watson, 2007. "Why Has U.S. Inflation Become Harder to Forecast?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(s1), pages 3-33, February.
    16. Stephen G. Cecchetti, 1997. "Measuring short-run inflation for central bankers," Review, Federal Reserve Bank of St. Louis, issue May, pages 143-155.
    17. Forni, Mario & Hallin, Marc & Lippi, Marco & Reichlin, Lucrezia, 2005. "The Generalized Dynamic Factor Model: One-Sided Estimation and Forecasting," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 830-840, September.
    18. Marlene Amstad & Andreas M. Fischer, 2009. "Do macroeconomic announcements move inflation forecasts?," Review, Federal Reserve Bank of St. Louis, vol. 91(Sep), pages 507-518.
    19. Mario Forni & Marc Hallin & Marco Lippi & Lucrezia Reichlin, 2000. "The Generalized Dynamic-Factor Model: Identification And Estimation," The Review of Economics and Statistics, MIT Press, vol. 82(4), pages 540-554, November.
    20. Stephen G. Cecchetti, 1995. "Inflation Indicators and Inflation Policy," NBER Chapters, in: NBER Macroeconomics Annual 1995, Volume 10, pages 189-236, National Bureau of Economic Research, Inc.
    21. Jim Dolmas, 2005. "Trimmed mean PCE inflation," Working Papers 0506, Federal Reserve Bank of Dallas.
    22. Frederic S. Mishkin & Klaus Schmidt-Hebbel, 2001. "One decade of inflation targeting in the world : What do we know and what do we need to know?," Working Papers Central Bank of Chile 101, Central Bank of Chile.
    23. Andreas Fischer & Marlene Amstad, 2004. "Sequential Information Flow and Real-Time Diagnosis of Swiss Inflation: Intra-Monthly DCF Estimates for a Low-Inflation Environment," Working Papers 04.06, Swiss National Bank, Study Center Gerzensee.
    24. Seamus Hogan & Marianne Johnson & Thérèse Laflèche, 2001. "Core Inflation," Technical Reports 89, Bank of Canada.
    25. Boivin, Jean & Ng, Serena, 2006. "Are more data always better for factor analysis?," Journal of Econometrics, Elsevier, vol. 132(1), pages 169-194, May.
    26. Cogley, Timothy, 2002. "A Simple Adaptive Measure of Core Inflation," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 34(1), pages 94-113, February.
    27. Vega, Juan Luis & Wynne, Mark A., 2001. "An evaluation of some measures of core inflation for the euro area," Working Paper Series 53, European Central Bank.
    28. 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.
    29. Stefano Eusepi & Bart Hobijn & Andrea Tambalotti, 2010. "The housing drag on core inflation," FRBSF Economic Letter, Federal Reserve Bank of San Francisco, issue apr5.
    30. Michael F. Bryan & Stephen G. Cecchetti & Rodney L. Wiggins II, 1997. "Efficient Inflation Estimation," NBER Working Papers 6183, National Bureau of Economic Research, Inc.
    31. Mikael Khan & Louis Morel & Patrick Sabourin, 2013. "The Common Component of CPI: An Alternative Measure of Underlying Inflation for Canada," Staff Working Papers 13-35, Bank of Canada.
    32. Gordon, Robert J, 1982. "Price Inertia and Policy Ineffectiveness in the United States, 1890-1980," Journal of Political Economy, University of Chicago Press, vol. 90(6), pages 1087-1117, December.
    33. Janine Aron & John Muellbauer, 2013. "New Methods for Forecasting Inflation, Applied to the US," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 75(5), pages 637-661, October.
    34. Brent Meyer & Guhan Venkatu & Saeed Zaman, 2013. "Forecasting inflation? Target the middle," Economic Commentary, Federal Reserve Bank of Cleveland, issue Apr.
    35. Domenico Giannone & Troy D. Matheson, 2007. "A New Core Inflation Indicator for New Zealand," International Journal of Central Banking, International Journal of Central Banking, vol. 3(4), pages 145-180, December.
    36. Marlene Amstad & Simon M. Potter, 2009. "Real time underlying inflation gauges for monetary policymakers," Staff Reports 420, Federal Reserve Bank of New York.
    37. Andrew Atkeson & Lee E. Ohanian, 2001. "Are Phillips curves useful for forecasting inflation?," Quarterly Review, Federal Reserve Bank of Minneapolis, vol. 25(Win), pages 2-11.
    38. Anna Cororaton & Richard Peach & Robert W. Rich, 2011. "How does slack influence inflation?," Current Issues in Economics and Finance, Federal Reserve Bank of New York, vol. 17(June).
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    Cited by:

    1. Elena Deryugina & Alexey Ponomarenko & Andrey Sinyakov & Constantine Sorokin, 2018. "Evaluating underlying inflation measures for Russia," Macroeconomics and Finance in Emerging Market Economies, Taylor & Francis Journals, vol. 11(2), pages 124-145, May.
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    3. Elena Deryugina & Alexey Ponomarenko & Andrey Sinyakov & Constantine Sorokin, 2018. "Evaluating underlying inflation measures for Russia," Macroeconomics and Finance in Emerging Market Economies, Taylor & Francis Journals, vol. 11(2), pages 124-145, May.
    4. Elena Deryugina & Alexey Ponomarenko, 2020. "Disinflation and Reliability of Underlying Inflation Measures," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 12(1), pages 91-111, March.
    5. Bańbura, Marta & Bobeica, Elena, 2020. "PCCI – a data-rich measure of underlying inflation in the euro area," Statistics Paper Series 38, European Central Bank.
    6. Eliana R. González-Molano & Ramón Hernández-Ortega & Edgar Caicedo-García & Nicolás Martínez-Cortés & Jose Vicente Romero & Anderson Grajales-Olarte, 2020. "Nueva Clasificación del BANREP de la Canasta del IPC y revisión de las medidas de Inflación Básica en Colombia," Borradores de Economia 1122, Banco de la Republica de Colombia.
    7. Min Jeong Kim & Dohyoung Kwon, 2023. "Dynamic asset allocation strategy: an economic regime approach," Journal of Asset Management, Palgrave Macmillan, vol. 24(2), pages 136-147, March.
    8. Marlene Amstad & Ye Huan & Guonan Ma, 2014. "Developing an underlying inflation gauge for China," Working Papers 853, Bruegel.
    9. Bjarni G. Einarsson, 2014. "A Dynamic Factor Model for Icelandic Core Inflation," Economics wp67, Department of Economics, Central bank of Iceland.
    10. The People's Bank of China, 2016. "An underlying inflation gauge (UIG) for China," BIS Papers chapters, in: Bank for International Settlements (ed.), Inflation mechanisms, expectations and monetary policy, volume 89, pages 117-121, Bank for International Settlements.
    11. Le Bihan, Hervé & Leiva-Leon, Danilo & Pacce, Matías, 2023. "Underlying inflation and asymmetric risks," Working Paper Series 2848, European Central Bank.

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    More about this item

    Keywords

    Inflation; Dynamic Factor Models; Core Inflation; Monetary Policy; Forecasting;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation

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