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The parts are more than the whole: separating goods and services to predict core inflation

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  • M. Henry Linder
  • Richard Peach
  • Robert W. Rich

Abstract

Economists have not been altogether successful in their efforts to forecast ?core? inflation?an inflation measure that typically excludes volatile food and energy prices. One possible explanation is that the models used to make these forecasts fail to distinguish the forces influencing price changes in core services from those affecting price changes in core goods. While core services inflation depends on long-run inflation expectations and the degree of slack in the labor market, core goods inflation depends on short-run inflation expectations and import prices. By using a composite model that combines these different sets of explanatory variables, the authors of this study are able to improve upon the inflation forecasts produced by a standard model.

Suggested Citation

  • M. Henry Linder & Richard Peach & Robert W. Rich, 2013. "The parts are more than the whole: separating goods and services to predict core inflation," Current Issues in Economics and Finance, Federal Reserve Bank of New York, vol. 19(Aug).
  • Handle: RePEc:fip:fednci:y:2013:i:aug:n:v.19no.7
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    References listed on IDEAS

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    1. Jeffrey C. Fuhrer & Giovanni P. Olivei & Geoffrey M. B. Tootell, 2012. "Inflation Dynamics When Inflation Is Near Zero," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 44, pages 83-122, February.
    2. Michael F. Bryan & Brent Meyer, 2010. "Are some prices in the CPI more forward looking than others? We think so," Economic Commentary, Federal Reserve Bank of Cleveland, vol. 2010(02), pages 1-6, May.
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    Cited by:

    1. Joe Seydl & Malcolm Spittler, 2016. "Did globalization flatten the Phillips curve? U.S. consumer price inflation at the sectoral level," Journal of Post Keynesian Economics, Taylor & Francis Journals, vol. 39(3), pages 387-410, July.
    2. Marco Del Negro & Michele Lenza & Giorgio E. Primiceri & Andrea Tambalotti, 2020. "What’s up with the Phillips Curve?," NBER Working Papers 27003, National Bureau of Economic Research, Inc.
    3. Edward S. Knotek & Saeed Zaman, 2017. "Nowcasting U.S. Headline and Core Inflation," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 49(5), pages 931-968, August.
    4. Cobb, Marcus P A, 2018. "Improving Underlying Scenarios for Aggregate Forecasts: A Multi-level Combination Approach," MPRA Paper 88593, University Library of Munich, Germany.
    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. Tallman, Ellis W. & Zaman, Saeed, 2017. "Forecasting inflation: Phillips curve effects on services price measures," International Journal of Forecasting, Elsevier, vol. 33(2), pages 442-457.
    7. James H. Stock & Mark W. Watson, 2019. "Slack and Cyclically Sensitive Inflation," NBER Working Papers 25987, National Bureau of Economic Research, Inc.
    8. Mr. Yasser Abdih & Mr. Ravi Balakrishnan & Baoping Shang, 2016. "What is Keeping U.S. Core Inflation Low: Insights from a Bottom-Up Approach," IMF Working Papers 2016/124, International Monetary Fund.
    9. Richard Ashley & Randal Verbrugge, 2019. "Finding a Stable Phillips Curve Relationship: A Persistence-Dependent Regression Mode," Working Papers 201909R, Federal Reserve Bank of Cleveland, revised 08 Apr 2020.
    10. Antoni Espasa & Eva Senra, 2017. "Twenty-Two Years of Inflation Assessment and Forecasting Experience at the Bulletin of EU & US Inflation and Macroeconomic Analysis," Econometrics, MDPI, Open Access Journal, vol. 5(4), pages 1-28, October.
    11. Danica Unevska-Andonova, 2018. "Inflation Decomposition Model: Application to Macedonian inflation," Working Papers 2018-06, National Bank of the Republic of North Macedonia.

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