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Nowcasting U.S. Headline and Core Inflation

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  • EDWARD S. KNOTEK
  • SAEED ZAMAN

Abstract

Forecasting future inflation and nowcasting contemporaneous inflation are difficult. We propose a new and parsimonious model for nowcasting headline and core inflation in the U.S. consumer price index and price index for personal consumption expenditures that relies on relatively few variables. The model's nowcasting accuracy improves as information accumulates over a month or quarter, outperforming statistical benchmarks. In real‐time comparisons, the model's headline inflation nowcasts substantially outperform those from the Blue Chip consensus and the Survey of Professional Forecasters. Across all four inflation measures, the model's nowcasting accuracy is comparable to that of the Federal Reserve Board's Greenbook.

Suggested Citation

  • 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.
  • Handle: RePEc:wly:jmoncb:v:49:y:2017:i:5:p:931-968
    DOI: 10.1111/jmcb.12401
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    Cited by:

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    6. Chad Fulton & Kirstin Hubrich, 2021. "Forecasting US Inflation in Real Time," Econometrics, MDPI, vol. 9(4), pages 1-20, October.
    7. Knotek, Edward S. & Zaman, Saeed, 2023. "Real-time density nowcasts of US inflation: A model combination approach," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1736-1760.
    8. Richard Schnorrenberger & Aishameriane Schmidt & Guilherme Valle Moura, 2024. "Harnessing Machine Learning for Real-Time Inflation Nowcasting," Working Papers 806, DNB.
    9. Garciga, Christian & Knotek II, Edward S., 2019. "Forecasting GDP growth with NIPA aggregates: In search of core GDP," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1814-1828.
    10. Alina Stundziene & Vaida Pilinkiene & Jurgita Bruneckiene & Andrius Grybauskas & Mantas Lukauskas, 2023. "Nowcasting Economic Activity Using Electricity Market Data: The Case of Lithuania," Economies, MDPI, vol. 11(5), pages 1-21, May.
    11. Burcu Tunç & Burcu Çakmak & Cansu Gökçe Zeybek & Bruno Tissot, 2020. "Using financial accounts - a central banking perspective," IFC Bulletins chapters, in: Bank for International Settlements (ed.), Using financial accounts, volume 51, Bank for International Settlements.
    12. Adam Bahelka & Harmen de Weerd, 2024. "Comparative analysis of Mixed-Data Sampling (MIDAS) model compared to Lag-Llama model for inflation nowcasting," Papers 2407.08510, arXiv.org.
    13. Jack Fosten & Daniel Gutknecht, 2021. "Horizon confidence sets," Empirical Economics, Springer, vol. 61(2), pages 667-692, August.
    14. Aparicio, Diego & Bertolotto, Manuel I., 2020. "Forecasting inflation with online prices," International Journal of Forecasting, Elsevier, vol. 36(2), pages 232-247.
    15. Amy Higgins & Randal J. Verbrugge, 2015. "Tracking Trend Inflation: Nonseasonally Adjusted Variants of the Median and Trimmed-Mean CPI," Working Papers (Old Series) 1527, Federal Reserve Bank of Cleveland.
    16. Priyanka Sahu, 2021. "A Study on the Dynamic Behaviour of Headline Versus Core Inflation: Evidence from India," Global Business Review, International Management Institute, vol. 22(6), pages 1574-1593, December.
    17. Patrick C. Higgins, 2014. "GDPNow: A Model for GDP \"Nowcasting\"," FRB Atlanta Working Paper 2014-7, Federal Reserve Bank of Atlanta.
    18. Kim, Insu & Kim, Young Se, 2019. "Inattentive agents and inflation forecast error dynamics: A Bayesian DSGE approach," Journal of Macroeconomics, Elsevier, vol. 62(C).
    19. Sayag, Doron & Ben-hur, Dano & Pfeffermann, Danny, 2022. "Reducing revisions in hedonic house price indices by the use of nowcasts," International Journal of Forecasting, Elsevier, vol. 38(1), pages 253-266.
    20. de Bondt, Gabe J. & Hahn, Elke & Zekaite, Zivile, 2021. "ALICE: Composite leading indicators for euro area inflation cycles," International Journal of Forecasting, Elsevier, vol. 37(2), pages 687-707.
    21. Barış Soybilgen & M. Ege Yazgan & Hüseyin Kaya, 2023. "Nowcasting Turkish Food Inflation Using Daily Online Prices," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 19(2), pages 171-190, September.

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    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E3 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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