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Machine learning core inflation

Author

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  • Acosta, Marco A.

Abstract

In this article a novel methodology for building core inflation measures is proposed based on the k-means clustering machine learning algorithm. This new methodology is explored using Mexican CPI data in the spirit of getting a clear signal and having good predictions of the inflationary process based on selecting items with low volatility and assigning them to clusters. The results show that the core inflation built captures better the inflation signal and also outperforms the short-term inflation forecasts obtained by the trimmed means method and the core inflation excluding food and energy.

Suggested Citation

  • Acosta, Marco A., 2018. "Machine learning core inflation," Economics Letters, Elsevier, vol. 169(C), pages 47-50.
    • Handle: RePEc:eee:ecolet:v:169:y:2018:i:c:p:47-50
    DOI: 10.1016/j.econlet.2018.05.001
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    Citations

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    Cited by:

    1. Carlomagno, Guillermo & Fornero, Jorge & Sansone, Andrés, 2023. "A proposal for constructing and evaluating core inflation measures," Latin American Journal of Central Banking (previously Monetaria), Elsevier, vol. 4(3).
    2. Guillermo Carlomagno & Jorge Fornero & Andrés Sansone, 2021. "Toward a general framework for constructing and evaluating core inflation measures," Working Papers Central Bank of Chile 913, Central Bank of Chile.
    3. Thomas E. Koker & Dimitrios Koutmos, 2020. "Cryptocurrency Trading Using Machine Learning," JRFM, MDPI, vol. 13(8), pages 1-7, August.
    4. Philippe Goulet Coulombe & Karin Klieber & Christophe Barrette & Maximilian Goebel, 2024. "Maximally Forward-Looking Core Inflation," Papers 2404.05209, arXiv.org.
    5. Gabriel Rodríguez & Luis Surco, 2024. "Modeling the trend, persistence, and volatility of inflation in Pacific Alliance countries: an empirical application using a model with inflation bands," Documentos de Trabajo / Working Papers 2024-533, Departamento de Economía - Pontificia Universidad Católica del Perú.
    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.

    More about this item

    Keywords

    Machine learning; k-means algorithm; Core inflation;
    All these keywords.

    JEL classification:

    • 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
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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