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Argentina | Pronóstico de inflación de corto plazo con modelos Random Forest
[Argentina | Forecasting short-term inflation with Random Forest Models]

Author

Listed:
  • Federico Daniel Forte

Abstract

El presente trabajo examina el desempeño de los modelos Random Forest para pronosticar la inflación mensual de corto plazo en Argentina, utilizando una base de datos con indicadores en frecuencia mensual desde 1962. This paper examines the performance of Random Forest models in forecasting short-term monthly inflation in Argentina, based on a database of monthly indicators since 1962.

Suggested Citation

  • Federico Daniel Forte, 2024. "Argentina | Pronóstico de inflación de corto plazo con modelos Random Forest [Argentina | Forecasting short-term inflation with Random Forest Models]," Working Papers 24/10, BBVA Bank, Economic Research Department.
    • Handle: RePEc:bbv:wpaper:2410
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    More about this item

    Keywords

    Interest rates; Tasas de interés; Monetary policy; Política monetaria; Inflation; Inflación; Argentina; Argentina; Analysis with Big Data; Análisis con Big Data; Macroeconomic Analysis; Análisis Macroeconómico; Working Paper; Documento de Trabajo;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • 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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