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Forecasting Inflation in Argentina: A Probabilistic Approach

Author

Listed:
  • Tomás Marinozzi

    (University of CEMA (UCEMA))

Abstract

Probability forecasts are gaining popularity in the macroeconomic discipline as point forecasts lack the ability to capture the level of uncertainty in fundamental variables like inflation, growth, exchange rate, or unemployment. This paper explores the use of probability forecasts to predict inflation in Argentina. Scoring rules are used to evaluate several autoregressive models relative to a benchmark. Results show that parsimonious univariate models have a relatively similar performance to that of the multivariate models around central scenarios but fail to capture tail risks, particularly at longer horizons.

Suggested Citation

  • Tomás Marinozzi, 2023. "Forecasting Inflation in Argentina: A Probabilistic Approach," Ensayos Económicos, Central Bank of Argentina, Economic Research Department, vol. 1(81), pages 81-110, May.
    • Handle: RePEc:bcr:ensayo:v:1:y:2023:i:81:p:81-110
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    References listed on IDEAS

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    More about this item

    Keywords

    continuous ranked probability scores; inflation forecast; probability forecast;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation

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