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Inflation Forecasting in Costa Rica: The Contribution of Exogenous Variables in Item-Level Disaggregated Models

Author

Listed:
  • Carlos Segura-Rodriguez

    (Department of Economic Research, Central Bank of Costa Rica)

Abstract

This study proposes a methodology for forecasting inflation in Costa Rica based on a disaggregated analysis of the 289 items that comprise the Consumer Price Index (CPI). ARIMA models are used for most items, while ARIMAX models —which incorporate exogenous variables— are applied to those with higher weights and more volatile prices. The inclusion of specific information, such as the exchange rate, international commodity prices, and weekly agricultural prices, significantly improves forecast accuracy over short-term horizons. The disaggregated approach consistently outperforms more aggregated models or those without exogenous variables by reducing errors in sensitive items such as food, fuel, regulated goods, and products priced in U.S. dollars. The results highlight the value of integrating additional information into forecasting strategies based on disaggregated data and suggest that this methodology can effectively complement the short-term inflation forecasting models currently used by the Central Bank. ***Resumen: Este estudio propone una metodología para el pronóstico de la inflación en Costa Rica basada en el análisis desagregado de los 289 artículos que conforman el Índice de Precios al Consumidor (IPC). Se emplean modelos ARIMA para la mayoría de los artículos y modelos ARIMAX —que incorporan variables exógenas— para aquellos con mayor ponderación y precios más volátiles. La inclusión de información específica, como el tipo de cambio, precios internacionales de materias primas y precios agrícolas semanales, mejora significativamente la precisión de los pronósticos en horizontes de corto plazo. El enfoque desagregado supera sistemáticamente a modelos más agregados o sin variables exógenas, al reducir errores en productos sensibles como alimentos, combustibles, bienes regulados y aquellos cotizados en dólares. Los resultados evidencian el valor de integrar información adicional en estrategias de pronóstico basadas en datos desagregados, y sugieren que esta metodología puede complementar eficazmente los modelos de pronóstico de corto plazo utilizados por el Banco Central.

Suggested Citation

  • Carlos Segura-Rodriguez, 2025. "Inflation Forecasting in Costa Rica: The Contribution of Exogenous Variables in Item-Level Disaggregated Models," Documentos de Trabajo 2509, Banco Central de Costa Rica.
    • Handle: RePEc:apk:doctra:2509
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    References listed on IDEAS

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    JEL classification:

    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • G28 - Financial Economics - - Financial Institutions and Services - - - Government Policy and Regulation
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques

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