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Inflation Dynamics in a Small Open Economy: An SVAR Approach

Author

Listed:
  • Juan Diego Chavarría Mejía

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

  • Fabio Gómez-Rodríguez

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

  • Claudio Mora-García

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

Abstract

This article proposes a structural vector autoregression (SVAR) to study the forces driving inflation in Costa Rica, a small open economy. We estimate the model using Bayesian methods and combine several identification strategies. The resulting historical decomposition attributes inflation dynamics to structural drivers, including supply, demand, exchange-rate, and monetary-policy shocks, classified according to their global or domestic origin. The historical decomposition attributes the inflation surge from 2021Q4 to 2023Q1 primarily to global factors. The subsequent disinflation from 2023Q2 to 2024Q1 reflected both a decline in global inflationary pressures and additional downward pressure from domestic factors. Domestic monetary-policy shocks contributed little to realized inflation, averaging about +0.07 percentage points per quarter. Long-run expectations remained considerably more stable than headline inflation, while the model implied inflation target displayed a gradual downward drift and its associated shock contributed to the initial disinflation. Taken together, these results identify relative resilience, but not perfect alignment, of the perceived nominal anchor and highlight the implicit inflation target as a useful indicator for evaluating Costa Rica's inflation-targeting regime. ***Resumen: Este artículo propone un modelo estructural de vectores autorregresivos (SVAR) para estudiar las fuerzas que impulsan la inflación en Costa Rica, una economía pequeña y abierta. Estimamos el modelo mediante métodos bayesianos y combinamos varias estrategias de identificación. La descomposición histórica resultante atribuye la dinámica de la inflación a distintos determinantes estructurales, incluidos choques de oferta, demanda, tipo de cambio y política monetaria, clasificados según su origen global o doméstico. La descomposición histórica atribuye el aumento de la inflación entre el cuarto trimestre de 2021 y el primer trimestre de 2023 principalmente a factores globales. La posterior desinflación, entre el segundo trimestre de 2023 y el primer trimestre de 2024, reflejó tanto una disminución de las presiones inflacionarias globales como una presión adicional a la baja proveniente de factores domésticos. Los choques domésticos de política monetaria contribuyeron poco a la inflación observada, con un promedio de alrededor de +0,07 puntos porcentuales por trimestre. Las expectativas de largo plazo se mantuvieron considerablemente más estables que la inflación general, mientras que la meta de inflación implícita en el modelo mostró una tendencia gradual a la baja y el choque asociado a esta contribuyó a la desinflación inicial. En conjunto, estos resultados muestran una relativa resiliencia, aunque no una alineación perfecta, del ancla nominal percibida y destacan la meta de inflación implícita como un indicador útil para evaluar el régimen de metas de inflación de Costa Rica.

Suggested Citation

  • Juan Diego Chavarría Mejía & Fabio Gómez-Rodríguez & Claudio Mora-García, 2026. "Inflation Dynamics in a Small Open Economy: An SVAR Approach," Documentos de Trabajo 2607, Banco Central de Costa Rica.
  • Handle: RePEc:apk:doctra:2607
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    File URL: https://repositorioinvestigaciones.bccr.fi.cr/handle/20.500.12506/533
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    JEL classification:

    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy
    • F41 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - Open Economy Macroeconomics
    • 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

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