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El sistema de predicción desagregada: Una evaluación de las proyecciones de inflación 2006-2011

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  • Barrera, Carlos

    (Banco Central de Reserva del Perú)

Abstract

El presente estudio describe las características del Sistema de Predicción Desagregada (SPD) en el marco de la literatura y presenta los resultados de una evaluación de sus capacidades predictivas en términos de las variaciones del índice de precios al consumidor de Lima Metropolitana (IPC), del índice de precios subyacente y de su complemento, el índice de precios no subyacente para el periodo julio 2006 - mayo 2011. La evaluación ex post considera las diferencias no sólo entre las principales especificaciones multi-ecuacionales en el SPD sino también respecto a un modelo auto-regresivo uni-ecuacional para el (sub-)agregado que corresponda. Esta evaluación se realiza en dos versiones: (1) la versión estática de la evaluación, que calcula la raíz del error cuadrático medio (RECM) sobre la base de la muestra completa de errores de predicción para cada horizonte h, RECM(h), y (2) la versión dinámica de la evaluación, que la calcula sobre la base de sub-muestras de errores para un horizonte h prefijado en ventanas móviles de ancho fijo con el periodo τ como cota superior, RECM(τ; h prefijado). En línea con la literatura, la evaluación ex post estática muestra la conveniencia de desagregar y predecir con modelos multi-ecuacionales frente a la alternativa de no desagregar y predecir con modelos uni-ecuacionales. El principal resultado de la evaluación ex post dinámica es la presencia de cruces en su evolución temporal, en los que un grupo de modelos con un buen [no tan buen] desempeño previo pasa luego a tener uno no tan bueno [bueno] (Aiolfi & Timmermann (2006)), lo que justifica el uso de proyecciones combinadas.

Suggested Citation

  • Barrera, Carlos, 2013. "El sistema de predicción desagregada: Una evaluación de las proyecciones de inflación 2006-2011," Working Papers 2013-009, Banco Central de Reserva del Perú.
  • Handle: RePEc:rbp:wpaper:2013-009
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    References listed on IDEAS

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    Cited by:

    1. Barrera Chaupis, Carlos, 2016. "Expectations' Dispersion & Convergence towards Central Banks' IR forecasts: Chile, Colombia, Mexico, Peru & United Kingdom, 2004-2014," MPRA Paper 85410, University Library of Munich, Germany, revised 12 Dec 2016.
    2. Winkelried, Diego, 2013. "Modelo de Proyección Trimestral del BCRP: Actualización y novedades," Revista Estudios Económicos, Banco Central de Reserva del Perú, issue 26, pages 9-60.

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    More about this item

    Keywords

    Modelos de series de tiempo; construcción y evaluación de modelos; predicción;
    All these keywords.

    JEL classification:

    • 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
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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