Previsão de inflação utilizando modelos de séries temporais

• Autor(a) principal: Bonno, Simone Jager Patrocinio
• Data de Publicação: 2014
• Tipo de documento: Dissertação
• Idioma: por
• Título da fonte: Repositório Institucional do FGV (FGV Repositório Digital)
• Texto Completo: http://hdl.handle.net/10438/11750
• topic: Inflation-Brazil; National consumer price index (IPCA); Time series; Box and Jenkins; State-space; Structural model; The Kalman filter; SARIMA; Índice Nacional de Preços ao Consumidor Amplo (IPCA); Séries temporais; Box e Jenkins; Espaço de Estados; Modelo estrutural; Filtro de Kalman; Inflação-Brasil; Economia; Finanças; Inflação; Índice nacional de preços ao consumidor amplo; Previsão com Metodologia de Box-Jenkins; Kalman, Filtragem de

This paper compares time series models to forecast short-term Brazilian inflation measured by Consumer Price Index (IPCA). Were considered SARIMA Box-Jenkins models and structural models in state space, as estimated by the Kalman filter. For estimation of the models, the series of IPCA monthly basis from March 2003 to March 2012 was used. The SARIMA models were estimated in EVIEWS and structural models in STAMP. For the validation of the models out of sample forecasts were considered one step ahead for the period April 2012 to March 2013, based on the main criteria for assessing predictive ability proposed in the literature. The conclusion of the study is that, although the structural model allows, to decompose the series into components with direct interpretation and study them separately, while incorporating explanatory variables in a simple way, the performance of the SARIMA model to predict Brazilian inflation was higher in the period and horizon considered. Another important positive aspect is that the implementation of a SARIMA model is ready, and predictions from it are obtained in a simple and direct way.