Descobrindo modelos de previsão para a inflação brasileira: uma análise a partir de uma gama ampla de indicadores

Autores

DOI:

https://doi.org/10.1590/0101-41614833ase

Palavras-chave:

previsão, inflação, seleção de modelos, autometrics, model confidence set

Resumo

Este trabalho visa avaliar o poder preditivo que séries macroeconômicas tem sobre o índice de preços ao consumidor amplo do brasileiro (IPCA) utilizando técnicas de séries de tempo. As previsões são realizadas para um horizonte de até 12 períodos a frente e comparadas com um processo autoregressivo como referência. O período vai de janeiro de 2000 até Agosto de 2015. Utilizou-se um conjunto amplo de informação de 1170 séries diferentes. Para cada momento e horizonte utilizou-se o processo de seleção através do algoritmo Autometrics desenvolvido por Hendry e Doornik (2014). O desempenho preditivo dos modelos foi comparado utilizando o Model Confident Set, developed by Hansen, Lunde and Nason (2010). Os resultados sugerem que há ganhos expressivos de previsão principalmente para os horizontes mais longos.

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Publicado

30-09-2018

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Silva, A. M., & Marçal, E. F. (2018). Descobrindo modelos de previsão para a inflação brasileira: uma análise a partir de uma gama ampla de indicadores. Estudos Econômicos (São Paulo), 48(3), 423-450. https://doi.org/10.1590/0101-41614833ase