Descobrindo modelos de previsão para a inflação brasileira: uma análise a partir de uma gama ampla de indicadores
DOI:
https://doi.org/10.1590/0101-41614833asePalavras-chave:
previsão, inflação, seleção de modelos, autometrics, model confidence setResumo
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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Copyright (c) 2018 Anderson Moriya Silva, Emerson Fernandes Marçal
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