Pesquisa sobre métodos de previsão de inflação feita no CEMAP é publicada na revista Applied Economics

Pesquisa sobre métodos de previsão de inflação feita no CEMAP é publicada na revista Applied Economics:

Pesquisa realizada no Centro busca investigar o poder preditivo de modelos de projeção de inflação que utilizam métodos desagregados. O trabalho mostra que há ganhos de substanciais de previsão em períodos mais curtos todavia, para período mais longos (até 1 ano), os ganhos existem porém são bem mais modestos comparados com os benchmarks agrregados.

O link da revista é dado abaixo.

http://www.tandfonline.com/doi/full/10.1080/00036846.2016.1167824

 

ABSTRACT

This work aims to compare the forecast efficiency of different types of methodologies applied to Brazilian consumer inflation (Índice de Preços ao Consumidor Amplo; IPCA). We will compare forecasting models using disaggregated and aggregated data from IPCA over 12 months ahead. We used IPCA in a monthly basis, over the period between January 1996 and March 2012. Out-of-sample analysis will be made through the period of January 2008 to March 2012. The disaggregated models were estimated by Seasonal Autoregressive Integrated Moving Average (SARIMA) and will have different levels of disaggregation from IPCA as groups and items, as well as disaggregation with more economic sense used by Brazilian Central Bank as: (1) services, monitored prices, food and industrials and (2) durables, non-durables, semi-durables, services and monitored prices. Aggregated models will be estimated by time series techniques as SARIMA, state-space structural models and Markov-switching. The forecasting accuracy among models will be made by the selection model procedure known as Model Confidence Set developed by Peter Hansen, Asger Lunde and James Nason. We were able to find evidence of forecast accuracy gains in models using more disaggregated rather than aggregate data.