A Nonparametric Forecast for the Colombian Inflation                                         

Norberto Rodríguez & Patricia Siado

 

Abstract         

This paper contains the results of a non parametric multi-step ahead forecast for the monthly Colombian inflation, using Mean conditional kernel estimation over inflation changes, with no inclusion of exogenous variables. The results are compared with those from an ARIMA and a non-linear STAR. The nonparametric forecast over perform the others two, as well as being the only, from the three, that statistically improved the naďve forecast given by a random-walk model.

 

Key words: Nonparametric forecast, Kernel estimation, Forecast evaluation, Bandwidth selection, Rolling forecast.

 

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