Forecasting the Finnish Consumer Price Inflation Using Artificial Neural Network Models and Three Automated Model Selection Techniques

Anders Kock and Timo Teräsvirta

Finnish Economic Papers, 2013, vol. 26, issue 1, 13-24

Abstract: This paper is concerned with forecasting the Finnish inflation rate. It is being forecast using linear autoregressive and nonlinear neural network models. Perhaps surprisingly, building the models on the nonstationary level series and forecasting with them produces forecasts with a small er root mean square forecast error than doing the same with differenced series. The paper also contains pairwise comparisons between the benchmark forecasts from linear autoregressive models and ones from neural network models using Wilcoxon’s signed-rank test.

JEL-codes: C22 C45 C51 C52 C53 (search for similar items in EconPapers)
Date: 2013
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Citations: View citations in EconPapers (16)

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