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FORECASTING THE FINNISH CONSUMER PRICE INFLATION USING ARTIFICIAL NEURAL NETWORK MODELS AND THREE AUTOMATED MODEL SELECTION TECHNIQUES

Anders Kock & Timo Teräsvirta

Finnish Economic Papers2013article
ABDC B
Weight
0.40

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.

4 citations

Cite this paper

@article{anders2013,
  title        = {{FORECASTING THE FINNISH CONSUMER PRICE INFLATION USING ARTIFICIAL NEURAL NETWORK MODELS AND THREE AUTOMATED MODEL SELECTION TECHNIQUES}},
  author       = {Anders Kock & Timo Teräsvirta},
  journal      = {Finnish Economic Papers},
  year         = {2013},
}

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FORECASTING THE FINNISH CONSUMER PRICE INFLATION USING ARTIFICIAL NEURAL NETWORK MODELS AND THREE AUTOMATED MODEL SELECTION TECHNIQUES

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Evidence weight

0.40

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.15 × 0.4 = 0.06
M · momentum0.80 × 0.15 = 0.12
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

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