Abstract
This paper compares the out-of-sample inflation forecasting performance of two non-linear models; a neural network and a Markov switching autoregressive (MS-AR) model. We find that predictable non-linearities in inflation are best accounted for by the MS-AR model.
| Original language | English |
|---|---|
| Pages (from-to) | 323-328 |
| Number of pages | 6 |
| Journal | Economics Letters |
| Volume | 93 |
| Issue number | 3 |
| DOIs | |
| Publication status | Published - 1 Dec 2006 |
Bibliographical note
© 2006, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/Keywords
- Inflation forecasting
- Markov switching models
- Recurrent neural networks