Forecasting the Estonian rate of inflation using factor models
The paper presents forecasts of headline and core inflation in Estonia with factor models in a recursive pseudo out-of-sample framework. The factors are constructed with a principal component analysis and are then incorporated into vector autoregressive (VAR) forecasting models. The analyses show th...
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2017-07-01
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| Series: | Baltic Journal of Economics |
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| Online Access: | http://dx.doi.org/10.1080/1406099X.2017.1371976 |
| Summary: | The paper presents forecasts of headline and core inflation in Estonia with factor models in a recursive pseudo out-of-sample framework. The factors are constructed with a principal component analysis and are then incorporated into vector autoregressive (VAR) forecasting models. The analyses show that certain factor-augmented VAR models improve upon a simple univariate autoregressive model but the forecasting gains are small and not systematic. Models with a small number of factors extracted from a large dataset are best suited for forecasting headline inflation. The results also show that models with a larger number of factors extracted from a small dataset outperform the benchmark model in the forecast of Estonian headline and, especially, core inflation. |
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| ISSN: | 1406-099X 2334-4385 |