Forecasting Costa Rican inflation with machine learning methods
We present a first assessment of the predictive ability of machine learning methods for inflation forecasting in Costa Rica. We compute forecasts using two variants of k-nearest neighbors, random forests, extreme gradient boosting and a long short-term memory (LSTM) network. We evaluate their proper...
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| Format: | Article |
| Language: | English |
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Elsevier
2020-01-01
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| Series: | Latin American Journal of Central Banking |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666143820300120 |