Ekonomi TEK

Ekonomi TEK

Forecasting Inflation Using Summary Statistics of Survey Expectations: A Machine-Learning Approach

Yazarlar: Bige KÜÇÜKEFE

Cilt 7 , Sayı 1 , 2018 , Sayfalar 1 - 16

Konular:İktisat

Anahtar Kelimeler:Machine learning,Forecast evaluation,Inflation forecasting,Surveys of expectations,Summary statistics

Özet: This paper aims to produce more accurate short-term inflation forecasts based on surveys of expectations by employing machine-learning algorithms. By treating inflation forecasting as an estimation problem consisting of a label (inflation) and features (summary statistics of surveys of expectations data), we train a suite of machine-learning models, namely, Linear Regression, Bayesian Ridge Regression, Kernel Ridge Regression, Random Forests Regression, and Support Vector Machines, to forecast the consumer-price inflation (CPI) in Turkey. We employ the Time Series Cross Validation Procedure to ensure that the training data exclude forecast horizon data. Our results indicate that these machine-learning algorithms outperform the official forecasts of the Central Bank of Turkey (CBT) and a univariate model.

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@article{2018, title={Forecasting Inflation Using Summary Statistics of Survey Expectations: A Machine-Learning Approach}, volume={7}, number={1–16}, publisher={Ekonomi TEK}, author={Bige KÜÇÜKEFE}, year={2018} }
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Bige KÜÇÜKEFE. (2018). Forecasting Inflation Using Summary Statistics of Survey Expectations: A Machine-Learning Approach (Vol. 7). Vol. 7. Ekonomi TEK.
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Bige KÜÇÜKEFE. Forecasting Inflation Using Summary Statistics of Survey Expectations: A Machine-Learning Approach. no. 1–16, Ekonomi TEK, 2018.
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