Can Machine Learning Models Predict Inflation?

Ivașcu Codruț ()
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Ivașcu Codruț: Bucharest University of Economic Studies, Bucharest, Romania

Proceedings of the International Conference on Business Excellence, 2023, vol. 17, issue 1, 1748-1756

Abstract: This paper studies the performance of Machine Learning models in inflation forecasting. The most popular algorithms have been used, respectively Support Vector Regression, Neural Networks, LSTM, Random Forest, XGBoost and LightGBM in both univariate and multivariate form, in order to predict the inflation in Romania, expressed as CPI, Core-1, Core-2 and Core-3, on multiple time horizons. The results suggest that the heuristic methods are not suited in a data-poor environment, being unable to surpass a simple autoregressive model.

Keywords: inflation forecasting; machine learning; XGBoost; monetary policy; emerging markets (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:vrs:poicbe:v:17:y:2023:i:1:p:1748-1756:n:10

DOI: 10.2478/picbe-2023-0155

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