Inflation in Croatia: a new era of forecasting with machine learning
https://doi.org/10.3326/pse.50.1.3 | Published online: March 18, 2026 Table 1
Input features Figure 1
Illustrative display of the expanding window approach Table 2
RMSE in the pre-COVID-19 period for the 3-, 6- and 9-month forecasting horizons Table 3
RMSE in the post-COVID-19 period for the 3-, 6- and 9-month forecasting horizons Table 4
RMSE over the full observation period for the 3-, 6- and 9-month forecasting horizons Figure 2
Forecasted average annual inflation rate by the European Commission compared with forecasts from the SARIMA and LightGBM models (in %) Table A1
RMSE expressed as indices relative to the SARIMA model for the pre-COVID-19 period Table A2
RMSE expressed as indices relative to the SARIMA model for the post-COVID-19 period Table A3
RMSE expressed as indices relative to the SARIMA model for the full observation period Table A4
Average RMSE by feature set used This is an Open Access article distributed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC-BY-NC) which permits non commercial use and redistribution, as long as you give appropriate credit, provide a link to the license, and indicate if changes were made.
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