Models with time-varying parameters improve GDP forecasting, finds Croatian working paper
Bayesian models better at predicting short-term GDP performance, paper finds
A working paper published by the Croatian National Bank (CNB) finds that models with time-varying parameters improve short-term forecasting of Croatian GDP in comparison with naïve benchmark models.
Short-term forecasting of GDP under structural changes, by Rafael Ravnik, proposes several Bayesian models for GDP forecasting. The predictive ability of the models is then compared with a benchmark forecast.
"The results indicate that the modelling of time-varying parameters improves GDP forecasts
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