Original scientific paper
https://doi.org/10.1080/1331677X.2022.2096093
Modelling inflation dynamics: a Bayesian comparison between GARCH and stochastic volatility
Hai Le
Abstract
This study employs a prominent model comparison criterion,
namely the Bayes factor, to compare three commonly used
GARCH models with their stochastic volatility (SV) counterparts in
modelling the dynamics of inflation rates. By using consumer
price index (CPI) data from 18 developed countries to evaluate
these models, we find that the GARCH models are generally outperformed
by their stochastic volatility counterparts. Furthermore,
the stochastic volatility in mean (SV-M) model is shown to be the
best for all 18 countries considered. The paper also examines
which model characteristics play a main role in modelling inflation
rates. It turns out that inflation volatility feedback is a crucial
feature that we should take into consideration when modelling
inflation rates. The relevance of a leverage effect, however, is
found to be rather ambiguous. Finally, the forecasting results
using the log predictive score confirm these findings.
Keywords
Bayes factor; GARCH; inflation volatility; log predictive score; marginal likelihood; stochastic volatility
Hrčak ID:
304219
URI
Publication date:
31.3.2023.
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