Modelling inflation dynamics: a Bayesian comparison between GARCH and stochastic volatility

被引:3
作者
Le, Hai [1 ,2 ]
机构
[1] Kyoto Univ, Grad Sch Econ, Kyoto, Japan
[2] Banking Acad, Fac Int Business, Hanoi, Vietnam
来源
ECONOMIC RESEARCH-EKONOMSKA ISTRAZIVANJA | 2022年
关键词
Bayes factor; GARCH; inflation volatility; log predictive score; marginal likelihood; stochastic volatility; UNITED-KINGDOM; HESSIAN METHOD; UNCERTAINTY; LEVERAGE;
D O I
10.1080/1331677X.2022.2096093
中图分类号
F [经济];
学科分类号
02 ;
摘要
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.
引用
收藏
页码:2112 / 2136
页数:25
相关论文
共 33 条
[1]   Inflation and inflation uncertainty: A dynamic framework [J].
Berument, M. Hakan ;
Yalcin, Yeliz ;
Yildirim, Julide .
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2012, 391 (20) :4816-4826
[2]   GENERALIZED AUTOREGRESSIVE CONDITIONAL HETEROSKEDASTICITY [J].
BOLLERSLEV, T .
JOURNAL OF ECONOMETRICS, 1986, 31 (03) :307-327
[3]  
Chan Joshua C. C., 2009, International Journal of Mathematical Modelling and Numerical Optimisation, V1, P101, DOI 10.1504/IJMMNO.2009.030090
[4]   The Stochastic Volatility in Mean Model With Time-Varying Parameters: An Application to Inflation Modeling [J].
Chan, Joshua C. C. .
JOURNAL OF BUSINESS & ECONOMIC STATISTICS, 2017, 35 (01) :17-28
[5]   On the Observed-Data Deviance Information Criterion for Volatility Modeling [J].
Chan, Joshua C. C. ;
Grant, Angelia L. .
JOURNAL OF FINANCIAL ECONOMETRICS, 2016, 14 (04) :772-802
[6]   Modeling energy price dynamics: GARCH versus stochastic volatility [J].
Chan, Joshua C. C. ;
Grant, Angelia L. .
ENERGY ECONOMICS, 2016, 54 :182-189
[7]   Marginal Likelihood Estimation with the Cross-Entropy Method [J].
Chan, Joshua C. C. ;
Eisenstat, Eric .
ECONOMETRIC REVIEWS, 2015, 34 (03) :256-285
[8]   A THEORY OF AMBIGUITY, CREDIBILITY, AND INFLATION UNDER DISCRETION AND ASYMMETRIC INFORMATION [J].
CUKIERMAN, A ;
MELTZER, AH .
ECONOMETRICA, 1986, 54 (05) :1099-1128
[9]   Re-examining inflation and inflation uncertainty in developed and emerging countries [J].
Daal, E ;
Naka, A ;
Sanchez, B .
ECONOMICS LETTERS, 2005, 89 (02) :180-186
[10]   The HESSIAN Method for Models with Leverage-like Effects [J].
Djegnene, Barnabe ;
Mccausland, William J. .
JOURNAL OF FINANCIAL ECONOMETRICS, 2015, 13 (03) :722-755