Time-varying volatility is common in macroeconomic data and has been incorporated into macroeconomic models in recent … countries or regions. This paper estimates dynamic panel data models with stochastic volatility by maximizing an approximate … particle filter-based estimator. When the volatility of volatility is high, or when regressors are absent but stochastic …

general class of discrete-time stochastic volatility (SV) models, characterized by both a leverage effect and jumps in returns … provides a feasible basis for undertaking the nontrivial task of model comparison. Furthermore, we introduce new volatility … model, namely SV-GARCH which attempts to bridge the gap between GARCH and stochastic volatility specifications. In nesting …

volatility processes. This is called a GSSF-SV model. We show that conventional MCMC algorithms for this type of model are …

-varying parameter models that incorporate both stochastic volatility and a Heckman-type two-step estimation procedure that deals with …

is given for the stochastic volatility model with leverage. …