The Stochastic Volatility in Mean Model with Time-Varying Parameters: An Application to Inflation Modeling
This code estimates a model that generalizes the popular stochastic volatility in mean model of Koopman and Hol Uspensky (2002) to allow for time-varying parameters in the conditional mean.
The MCMC algorithm is based on fast band matrix routines instead of the Kalman filter.
The methodology is illustrated with an application that involves US CPI inflation. The estimation results show substantial time-variation in the coefficient associated with the volatility.