Time varying structural VARs with sign restrictions: The case of Taiwan

I apply a Bayesian approach to a time-varying structural vector autoregression model with stochastic volatility (TVP-SVAR-SV) to study the time-varying nature of the Taiwanese economy. In particular, the structural parameters are identified via the sign information in a three-variable VAR system. The estimated results show that TVP-SVAR-SV model has the best fit to the data, compared to the time-varying parameters VAR model with constant volatility and a classical VAR model with constant parameters and volatilities. Moreover, I find the time-varying contemporaneous relationship between the output growth and inflation rates, particularly significant before the year 2000. Lastly, the impulse responses and the volatilities of all the variables are found to be time-varying.