Empirical Study on Time Varying Relationships Between Oil Prices, Exchange Market and Stock Market in Kazakhstan Economy

Abstract

In this study, a vector autoregression model with time-varying parameters is considered. The time varying parameter VAR model with stochastic volatility enables us to capture possible changes in underlying structure of the economy in a flexible and robust manner. The Markov chain Monte Carlo method is employed for the estimation. As an empirical application, the time varying parameter VAR model with stochastic volatility is estimated using the transformed data of oil price, stock index and seven different versions of exchange rates in Kazakhstan Tinge with significant structural changes in the dynamic relationship between the macroeconomic variables. The findings are in order. One is that the Kazakhstan economy shows significantly different macroeconomic performance, thus implying the possibility of important structural changes in the economy over time. The other one is that the time-varying impulse responses show remarkable changes in the relations between the macroeconomic variables compared with those estimated by a constant parameter VAR.