Extraction of dynamic financial condition index in Iran by time-varying parameters approach

Abstract

Structural changes and economic and financial condition change the nature of economic models, and this shows the importance of using models that consider the dynamics of model parameters over time.In this paper, we use factor augmented vector autoregressive models with time-varying coefficients and stochastic volatility to construct a financial conditions index that can track expectations about financial conditions and economic trends. Time variation in the model’s parameters allows for the weights attached to each financial variable in the index to evolve over time. Furthermore, we develop methods for dynamic model averaging or selection that allow the financial variables entering into the FCI to change over time. The results show that the financial conditions in our country have been associated with many instabilities, which has periodically weakened the efficiency of the country's economy by creating imbalances in the financial system of the economy.

Keywords

• financial conditions index (fci)
• time-varying parameter factor-augmented vector autoregressive model
• economic trend