摘要：In this paper, we propose a macro-financial model that combines a semi-structural, medium-term macroeconomic model with the Dynamic Gordon Model or DGM (Campbell and Shiller, 1988). The proposed framework allows us to analyze the relationship between the output gap, inflation, short-term interest rate, and stock market indicators: price, dividend, and volatility. We estimate the model for the US economy using Bayesian techniques on quarterly data from 1984 to 2020. The decomposition of the unconditional variance of the variables shows that (i) demand shocks are relevant for most macroeconomic variables and stock prices; (ii) supply shocks affect inflation mainly; (iii) shocks to the price-dividend ratio account for around 12%, 5% and 16% of the variability of the output gap, inflation, and interest rates, respectively; and (iv) the DGM mechanism helps to cushion the effects of an interest rate shock and increases the speed of convergence of all macroeconomic variables after an inflation shock, compared to a standard, semi-structural model, reflecting in this manner the importance of stock prices on the dynamics of macroeconomic variables.
