S&P 500 Under A Structural Macro-Financial Model

Rodrigo Alfaro; Andrés Sagner

doi:10.4067/S0718-88702021000200003

Authors

Rodrigo Alfaro Central Bank of Chile
Andrés Sagner Central Bank of Chile

DOI:

https://doi.org/10.4067/S0718-88702021000200003

Keywords:

New-Keynesian model, asset pricing, Bayesian estimation, business cycles

Abstract

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.

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Author Biographies

Rodrigo Alfaro, Central Bank of Chile

Financial Studies Area, Central Bank of Chile

Andrés Sagner, Central Bank of Chile

Financial Stability Area, Central Bank of Chile

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