Working Paper: CEPR ID: DP16183
Authors: Minsu Chang; Xiaohong Chen; Frank Schorfheide
Abstract: We develop a state-space model with a state-transition equation that takes the form of a functional vector autoregression and stacks macroeconomic aggregates and a cross-sectional density. The measurement equation captures the error in estimating log densities from repeated cross-sectional samples. The log densities and the transition kernels in the law of motion of the states are approximated by sieves, which leads to a finite-dimensional representation in terms of macroeconomic aggregates and sieve coefficents. We use this model to study the joint dynamics of technology shocks, per capita GDP, employment rates, and the earnings distribution. We find that the estimated spillovers between aggregate and distributional dynamics are generally small, a positive technology shock tends to decrease inequality, and a shock that raises the inequality of earnings leads to a small but not significant increase in GDP.
Keywords: Bayesian model selection; Econometric model evaluation; Earnings distribution; Functional vector autoregressions; Heterogeneous agent models; Statespace model; Technology shocks
JEL Codes: C11; C32; C52; E32
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| technology shock (O33) | income inequality (D31) |
| technology shock (O33) | mass of individuals earning below GDP per capita (D31) |
| technology shock (O33) | GDP (E20) |
| distributional shock (D39) | employment rates (J68) |
| distributional shock (D39) | GDP (E20) |