Identifying Macro Shocks from Micro Evidence: A Mixed Autoregressive Approach

This paper develops a methodology to identify aggregate shocks by employing heterogeneous direct (partial equilibrium) effects estimated from microeconometric research designs. The total effect of a shock consists of direct and indirect (general equilibrium) effects, but standard microeconometric approaches do not capture the latter. Our framework builds on a time-series econometric model that integrates aggregate variables with functional observations, such as cross-sectional densities of micro-level variables. We show how direct effects can serve as identification restrictions to recover total macroeconomic and distributional effects. We illustrate our approach by comparing the effects of lump-sum and targeted stimulus transfer policies on aggregate outcomes and consumption inequality.