Title: Structural estimation combining micro and macro data
Authors: Luca Neri - Aarhus University (Denmark) [presenting]
Abstract: A novel approach is introduced for estimating heterogeneous-agent macroeconomic models adding information from micro data. The methodology covers both panels and repeated cross sections, with applications to a wide class of dynamic structural models used in macroeconomics. The routine involves the estimation of dynamic moments over subgroups of the cross-sectional dimension of agents. Additionally it proposes a method for comparison of alternative choices of sub-population moments for the estimation of deep parameters of the economy. Micro moments differ from each other in the informative content that they carry for point estimation of the structural parameters. For instance, variability of moments over the cross-sectional distribution of households' wealth contains relevant information for the correct estimation of the subjective discount rate. However, data from the cross section are not relevant for the identification of a technology shock.