CAREER: Inference on Macroeconomic Heterogeneity

Recent research on the aggregate economy tries to understand how aggregate economic performance has differential impacts on individual economic units. This is partly due to increased access to detailed micro-level data sets, increased and cheaper computing power, and partly due to growing concerns about whether economic growth benefits all of society. While much progress has been made in both theory and empirical methods of understanding the links between the distribution of income and aggregate economic activity, current statistical methods used by academic researchers, central banks, and other policy institutions are not designed to account for these differences. This proposal consists of four projects that will develop new and modern econometric tools to improve empirical research on differential effects of macroeconomic outcomes. The project will also develop video materials to educate students and practitioners in these econometric tools. This CAREER research proposal will use three projects to develop new econometric methods for studying heterogeneity in macroeconomics. The first project develops an inference procedure with formal coverage that guarantees visualizing multi-dimensional cross-sectional heterogeneity, such as heterogeneity in dynamic response profiles across groups of households or firms. The second project provides a causal reinterpretation of popular methods for estimating temporal heterogeneity and nonlinearities in time series data, such as state- or sign-dependence of impulse responses. The third project runs a large-scale simulation study of impulse response estimators and provides quantitative recommendations on how to choose between the many available procedures. Finally, the project proposes a plan for developing a collection of interactive educational materials on modern macro-econometric methods. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. NSF Award ID: 2625929 | Program: 01002526DB NSF RESEARCH & RELATED ACTIVIT,01002324DB NSF RESEARCH & RELATED ACTIVIT | Principal Investigator: Mikkel Plagborg-Moller | Institution: University of Chicago, CHICAGO, IL | Award Amount: $184,591 View on NSF Award Search: https://www.nsf.gov/awardsearch/show-award/?AWD_ID=2625929 View on Research.gov: https://www.research.gov/awardapi-service/v1/awards/2625929.html