Many of the most important questions in contemporary macroeconomics have yet to be answered in a convincing way, in part due to heavy reliance by empirical macroeconomists on time series variation of economic aggregates to find answers. The amount of historical time series data is fairly limited, and thus it is difficult to limit analysis to parts of the variation where causal effects can be convincingly demonstrated. This project uses a common methodological approach of spatial cross-sectional variation in addition to time series variation to demonstrate that it is possible to address macroeconomic questions empirically in a more credible way than is practiced in contemporary macroeconomics.
A Spatial Approach to Macroeconomic Inference
This research project uses spatial cross-sectional variation in addition to time series variation to estimate fiscal multipliers; the impact of anti-predatory lending laws on housing prices, default rates, and foreclosures; and the impact of raising wages during recessions.