Beneath the Surface: Disaggregated Data in Macroeconomic Applications

Aggregating across heterogenous groups can conceal underlying relationships that can appear when data is disaggregated. This dissertation provides evidence for the importance of heterogeneity by (i) showing how accounting for gender difference in a theoretical model can improve the model's ability to match U.S. business cycle statistics (chapter 1); (ii) empirically documenting the bias by various disaggregated unemployment groups and decomposition methodologies (chapter 2); and (iii) investigating geographical differences in Okun's law and their causes (chapter 3). These three chapters combine to demonstrate the importance of accounting for heterogenous groups when considering various policy implications.