Ulric B. and Evelyn L. Bray Social Sciences Seminar

Abstract: Aggregate shocks affect most households' and firms' decisions. Using three stylized models we show that inference based on cross-sectional data alone generally fails to correctly account for decision making of rational agents facing aggregate uncertainty. We propose an econometric framework that overcomes these problems by explicitly parametrizing the agents' inference problem relative to aggregate shocks. Our framework and examples illustrate that the cross-sectional and time-series aspects of the model are often interdependent. Estimation of model parameters in the presence of aggregate shock requires, therefore, the combined use of cross-sectional and time series data. We provide easy-to-use formulas for test statistics and confidence intervals that account for the interaction between the cross-sectional and time-series variation.