Estimation with Aggregate Shocks
指出仅用截面数据无法正确估计面临总体冲击的理性主体决策，提出一个同时利用截面和时间序列数据的计量框架，并给出易于使用的检验统计量和置信区间公式。
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 parameterizing the agents’ decision problem relative to aggregate shocks. Our framework and examples illustrate that the cross-sectional and time-series aspects of the model are often interdependent. Therefore, estimation of model parameters in the presence of aggregate shocks requires 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. Lastly, we perform Monte Carlo simulations that highlight the properties of the proposed method and the risks of not properly accounting for the presence of aggregate shocks.