An Illustration of a Pitfall in Estimating the Effects of Aggregate Variables on Micro Units
通过工资回归示例，说明将聚合数据与微观观测合并时，若忽视分组结构导致的误差项非独立，使用普通最小二乘法会严重低估标准误，产生虚假回归。
Many economic researchers have attempted to measure the effect of aggregate market or public policy variables on micro units by merging aggregate data with micro observations by industry, occupation, or geographical location, then using multiple regression or similar statistical models to measure the effect of the aggregate variable on the micro units. The methods are usually based upon the assumption of independent disturbances, which is typically not appropriate for data from populations with grouped structure. Incorrectly using ordinary least squares can lead to standard errors that are seriously biased downward. This note illustrates the danger of spurious regression from this kind of misspecification, using as an example a wage regression estimated on data for individual workers that includes in the specification aggregate regressors for characteristics of geographical states. Copyright 1990 by MIT Press.