Aggregation, Structural Change, and Cross-Section Estimation
本文刻画了参数化行为模型变化对加总变量关系的局部影响，并提出了利用横截面数据一致估计这些影响的方法，同时解释了模型变化效应与最大似然估计的关系，以及R²作为敏感性度量的适用性。
Abstract This article characterizes the local effects of parametric behavioral model change on relationships between aggregate variables, and it presents consistent estimators of such effects using cross-section data. Two equivalent interpretations of model-change effects are given: an “average-marginal” formulation and a cross-section regression formulation. The relation between model-change effects and maximum likelihood estimation of the behavioral parameters is explained. Finally, the article addresses the question of whether R 2 [from a crosssection ordinary least squares (OLS) regression] is a general measure of the sensitivity of aggregate relationships to model-change effects.