Graphical conditional moment tests
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图形化条件矩检验
- 研究问题
- 样本平均可能掩盖哪些局部模型误设，如何在样本点邻域检查设定，并识别同时存在的欠离散与过度离散？
- 方法与思路
- 作者平滑由估计模型导出的两个辅助变量，并根据正确设定下平滑曲线位置的抽样分布建立拒绝规则。
- 材料陈述的贡献
- 摘要称可直接以平滑曲线作为检验统计量，尤其适合平均化检验可能低功效的混合离散情形，并给出两个应用。
- 阅读关注点
- 应核对辅助变量构造、平滑参数和拒绝规则，以及曲线位置的抽样分布如何支持局部设定诊断。
- 阅读边界
- 摘要未说明临界值、误拒控制方式或功效比较的具体条件；收购与缺勤应用本身也不能确定方法的普遍表现。
原文摘要
Tests of misspecification or other defects in microeconometric models are usually numerical and based on an average over the sample. In this paper, it is shown that certain types of misspecification can be concealed by averaging, and a framework is developed which allows the specification to be checked in the near neighbourhood of each sample point, rather than for the sample as a whole. The framework involves the application of a scatter-plot smoothing technique to a pair of auxiliary variables derived from the estimated model. Using the sampling distribution of the location of the smooth under correct specification, a rejection rule based on the location of the realized smooth is established. Thus the smooth itself is used as a test statistic. A natural application of the procedure is to tests of equi-dispersion in count data models, and we find that it is particularly useful in the case in which a sample contains elements of both under- and over-dispersion, since it is in this case that numerical tests based on averaging are most likely to lack power. Two specific applications, one on takeover bids and the other on worker absenteeism, are used to illustrate the procedure.