Asymptotic properties of weighted M-estimators for variable probability samples

• 成果类型: Article
• 署名作者: Wooldridge, JM
• 署名单位: Michigan State University
• 刊物名称: ECONOMETRICA
• ISSN/ISSBN: 0012-9682
• DOI: 10.1111/1468-0262.00083
• 发表日期: 1999
• 页码: 1385-1406
• 关键词: STRATIFIED SAMPLES; regression; models

摘要

I provide a systematic treatment of the asymptotic properties of weighted M-estimators under variable probability stratified sampling. The characterization of the sampling scheme and representation of the objective function allow for a straightforward analysis. Simple, consistent asymptotic variance matrix estimators are proposed for a large class of problems. When stratification is based on exogenous variables, I show that the unweighted M-estimator is more efficient than the weighted estimator under a generalized conditional information matrix equality. When population frequencies are known, a more efficient weighting is possible. I also show how the results carry over to multinomial sampling.