Automating the selection of model-implied instrumental variables

被引:36
|
作者
Bollen, KA [1 ]
Bauer, DJ
机构
[1] Univ N Carolina, Odum Inst Res Social Sci, Chapel Hill, NC 27514 USA
[2] Univ N Carolina, Dept Psychol, Chapel Hill, NC USA
关键词
instrumental variables; structural equation models; two-stage least squares; algorithm;
D O I
10.1177/0049124103260341
中图分类号
O1 [数学]; C [社会科学总论];
学科分类号
03 ; 0303 ; 0701 ; 070101 ;
摘要
Recently, interest has grown in the use of instrumental variables (IVs) in estimating factor analysis and latent variable models such as structural equations models. Bollen (1996) suggested a two-stage least squares (2SLS) technique that makes use of model-implied IVs in estimating the measurement and latent variable models. Model-implied instrumental variables are the observed variables in the model that can serve as instrumental variables in a given equation. One difficulty inhibiting the practical use of the 2SLS estimator is identifying the model-implied IVs. The authors provide a simple procedure that identifies the model-implied IVs and a computer algorithm that can easily be implemented to automate the selection of IVs for simultaneous equations, factor analysis, and latent variable models.
引用
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页码:425 / 452
页数:28
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