The Impact of Community Level Variables on Individual Level Outcomes: Theoretical Results and Demographic Applications
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Author(s): Angeles G, Guilkey D K, Mroz T A
We study alternative estimators of the impacts of higher level variables in multilevel models. This is important since many of the important variables in demographic research, such as community level access to family planning facilities, prices for services, and media campaigns are higher level factors having impacts on lower level outcomes such as contraceptive use. We present theoretical and Monte Carlo evidence about point estimation and standard error estimation for both two and three level models for continuous dependent variables, and we discuss the extension of these results to models with discrete dependent variables. A major conclusion of the paper is that readily available commercial software can be used to obtain both reliable point estimates and coefficient standard errors in models with two or more levels as long as appropriate corrections are made for possible error correlations at the highest level.
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