Estimating the Impact of State Policies and Institutions with Mixed-Level Data

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Estimating the Impact of State Policies and Institutions with Mixed-Level Data

Please use this identifier to cite or link to this item: http://hdl.handle.net/10355/2614

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Title: Estimating the Impact of State Policies and Institutions with Mixed-Level Data
Author: Primo, David M.; Jacobsmeier, Matthew L.; Milyo, Jeffrey
Date: 2006-02
Publisher: Department of Economics
Citation: Department of Economics, 2006
Series/Report no.: Working papers (Department of Economics);WP 06-03
Abstract: Researchers often seek to understand the effects of state policies or institutions on individual behavior or other outcomes in sub-state-level observational units (e.g., election results in state legislative districts). However, standard estimation methods applied to such models do not properly account for the clustering of observations within states and may lead researchers to overstate the statistical significance of state-level factors. We discuss the theory behind two approaches to dealing with clustering—clustered standard errors and multilevel modeling. We then demonstrate the relevance of this topic by replicating a recent study of the effects of state post-registration laws on voter turnout (Wolfinger, Highton, and Mullin 2005). While we view clustered standard errors as a more straightforward, feasible approach, especially when working with large datasets or many cross-level interactions, our purpose in this Practical Researcher piece is to draw attention to the issue of clustering in state and local politics research.
URI: http://hdl.handle.net/10355/2614

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  • Economics publications (MU) [120]
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