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Replication data for: Using Auxiliary Data to Estimate Selection Bias Models, With an Application to Interest Group Use of the Direct Initiative Process
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Frederick J. Boehmke, 2007, "Replication data for: Using Auxiliary Data to Estimate Selection Bias Models, With an Application to Interest Group Use of the Direct Initiative Process", hdl:1902.1/10212 UNF:3:MdCmHQFlPB2CIFkIWgEdRw== Frederick J. Boehmke [Distributor]
Study Global Idhdl:1902.1/10212
AuthorsFrederick J. Boehmke (University of Iowa)
Production Date2003
DistributorFrederick J. Boehmke Logo
Distributor Contactfrederick-boehmke@uiowa.edu
Distribution Date2007
Deposit Date2007
Replication ForFrederick J. Boehmke. 2003. "Using Auxiliary Data to Estimate Selection Bias Models, With an Application to Interest Group Use of the Direct Initiative Process." Political Analysis: Volume 11 (Summer 2003): 234-254. article available here
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Abstract

Recent work in survey research has made progress in estimating models involving selection bias in a particularly difficult circumstance—all non-respondents are unit non-responders, meaning that no data are available for them. These models are reasonably successful in circumstances where the dependent variable of interest is continuous, but they are less practical empirically when it is latent and only discrete outcomes or choices are observed. I develop a method in this article to estimate these models that is much more practical in terms of estimation. The model uses a small amount of auxiliary information to estimate the selection equation parameters, which are then held fixed while estimating the equation of interest parameters in a maximum-likelihood setting. After presenting Monte Carlo analyses to support the model, I apply the technique to a substantive problem: Which interest groups are likely to be involved in support of potential initiatives to achieve their policy goals?

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