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Frederick J. Boehmke Dataverse (University of Iowa)
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1 to 7 of 7 Results
May 29, 2014
Boehmke, Frederick J.; Skinner, Paul, 2012, "State policy innovativeness scores V1.1", hdl:1902.1/18507, Harvard Dataverse, V4, UNF:5:fyY1vugTygW2g3pehCmgHg==
These data include measures of state policy innovativeness drawn from a database of over 180 different policies as used in Boehmke and Skinner (2012) to construct static and dynamic measures covering the period 1912-2009. The data include three static innovation scores. The first...
Sep 6, 2012
Boehmke, Frederick J.; Branton, Regina; Dillingham, Gavin; Witmer, Richard, 2012, "Replication data for: Close Enough for Comfort: A Spatial Analysis of Gaming Initiatives in California", hdl:1902.1/18799, Harvard Dataverse, V1, UNF:5:4F6YxZLdnzcEuxjDfKohVA==
This study considers the importance of spatial context in state ballot-initiative elections. We argue that spatial context provides important information voters use to decide how to vote on initiatives with geographically based policy implications. Herein, we analyze tract-level...
Jan 20, 2009
Frederick J. Boehmke, 2009, "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, Harvard Dataverse, V1, UNF:3:MdCmHQFlPB2CIFkIWgEdRw==
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 circumstance...
Jan 20, 2009
Frederick J. Boehmke; Daniel S. Morey; and Megan Shannon, 2009, "Replication data for: Selection Bias and Continuous-Time Duration Models: Consequences and a Proposed Solution", hdl:1902.1/10209, Harvard Dataverse, V1, UNF:3:M58IA+PIthnK/HqAgDf6HA==
This article analyzes the consequences of nonrandom sample selection for continuous-time duration analyses and develops a new estimator to correct for it when necessary. We conduct a series of Monte Carlo analyses that estimate common duration models as well as our proposed durat...
Jan 20, 2009
Frederick J. Boehmke, 2009, "Replication data for: Sources of Variation in the Frequency of Statewide Initiatives: The Role of Interest Group Populations", hdl:1902.1/10210, Harvard Dataverse, V1, UNF:3:5J7x/IttTq78h4mTE8t21w==
In this article I study the factors that determine the number of initiatives that appear on statewide ballots, with an emphasis on the characteristics of state interest group populations. In particular, I test whether the size of state citizen or economic group populations influe...
Jan 20, 2009
Frederick J. Boehmke, 2009, "Replication data for: The Influence of Unobserved Factors on Position Timing and Content in the NAFTA Vote", hdl:1902.1/10208, Harvard Dataverse, V1, UNF:3:rJz2PtnR7SW6U5uJdbU0OA==
A variety of factors have been shown to influence position timing and the content of positions taken by legislators on important issues. In addition to these observed factors, I argue that unobserved factors such as behind-the-scenes lobbying and party loyalty may also influence...
Jan 20, 2009
Frederick J. Boehmke; Richard Witmer, 2009, "Replication data for: Disentangling Diffusion: The Effects of Social Learning and Economic Competition on State Policy Innovation and Expansion", hdl:1902.1/10211, Harvard Dataverse, V1, UNF:3:2aKmDp20w6tknaeBbK0RIA==
When modeling regional policy diffusion effects, scholars have traditionally made appeals to both social learning and economic competition as causes of diffusion. In their empirical studies of policy adoption, however, they do not attempt to determine which of these two processes...
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