Date of Award:

5-2015

Document Type:

Thesis

Degree Name:

Master of Science (MS)

Department:

Political Science

Committee Chair(s)

Damon Cann

Committee

Damon Cann

Committee

Michael Lyons

Committee

Ryan Bosworth

Abstract

The purpose of this research is to better understand what causes partisan change in House of Representatives open seat elections from 2000-2014. Despite being the source of the majority of freshman entering the House and traditionally having a higher rate of partisan change, open seats receive less attention in the political science literature than seats involving incumbents. The most comprehensive look at open seats came from Ronald Keith Gaddie and Charles S Bullock III in their 2000 book Elections to Open Seats in the U.S. House. Since 2000, very little research has been done to update the ever-changing environment surrounding House seats.

In addition to examining a new set of data, a unique approach was taken by using the dichotomous variable of partisan change as the dependent variable. The focus on partisan change rather than vote share is also something rarely done in the literature. Vote-share models and public polling are the dominant methods for predicting House seats. A logit model that estimates the predicted probability of partisan change occurring can be a useful tool for scholars and for campaigns as it provides unique insights into what factors will make a seat competitive. A benefit of this model is that it can be used for long-term forecasting for parties to determine where their efforts may be best served.

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