Presidential approval ratings are a political resource that presidents and their advisors hope to influence through strategic action in order to achieve their policy goals (McAvoy 2008, 284). Through 1999, scholarly literature had largely ignored the president's use of unilateral powers. Since Moe and Howell (1999a, 1999b), however, the literature on the unilateral presidency has expanded rapidly. Despite the rapid growth of literature examining the unilateral presidency, and 45 years of presidential approval ratings literature, literature examining the link between the president's use of unilateral powers and subsequent presidential approval ratings is virtually nonexistent. Existing research has not statistically examined what effect, if any, the president's issuing executive orders has on subsequent job approval ratings. This thesis seeks to address that research gap. By modeling aggregate and individual-level presidential approval ratings, using fixed-effect models, OLS regression, and binary logistic regression, this thesis finds evidence indicating the president's issuing of executive orders has a negative impact on the subsequent presidential job approval ratings that individuals report. If an executive order is salient to the public, presidents receive lower presidential approval ratings from persons of all political parties; however, if the executive order is non-salient then presidents only receive lower presidential approval ratings from members of their own political party. Members of the opposition party report higher presidential approval ratings when the president issued non-salient executive orders. Thus, this thesis concludes that the president's issuing of executive orders has significant effects on subsequent presidential job approval ratings, and future research should be conducted to explore this relationship further.
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Master of Arts (M.A.)
College of Sciences
Political Science; American & Comparative Politics
Length of Campus-only Access
Masters Thesis (Open Access)
Jones, Brett, "Public Opinion and the President's Use of Executive Orders: Aggregate- and Individual-Level Analyses Across Time" (2016). Electronic Theses and Dissertations. 4930.