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UNIVERSITY OF CALIFORNIA, SAN DIEGO Strategy, Choice and the Pathways to Power: Sequence Analysis of Political Careers A dissertation submitted in partial satisfaction of the requirements for the degree Doctor of Philosophy in Political Science by Scott Alan MacKenzie Committee in charge: Professor Samuel Kernell, Chair Professor Kate Antonovics Professor Steven P. Erie Professor Keith T. Poole Professor Matthew Soberg Shugart 2009 Copyright Scott Alan MacKenzie, 2009 All rights reserved. The Dissertation of Scott Alan MacKenzie is approved, and it is acceptable in quality and form for publication on microfilm and electronically: Chair University of California, San Diego 2009 iii DEDICATION To Cheryl for love, laughter, and inspiration, past, present, and future To Mom and Dad for encouraging big dreams and the sacrifices you made in helping them come true iv TABLE OF CONTENTS Signature Page …………………………………………………………………….. iii Dedication …………………………………………………………………………. iv Table of Contents ………………………………………………………………….. v List of Figures ……………………………………………………………………… vii List of Tables ……………………………………………………………………… ix Acknowledgements ………………………………………………………………… xi Vita ………………………………………………………………………………… xv Abstract ……………………………………………………………………………. xvi Chapter 1: Taking Sequences Seriously: An Argument for New Data and Methods In Political Career Studies ………………………………………… 1 Chapter 2: Putting the “Career” Back Into Political Career Studies: Does How They Got There Determine What They Do? ……………………..… 19 Chapter 3: Finding Patterns in Office-Holding Sequences: Exploratory Methods For Political Career Studies ………………………………………... 54 Chapter 4: Professionalizing the Politicians: Institutionalization and Careerism in Six Public Offices ………………………………………………… 107 Chapter 5: Big City Ambitions: Individual Characteristics, Political Institutions and The Pathways to City Hall ………………………………………… 156 Chapter 6: Careerism in Your Neighborhood: The Effects of Political Experience On Mayoral Reelection and Retirement …………………………… 200 v Chapter 7: Amateurs and Professionals in the Washington Community: Career Paths and Voluntary Retirement from the House of Representatives 237 Chapter 8: Sequence Analysis and Career Studies: A Review and Prospectus …. 285 References …………………………………………………………………………. 298 vi LIST OF FIGURES Figure 3.1: Alignment of Career Sequences for Two State Governors ……..……. 68 Figure 3.2A: First Possible Alignment of “Methodist” and “Scientist” Sequences ………………………………………………………….. 72 Figure 3.2B: Second Possible Alignment of “Methodist” and “Scientist” Sequences ………………………………………………………….. 72 Figure 3.3A: Minimization Through Optimal Matching, Solution 1 ………..……. 74 Figure 3.3B: Minimization Through Optimal Matching, Solution 2 ………..……. 75 Figure 3.4: Matrix of Substitution Costs ……………………………..……..……. 80 Figure 3.5: Non-Metric MDS Representation of Judicial Careers, 1809-1944 …… 90 Figure 3.6: Stress Values for Judicial Careers, 1809-1944 ……………………….. 93 Figure 3.7: Dendrogram of Pre-Cabinet Careers …………………………………. 96 Figure 3.8: Over-Time Distribution of Pre-Cabinet Careers …………………..…. 101 Figure 3.A1: FileMaker Interface for Coding of Political Careers, 1 ………..……. 105 Figure 3.A2: FileMaker Interface for Coding of Political Careers, 2 ………..……. 106 Figure 4.1: Alignment of Career Sequences for Two Cabinet Members ……..……. 127 Figure 4.2: Cumulative Share of Members of the Senate and House by Level of Experience …………………………………………………………. 129 Figure 4.3: Cumulative Share of Cabinet Members and Federal Judges by Level of Experience …………………………………………………………. 131 Figure 4.4: Cumulative Share of Governors and Big City Mayors by Level of Experience …………………………………………………………. 134 vii Figure 4.5: Share of Professional Politicians by Office and Era ……..…………... 137 Figure 5.1: Alignment of Career Sequences for Two Big City Mayors ……….…. 169 Figure 5.2: Dendrogram of Pre-Mayoral Careers …………………………………. 183 Figure 6.1: Alignment of Career Sequences for Two Big City Mayors ……….…. 210 Figure 7.1: Alignment of Career Sequences for Two Representatives ………...…. 250 Figure 7.2: Dendrogram of Pre-House Careers ……………………………..……. 258 viii LIST OF TABLES Table 3.1: Career-Year Observations By Office and Era………………………….. 62 Table 3.2: Classification of Public Sector Jobs ………………………………….... 65 Table 3.3: Inter-Sequence Distances Under Varying Insertion / Deletion Penalties 83 Table 3.4: Inter-Sequence Distances Under Varying Substitution Penalties ……… 85 Table 3.5: Correlation Tests for Six Substitution Cost Matrices …………………. 86 Table 3.6: Calinski-Harabasz Statistics for Pre-Cabinet Cluster Solutions ………. 98 Table 3.7: Description of Pre-Cabinet Clusters ……………………………………. 99 Table 4.1: Career-Year Observations By Office and Era………………………….. 122 Table 4.2: Classification of Public Sector Jobs ………………………………….... 125 Table 4.3A: Professionalization by Era – Senate, House and Cabinet ………….... 140 Table 4.3B: Professionalization by Era – Governor, Federal Judge and Mayor ..... 142 Table 4.4A: Within- and Between-Group Distances by Era, Senate and House ..... 149 Table 4.4B: Within- and Between-Group Distances by Era, Cabinet and Judges ... 149 Table 4.4C: Within- and Between-Group Distances by Era, Governor and Mayor . 149 Table 4.5: Results of ANOVA on Pre-Destination Career Distances …….…….... 152 Table 5.1: Distribution of Mayoral Careers by City and Era………………………. 166 Table 5.2: Classification of Public Sector Jobs ………………………………….... 168 Table 5.3: Within- and Between-Group Distances by City and Era………….……. 177 Table 5.4: Results of ANOVA on Pre-Mayoral Career Distances …….……......... 179 Table 5.5: Description of Pre-Mayoral Clusters ……………………..……………. 185 Table 5.6: Features of Pre-Mayoral Career Clusters ……………………..….……. 186 ix Table 5.7: Distribution of Pre-Mayoral Career Clusters Across Time ……………. 188 Table 5.8: Explaining Pre-Mayoral Career Clusters ………………………………. 189 Table 5.9: Consequences of Pre-Mayoral Career Clusters …………………….…. 190 Table 5.10: Model of Pre-Mayoral Career Paths ……………………………….…. 195 Table 5.11: Changes in the Probability of Pre-Mayoral Career Paths ………….…. 197 Table 6.1: Classification of Public Sector Jobs ………………………………….... 208 Table 6.2: Description of Pre-Mayoral Clusters ……………………..……………. 219 Table 6.3: Three Fixed Effects Models of Mayoral Reelection ……………..……. 228 Table 6.4: Changes in the Probability of Reelection ………….………………….. 229 Table 6.5: Three Competing Risks Models of Mayoral Retirement ………..….…. 231 Table 6.6: Changes in the Probability of Retiring, Moving Up .………………….. 234 Table 7.1: Classification of Public Sector Jobs ………………………………….... 249 Table 7.2: Description of Pre-House Clusters ……………………..……...………. 260 Table 7.3: Distribution of Pre-House Career Clusters Across Time …………..…. 262 Table 7.4: Explaining Pre-House Career Clusters …………………………...……. 263 Table 7.5: Three Models of Primary Reelection …………………………….……. 274 Table 7.6: Three Models of General Reelection …………………………….……. 275 Table 7.7: Changes in the Probability of Reelection ………….………………….. 276 Table 7.8: Three Models of Retirement …………………………………….….…. 279 Table 7.9: Changes in the Probability of Retiring, Moving Up .………………….. 280 Table 7.A1: Three Models of Moving Up ……………………………………..…. 284 x ACKNOWLEDGEMENTS Does who they are and how they got to be there influence what politicians do? This basic question, which has engaged several generations of scholars, was the starting point for this dissertation. The Framers believed that political institutions could be designed to increase the probability of selecting individuals of good character and experience to serve in public office. Empirical research on political careers has proceeded under a similar presumption – that the backgrounds of politicians and the paths they follow to public office will inform studies of political behavior and institutional development. Unfortunately, past work has failed to conclusively demonstrate this link. The results reported in this dissertation indicate that, when measured appropriately, previous political experience does influence behavior in office. Demonstrating this link, however, requires both new data and new methods. New data are required because existing sources typically lack sufficient information on the number, type and order of offices occupied by politicians. New methods are needed because traditional statistical techniques are ill-equipped to handle complex career sequences. Over the past three years, I have spent many hours compiling new data, learning new methods and assembling the chapters for this project. Fortunately, I received a great deal of help along the way. The original prospectus for this project was overly broad and unfocused. My advisor, Samuel Kernell, was patient as I fumbled around for an action plan and tried to prevent this dissertation from “sprouting like a MacKenzie potato.” Sam contributed some of the data used in this dissertation. The modeling strategies followed in several of xi the empirical chapters build on his published and unpublished work. Sam is the co- author of the material in Chapter 7, which studies the effects of previous political experience on the behavior of members of the U.S. House of Representatives. I owe a substantial debt to those who contributed to my intellectual development and practical training at UCSD. In particular, I would like to thank the five members of my dissertation committee – Samuel Kernell (Chair), Kate Antonovics, Steven P. Erie, Keith T. Poole and Matthew Soberg Shugart. Kate Antonovics enthusiastically joined this project in its nascent