Policy Collaboration in the United States Congress Dissertation Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy in the Graduate School of The Ohio State University By Alison W. Craig, M.A. Graduate Program in Political Science The Ohio State University 2017 Dissertation Committee: Janet M. Box-Steffensmeier, Advisor Skyler J. Cranmer Michael A. Neblo Herbert F. Weisberg ⃝c Copyright by Alison W. Craig 2017 Abstract Is there a benefit to working well with others in Congress? Many of the bills introduced are written not only by the single member listed as its sponsor, but by a coalition of representatives who have worked together to author mutually agreeable language. Similarly, members frequently collaborate with colleagues in writing policy letters, running caucuses, and hosting events. Yet there is very little understanding of the nature of these relationships, or how members of Congress benefit from them, as data availability has limited the ability of legislative politics scholars to estimate their impact. Using a unique dataset of Dear Colleague letters, which are an essential communication tool in the modern Congress, I identify the members who collaborate on policy initiatives in a substantive manner. I use these data to map the policy collaboration network of the House of Representatives to answer three key questions that will greatly improve our understanding of congressional behavior and the legisla- tive process: 1) How do members of Congress choose their collaborative partners? 2) What are the legislative benefits of collaboration? 3) What are the electoral benefits of collaboration? The first question is addressed using a temporal exponential random graph model (TERGM) that allows me to consider the policy collaboration network for each Congress in its entirety and examine the endogenous and exogenous factors that lead members to working with each other. I find evidence of several distinctive patterns, ii including a strong tendency towards bipartisan collaboration in a highly polarized Congress, an overall inclination towards collaboration where there are shared con- stituencies, and a network where personal relationships and reputations are key. The second essay examines the legislative benefits of collaboration, specifically whether more collaborative members are more effective legislators. I create several new mea- sures of propensity towards collaboration and use them in a series of temporal network autocorrelation models that examine whether the relationship between collaboration and legislative effectiveness is the result of members putting in effort to advance their agenda, working with other successful colleagues, or using collaboration to send infor- mative signals. I find that members who are strategic in their collaborative decisions find the most success, particularly those who moderate their usage of collaboration. Finally, I consider the electoral benefits of collaboration, again using the temporal network autocorrelation model and my measures of propensity towards collaboration. I find that for electorally vulnerable members of Congress, there is a significant ben- efit to collaborating with members of the other party as it allows them tobuilda reputation for bipartisanship with their constituents. Taken together, these three essays provide us with a greater understanding of the role that policy collaboration plays in the modern Congress. Members use collabora- tion with their colleagues to find common ground in a polarized Congress, to advance their legislative agenda, and as a form of symbolic representation that allows them to distance themselves from the “dysfunctional” Congress. iii For my parents, who never stopped teaching me about politics. iv Acknowledgments I am indebted to the institutions who provided invaluable financial support for my research: the National Science Foundation Political Science program (grant #1627358), the National Science Foundation Graduate Research Fellowship (DGE-1343012), the Dirksen Congressional Center (grant #00031432) and the Institute for the Study of Democracy at the Ohio State University. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author and do not necessarily reflect the views of the National Science Foundation or other sponsoring entity. This research would not have been possible without the work of scholars who have come before me. In particular, I would like to thank those whose data and resources were essential to this project: Scott Adler and John Wilkerson with the Congressional Bills Project, Craig Volden and Alan Wiseman with the Legislative Effectiveness Project, and Philip Leifeld, Skyler Cranmer, and Bruce Desmarais with the xergm: Extensions of Exponential Random Graph Models package. I would also like to thank those who have provided helpful comments and sugges- tions for portions of this project along the way including Jenna Bednar, Sarah Binder, Matthew Green, Michael Heaney, Greg Koger, Michael Lynch, Will Massengill, Nate Monroe, Jason Morgan, Vincent Moscardelli, Jason Roberts, Wendy Schiller, Sean v Theriault, and Jennifer Victor, as well participants in the American Politics Workshop at Ohio State University and the Visions in Methodology Conference. I have been incredibly fortunate to work with a truly fantastic committee and I would have been lost at several points along the way without their advice and support. My chair, Jan Box-Steffensmeier, is the best mentor a person could ask for, inspiring me with her brilliance, gently steering me back on course whenever I was distracted by shiny objects, and encouraging me with her endless faith in me. Skyler Cranmer provided not only methodological guidance, but also pushed me to work harder, think bigger, and stop giving boring presentations. Michael Neblo’s enthusiasm for me and my project was a constant source of inspiration, and Herb Weisberg could always be counted on to talk out even my most half-baked ideas. I am also indebted to the colleagues from my past life as a congressional staffer who supported me in the decision to turn my life upside down to become an academic and have continued to serve as a resource in my research. And I would be remiss if I did not mention the influence of a certain John McCain campaign volunteer who sparked my political involvement at the age of six when he stole my sign. Finally, I owe thanks to all of my cheerleaders who provided endless support and encouragement along the way, but in particular Kati, who put up with my whining and yelled at me when I needed it, Bri, who kept me going with a healthy balance of coffee and wine, and Greg, who never shut up about how proud he was ofme.And my parents, who helped me be fearless, with the knowledge that they would catch me if I fell. vi Vita 2001 . .B.S. Political Science, University of Oregon 2001-2008 . Congressional Staff, Congresswoman Darlene Hooley 2009-2012 . Congressional Staff, Congressman Kurt Schrader 2014 . .M.A. Political Science, Ohio State University 2014-2017 . Graduate Research Fellow, National Science Foundation Fields of Study Major Field: Political Science vii Table of Contents Page Abstract . ii Dedication . iv Acknowledgments . .v Vita......................................... vii List of Tables . .x List of Figures . xii 1. Introduction . .1 2. The Room Where it Happens: Collaborative Strategies in the U.S. House of Representatives . 13 3. Lone Wolves and Team Players: Policy Collaboration Networks and Leg- islative Effectiveness in the House of Representatives . 52 4. Running from Washington: Policy Collaboration as Symbolic Representation 92 5. Conclusion . 126 Bibliography . 133 viii Appendices . 147 A. Sample Dear Colleague Letters . 149 B. Alternate ERGM Specifications . 153 ix List of Tables Table Page 2.1 Probability of Policy Collaboration . 43 3.1 Policy Collaboration Network Summary Statistics . 71 3.2 Most and Least Collaborative Members of the 110th Congress . 76 3.3 Relationship Between Collaboration and Legislative Effectiveness . 83 3.4 Relationship Between Bipartisanship and Legislative Effectiveness . 88 4.1 Summary Statistics for Dependent and Key Independent Variables . 113 4.2 Relationship Between Past Electoral Performance and Collaboration . 118 4.3 Relationship Between Collaboration and Electoral Performance . 120 x B.1 Probability of Policy Collaboration with Party Mixing Covariate . 154 xi List of Figures Figure Page 2.1 Promoting Bipartisan Collaboration via Twitter . 18 2.2 Distribution of Letters by Purpose in Sample Population . 25 2.3 Signers per Letter . 29 2.4 One-Mode Projections of the Member Networks . 31 2.5 Partisanship of Ties by Congress . 34 2.6 GWESP and GWDSP statistics . 37 2.7 Probability of Tie Formation Coefficients . 45 2.8 Goodness-of-fit Diagnostics . 47 xii 3.1 Distribution of Dear Colleague Letters by Purpose . 64 3.2 Sample Dear Colleague Letter from 110th Congress . 66 3.3 Distribution of Signers by Source . 68 3.4 Policy Collaboration Network for the 110th Congress . 70 4.1 Promotion of Policy Collaboration via Twitter . 99 4.2 Distribution of Dear Colleague Letters by Purpose . 102 4.3 Sample Dear Colleague Letter from 111th Congress . 104 4.4 Ego Networks for Congressman Henry Cuellar (D-TX) and Congress- man Glenn Thompson (R-PA) in the 111th Congress (2009-2010) . 109 A.1 Dear Colleague Example: Community Pharmacies . 150 A.2 Dear Colleague Example: U.S.-Qatar Relations . 151 A.3 Dear Colleague Example: Health Care . 152