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I Get By with a Little Help from My Friends: Leveraging Campaign Resources to Maximize Congressional Power

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  • Janet M. Box‐Steffensmeier
  • Benjamin W. Campbell
  • Andrew W. Podob
  • Seth J. Walker

Abstract

Central to the study of Congress is the study of relationships among members. Electoral collaboration is a function of a member's position in the broader congressional power network. It allows members to leverage their campaign resources to achieve the four classic goals of members of Congress: reelection, making good public policy, obtaining power within the institution, and having one's party in the majority. Using nearly 3.2 million FEC records from 2010 to 2016, we explore the dynamics that influence electoral collaboration. We find members are most likely to collaborate electorally with other members from the same state, party, and committee, and the most electorally vulnerable. Further, party leaders share most frequently with the rank and file. These findings build upon our expanding understanding of congressional collaboration, the networks members of Congress form, and the congressional power structure members operate within.

Suggested Citation

  • Janet M. Box‐Steffensmeier & Benjamin W. Campbell & Andrew W. Podob & Seth J. Walker, 2020. "I Get By with a Little Help from My Friends: Leveraging Campaign Resources to Maximize Congressional Power," American Journal of Political Science, John Wiley & Sons, vol. 64(4), pages 1017-1033, October.
  • Handle: RePEc:wly:amposc:v:64:y:2020:i:4:p:1017-1033
    DOI: 10.1111/ajps.12528
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    References listed on IDEAS

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    1. Cann, Damon M., 2008. "Modeling Committee Chair Selection in the U.S. House of Representatives," Political Analysis, Cambridge University Press, vol. 16(3), pages 274-289, July.
    2. Fowler, James H., 2006. "Connecting the Congress: A Study of Cosponsorship Networks," Political Analysis, Cambridge University Press, vol. 14(4), pages 456-487, October.
    3. Masters, Nicholas A., 1961. "Committee Assignments in the House of Representatives," American Political Science Review, Cambridge University Press, vol. 55(2), pages 345-357, June.
    4. Koger, Gregory & Masket, Seth & Noel, Hans, 2009. "Partisan Webs: Information Exchange and Party Networks," British Journal of Political Science, Cambridge University Press, vol. 39(3), pages 633-653, July.
    5. Steven Goodreau & James Kitts & Martina Morris, 2009. "Birds of a feather, or friend of a friend? using exponential random graph models to investigate adolescent social networks," Demography, Springer;Population Association of America (PAA), vol. 46(1), pages 103-125, February.
    6. Masket, Seth E., 2008. "Where You Sit is Where You Stand: The Impact of Seating Proximity on Legislative Cue-Taking," Quarterly Journal of Political Science, now publishers, vol. 3(3), pages 301-311, October.
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    Cited by:

    1. James Rockey & Nadia Zakir, 2021. "Power and the money, money and the power: A network analysis of donations from American corporate to political leaders," Discussion Papers 21-03, Department of Economics, University of Birmingham.

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