IDEAS home Printed from https://ideas.repec.org/a/wly/amposc/v64y2020i4p1017-1033.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/ajps.12528
    Download Restriction: no

    File URL: https://libkey.io/10.1111/ajps.12528?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    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. 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.
    6. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Jäckle Sebastian & Metz Thomas, 2019. "Oral Questions in the European Parliament: A Network Analysis," Statistics, Politics and Policy, De Gruyter, vol. 10(2), pages 87-113, December.
    2. Marco Battaglini & Eleonora Patacchini & Edoardo Rainone, 2019. "Endogenous Social Connections in Legislatures," NBER Working Papers 25988, National Bureau of Economic Research, Inc.
    3. Marco Battaglini & Valerio Leone Sciabolazza & Eleonora Patacchini, 2020. "Effectiveness of Connected Legislators," American Journal of Political Science, John Wiley & Sons, vol. 64(4), pages 739-756, October.
    4. Marco Battaglini & Eleonora Patacchini, 2018. "Influencing Connected Legislators," Journal of Political Economy, University of Chicago Press, vol. 126(6), pages 2277-2322.
    5. Duxbury, Scott W, 2017. "Diagnosing Multicollinearity in Exponential Random Graph Models," OSF Preprints hz93j, Center for Open Science.
    6. Tom A. B. Snijders & Christian E. G. Steglich, 2015. "Representing Micro–Macro Linkages by Actor-based Dynamic Network Models," Sociological Methods & Research, , vol. 44(2), pages 222-271, May.
    7. Neal, Zachary & Domagalski, Rachel & Yan, Xiaoqin, 2020. "Party Control as a Context for Homophily in Collaborations among US House Representatives, 1981 -- 2015," OSF Preprints qwdxs, Center for Open Science.
    8. Veremyev, Alexander & Boginski, Vladimir & Pasiliao, Eduardo L. & Prokopyev, Oleg A., 2022. "On integer programming models for the maximum 2-club problem and its robust generalizations in sparse graphs," European Journal of Operational Research, Elsevier, vol. 297(1), pages 86-101.
    9. Patrick O. Perry & Patrick J. Wolfe, 2013. "Point process modelling for directed interaction networks," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 75(5), pages 821-849, November.
    10. Cornelius Fritz & Michael Lebacher & Göran Kauermann, 2020. "Tempus volat, hora fugit: A survey of tie‐oriented dynamic network models in discrete and continuous time," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 74(3), pages 275-299, August.
    11. Lauren Cohen & Christopher Malloy, 2010. "Friends in High Places," NBER Working Papers 16437, National Bureau of Economic Research, Inc.
    12. Lever Guzmán Carlos, 2010. "Strategic Spending in Voting Competitions with Social Networks," Working Papers 2010-16, Banco de México.
    13. Ilona Babenko & Viktar Fedaseyeu & Song Zhang, 2017. "Executives In Politics," BAFFI CAREFIN Working Papers 1762, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    14. Jan Hanousek & Hoje Jo & Christos Pantzalis & Jung Chul Park, 2023. "A Dilemma of Self-interest vs. Ethical Responsibilities in Political Insider Trading," Journal of Business Ethics, Springer, vol. 187(1), pages 137-167, September.
    15. Omar A. Guerrero & Ulrich Matter, 2016. "Revealing the Anatomy of Vote Trading," Papers 1611.01381, arXiv.org.
    16. Huremović, Kenan & Ozkes, Ali I., 2022. "Polarization in networks: Identification–alienation framework," Journal of Mathematical Economics, Elsevier, vol. 102(C).
    17. Vicinanza, Paul & Goldberg, Amir & Srivastava, Sameer, 2021. "Quantifying Vision through Language Demonstrates that Visionary Ideas Come from the Periphery," OSF Preprints 3h8xp, Center for Open Science.
    18. Arndt Wonka & Sebastian Haunss, 2020. "Cooperation in networks: Political parties and interest groups in EU policy-making in Germany," European Union Politics, , vol. 21(1), pages 130-151, March.
    19. Adam M. Kleinbaum & Toby E. Stuart & Michael L. Tushman, 2013. "Discretion Within Constraint: Homophily and Structure in a Formal Organization," Organization Science, INFORMS, vol. 24(5), pages 1316-1336, October.
    20. Duncan A. Clark & Mark S. Handcock, 2022. "Comparing the real‐world performance of exponential‐family random graph models and latent order logistic models for social network analysis," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(2), pages 566-587, April.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:wly:amposc:v:64:y:2020:i:4:p:1017-1033. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: https://doi.org/10.1111/(ISSN)1540-5907 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.