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Inferring the Ideological Affliations of Political Committees via Financial Contributions Networks

Author

Listed:
  • Yiran Chen

    (Department of Economics, University of Pennsylvania)

  • Hanming Fang

    (Department of Economics, University of Pennsylvania)

Abstract
About two thirds of the political committees registered with the Federal Election Commission do not self identify their party affiliations. In this paper we propose and implement a novel Bayesian approach to infer about the ideological affiliations of political committees based on the network of the financial contributions among them. In Monte Carlo simulations, we demonstrate that our estimation algorithm achieves very high accuracy in recovering their latent ideological affiliations when the pairwise difference in ideology groups' connection patterns satisfy a condition known as the Chernoff-Hellinger divergence criterion. We illustrate our approach using the campaign finance record in 2003-2004 election cycle. Using the posterior mode to categorize the ideological affiliations of the political committees, our estimates match the self reported ideology for 94.36% of those committees who self reported to be Democratic and 89.49% of those committees who self reported to be Republican.

Suggested Citation

  • Yiran Chen & Hanming Fang, 2017. "Inferring the Ideological Affliations of Political Committees via Financial Contributions Networks," PIER Working Paper Archive 17-022, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 10 Dec 2017.
    • Handle: RePEc:pen:papers:17-022
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    References listed on IDEAS

    as
    1. Francesco Trebbi & Eric Weese, 2019. "Insurgency and Small Wars: Estimation of Unobserved Coalition Structures," Econometrica, Econometric Society, vol. 87(2), pages 463-496, March.
    2. Leung, Michael P., 2019. "A weak law for moments of pairwise stable networks," Journal of Econometrics, Elsevier, vol. 210(2), pages 310-326.
    3. Barberá, Pablo, 2015. "Birds of the Same Feather Tweet Together: Bayesian Ideal Point Estimation Using Twitter Data," Political Analysis, Cambridge University Press, vol. 23(1), pages 76-91, January.
    4. McKay Amy, 2010. "The Effects of Interest Groups' Ideology on Their PAC and Lobbying Expenditures," Business and Politics, De Gruyter, vol. 12(2), pages 1-23, August.
    5. McKay, Amy, 2010. "The Effects of Interest Groups' Ideology on Their PAC and Lobbying Expenditures," Business and Politics, Cambridge University Press, vol. 12(2), pages 1-21, August.
    6. Amy McKay, 2008. "A simple way of estimating interest group ideology," Public Choice, Springer, vol. 136(1), pages 69-86, July.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Ideology; Network Analysis; Stochastic Block Models;
    All these keywords.

    JEL classification:

    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation
    • D72 - Microeconomics - - Analysis of Collective Decision-Making - - - Political Processes: Rent-seeking, Lobbying, Elections, Legislatures, and Voting Behavior
    • P16 - Political Economy and Comparative Economic Systems - - Capitalist Economies - - - Capitalist Institutions; Welfare State

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