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Democratic Representation and Partisan Bias in Congressional Elections

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  • King, Gary
  • Browning, Robert X

Abstract

The translation of citizen votes into legislative seats is of central importance in democratic electoral systems. It has been a longstanding concern among scholars in political science and in numerous other disciplines. Throughout this literature, two fundamental tenets of democratic theory, partisan bias and democratic representation, have often been confused. We develop a general statistical model of the relationship between votes and seats and separate these two important concepts theoretically and empirically. In so doing, we also solve several methodological problems with the study of seats, votes, and the cube law. An application to U.S. congressional districts provides estimates of bias and representation for each state and demonstrates the model's utility. Results of this application show distinct types of representation coexisting in U. S. states. Although most states have small partisan biases, there are some with a substantial degree of bias.

Suggested Citation

  • King, Gary & Browning, Robert X, 1987. "Democratic Representation and Partisan Bias in Congressional Elections," American Political Science Review, Cambridge University Press, vol. 81(4), pages 1251-1273, December.
    • Handle: RePEc:cup:apsrev:v:81:y:1987:i:04:p:1251-1273_20
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    Cited by:

    1. Bernard Tamas & Ron Johnston & Charles Pattie, 2022. "The impact of turnout on partisan bias in U.S. House elections, 1972–2018," Social Science Quarterly, Southwestern Social Science Association, vol. 103(1), pages 181-192, January.
    2. Barry Burden & Corwin Smidt, 2020. "Evaluating Legislative Districts Using Measures of Partisan Bias and Simulations," SAGE Open, , vol. 10(4), pages 21582440209, December.
    3. Thomas A. C. & Gelman Andrew & King Gary & Katz Jonathan N., 2013. "Estimating Partisan Bias of the Electoral College Under Proposed Changes in Elector Apportionment," Statistics, Politics and Policy, De Gruyter, vol. 4(1), pages 1-13, January.
    4. Wolfgang Pesendorfer & Faruk Gul, 2007. "Strategic Redistricting," Levine's Bibliography 843644000000000351, UCLA Department of Economics.
    5. Timothy Besley & Ian Preston, 2007. "Electoral Bias and Policy Choice: Theory and Evidence," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 122(4), pages 1473-1510.
    6. Christian Haas & Lee Hachadoorian & Steven O Kimbrough & Peter Miller & Frederic Murphy, 2020. "Seed-Fill-Shift-Repair: A redistricting heuristic for civic deliberation," PLOS ONE, Public Library of Science, vol. 15(9), pages 1-34, September.
    7. Christopher Warshaw & Eric McGhee & Michal Migurski, 2022. "Districts for a New Decade—Partisan Outcomes and Racial Representation in the 2021–22 Redistricting Cycle," Publius: The Journal of Federalism, CSF Associates Inc., vol. 52(3), pages 428-451.
    8. Matthew P. Dube & Jesse T. Clark & Richard J. Powell, 2022. "Graphical metrics for analyzing district maps," Journal of Computational Social Science, Springer, vol. 5(1), pages 449-475, May.
    9. Tim R. Sass, 2000. "The Determinants of Hispanic Representation in Municipal Government," Southern Economic Journal, John Wiley & Sons, vol. 66(3), pages 609-630, January.
    10. Justin Svec & James Hamilton, 2015. "Endogenous voting weights for elected representatives and redistricting," Constitutional Political Economy, Springer, vol. 26(4), pages 434-441, December.
    11. Benadè, Gerdus & Ho-Nguyen, Nam & Hooker, J.N., 2022. "Political districting without geography," Operations Research Perspectives, Elsevier, vol. 9(C).
    12. David Niven & Benjamin Plener Cover & Michael Solimine, 2021. "Are Individuals Harmed by Gerrymandering? Examining Access to Congressional District Offices," Social Science Quarterly, Southwestern Social Science Association, vol. 102(1), pages 29-46, January.
    13. Stephen Coate & Brian Knight, 2005. "Socially Optimal Districting," NBER Working Papers 11462, National Bureau of Economic Research, Inc.

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