Public choice principles of redistricting

Gilligan, Thomas W.; Matsusaka, John G.

doi:10.1007/s11127-006-9062-8

Cited by 47 publications

(27 citation statements)

References 29 publications

(16 reference statements)

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“…For example, if legislators draw lines to increase the number of seats held by their party, they may actually create numerous competitive districts, each with a small margin in their favor (Gelman and King, 1994). Even if districts are competitive so that each legislator ends up representing the district's median voter, district lines can be gerrymandered so that the median legislator is not congruent with the median voter in the population, and even random redistricting will result in noncongruent policies (Gilligan and Matsusaka, 2006). • Ballot access.…”

Section: Determinants Of Congruence: Election Institutionsmentioning

confidence: 99%

Popular Control of Public Policy: A Quantitative Approach

Matsusaka

2010

QJPS

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The quality of government is often measured by the degree of congruence between policy choices and public opinion, but there is not an accepted method for calculating congruence. This paper offers a new approach to measuring policy-opinion congruence, and uses it to study 10 high-profile issues across the 50 states. For the issues examined, states chose the policy preferred by a majority of citizens (equivalent to the median voter outcome) 59 percent of the time -only 9 percent more than would have happened with random policymaking. Majoritarian/median outcomes were 18-19 percent more likely when direct democracy was available, and 11-13 percent more likely when judges were required to stand for reelection. The likelihood of a majoritarian/median outcome was not correlated with a variety of election laws, including campaign contribution limits, public funding of campaigns, and commission-based redistricting.In a democracy, citizen preferences are supposed to play an important role in public policy decisions. Indeed, as Erikson et al. (1993, p. 1) note, "we often gauge the quality of government by the responsiveness of public policymaking to the preferences of the mass public," and scholars and activists continue to search for institutions that will enhance responsiveness. The Downsian model (Downs, 1957) shows that competition between * I received helpful comments from Michael Alvarez, Jonathan Barnett, Christina Gathmann, Tim Groseclose, Andy Hanssen, Arthur Lupia, Mathew McCubbins, Jaffer Qamar, anonymous referees, and seminar participants at Stanford University, UC-San Diego, the University of Chicago, and the University of Southern California. candidates can bring policy decisions into alignment with the preferences of the median voter, but the predominant theme of recent research is the many obstacles that stand in the way of citizen control, such as the limited information of voters and representatives (Campbell et al., 1960;Miller and Stokes, 1963;Lupia and McCubbins, 1998;Groseclose and McCarty, 2000), interest groups (Olson, 1965;Stigler, 1971;Peltzman, 1976;Grossman and Helpman, 2001), and legislative structure (Weingast et al., 1981;Cox and McCubbins, 2005). Opinion surveys consistently reveal that most citizens believe government responds more to powerful interests than the general public.Despite its importance for the practice and study of democracy, there is little statistical evidence on the amount of congruence between preferences and policy that actually prevails, and little evidence on how institutions affect the amount of congruence. Numerous studies, such as the well-known contributions of Erikson et al. (1993), Borcherding and Deacon (1972), Bergstrom andGoodman (1973), andStimson et al. (1995) document a correlation between policy and indirect measures of citizen preferences, such as demographic and economic variables or indexes of ideology along a liberal-conservative continuum. 1 While such evidence shows that policies respond at the margin to changes in opinion, several studies ...

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Section: Determinants Of Congruence: Election Institutionsmentioning

confidence: 99%

Popular Control of Public Policy: A Quantitative Approach

Matsusaka

2010

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122

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“…That is, ρ(H) is the unique distribution such that ρ(H)(x) = 1 − H(−x) at every continuity point of ρ(H). 6 If G is the segregation constraint for party 2 then ρ(G) is the translation of G that makes G comparable to F , the segregation constraint of party 1. If ρ(G) = F then both parties face the same segregation constraint.…”

Section: An Example With No Local Uncertaintymentioning

confidence: 99%

Strategic Redistricting

Gül

Pesendorfer

2010

American Economic Review

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We develop and analyze a model of strategic redistricting. Two parties choose optimal redistricting plans for their respective territory. Parties redistrict before aggregate uncertainty is resolved. We show that in the unique equilibrium, parties maximally segregate their opponent's supporters but pool their own supporters into uniform districts. We show that the stronger a party gets, the more it segregates. Hence, of the two competing parties, ceteris paribus, the stronger party segregates more than the weaker one. Finally, we show that if the district level uncertainty is sufficiently small, the stronger party chooses polarizing policies while the weaker party accommodates the stronger party's supporters.

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“…Bradbury and Crain (2001) present empirical evidence of differences in the strength of the Law of 1/n between unicameral and bicameral legislatures. Gilligan and Matsusaka (2006) argue that the relationship between legislature size and spending may in fact be due to gerrymandering. Ansolabehere, Snyder Jr., and Ting (2003) model bicameral legislatures in a bargaining framework and considers the possibility of forming minimum winning coalitions among house representatives alone; Chen and Malhotra (2007) use a similar game theoretic approach and shows that the ratio of chamber sizes is the more relevant variable (and is negatively related to spending), while Maldonado (2013) uses international data to find a linear relationship between chamber size and spending in countries with unicameral legislatures and a nonlinear relationship in those with bicameral legislatures.…”

Section: Introductionmentioning

confidence: 99%

The Law of 1/n Revisited: Distributive Politics, Legislature Size, and the Costs of Collective Action

Crowley

2019

Southern Economic Journal

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The foundational model of distributive politics predicts a positive relationship between the number of legislative districts and the level of inefficiency of projects approved by the legislature—Weingast, Shepsle, and Johnsen's “Law of 1/n.” This relationship has been tested extensively in the empirical literature, with mixed results. This article presents a model wherein passing the omnibus legislation typical of distributive politics is a costly process. The model predicts a nonlinear relationship between legislature size and spending as increasing the size of the legislature also increases the costs of collective action. Results from an empirical exercise based on U.S. state legislatures (1962–2014) are consistent with the proposed model, showing a 1/n effect which diminishes at the margin as the legislature's size increases, especially in the lower chamber.

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Public choice principles of redistricting

Cited by 47 publications

References 29 publications

Popular Control of Public Policy: A Quantitative Approach

Popular Control of Public Policy: A Quantitative Approach

Strategic Redistricting

The Law of 1/n Revisited: Distributive Politics, Legislature Size, and the Costs of Collective Action

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