A GREEMENT S CORES, I DEAL P OINTS, AND L EGISLATIVE P OLARIZATION Betsy Sinclair Jennifer N. Victor University of Chicago University of Pittsburgh Seth.

AGREEMENT SCORES, IDEAL POINTS, AND LEGISLATIVE POLARIZATION

Betsy Sinclair Jennifer N. Victor

University of Chicago University of Pittsburgh

Seth Masket Gregory Koger

University of Denver University of Miami

ORGANIZATION OF THIS PROJECT

(Re)introduce “agreement scores” to the political science community as a measure of legislative behavior.

Compare agreement scores to other commonly used legislative behavior measures, such as NOMINATE.

Apply agreement scores to theories of legislative polarization.

Demonstrate that agreement scores provide similar findings about the sources of polarization, without hefty assumptions about independence.

THE STUDY OF LEGISLATIVE VOTING (A BRIEF HISTORY)

Studying the voting cohesion of legislative party members: Lowell (1902), Rice (1925)

“Agreement Scores”: Truman (1959)

Party cohesion: Mayhew (1966), Sinclair (1976, 1977)

Signaling, cue taking: Kingdon 1989, Matthews and Stimson (1975)

The NOMINATE revolution: Poole and Rosenthal (1985, 1997)

DAVID TRUMAN’S AGREEMENT SCORES, 1959

WHAT’S THE TROUBLE WITH NOMINATE?

Assume legislators always vote for policies closer to their ideal point.

Votes are treated as a single-shot game.

Spatial model assumptions make it difficult to discern the influence of constituents and parties (Krehbiel 1993, Sinclair 2002).

Unrealistic assumptions dimensionality of bills and legislators (Londregan 1999).

The independence assumption.

THE UNREASONABLENESS OF INDEPENDENCE

Evidence of legislators influencing one another.

Logrolling: Calvert and Fenno 1994

Social interaction

Boardinghouses: Young 1966

Cue Taking: Kingdon 1973, Matthews and Stimson 1975

Seat Assignments: Masket 2008

Cosponsorship: Koger 2003, Fowler 2006

Caucus participation: Victor and Ringe 2009

WE NEED A NEW HAMMER

We require a tool that doesn’t require us to assume legislators are atomistic actors.

Network Analysis.

AGREEMENT SCORES

For each Congress, create an M-by-M matrix, where M is the number of legislators in a Congress.

The cells in the matrix describe the rate that any two legislators voted the same way, given that they both voted.

Adjacency matrix, A, with agreement between i and j.

A disadvantage: bills treated equally

AN ILLUSTRATIVE APPLICATION: SOURCES OF LEGISLATIVE POLARIZATION

Theory 1: Mass Partisanship Trends Red state/Blue state Evidence in NOMINATE scores H1: Do we observe increasing agreement among

same party legislators over time?

Theory 2: Institutional Influence Size of the majority party determines party

cohesion H2: Do we observe decreasing agreement

among same party pairs as the size of the majority party increases?

AN ILLUSTRATIVE APPLICATION: SOURCES OF LEGISLATIVE POLARIZATION

Theory 3: Party Culture Republicans are more authoritarian, disciplined H3: Do we observe increasing agreement among

Republican pairs when Republicans are in the majority?

Empirical Investigation Data: Roll Call Votes from the 90th-110th

Congresses (1967-2008).

Calculate agreement scores among all pairs in each congress.

TEST 1: LONGITUDINAL

TEST 2: INSTITUTIONAL INFLUENCE (MAJORITY)

TEST 2: INSTITUTIONAL INFLUENCE (MINORITY)

TEST 3: CULTURE

CONCLUSIONS—ON SUBSTANCE (NO SURPRISES)

Legislative parties are becoming more internally homogenous.

Parties vote with greater discipline when they are in near numerical parity in the chamber.

Republicans are more cohesive than Democrats.

CONCLUSIONS—ON METHODS (A LIGHTER HAMMER)

We reach the same substantive conclusions as other research, but…

without complex mathematical algorithms or sophisticated programs, and…

without unrealistic assumptions of independence.

This method offers parsimony and intuitiveness, without sacrificing explanatory power.

Addenda

SIMPLE EXAMPLE

Consider 5 Senators’ votes over 4 bills Votes are either “yea” (1) or “nay” (0)

Bill 1 Bill 2 Bill 3 Bill 4

Helms 1 1 1 0

Dole 1 1 1 1

Nunn 1 1 0 1

Gore 1 0 0 1

Kerry 0 0 0 1

EXAMPLE: NOMINATE

-0.1-0.08-0.05-0.02 0 0.01 0.030.05 0.080.1

Nun

n

Ker

ry

Hel

ms

Gor

e

Dol

e

EXAMPLE: AGREEMENT SCORES

Calculate the agreement rate: = number of votes on which i,j agreed/number of votes on which i,j voted

Helms Dole Nunn Gore Kerry

Helms 1 0.75 0.5 0.25 0

Dole 0.75 1 0.75 0.5 0.25

Nunn 0.5 0.75 1 0.75 0.5

Gore 0.25 0.5 0.75 1 0.75

Kerry 0 0.25 0.5 0.75 1

EXAMPLE: AGREEMENT SCORES Calculate power centrality (Bonacich)

Measures “agreeability,” or tendency of member to vote with others. Describes power within a network (although direction is unclear).

SenatorBonacich Power

Centraity

Helms 0.75

Kerry 0.75

Dole 1.125

Gore 1.125

Nunn 1.25

AGREEMENT NETWORK