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What is the Partisan Advantage Tracker?

How Does the Partisan Advantage Tracker Work?

Election Data

What Is Fair? Four Notions of Fairness

Partisan Advantage Data

The table below indicates the partisan advantage in each state, in number of seats, calculated using data from 2016-2020 elections for US President, US Senate, and Governor in each state produced by VEST, as compiled by DRA 2020. Positive numbers indicate an advantage for the GOP, and negative numbers for the Democratic party. The last two columns indicate the number of seats each party would get under the current maps. The maps are those adopted as of 5/30/2022.

State Seats Eff. Gap Quadratic Cubic JurisdictionalDem Seats GOP Seats
UNITED STATES
435
9.91
7.48
14.04
19.02
223.10
211.90
Alabama
7
1.08
1.27
0.69
0.90
1.00
6.00
Alaska
1
0.00
1.00
Arizona
9
0.77
0.80
0.60
0.38
3.33
5.67
Arkansas
4
0.81
0.99
0.56
0.75
0.00
4.00
California
52
-3.75
-5.82
-0.25
-1.41
44.33
7.67
Colorado
8
-0.34
-0.37
-0.04
0.09
5.00
3.00
Connecticut
5
-1.23
-1.33
-0.95
0.01
4.60
0.40
Delaware
1
1.00
0.00
Florida
28
3.85
3.88
3.49
5.11
9.40
18.60
Georgia
14
1.57
1.60
1.38
2.06
5.00
9.00
Hawaii
2
-0.25
-0.39
-0.18
0.00
2.00
0.00
Idaho
2
0.35
0.46
0.25
0.18
0.00
2.00
Illinois
17
-2.67
-2.91
-1.55
-1.92
14.00
3.00
Indiana
9
1.20
1.32
0.73
0.90
2.00
7.00
Iowa
4
0.97
1.00
0.81
0.80
0.60
3.40
Kansas
4
0.59
0.67
0.41
0.47
0.80
3.20
Kentucky
6
0.42
0.54
0.18
0.26
1.67
4.33
Louisiana
6
0.98
1.10
0.66
0.72
1.00
5.00
Maine
2
0.05
0.05
0.08
0.02
1.00
1.00
Maryland
8
-0.45
-0.74
-0.15
-0.86
6.20
1.80
Massachusetts
9
-1.32
-1.55
-0.97
-0.31
7.40
1.60
Michigan
13
-0.16
-0.18
0.10
0.08
7.20
5.80
Minnesota
8
0.00
-0.06
0.33
0.11
4.83
3.17
Mississippi
4
0.51
0.54
0.30
0.13
1.00
3.00
Missouri
8
1.08
1.16
0.72
1.00
2.00
6.00
Montana
2
0.48
0.50
0.42
0.47
0.33
1.67
Nebraska
3
0.32
0.44
0.15
0.71
0.40
2.60
Nevada
4
-0.86
-0.87
-0.79
0.01
3.00
1.00
New Hampshire
2
-0.05
-0.04
-0.05
-0.10
1.00
1.00
New Jersey
12
-1.86
-1.99
-1.14
-0.58
9.60
2.40
New Mexico
3
-1.09
-1.12
-0.93
-0.88
3.00
0.00
New York
26
-1.11
-2.33
0.33
-0.24
21.80
4.20
North Carolina
14
0.42
0.41
0.45
0.35
6.67
7.33
North Dakota
1
0.00
1.00
Ohio
15
1.60
1.69
1.18
1.49
4.80
10.20
Oklahoma
5
0.87
1.17
0.68
0.30
0.00
5.00
Oregon
6
-0.31
-0.38
0.02
-0.40
4.17
1.83
Pennsylvania
17
0.68
0.60
1.08
0.42
8.80
8.20
Rhode Island
2
-0.56
-0.61
-0.42
-0.12
2.00
0.00
South Carolina
7
1.53
1.61
1.15
0.59
1.00
6.00
South Dakota
1
0.00
1.00
Tennessee
9
1.40
1.64
0.80
1.07
1.10
7.90
Texas
38
2.26
2.42
0.83
4.06
13.60
24.40
Utah
4
0.69
0.91
0.49
0.54
0.00
4.00
Vermont
1
0.50
0.50
Virginia
11
-0.14
-0.21
0.37
0.43
6.80
4.20
Washington
10
-0.09
-0.22
0.54
0.59
6.67
3.33
West Virginia
2
0.11
0.31
0.11
0.00
0.00
2.00
Wisconsin
8
1.53
1.52
1.58
0.83
2.60
5.40
Wyoming
1
0.00
1.00

Geochart by Variable

Use the button below to generate a Google GeoChart representing the requested fairness variable as demonstrated above.




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Updates

Additional Links to Other Resources

  • Our complete set of election-by-election results in each state are available in this downloadable file (.xlsx).
  • Fivethirtyeight.com redistricting tracker analyzes several proposed and adopted maps in each state, and compares whether each of these maps provides seat gains or losses for each party, compared to the 2012 maps.
  • Politico redistricting tracker similarly evaluates the likely number of seats for each party under the 2022 maps, and compares gains and losses for each party in each state relative to the 2012 maps.
  • Planscore library of redistricting plans provides extensive information, including shapefiles and authoritative links, and an evaluation of partisan fairness according to the Efficiency Gap, for a collection of maps. Further, it allows users to automatically evaluate any map they upload.
  • The ALARM project compares the congressional map adopted in each state to 5,000 computationally-generated alternative maps.
  • Princeton Gerrymandering Project redistricting report cards evaluate and grade maps according to several criteria, including partisan fairness.
  • The online application DRA 2020; provides multiple measures of partisan fairness for a large collection of maps, including user-generated ones.

About This Project

Jon X. Eguia, Ph.D., a Professor of Economics and (by courtesy) of Political Science at Michigan State University, is lead author of this project. He joined Michigan State in 2014. He serves as an Associate Editor for the Journal of the European Economic Association. His expertise is in Collective Choice, Institutional Design and Political Economy. His work on partisan fairness in redistricting is published in the Election Law Journal, and he is the lead author of the IPPSR 2021 Michigan Redistricting Map Analysis and Report. He earned his doctorate in Social Sciences at Caltech in 2007.

Henry Fleischmann, Research Assistant, is an Honors Math and Computer Science Major at the University of Michigan-Ann Arbor Residential College and Goldwater Scholar.

This project is jointly undertaken by Michigan State University’s Institute for Public Policy and Social Research (IPPSR) and the University of Michigan’s Center for Local, State, and Urban Policy (CLOSUP). The Institute for Public Policy and Social Research (IPPSR) applies research to pressing public policy issues and builds problem-solving relationships between the academic and policymaking communities. CLOSUP conducts, supports and fosters applied academic research to improve understanding of local, state, and urban policy issues.

This project could not have been completed without the expertise, guidance and direction of IPPSR Director Dr. Matt Grossmann and CLOSUP Executive Director Tom Ivacko. We are indebted to all those at Michigan State University and the University of Michigan who contributed to this informative and educational effort, including Cindy Kyle.

Contact information : For any inquiries or comments please contact Cindy Kyle at kylec@msu.edu