One Way To Spot A Partisan Gerrymander

Will it convince the Supreme Court?

By William T. Adler and Ella Koeze

On March 26, challengers to North Carolina’s congressional map will argue before the Supreme Court that it is a partisan gerrymander — that is, the district boundaries were drawn to benefit one political party, the GOP, in a way that violates the Constitution. The challengers are using a variety of quantitative tools to make their argument, including a metric called “partisan bias” that tries to evaluate how skewed a map is by looking at the number of seats a party would have won in a hypothetical election in which the vote was evenly split between Republicans and Democrats. Here’s how that metric works and what it says about congressional maps going back a few decades.

We can also draw seats-votes curves for individual states, which typically redo their congressional and legislative maps every 10 years, after the decennial census. In the North Carolina case, however, the congressional map that is being challenged was enacted in 2016 after a 2011 map was declared unconstitutional (in that case, because the map makers relied too heavily on race). To support their argument that the 2016 map is a partisan gerrymander that disadvantages Democrats, the challengers use an expert’s finding that the map’s partisan bias in the 2016 election was the largest in the state since at least 1972. In the chart below, which looks at the state’s congressional elections since 1992, you can see that the partisan bias against Democrats increased dramatically in this decade.

The 2016 map’s defenders argue, however, that metrics such as partisan bias may incorrectly classify a district map as favoring Republicans because Democrats tend to cluster in cities. In response, the challengers say that a computational method that takes clustering into account also reveals the 2016 map’s unusually high degree of partisan skew.

But Republicans are not the only ones who critics say have unfairly drawn maps to their advantage. The Supreme Court is also considering a case out of Maryland, in which Democrats are accused of partisan gerrymandering. The challengers aren’t citing the partisan bias metric in their case, but they are arguing that the map makers diluted Republican votes with the intention of creating an additional Democratic district.

Sometimes challenges to maps result in court orders that the maps be redrawn. Last year, Pennsylvania’s congressional district boundaries were redrawn after the state’s Supreme Court ruled that the map used from 2012 to 2016 was an unconstitutional partisan gerrymander. And according to the partisan bias metric, it seems as though the new map is indeed fairer. As you can see in the charts below, the 2018 map had a partisan bias of 0, while the map that was used for the three other elections this decade had a partisan bias of roughly 22 points against Democrats.

Remember that partisan bias is just one of several ways to measure whether a map is gerrymandered and that it’s only a piece of the argument being made by the challengers to North Carolina’s map. So far, the Supreme Court has shied away from offering a clear decision on the constitutionality of partisan gerrymanders. Previous attempts to use metrics to persuade the court have not seen much success. Whether it will prove persuasive this time around remains to be seen.

Notes on methodology: The seats-votes curves in this project were built with U.S. House election results from 1992 through 2018. We used the two-party vote share, which considers only votes that were cast for Republican or Democratic candidates. All races won by independents were excluded, as was the 2018 result in North Carolina’s 9th Congressional District. For races that did not have both a Democrat and a Republican running, a statistical model was used to determine the likely two-party vote share. To find the average Democratic or Republican two-party vote share in the country or a state, the individual results in each district were averaged.

When simulating hypothetical elections, we assume that an equal number of percentage points are lost or gained in each district even though vote changes would be more variable across districts if it were possible to re-run an election with a different average two-party vote share.