Princeton Election Consortium

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Introducing the new Pennsylvania Congressional map

February 19th, 2018, 3:20pm by Sam Wang


Here’s the new Congressional map for Pennsylvania, drawn by advisor to the court Nate Persily. I think it’s a landmark contribution to the understanding of partisan fairness, in one of the most politically heterogeneous states in the Union – “Pennsatucky.”

For anyone who’s drawn such maps, this particular one is a pleasure to look at. It does a great job at compliance. It splits 13 counties, less than any plan offered to the court. The only plan that splits fewer counties or municipalities is the “compact D gerrymander” that the Princeton Gerrymandering Project posted over the weekend. So in terms of basic compliance, it wins.

But more importantly, this map undoes the effects of population clustering. As we showed over the weekend, it is just possible within the Pennsylvania Supreme Court’s rules to allow a plan that reaches partisan balance, i.e. a 9 D, 9 R outcome for a 50-50 statewide vote. However, those rules bias the range of possibilities in favor of Republicans, so that a Republican gerrymander – one of the proposals on the table – was also a possibility.

It appears as if the advisor was either trying to achieve partisan balance or build competitive races (as opposed to, say, picking a plan that was in the middle of the range of possible maps). His map – and the one we gave over the weekend – show that even under the constraint of compactness and not splitting political jurisdictions, it is still possible to build a map that treats both parties approximately equally. Notably, he did so while keeping most population centers together. This map passes all three of our tests of partisan asymmetry.

This outcome fits with an unspoken principle in the court’s decision of partisan symmetry: if the two sides swapped vote totals, then their seat totals should be swapped as well. This fundamental principle of fairness underlies our proposed standards for detecting gerrymandering, as described in our amicus brief in the Whitford case.

It is commonly claimed that partisan bias arises naturally from the way that voters distribute themselves. Certainly such a bias could be visible if one drew thousands (or millions) of maps at random. But districting is not a random process. It is done by human beings, and reflects real-life political and social considerations. In that respect, we shouldn’t care about millions of maps; we should only care about one map, the one that is drawn. Persily has shown that it is possible to maintain all the old principles of geographic contiguity, and still create an overall map that does not give either party an undue advantage. In my view, this is a big deal because it shows that the ideal of partisan symmetry can be a primary criterion for drawing a map.

It seems clear that the Pennsylvania GOP made a serious tactical error. The governor and Democratic legislators had offered a plan that would have retained some GOP advantage. The new plan erases that advantage entirely. In our analysis, based on the 2016 vote the new map produces 5 Democratic districts, 7 Republican districts, and 6 tossup districts. The maximum likely performance by Democrats in 2018 would be 11 seats, a gain of 6 seats over their current representation. That gain would be one-fourth of the 24 seats they need to win control of the House of Representatives. Of course, some of those gains could also go away in a later year that was good for Republicans. That’s the point of electoral competition.

→ 24 CommentsTags: 2018 Election · Redistricting

Pennsylvania partisanship, part II: Democrats in chains

February 17th, 2018, 8:02am by Sam Wang


The following analysis is a team effort by the Princeton Gerrymandering Project. John O’Neill drew maps which he, Brian Remlinger, Will Adler, and Madeleine Parker analyzed. For other people’s plans, we cited the work of Brian Amos.

In a previous post, we evaluated the Pennsylvania GOP leaders’ proposal for redrawing the congressional map and found strong signs of partisanship. We got curious: under the limits set by the state Supreme Court, what is the maximum advantage in the other direction, favoring Democrats?

We did this in order to put all the proposals into context. If we know the extreme limit on how favorably a map could treat Democrats while following the Court’s directives, then we can evaluate the partisanship of the many Democratic proposals.

We find that the Court’s simple rules (compactness, equal population, and minimization of county/municipality splitting) may still allow Republicans to commit mischief, but they effectively limit Democratic opportunities to gerrymander. Interestingly, Democratic players didn’t go nearly as far as they could have, but instead drew plans that were at the middle of the range of possibilities.

Here’s a map that is impressively compact:
It is the most Democrat-favoring map we could draw under the court’s criteria. On average, it would elect 9 Democrats, 9 Republicans for an equally split statewide vote (using 2012/2016 presidential vote data), with 7 safe seats for each party and 4 tossup seats where the expected margin between parties would be 10 points or less. Democrats can get to 11 seats if they win all the tossups. That’s still 1-2 seats less lopsided than the Republican proposal in the other direction – and requires a wave election.

As far as literal compliance with “floor criteria” goes, this map splits 12 counties, 14 municipalities, and 11 precincts, equal to or fewer than all of the plans we examined. It also performs as well as or better than the other proposed maps on compactness metrics. There could well be a better map out there by these criteria, but we haven’t seen it.

This table contains an analysis of the map above (“Princeton D compact”) and other maps. Click to enlarge:

Democrats gain the biggest advantage by splitting Philadelphia and Pittsburgh. This is the converse of what we saw in the Republican plan, which packed those cities tightly while splitting other communities such as Reading, Montgomery County, and greater Harrisburg.

It’s possible to squeeze out a little more performance by being less attentive to the compactness metrics. The following map (“Princeton D extreme” in the table above) still makes fewer splits than all the submitted plans. Compared with the top map, it converts one safe Republican seat to a toss-up. It’s still a 9-9 map, but its ceiling performance is 12 Democrats, 6 Republicans.

Assuming that the Republican legislative leaders’ proposed map of February 9 was as favorable to their party as possible, this means that under any nominally Court-compliant map, Republicans will always win at least 6 seats and Democrats will always win at least 6 seats. The remaining 6 seats — a full one-third of them — are limited not by geography, but by the whims of redistricters.

Interestingly, none of the remedial plans submitted to the Court, even those submitted by Democratic politicians, sought to maximize Democratic seats. All submitted plans had between 6 and 8 Democratic seats, with most plans settling on 7 Democratic seats. Basically, everybody but the Republicans played it down the middle.

Why didn’t Democrats go for broke? Maybe they think toss-up seats are flippable in 2018. Maybe they wanted to protect their five incumbents. Maybe they prioritized “softer” criteria like maintaining certain political or economic communities. Or maybe they are simply good-faith actors. Whether the Court picks one of their plans or draws its own, the outcome is highly likely to be more fair than the existing plan.

One lesson here is that the median neutrally-drawn map appears to be about tilted two seats toward the Republicans. This cycle, partisan gerrymandering added two seats on top of that.

Back to our maps…to be clear, we don’t believe that our maps are good simply because they perform well on the metrics. Looking at our map one way, it’s the extreme endpoint of a range of possibilities. Looking at it another way, it shows that it’s possible to attain representational equity even in a state as heterogeneous as Pennsylvania.

Whichever way you look at it, we have shown that the simple rules and traditional redistricting criteria used here by the Court can only do so much to constrain partisan actors. The court’s floor criteria of compactness and no splitting can be useful to prevent the flagrant geographic offenses we saw on both sides of the aisle nationwide in 2011. However, a truly fair process can only result from a nonpartisan process that examines the many tradeoffs in redistricting.

The fine print:

We used 2016 2-way presidential vote to categorize districts as Democratic or Republican. 2016 was probably the high-water mark for Republicans in Pennsylvania, so our map (and the other maps) may be slightly more favorable to Democrats than the data suggests. We did not examine incumbency, nor did we attempt to keep communities together beyond counties or municipalities. The plans above were drawn by John O’Neill, an expert with real life redistricting experience. We can’t rule out that there is some plan much more advantageous to Democrats than what he drew, though we suspect not. A shapefile of our map is available here, and summary statistics of our plan, as well as some others, are here.

We examined the following maps, which are available at the PA Supreme Court website. The analysis here taken from Brian Amos on Twitter, unless otherwise noted. All analysis uses 2016 presidential results:

  • PA House Democratic caucus’ plan: 6 safe D, 1 lean D, 2 lean R, 9 safe R

  • PA State Senate Democratic caucus’ plan: 6 safe D, 1 lean D, 2 lean R, 9 safe R

  • Gov. Wolf’s plan: 5 safe Dem, 2 lean Dem, 2 lean R, 9 safe R

  • Lt. Gov. Stackhouse’s plan: 5 safe D, 2 lean D, 2 lean R, 9 safe R

  • Petitioner’s plans: 5 safe D, 2-3 lean D, 1-2 lean R, 8-9 safe R

  • Republican intervenors’ plan: 5 Dem safe, 1 Dem lean, 2 R lean, 10 R safe

  • Republican legislative plan (aka Scarnati and Turzai): 5 safe D, 1 lean D, 3 lean R, 9 safe R (analysis)

  • Schneider/Wolf amicus plans: 4-5 Dem safe, 2-3 Dem lean, 3 Rep lean, 8 Rep safe (analysis)

→ 4 CommentsTags: 2018 Election · Redistricting

Happy Valentine’s Day!

February 14th, 2018, 1:05pm by Sam Wang


From the crew at Voters Not Politicians in Michigan, we have this awesomely dorky yet sweet sentiment: Be My Valid-Line!

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When simple rules aren’t enough

February 13th, 2018, 6:36pm by Sam Wang


As the old political-science saying goes, “all redistricting is gerrymandering.” Inevitably, choices and tradeoffs have to be made. When it comes to representation, the resulting map can end up balanced – unless partisan advantage is made the primary criterion.

The Pennsylvania Supreme Court set down clear “floor criteria” for what was absolutely required in the revised map. They said that counties, cities, and wards should not be divided, except to achieve equal population as required by federal law, and to comply with the Voting Rights Act. However, they also said (see page 124 of the decision):

We recognize…that there exists the possibility that advances in map drawing technology and analytical software can potentially allow mapmakers, in the future, to engineer congressional districting maps, which, although minimally comporting with these neutral “floor” criteria, nevertheless operate to unfairly dilute the power of a particular group’s vote for a congressional representative.

Although compliant with floor criteria, a close look at the Pennsylvania GOP legislative leaders’ proposed map reveals some of the choices they made. All it takes is an overlay of population density. Here are some examples. [Read more →]

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A statistical toolbox reveals Pennsylvania’s extreme Congressional plan

February 13th, 2018, 8:27am by Sam Wang


Today, Philly.com highlights multiple measures of partisan gerrymandering, including several developed here at Princeton.

Now, a major disclaimer: I didn’t think of these, exactly. Several tests (mean-median difference, and lopsided-wins) are over a hundred years old. Another (simulated elections) relies on an equally-old technique, Monte Carlo simulations. These tests are so old that they have whiskers.

There’s one lesson, though: there isn’t just one way to evaluate a gerrymander. Think of these as tools that capture different aspects of partisan asymmetry. For example, Monte Carlo simulations actually account for some of the clustering effect that comes from Republicans gravitating toward rural areas and Democrats gravitating toward population centers.

For more on the tests, see our explainer. If you like, support our work!

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Three clues that today’s proposed Pennsylvania map is still a gerrymander

February 10th, 2018, 4:38pm by Sam Wang


An image of the Pennsylvania legislature’s proposed Congressional map has been released. It appears to be nominally in compliance with the Pennsylvania Supreme Court’s order, since it splits fewer counties than the current map. However, as we have seen in North Carolina, a prettier map can still conceal ill intent.

Despite the low resolution, enough information is available to conclude that this is still a partisan gerrymander. Of course one can do a detailed partisan calculation, and Dave Wasserman thinks that it’s still 12 R, 6 D, and Nate Cohn thinks it’s 13 R, 5 D. It is absolutely central to remember that even under compactness-based rules, a wide range of partisan outcomes is possible – and this plan is extreme.

Even without making such seat-based calculations, three clues indicating a gerrymander are apparent: [Read more →]

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Partisan gerrymandering, the origin story

February 6th, 2018, 7:31am by Sam Wang


Where did this decade’s festival of partisan gerrymandering come from? Dave Daley dives into a trove of documents by Thomas Hofeller and other architects of the grand plan to make hundreds of Congressional and legislative seats uncompetitive after the 2010 Census.

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Justice Alito draws the line

February 5th, 2018, 11:11pm by Sam Wang


gavelToday, U.S. Supreme Court Justice Samuel Alito denied Republican legislators’ request for a stay of the Pennsylvania Supreme Court’s redistricting decision. That decision overturned the state’s partisan gerrymander, and remains in place. Therefore the drawing of new maps will go forward.

Here’s a quick rundown of what the decision does – and doesn’t – mean. [Read more →]

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Pennsylvania Congressional gerrymander overturned – and it seems likely to stick

January 22nd, 2018, 2:51pm by Sam Wang


Update, February 5th: Justice Alito denied the Pennsylvania GOP legislators’ motion for a stay. He did so without referring the matter to the full Supreme Court. Justice Alito is one of the three most conservative members of the court, and a near-guaranteed vote against restrictions on partisan gerrymandering…based on the U.S. Constitution. I would call his ruling today a clear signal of what he thought of this desperate Hail Mary pass.

This doesn’t have any bearing on the federal cases in Wisconsin, Maryland, or North Carolina. But it does mean that Pennsylvania will have new Congressional maps within 1-2 weeks.

Update, January 26th: The Commonwealth Court has announced the details of the redistricting, including which definitions of compactness to use. They’ve also retained veteran redistricter Nathaniel Persily in case the legislative process does not produce an acceptable map.

Just in – Pennsylvania’s Commonwealth Court has overturned that state’s Congressional map as a partisan gerrymander. Maps are ordered to be redrawn there in time for this year’s November election (and the primary in May).

The order was 5-2, with the court’s two Republican appointees in the minority. However, even they were soft no’s. One of them, Chief Justice Saylor, wants to wait to see how Gill v. Whitford, the federal Wisconsin case, turns out. The other, Justice Mundy, says it is not clear which provision of the Commonwealth Constitution applies here. A third justice, Democrat-appointed Justice Baer, raised concerns that subsequent litigation will compress this year’s election calendar too much.

Of particular note, the court order says to redistrict by compactness, equal population, and preserving towns/counties/cities. However, no reference to communities of interest, which is probably good because it closes a loophole that partisans would otherwise try to exploit.

This decision is huge because it does not depend on the U.S. Constitution. Instead, it is based on the Commonwealth Constitution of Pennsylvania, which has First/Fourteenth-Amendment-like protections – but is not subject to appeal to the Supreme Court. I think intervention by the Supreme Court would occur only if the decision expressly contradicted federal law. Even if Gill were to win over Whitford in the Wisconsin case, a decision there would probably still not find a right to gerrymander in the U.S. Constitution. That said, Rick Hasen has described a possible Hail Mary strategy for the state of Pennsylvania. None of this will stop the initial appeals and litigation…but it sure seems like Pennsylvania just took a big step toward fairer districting for this cycle (2018 and 2020). Considering that Pennsylvania is the site of the (in)famous Vieth v. Jubelirer decision, it would be poetic justice.

What does this mean for this year? According to the order, the special election in the 18th Congressional District should proceed as planned, in March. That makes sense, since otherwise, dependent on the new boundaries, some Pennsylvanians would have two members of Congress and others would have none. After that, once the map is redrawn, political conditions in 2018 are likely to resemble 2012 for Democrats, or better. Neutral districting then would have led to 8-9 D seats. The actual result was 13 R, 5 D (and has been since then). Therefore today’s decision, implemented via neutral redistricting principles, might reasonably mean a 3 or 4-seat gain for Democrats.

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Gobbledygook 101: Buttercup Petals and Partisan Gerrymandering

January 17th, 2018, 9:34am by Sam Wang


What do all these phenomena have in common with partisan gerrymandering?
Tools developed over a century ago can help us detect and limit partisan gerrymandering today. Maps and geometry by themselves won’t do the job. Find out why in our new Vox explainer.

Image: table from Karl Pearson’s original 1895 paper on the mean-median difference.

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