Exciting news

I’ve been tapped as the new executive director of the Analyst Institute. I’ve worked with AI’s fantastic team before, and I could not be more excited to continue and expand the culture of experimentation that has developed on the Democratic/progressive side.

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2048 Frivolity

I spent a good chunk of Saturday and Sunday ignoring the NCAAs and spent my time on something only slightly less frivolous: crafting an algorithm to beat the awesomely addicting game 2048. Spoilers below

Wednesday update: I’ve updated this post to reflect recent improvements in the algorithm.

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What’s on Your DC Primary Ballot?

There’s more than just mayor on the DC April 1st Democratic Primary ballot. Find out here:
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The Obervationalist’s Lament

The Monkey Cage Blog was kind enough to run my guest post about the impact of 2012 GOTV efforts [1]. I relied on observational data from Catalist to conduct my analysis (many thanks there) because randomized experiments (which are deservedly the “gold standard”) are unavailable for such a broad investigation. Even with Catalist’s “incredible data”—which is at the individual-level data—the observational analysis is extremely tricky. This wonky, methodological blog post explains why. (Thanks to Mark Mellman—former boss; mentor of mine—and Josh Rosmarin for prompting this train of thought, and to Kevin Collins for helping refine it.)

They key to estimating 2012 GOTV effects is isolating the impact of 2012 campaign activity. Crucially, this means (a) eliminating non-campaign competitiveness effects while (b) not wiping away campaign activity from the data. [2]

When performing battleground state analyses like mine, competitiveness effects are a large confounder. Not only are battleground state voters more likely to cast a ballot because their vote matters more in these competitive states, but this effect should naturally be larger among partisans. To re-state: partisans in battleground states are the voters most affected by non-campaign competitiveness effects, and these are the voters whom campaigns most target. That’s a tricky knot to disentangle.

To alleviate this problem, I control for individual-level a priori turnout score—i.e., the probability (at the beginning of the campaign season) that political practitioners assigned to each voter for the likelihood that she would cast a ballot. The reason this control is so important is that since competitiveness affected the battleground states in 2008, 2004, etc, then partisans are naturally more likely to vote in presidential years. Crucially, this increased probability is reflected in their turnout scores. By controlling for this score, I (attempt to) isolate 2012 campaign effects.

I’ll be honest that there are a multitude of small problems that make this 2008-based turnout score an imperfect control. State competitiveness could have changed from 2008 to 2012 (though it barely did). Voters could have become more (or less) partisan in the intervening four years, thus altering their individual competitiveness effects. Some voters moved from a non-battleground state to a battleground state, and their turnout score might not reflect the effect of this move.

However, those cavils pale in contrast to the issue if controlling for 2008 (via a turnout score) masks 2012 competitiveness effects, shouldn’t this control also mask 2012 campaign effects? After all, Obama and McCain ran full-fledged campaigns in 2008—those effects should be baked into the 2012 turnout score just as I hope the competitiveness effects are. And, if I excuse this issue by claiming (a) 2008 turnout is diluted within the holistic turnout score, (b) some people’s scores will have shifted between elections (thus entering or exiting campaigns’ target universes) and (c) some people have moved between states, then don’t those same excuses mean I similarly failed to fully account for the competitiveness effect?

The good news is that the data do not support this final worry. If the competitiveness effect incidentally dominated my analysis, then the partisan effect would be most observed at the extremes of the scale (as the sporadic voters who are the biggest partisans would be the ones to care most about living a battleground state). However, this pattern is not observed. Thus, I feel fairly confident that I eliminate competitiveness concerns through the turnout score control.

However, my hunch is that by controlling for 2008 turnout (via the turnout score), I do in fact mask some of the 2012 campaign effects, thus biasing my estimates downward. As a cautious person, I’ll take that risk rather than potentially inflating the numbers upward and seeing an effect where there is none. Others may make a different decision.

To reinforce to the idea that its difficult to tease out campaign effects from competitiveness effects, image if Catalist had provided me with a list of voters who had moved from non-battleground states to battleground states between 2008 and 2012. It’s tempting to think that examining those voters’ 2012 actions sheds insight into battleground state campaign effects. Unfortunately, this analysis is not fruitful because these movers’ 2012 turnout patterns reflect both campaign effects and their votes mattering more (or appearing to matter more) in 2012 than they did in 2008 because of competitiveness effects.

All of the above demonstrates why conducting a randomized controlled experiment, in which none of these confounding elements are an issue, is the key to estimating causality. It’s why I’m so glad that a culture of experiments on the Democratic/progressive side–and many props to Malchow, Podhorzer, and everyone at AG/AI for making it happen.

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2012 Turnout Analysis: Methodological Notes

This is a semi-live document where I’ll answer various questions people have about my recent MonkeyCage blog post

  • I used Catalist’s turnout score and Obama support score the two microtargeting scores that I reference in the post. Neither was affected by 2012 campaign activity, thus reducing endogeneity problems. Special thanks to Catalist for the data and helping me understand its nuances.

  • Chris Kennedy rightly points out that other organizations besides the official Obama and Romney campaigns were engaged in targeted GOTV. The correct interpretation is to read “Obama campaign” and “Romney campaign” as stand-ins for “Democratic efforts” and “Republican efforts.” I apologize for the error.

  • Figure 1 was distorted by Monkey Cage. Here’s the real one:

  • Sporadic voters are defined as those having ex-ante turnout probabilities of below 85% (which is about the median probability, and much higher than the mean value of 71%). Campaign effect estimate are much lower among voters with the highest turnout probabilities (>95%); inclusion of borderline GOTV voters (with vote propensity scores 85%-95%) would increase the estimated net Obama effect, but it’s not clear that these voters were targeted by the campaigns, so they are left out. Republicans are defined as having a pre-campaign, Catalist-estimated likelihood of supporting Obama below 40%; Democrats, above 60%. One standard error is shown as error bars in the Figures. The nationwide turnout of 66% is calculated from Catalist’s voter file and includes inactive voters (using official designations) in the denominator.

  • The turnout and partisanship scores were developed by Catalist and used by them in Spring 2012. No 2012 campaign activities affect these microtargeting scores. This helps avoid endogeneity issues.

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The Importance of Same-Day Registration

Yesterday, I registered a wonky disagreement with the presidential voting commission’s report. Today, I raise a more straightforward cavil. Kevin Collins and StephanieWDC kick things off:

Same-day registration (aka, Election Day registration, or EDR) allows people to register (or fix their existing registration) at the polls on Election Day. The beauty of this system is that if a citizen who is generally uninterested in politics is persuaded to vote on Election Day (perhaps because of the media attention, peer pressure, or the prevalence of “I Voted” stickers) then that person doesn’t have to worry about the fact that they didn’t do any pre-planning with respect to their registration. Their vote will count. Thus, EDR boosts turnout by 3 to 7 percentage points.

Perhaps the commission didn’t endorse EDR because more people showing up on Election Day who need help with registration slows the process down. But if local election officials use resource calculators, we can solve that problem while boosting turnout and improving our democracy.

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Helping Local Election Officials Succeed

The Presidential Commission on Election Administration (PCEA, or Bauer-Ginsberg) released its report this week. While I support nearly all the recommendations in the report, they miss a key point about data modeling.

First, the good news: The report provides excellent recommendations on electronic voter registration, early voting, absentee ballot tracking, the use of school as polling places, and the availability of resource calculators (this tool is better than mine). And I was very happy how much the committee relied on the work of professors Stewart, Ansolabehere, and others.

However, I think the recommendation of local officials to monitor wait times themselves is misguided (bottom of page 43, top of page 44). Specifically, the committee’s call to action is:

Addressing long lines requires systematic procedures to spot when and where long lines occur. Keeping track of wait times at individual polling places can be done using simple management techniques, such as recording line length at regular intervals during Election Day and giving time-stamped cards to voters during the day to monitor turnout flow.

Election officials have a ton to worry about on Election Day; adding to their stress by suggesting they hand out time cards is an unrealistic and unnecessary burden. We shouldn’t expect expect local election officials to go through the trouble of exactly monitoring wait times when post-Election Day they would have results for only (say, for example) the 15 precincts in their county, many of which are likely homogenous. To produce great models, data analysts need many data points and heterogeneous input variables. Both criteria help the model understand exactly what happens under different conditions, and local election officials may not be able to satisfy either one.

A better approach would be to fund or promote national projects that inform us about our election system. For instance, Prof Stewart’s survey provided information on wait times, and Foursquare’s “I Voted” badge lets us know when people vote (middle of infographic). We should expand these existing efforts, as well as fund new ideas, such as a web app that records wait times (ala TSA wait times). These data and models can then be integrated into the next generation of resource calculators, which are easy to disseminate to local election officials. These officials are incentivized to use the calculators to double check that they have the proper amount of equipment assigned to each precinct’s polling location, ensuring they don’t have egg on their face later.

In sum, let’s not give local election officials more work; instead let’s provide them with the tools they need to conduct successful elections.

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Best Books I Read in 2013

One year ago today, Aaron Swartz took his own life. One of his most impressive qualities was his appetite for reading books. For instance, he read 70 books in 2011 and kindly posted his thoughts on all of them on his blog. In memory of Aaron and in that same spirit of sharing with the community, here are the best books I read in 2013.

  • I am Malala by Malala Yousafzai — The riveting, first-person story of a teenager from the Swat Valley who stood up to the Taliban. It will bring you to tears and inspire you to pursue great things with your life.

  • Zealot by Reza Aslan — a compelling narrative of the Life and Times of the historical Jesus, Aslan answers such interesting questions such as: why was Jesus said to have been born in Bethlehem when he was from Nazareth? Why did he overturn the money tables? What’s the meaning of the “Render unto Ceaser” quote? Why is Paul, who never met Jesus, such an important figure in early Christianity? And, perhaps most crucially, what happened to Jesus’s brother, James the Just?

  • Far From The Tree by Andrew Solomon — an incredibly in-depth books about having children with horizontal identities different than yours (e.g., deaf, gay). A must read for perspective parents.

  • Mean and Lowly Things by Kate Jackson — How would handle 30 days in the Congolese jungle trying to find new species of snakes? Not as well as Kate Jackson who, amazingly, outlasts the locals. An educational and inspiring tale.

  • Mountains Beyond Mountains by Tracy Kidder — the story of how Paul Farmer is changing the world through medicine. I actually didn’t like Kidder’s writing style and I hope to pick up a book by Farmer–giving a first-person account–sometime in 2014.

  • Thinking Fast and Slow by Daniel Kahneman — a seminal social psychology work that I should have read a long time ago.

  • Writing on the Wall by Tom Standage — how social media has developed (and shrunk at times) over the course of civilization. Euro-centric, but interesting. Intersects with the ideas Zealot when talking about Paul’s letters (e.g., his letter to the Corinthians).

  • The Gamble by Sides and Vavreck — political science applied to the 2012 election. One book such as this needs to be published each presidential cycle to push back against the unsupported-by-data media narratives. Political scientists don’t need to read this book; journalists do.

  • The Signal and the Noise by Nate Silver — how statistics influences a variety of fields, from sports to the weather. I love the explanation of Bayesian statistics.

  • The Casual Vacancy by JK Rowling — in which Rowling proves that she can write about more than wizards. A wonderful book for people who like politics, as the story revolves around a local town council.

  • Harry Potter and the Methods of Rationality by Eliezer Yudkowsky — I believe I started reading this in 2012, but the story isn’t finished yet (it will wrap up this year), and I have to include this fantastic story on this list because I believe I learned about it through Aaron Swartz telling Taren about it, who then told me to check it out. And I’m glad I did. Furthermore, Yudkowsky recommends Worm, which I quickly became addicted to.

May Aaron’s life inspire others to both read and act.

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Merry Christmas, 2013

Hope this provides a few more laughs today.

‘Twas the eve before Christmas and a glitchy website
Kept Obamacare phones open all through the night.
Last minute shoppers with many a question
Were giving us workers severe indigestion.

Line one held Miley, whose plan had to work
For her concert-based aches, from a jerk to a twerk.
Holding was Edward, who hoped that we knew
If his coverage extended to Russia? Peru?

And from Cuba, Diana did give us a ring.
“Would bronze, silver, or gold cover jellyfish sting?”
But no calls did arrive from Prince William or Kate:
Little George will be covered, as with all in his State.

The requests flooded in and we kept up the pace
With just one hour left, we might finish this race…
But oh no! In the Superbowl’s fashion our power went black!
And Voice Over IP meant dial tones we did lack.

Through our windows we saw some bored teens on the lawn.
They were cutting up fiber while waiting for dawn.
“You fools!” we all cried, “People need this insurance!”
The gang of kids snickered, our rage no deterrence.

When up on the roof there arose such a clatter;
It happened so quickly the teens couldn’t scatter.
We stood back in awe as a figure descended.
It took but a moment; then all comprehended.

“It’s the Pope!” a gal cried, out of fear that he’d trounce her.
The teens, they all cowered from this former bouncer.
“No need to fret, I’m not that kind of Pope.
Bring neither brimstone nor fire, I preach passion and hope.

“I get it, you’re young; you think you’re the ‘invincibles’.
And there’ll be time yet to compose your own principles.
But tonight brings the chance to save thousands of lives.
And improving the world means much more than a rhyme.

“If you undo your deeds and restore building power.
Those in need will get care; though 11th the hour.
And since you’re all here, maybe buy some yourself.
The mandate applies to ev’ry Prez, kid and elf.”

And with the teens help, our last calls were complete.
We thanked the Pope kindly as he washed our feet.
Yet his smile flickered; I asked him “What gives?”
–“Remind me your policy on contraceptives?”

No Popemobile, reindeer, no not even a sleigh,
Just a beat up Renault took Pope Francis away.
And I heard him exclaim as he drove out of here,
“Merry Healthcare to most, but to all a great year!”

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Links from “Map Anyting” Presentation

At Rootscamp13, I gave a presentation called “Map Anything” that discussed how we combine common political geography identifiers and shapefiles to create a political data visualization revolution. Here are some links I promised attendees:

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