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Archive of posts filed under the Political Science category.

The return of the red state blue state fallacy

Back in the early days of this blog, we had frequent posts about the differences between Republican or Democratic voters and Republican or Democratic areas. This was something that confused lots of political journalists, most notably Michael Barone (see, for example, here) and Tucker Carlson (here), also academics such as psychologist Jonathan Haidt (here) and […]

10 on corona

Here are some things people have sent me lately. They are in no particular order, except that I put the last item last so we could end with some humor. After this, I’ll write a few more blog posts, then it’ll be time to do some real work. Table of contents 1. Suspicious coronavirus numbers […]

MRP with R and Stan; MRP with Python and Tensorflow

Lauren and Jonah wrote this case study which shows how to do Mister P in R using Stan. It’s a great case study: it’s not just the code for setting up and fitting the multilevel model, it also discusses the poststratification data, graphical exploration of the inferences, and alternative implementations of the model. Adam Haber […]

The best coronavirus summary so far

I’d still go with this article by Ed Yong, which covers biology, epidemiology, medicine, and politics. Here’s one bit: In 2018, when writing about whether the U.S. was ready for the next pandemic, I [Yong] noted that the country was trapped in a cycle of panic and neglect. It rises to meet each new disease, […]

“The Evidence and Tradeoffs for a ‘Stay-at-Home’ Pandemic Response: A multidisciplinary review examining the medical, psychological, economic and political impact of ‘Stay-at-Home’ implementation in America”

Will Marble writes: I’m a Ph.D. student in political science at Stanford. Along with colleagues from the Stanford medical school, law school, and elsewhere, we recently completed a white paper evaluating the evidence for and tradeoffs involved with shelter-in-place policies. To our knowledge, our paper contains the widest review of the relevant covid-19 research. It […]

I’m frustrated by the politicization of the coronavirus discussion. Here’s an example:

Flavio Bartmann writes: Over the last few days, as COVID-19 posed some serious issues for policy makers who, both in the US and elsewhere, have employed statistical models to develop mitigation strategies, a number of non-statisticians have criticized the use of such models as useless or worse. A typical example is this article by Victor […]

“America is used to blaming individuals for systemic problems. Let’s try to avoid that this time.”

I like this news article by Aviva Shen: In normal times, policing has been America’s primary response to a host of societal ills that cannot be solved by punishment. Homelessness, mental illness, violence, racism, poverty, and toxic masculinity are all fed through the criminal justice system, rather than getting addressed in any meaningful way, never […]

Big trouble coming with the 2020 Census

OK, first things first. For readers of this blog who live in the United States: Don’t forget to fill out your census. They’re doing in online, and you should’ve received a letter in the mail last month telling you how to do it. And now the news. Dr. Z points us to this post by […]

Conference on Mister P online tomorrow and Saturday, 3-4 Apr 2020

We have a conference on multilevel regression and poststratification (MRP) this Friday and Saturday, organized by Lauren Kennedy, Yajuan Si, and me. The conference was originally scheduled to be at Columbia but now it is online. Here is the information. If you want to join the conference, you must register for it ahead of time; […]

“How to be Curious Instead of Contrarian About COVID-19: Eight Data Science Lessons From Coronavirus Perspective”

Rex Douglass writes: I direct the Machine Learning for Social Science Lab at the Center for Peace and Security Studies, UCSD. I’ve been struggling with how non-epidemiologists should contribute to COVID-19 questions right now, and I wrote a short piece that summarizes my thoughts. 8 data science suggestions For people who want to use theories […]

Breaking the feedback loop: When people don’t correct their errors

OK, so here’s the pattern: 1. Someone makes a public statement with an error, an error that advances some political or personal agenda. 2. Some other people point out the error. 3. The original author refuses to apologize, or correct the error, or thank people for pointing out the error, and sometimes they don’t even […]

“Older Americans are more worried about coronavirus — unless they’re Republican”

Philip Greengard points us to the above-titled news article by Philip Bump. The article was just fine, a reminder of modern-day political polarization. The only thing that bothered me were the graphs. I redrew them above. Here were the original versions: I see a few problems with these graphs. First, the information is duplicated because […]

100 Things to Know, from Lane Kenworthy

The sociologist has this great post: Here are a hundred things worth knowing about our world and about the United States. Because a picture is worth quite a few words and providing information in graphical form reduces misperceptions, I [Kenworthy] present each of them via a chart, with some accompanying text. This is great stuff. […]

Bernie electability update

The other day we discussed an article, “New research suggests Sanders would drive swing voters to Trump — and need a youth turnout miracle to compensate,” by David Broockman and Joshua Kalla. A commenter pointed us to a post by Seth Ackerman, “Study Showing Bernie Needs Huge Youth Turnout Is Nonsense,” which states: In the […]

So . . . what about that claim that probabilistic election forecasts depress voter turnout?

A colleague pointed me to this article by Sean Westwood, Solomon Messing, and Yphtach Lelkes, “Projecting confidence: How the probabilistic horse race confuses and demobilizes the public,” which begins: Recent years have seen a dramatic change in horserace coverage of elections in the U.S.—shifting focus from late-breaking poll numbers to sophisticated meta-analytic forecasts that emphasize […]

The Great Society, Reagan’s revolution, and generations of presidential voting

> Continuing our walk through the unpublished papers list: This one’s with Yair and Jonathan: We build a model of American presidential voting in which the cumulative impression left by political events determines the preferences of voters. This impression varies by voter, depending on their age at the time the events took place. We find […]

“New research suggests Sanders would drive swing voters to Trump — and need a youth turnout miracle to compensate.”

Political scientists David Broockman and Joshua Kalla write: Decades of evidence from academic studies suggests that more moderate nominees tend to perform better in general elections than more ideologically extreme nominees. For example, [political scientist Alan Abramowitz found that] Democratic US House candidates who supported Medicare-for-all fared approximately 2.2 percentage points worse [on average] in […]

What up with red state blue state?

Jordan Ellenberg writes: I learned from your book that Democrats doing better in richer counties and Republicans doing better in poorer counties did not imply that richer people were more likely to vote for Democrats and that in fact, the opposite is true. I do wonder, though, to what extent that’s changing with the current […]

Is it really true that candidates who are perceived as ideologically extreme do even worse if “they actually pose as more radical than they really are”?

Most of Kruggy’s column today is about macroeconomics, a topic I’m pretty much ignorant of. But I noticed one political science claim: It’s easy to make the political case that Democrats should nominate a centrist, rather than someone from the party’s left wing. Candidates who are perceived as ideologically extreme usually pay an electoral penalty; […]

MRP Conference at Columbia April 3rd – April 4th 2020

The Departments of Statistics and Political Science and Institute for Social and Economic Research and Policy at Columbia University are delighted to invite you to our Spring conference on Multilevel Regression and Poststratification. Featuring Andrew Gelman, Beth Tipton, Jon Zelner, Shira Mitchell, Qixuan Chen and Leontine Alkema, the conference will combine a mix of cutting […]