Trump Archives - kai arzheimer

This morning, I came across ~~an outrageously funny~~ a moderately amusing video involving Shaggy’s early 2000s classic, some seriously revamped lyrics, and the man himself (btw, is this blond-hairing an act of cultural appropriation?). Cheap laughs, and the almost heart-warming idea that the FBI could end this, and everything would go back to normal. And yes, they manage to squeeze a lot of legalese into these lyrics.

Which then reminded me (yes, I’m old enough to remember both the outrage over Iraq and the euphoria of Blair coming to power in 1997) of a cartoon video featuring Tony Blair, Michael Howard, and other politicians of the day, happily dancing to the same song (“I was told that there were weapons hidden underneath the sand”). I tried to google it, but it is gone, a victim of the death of flash.

What is it about this song and wildly unpopular politicians? Is there something about this song that could be coaxed into a paper (“Pseudo-Rap as Liberalism. A Conceptual Sketch and Some Applications”)? Most certainly not, so let’s just post the latest video.

One of the best (and most depressing) articles on Trump I’ve read so far: “Inside Trump’s Hour-by-Hour Battle for Self-Preservation”
If you learnt R as a grad student and if that was some time ago (cough), here is help to get you started on the new ways of doing things in R
To further drive this home, here is a quick and only slightly dirty analysis of the Weinstein effect in newspaper reporting using tidytext
What remains of the traditional French centre-right after Macron is poaching on the Front National. Art Goldhammer nails it.
Meanwhile, the Front National is once more in hot water over the misuse of EU funds.

Does the European Radical Right present a united front vis-a-vis the European Union, and is there a Trump effect that could further the cause of the Radical Right in Europe? I don’t think so (and here is an automated English translation).

UE debaixo de fogo dentro de casa no ano do ″vai ou racha″

São cada vez mais os dirigentes políticos que lutam contra a União Europeia e os partidos anti-integração estão cada vez mais fortes nas sondagens

The one and only Philip Schrodt has written what I think is the perfect seven-take-home-messages rant on that election and it’s likely outcomes. Skip all the self-flagellation/yes-but posts and read this instead:

Seven Observations on the 2016 Election

On my day-pack I’ve got a little enamelled pin I bought several years back in a small shop in Juneau run by a guy who has, well, opinions. It shows a typewriter with the words “Write ha…

asecondmouse

Then again, there is one thing that does not get enough coverage in there, and that is the whole polling/prediction disaster. So you should read this, too:

Election surprise, and Three ways of thinking about probability - Statistical Modeling, Causal Inference, and Social Science

Background: Hillary Clinton was given a 65% or 80% or 90% chance of winning the electoral college. She lost. Naive view: The poll-based models and the prediction markets said Clinton would win, and she lost. The models are wrong! Slightly sophisticated view: The predictions were probabilistic. 1-in-3 events happen a third of the time. 1-in-10 …

Statistical Modeling, Causal Inference, and Social Science

There. Your Sunday sorted out.

Primary Model Predicts Trump Victory | PS: Political Science & Politics | Cambridge Core

Primary Model Predicts Trump Victory - Volume 49 Special Issue - Helmut Norpoth

Cambridge Core

I’m not a huge fan of predictive Social Science. People are not the weather; they are bound to react to our predictions, which may become self-defeating or self-fulfilling in the process. Either scenario is unpleasant for obvious reasons. Predictive models are often subject to herd behaviour. They rarely rely on first principles, which makes them rather less interesting in terms of understanding the underlying dynamics, and may therefore fail rather spectacularly if the underlying, often implicit assumptions fail. This, in turn, tends to leave us with egg on our collective face.

Having said that, and looking at the rather spectacular result of the US presidential election, it’s difficult not to be impressed by Helmut Norpoth’s “Primary Model”, which predicted a solid Trump victory back in March. The Primary Model relies on very little data, has a relatively long lead (time from prediction to event), and a good track record: It has correctly identified the winner ever since it was introduced in 1996. Whether that makes HN a happy man today is a different matter.

The Primary Model’s rather quaint website is here; the link above points to a more accessible contribution by Norpoth to the PS symposium on forecasting the 2016 election. Which brings us back to the collective egg/face problem.

Update

I wrote the original post in the early hours of November 9, when it was clear that Trump had a majority in the Electoral College. Since then, it has become clear that Clinton has won the popular vote, probably by a considerable margin. Because (as a couple of people have noted on Twitter) the Primary Model aims at predicting the popular vote, even Political Science’s consolation prize is gone.

@carlberning @kai_arzheimer isn't the model about the popular vote? And if I recall correctly, Clinton might win the popular vote. #usdesaster2016
— Daniel Schultz (@thediceareright) November 9, 2016

Not exactly: Norpoth's model predicted Trump would win *the popular vote*. https://t.co/uJkjvx2f0n
— Frederik Hjorth (@fghjorth) November 13, 2016

kai arzheimer

Trump, Blair, Shaggy: It wasn’t me

Trump, R, and the French right: five links I liked

Interview with Diário de Notícias on the Nationalist International (or not)

All the Political Science wisdom on the Trump victory /presidency in one single blog post. Or two, perhaps

Gespräch mit dem Handelsblatt: Was Trumps Sieg für die AfD bedeutet

In March 2016, Helmut Norpoth predicted a Trump victory

Namechecked by the Huffington Post