Research papers from policy school

Today I went digging through my hard drive for a research paper I wrote in policy school that used structural equations modeling to analyze the 2004 United States presidential election.  Sadly, it seems I lost the final version and only have a rough draft.  I did, however, find another research paper on population changes in Wayne and Oakland counties (roughly, Detroit and its wealthier suburbs.)


You might find it interesting if you like Detroit or pretty choropleths:choro

Some mixed, sort-of tooting my own horn: I independently discovered one of the most important urban trends in the United States – the dispersal of poor, urban blacks to inner ring suburbs, which in many ways laid the ground for the recent conflict in Ferguson.  Of course, by that time, the professionals had already discovered it.

I also found, in retrospect, absolutely no evidence for gentrification in Detroit from 1990-2000; at the time I worded my conclusion a bit more weakly, probably because no one I talked to wanted to hear this conclusion.  Fortunately, I’m coming to care less what others think in my old age.  Also in retrospect, the most likely cause of the changes I observed is the Third Great Migration.

I guess I’ll take a stab at explaining the lost structural equations modeling paper as well.

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Concentric circles of free speech, via Colin Kaepernick.

(copied from a months-old Facebook post)

1) If someone calls Colin Kaepernick unpatriotic for kneeling during the national anthem, there’s no free speech issue. It may be a violation of some other values – civil discourse, reasoned debate – but definitely not free speech. Of course, it’s a bit disingenuous of me to pick Kaepernick as an example, because this fallacy is currently far more common on the right – the Kaepernick incident is one of the few recent cases when I’ve seen columnists invoke it from the left.

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Sanders versus Clinton supporters in the American National Election Studies data

Were it not for Trump, the great drama of the 2016 election would have been the primary contest between Hillary Clinton and Bernie Sanders.  Sanders generally fit the mold of a “leftist protest candidate”, but was far more successful than previous such candidates have been.  In this post, I will examine the 2016 American National Election Studies data, hoping to find clues that explain why.

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Other people study Obama/Trump voters reports on several papers using data from the Voter Study Group, focusing on Obama/Trump voters – the same voters I analyzed in my series of posts.  (I’m also linking to the article because I take petty joy in being responsible for a correction in a published piece – the one from June 22nd was my catch.) They reach basically the same conclusions as I did: That Obama/Trump voters were ethnocentric but economically populist.

Jamelle Bouie, the author of the piece, raises a possibility that I did not mention in my posts: That Trump’s economically moderate campaign messages may have mattered almost as much as his ethnocentric messages on immigration and crime.  Given Trump’s governing record, he will be unable to re-run convincingly as an economic moderate in 2020, which may mean that the Democrats can win back some of these voters without changing their messaging in any way.

(It’s also possible that if Black Lives Matter protests become fewer or less visible by 2020, the racially-loaded politics of crime may seem less salient to these voters.)

Book Review – Dividing Lines: The Politics of Immigration Control in America

Dividing Lines would be a dry read if immigration control weren’t a hot issue now.  And hey, maybe it’s still dry to you, but I found it interesting.  It’s a blow-by-blow history of immigration policy in the United States since the founding, with special attention to the political coalitions that supported several very different policy regimes.
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Machine learning and racial bias

Warning: Second-order contrarianism.
You may remember this Propublica article from about a year ago, arguing that the COMPAS scores, a machine-learning algorithm that predicts risk of criminal recidivism, is racially biased.  Their methodology was a bit strange and they made their data available openly, so I had been intending to reanalyze using more straightforward methods.  Fortunately, several people have already done this, sparing me the effort; several of them found that according to commonly accepted standards, the COMPAS algorithm is not racially biased.  The Washington Post also published an article, saying the question is complicated. Continue reading

Obama/Trump voters in the National Election Studies data, Part 4


I conducted three analyses and found that:

  1. There were a surprisingly large number of Obama/Trump voters, and with some exceptions they matched the media portrait – white, working class, low income, older, and Midwestern.
  2. These voters probably chose Trump based on racially loaded policy issues; in particular, “law and order” issues related to fear of criminal violence.
  3.  These voters held economically populist views on a number of issues, even if those views did not drive their votes in the 2016 election.  However, their economic views on most issues were at least slightly to the right of the views of Obama/Clinton voters.

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