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3 October 2008

Biden-Palin Linguistics

This post looks at the linguistics of last night's Biden-Palin debate. Palin used the word "reform" 12 times compared to Biden's none. Biden used "middle class" 12 times to Palin's one.

Here's a sequel to my earlier Obama-Clinton post. Overall,

Overall, Biden uttered 7,065 words and Palin 7,646, with a total of 2,117 unique words. Which words did Biden use significantly more or less than Palin? For each word, we apply a chi-squared test that the candidates spoke the word with equal probability. Finally, we sort the list by p-value, highlighting the differences. I've eliminated words that appear over 50 times (mostly stop words like "the," which Palin evidently used a couple hundred times more than Biden).

Observations:

• Look at all the connectors in the Palin column: "also," "just," "too." She uses these words to string together her thoughts.


• Biden's favored conjunctions are "number" -- from his several "number one, number two" formulations -- and "well."


• Two interesting ones are "policy" (Biden 22, Palin 4) and "reform" (Palin 12, Biden 0). These were certainly buzzwords from debate prep.

We can also look at bigrams, pairs of words, in a similar way.

• Biden used "United States" 16 times as opposed to Palin's 1.


• Like McCain, Palin only once used the term "middle class," compared to Biden's 12. To be fair, she made several allusions to the middle class without mentioning the word.
  
• Here's an interesting observation: Palin shares many of Obama's constructions; her favorite conjunctions are "and that's" and "and i."

Posted by Kevin Bartz at 11:38 AM

Regression Discontinuity Reversed

I recently came across a new paper by David Card, Alexandre Mas, and Jesse Rothstein entitled "Tipping and the Dynamics of Segregation." What's interesting from a methodological standpoint is that the authors use what may be called "inverted" regression discontinuity methods to test for race-based tipping in neighborhoods in American cities.

In a classic regression discontinuity design researchers commonly exploit the fact that treatment assignment changes discontinuously as a function of one or more underlying variables. For example scholarships may be assigned based on whether students exceed a test score threshold (like in the classic paper by Thistlethwaite and Campbell (1960)). Unlucky students who just miss the threshold are assumed to be virtually identical to lucky ones who score just above the cutoff value so that the threshold offers a clean identification of the counterfactual of interest (assuming no sorting).

In the Card et al. paper, the situation is slightly different because the authors have no hard-and-fast decision rule, but a theory that posits that whites' willingness to pay for homes depends on the neighborhood minority share and exhibits a tipping behavior. If the minority share exceeds a critical threshold, all the white households will leave. Since the location of the (city-specific) tipping point is unknown, the author's estimate it from the data and find that there are indeed significant discontinuities in the white population growth rate at the identified tipping points. Once the tipping point is located, they go on to examine whether rents or housing prices exhibit non-linearity around the tipping point but find no effects. They also try to explain the location of the tipping points by looking at survey data on racial attitudes of whites. Cities with more tolerant whites appear to have higher tipping points.

I think this is a very creative paper. The general approach could be useful in other contexts so take a look!

Posted by Jens Hainmueller at 8:10 AM