Hi,
I am using a Regression Discontinuity Designs and Austin Nichols's rd command to estimate the effect of some outcome y on a treatment D, which is defined by a cutoff point c in some continuous variable x. My outcome variable y is binary. This is a pretty common situation for RDD. E.g. the classical incumbency advantage example often uses "winning in the next election" as one of the outcome variables (e.g. Lee and Lemieux 2010).
Here is my question: I never read something about linear vs. logistic regression in the RDD literature (or the distribution of the outcome variable in general). Linear (or polynomial) local regressions are commonly used such as `lpoly` in the rd package. Why not some local logistic regression?
Thanks!
Lee, David S., and Thomas Lemieux. 2010. “Regression Discontinuity Designs in Economics.” Journal of Economic Literature 48:281–355.
rd package
http://ideas.repec.org/c/boc/bocode/s456888.html
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