New Stata module for estimation and robust inference for quantile treatment effects (QTE) in regression discontinuity designs (RDD).

[Yuya Sasaki]

A new Stata module for estimation and robust inference for quantile treatment effects (QTE) in regression discontinuity designs (RDD) is now available in ssc, thanks to Kit Baum. The method is robust against large bandwidths and unknown functional forms. See https://sites.google.com/site/yuyasa...-command-rdqte for online resources. Thanks!

ssc install rdqte

[ericmelse]

Dear Yuya,

It would be helpful if you can include a brief example in the help file; in addition to the syntax explanation.

[Yuya Sasaki]

Dear Eric,

Thanks for your message. I will include a brief example and will let you know when the update occurs in SSC.

[Yuya Sasaki]

Dear Eric,

Thanks for your suggestion. I added the following example in the help file, an example that we actually implemented in our paper. I have not yet updated it on SSC, but I will do very soon, perhaps after finding another concrete example.

2. score scores on the Woodcock-Johnson sub-tests, treat an indicator for
participation in the pre-K program in the previous year, bdate birth
date - example drawn from Chiang, Hsu, and Sasaki (2019, Sec. 6).
Students with bdate >= 0 (location-normalized) are eligible for a
participation in the pre-K program. Participation in the program is
not sharp, and we therefore use a fuzzy RDD. Quantile treatment
effects of the program on scores on the Woodcock-Johnson sub-tests
are estimated with 90% uniform confidence bands by:

rdqte score bdate, fuzzy(treat) cover(0.9) ql(0.1) qh(0.9) qn(9)