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Introduction to Regression Discontinuity 

Michael Toland
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On October 2, 2017, Dr. Joe Wadding presented this 50-minute talk at the University of Kentucky on Regression Discontinuity, the first presentation in the Fall 2017 Applied Quantitative and Psychometric Series (AQPS). This presentation focused on the theory, design, and implementation of regression discontinuity (RDD). RDD is one of the most powerful tools in the suite of quasi-experimental methods used to capture causal effects of programs and policies. During the presentation, he discussed and worked through a relevant example using data/syntax/output in STATA of the implementation of RDD in the education literature from the following paper: Angrist, J. & Lavy, V. (1999). Using Maimonides’ Rule to estimate the effect of class size on scholastic achievement. The Quarterly Journal of Economics, 114(2), 533-575. Visit education.uky.edu/edp/apslab/... to download the Handout and Stata Files for this talk.

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4 окт 2017

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Комментарии : 7   
@flavianepomuceno7465
@flavianepomuceno7465 3 года назад
That was a wonderful complement to Angrist's reading. Thank you for the lecture and for making the Stata files available. You were of much help!
@sophiej4605
@sophiej4605 3 года назад
Great explanation!
@everetthayes5851
@everetthayes5851 4 года назад
Awesome stuff!
@corinaniculaescu8659
@corinaniculaescu8659 3 года назад
Great lecture thank you very much! I have a question about the Stata code. I downloaded it, and tried it out, but I can't seem to get the red line in the graphs at the cutoff point. How do you code that? Many thanks!
@franksantos7890
@franksantos7890 3 года назад
is there a way to get the dofile? (please); it was a good presentation but I need to learn more how to do it in STATA
@johsenfirgunsen8571
@johsenfirgunsen8571 4 года назад
is this a Sharp Rdd Model?
@pragjn
@pragjn 5 лет назад
Hi. Thank you for this video. I have to apply RDD in a real life problem and I am not able to understand how to do it. Our intervention is a training program at district level which will help correct and more identification of a particular disease. This disease is defined by a value which is less than a particular no. Now my intervention will focus only on those individuals in the city who have value below that no and above that no will become our control. We will collect data on both baseline and endline for all invididuals in the district. I just know what my cut off point is. Rest is unclear.
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