discrete dependent variables
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2013 ◽  
Vol 103 (3) ◽  
pp. 557-562 ◽  
Author(s):  
Andrew Chesher ◽  
Adam M Rosen

We compare nonparametric instrumental variables (IV) models with linear models and 2SLS methods when dependent variables are discrete. A 2SLS method can deliver a consistent estimator of a Local Average Treatment Effect but is not informative about other treatment effect parameters. The IV models set identify a range of interesting structural and treatment effect parameters. We give set identification results for a counterfactual probability and an Average Treatment Effect in a IV binary threshold crossing model. We illustrate using data on female employment and family size (employed by Joshua Angrist and William Evans (1998)) and compare with their LATE estimates.


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