Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/263643 
Year of Publication: 
2022
Series/Report no.: 
IZA Discussion Papers No. 15427
Publisher: 
Institute of Labor Economics (IZA), Bonn
Abstract: 
In cases of non-compliance with a prescribed treatment, estimates of causal effects typically rely on instrumental variables. However, when participation is also misreported, this approach can be severely biased. We provide an instrumental variable method that researchers can use to identify the true heterogeneous treatment effects in data that include both non-compliance and misclassification of treatment status. Our method can be used regardless of whether the treatment is misclassified because it is missing at random, missing not at random, or was generally mismeasured. We conclude with the use of a dedicated Stata command, ivreg2m, to assess the return on education in the United Kingdom.
Subjects: 
treatment effect
causality
non-differential misclassification
weighted average of LATEs
endogeneity
program evaluation
JEL: 
C14
C21
C26
C35
C51
Document Type: 
Working Paper

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