Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/223872
Authors: 
Tommasi, Denni
Zhang, Lina
Year of Publication: 
2020
Series/Report no.: 
IZA Discussion Papers No. 13430
Abstract: 
In empirical research, measuring correctly the benefits of welfare interventions is incredibly relevant for policymakers as well as academic researchers. Unfortunately, the endogenous program participation is often misreported in survey data and standard instrumental variable techniques are not sufficient to point identify and consistently estimate the effects of interest. In this paper, we focus on the weighted average of local average treatment effects (LATE) and (i) derive a simple relationship between the causal and the identifiable parameter that can be recovered from the observed data, (ii) provide an instrumental variable method to partially identify the heterogeneous treatment effects, (iii) formalize a strategy to combine administrative data on the misclassification probabilities of treated individuals to further tighten the bounds. Finally, we use our method to reassess the benefits of participating to the 401(k) pension plan on savings.
Subjects: 
heterogenous treatment effects
causality
binary treatment
endogenous measurement error
discrete or multiple instruments
weighted average of LATEs
endogeneity
program evaluation
JEL: 
C14
C21
C26
C35
C51
Document Type: 
Working Paper

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