TY  - RPRT
        AU  - Tommasi, Denni
AU  - Zhang, Lina
        TI  - Bounding Program Benefits When Participation Is Misreported
        PY  - 2020/Jun/
        PB  - Institute of Labor Economics (IZA)
        CY  - Bonn
        T2  - IZA Discussion Paper
        IS  - 13430
        UR  - https://www.iza.org/publications/dp13430
        AB  - 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.
        KW  - heterogenous treatment effects
KW  - causality
KW  - binary treatment
KW  - endogenous measurement error
KW  - discrete or multiple instruments
KW  - weighted average of LATEs
KW  - endogeneity
KW  - program evaluation
        ER  -