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Heterogeneous treatment effects: instrumental variables without monotonicity?
[journal article]
Abstract "Imbens and Angrist (1994) were the first to exploit a monotonicity condition in order to identify a local average treatment effect parameter using instrumental variables. More recently, suggested estimation of a variety of treatment effect parameters using a local version of their approach. We inve... view more
"Imbens and Angrist (1994) were the first to exploit a monotonicity condition in order to identify a local average treatment effect parameter using instrumental variables. More recently, suggested estimation of a variety of treatment effect parameters using a local version of their approach. We investigate the sensitivity of respective estimates to random departures from monotonicity. Approximations to respective bias terms are derived. In an empirical application the bias is calculated and bias corrected estimates are obtained. The accuracy of the approximation is investigated in a Monte Carlo study." [author's abstract]... view less
Classification
Methods and Techniques of Data Collection and Data Analysis, Statistical Methods, Computer Methods
Free Keywords
Program evaluation; Heterogeneity; Identification; Dummy endogenous variable; Selection on unobservables; Instrumental variables; Monotonicity; Nonseparable index selection model
Document language
English
Publication Year
2009
Page/Pages
p. 99-116
Journal
Journal of Econometrics, 155 (2009) 2
DOI
https://doi.org/10.1016/j.jeconom.2009.08.006
Status
Postprint; peer reviewed
Licence
PEER Licence Agreement (applicable only to documents from PEER project)