Late again, whithout Monotonicity
AbstractMonotonicity is not necessary for the Wald ratio to identify a Local Average Treatment Effect. Under random assignment and exclusion restriction, if for every value of potential outcomes there are more compliers than defiers, the Wald ratio identifies the average treatment effect within a subpopulation of compliers. I use a simple Roy selection model to show that this "less defiers than compliers" condition is substantially weaker than monotonicity. It has two implications which are testable from the data, and it is closely related to those testable implications. Similarly, the local monotonicity condition in Huber & Mellace (2012) is not necessary for their identification results to hold and can also be replaced by a substantially weaker condition
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Bibliographic InfoPaper provided by Centre de Recherche en Economie et Statistique in its series Working Papers with number 2012-12.
Date of creation: Jun 2012
Date of revision:
local average treatment effect; instrumental variable; monotonicity; local monotonicity; defiers;
Find related papers by JEL classification:
- C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
- C26 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Instrumental Variables (IV) Estimation
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