Bounds On Treatment Effects On Transitions
This paper considers the definition and identification of treatment effects on conditional transition probabilities. We show that even under sequential random assignment only the instantaneous average treatment effect is point identified. Because treated and control units drop out at different rates, randomization only ensures the comparability of treatment and controls at the time of randomization, so that long run average treatment effects are not point identified. Instead we derive informative bounds on these average treatment effects. Our bounds do not impose (semi)parametric restrictions, as e.g. proportional hazards, that would narrow the bounds or even allow for point identification. We also explore various assumptions such as monotone treatment response, common shocks and positively correlated outcomes.
|Date of creation:||18 Mar 2011|
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- Charles F. Manski & John V. Pepper, 1998.
"Monotone Instrumental Variables with an Application to the Returns to Schooling,"
NBER Technical Working Papers
0224, National Bureau of Economic Research, Inc.
- Charles F. Manski & John V. Pepper, 2000. "Monotone Instrumental Variables, with an Application to the Returns to Schooling," Econometrica, Econometric Society, vol. 68(4), pages 997-1012, July.
- Charles F. Manski & John V. Pepper, 1998. "Monotone Instrumental Variables: With an Application to the Returns to Schooling," Virginia Economics Online Papers 308, University of Virginia, Department of Economics.
- Ridder, G, 1986. "An Event History Approach to the Evaluation of Training, Recruitment and Employment Programmes," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 1(2), pages 109-26, April.
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