A Simple and Successul Method to Shrink the Weight
We propose a simple way to improve the efficiency of the average treatment effect on propensity score based estimators. As the weights become arbitrarily large for the propensity scores being close to one or zero, we propose to shrink the propensity scores away from these boundaries. Using a comprehensive Monte Carlo study we show that this simple method substantially reduces the mean squared error of the estimators in finite samples.
|Date of creation:||23 Mar 2013|
|Contact details of provider:|| Postal: D-78457 Konstanz|
Web page: https://www.wiwi.uni-konstanz.de/en
More information through EDIRC
|Order Information:||Web: https://www.wiwi.uni-konstanz.de/en|
When requesting a correction, please mention this item's handle: RePEc:knz:dpteco:1305. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Office Ursprung)
If references are entirely missing, you can add them using this form.