Strategic Sample Selection
What is the impact of sample selection on the inference payoff of an evaluator testing a simple hypothesis based on the outcome of a location experiment? We show that anticipated selection locally reduces noise dispersion and thus increases informativeness if and only if the noise distribution is double logconvex, as with normal noise. The results are applied to the analysis of strategic sample selection by a biased researcher and extended to the case of uncertain and unanticipated selection. Our theoretical analysis offers applied research a new angle on the problem of selection in empirical studies, by characterizing when selective assignment based on untreated outcomes benefits or hurts the evaluator.
If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
| Length: | |
| Date of creation: | Aug 2017 |
| Handle: | RePEc:cpr:ceprdp:12202 |
| Contact details of provider: | Postal: Centre for Economic Policy Research, 77 Bastwick Street, London EC1V 3PZ. Phone: 44 - 20 - 7183 8801 Fax: 44 - 20 - 7183 8820
|
| Order Information: | Email: |
No references listed on IDEAS
You can help add them by filling out this form.
This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.
When requesting a correction, please mention this item's handle: RePEc:cpr:ceprdp:12202. 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: ()
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.