Randomization as an Instrumental Variable: Notes
The Review of Economics and Statistics, 1996, vol. 78, issue 2, 336-41
This paper discusses how randomized social experiments operate as an instrumental variable. For two types of randomization schemes, the fundamental experimental estimation equations are derived from the principle that experiments equate bias in control and experimental samples. Using conventional econometric representations, I derive the orthogonality conditions for the fundamental estimation equations. Randomization is a multiple instrumental variable in the sense that one randomization defines the parameter of interest expressed as a function of multiple endogenous variables in the conventional usage of that term. It orthogonalizes the treatment variable simultaneously with respect to the other regressors in the model and the disturbance term for the conditional population. However, conventional 'structural' parameters are not in general identified by the two types of randomization schemes widely used in practice. Copyright 1996 by MIT Press.
References: Add references at CitEc
Citations: View citations in EconPapers (31) Track citations by RSS feed
Downloads: (external link)
http://links.jstor.org/sici?sici=0034-6535%2819960 ... 0.CO%3B2-V&origin=bc full text (application/pdf)
Access to full text is restricted to JSTOR subscribers. See http://www.jstor.org for details.
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:tpr:restat:v:78:y:1996:i:2:p:336-41
Ordering information: This journal article can be ordered from
https://mitpressjour ... rnal/?issn=0034-6535
Access Statistics for this article
The Review of Economics and Statistics is currently edited by Amitabh Chandra, Olivier Coibion, Bryan S. Graham, Shachar Kariv, Amit K. Khandelwal, Asim Ijaz Khwaja, Brigitte C. Madrian and Rohini Pande
More articles in The Review of Economics and Statistics from MIT Press
Bibliographic data for series maintained by Ann Olson ().