Please use this identifier to cite or link to this item: http://hdl.handle.net/2381/37057
Title: A Method for Measuring Treatment Effects on the Treated without Randomization
Authors: Swamy, P. A. V. B.
Hall, Stephen
Tavlas, G. S.
Chang, I. L.
Gibson, H. D.
Greene, W. H.
Mehta, J. S.
First Published: 25-Mar-2016
Publisher: MDPI
Citation: Econometrics, 2016, 4(2), 19
Abstract: This paper contributes to the literature on the estimation of causal effects by providing an analytical formula for individual specific treatment effects and an empirical methodology that allows us to estimate these effects. We derive the formula from a general model with minimal restrictions, unknown functional form and true unobserved variables such that it is a credible model of the underlying real world relationship. Subsequently, we manipulate the model in order to put it in an estimable form. In contrast to other empirical methodologies, which derive average treatment effects, we derive an analytical formula that provides estimates of the treatment effects on each treated individual. We also provide an empirical example that illustrates our methodology.
DOI Link: 10.3390/econometrics4020019
eISSN: 2225-1146
Links: http://www.mdpi.com/2225-1146/4/2/19
http://hdl.handle.net/2381/37057
Version: Publisher Version
Status: Peer-reviewed
Type: Journal Article
Rights: Copyright © 2016, The authors. This is an open-access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0/ ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Appears in Collections:Published Articles, Dept. of Economics

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