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Jahrbücher für Nationalökonomie und Statistik

Journal of Economics and Statistics

Editor-in-Chief: Winker, Peter

Ed. by Büttner, Thiess / Riphahn, Regina / Smolny, Werner / Wagner, Joachim

IMPACT FACTOR 2018: 0.200
5-year IMPACT FACTOR: 0.309

CiteScore 2018: 0.50

SCImago Journal Rank (SJR) 2018: 0.154
Source Normalized Impact per Paper (SNIP) 2018: 0.382

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Volume 238, Issue 3-4


OLS and 2SLS in Randomized and Conditionally Randomized Experiments

Jason Ansel / Han Hong / and Jessie Li
Published Online: 2018-07-03 | DOI: https://doi.org/10.1515/jbnst-2018-0016


We investigate estimation and inference of the (local) average treatment effect parameter when a binary instrumental variable is generated by a randomized or conditionally randomized experiment. Under i.i.d. sampling, we show that adding covariates and their interactions with the instrument will weakly improve estimation precision of the (local) average treatment effect, but the robust OLS (2SLS) standard errors will no longer be valid. We provide an analytic correction that is easy to implement and demonstrate through Monte Carlo simulations and an empirical application the interacted estimator’s efficiency gains over the unadjusted estimator and the uninteracted covariate adjusted estimator. We also generalize our results to covariate adaptive randomization where the treatment assignment is not i.i.d., thus extending the recent contributions of Bugni, F., I.A. Canay, A.M. Shaikh (2017a), Inference Under Covariate-Adaptive Randomization. Working Paper and Bugni, F., I.A. Canay, A.M. Shaikh (2017b), Inference Under Covariate-Adaptive Randomization with Multiple Treatments. Working Paper to allow for the case of non-compliance.

Keywords: big data; data science

JEL Classification: C1; C8; C9


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About the article

Received: 2017-02-22

Revised: 2018-01-08

Accepted: 2018-02-01

Published Online: 2018-07-03

Published in Print: 2018-07-26

Citation Information: Jahrbücher für Nationalökonomie und Statistik, Volume 238, Issue 3-4, Pages 243–293, ISSN (Online) 2366-049X, ISSN (Print) 0021-4027, DOI: https://doi.org/10.1515/jbnst-2018-0016.

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