Three essays in causal inference

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Abstract/Contents

Abstract
This thesis is a collection of three essays on causal inference. Chapter 1 considers the problem of constructing confidence intervals or bands for the quantiles of treatment effects under settings where point identification is impossible. I show that under settings where selection is only on observables bounds for the entire quantile function can nonetheless be estimated, and this enables the estimation of confidence bands. I also extend these results to instrumental variable settings. Computational complexity analysis demonstrates that the methodology I propse is computationally attractive. Chapters 2 and 3 consider extending the synthetic control approach of Abadie, Diamond, and Haimueller (2010) to two different settings where individual-level data is available. In Chapter 2 I consider estimating average treatment effects by constructing for every subject in the treatment group a synthetic twin composed of individuals in the control group. I show that the resulting estimator is unbiased when selection is dependent only on observables. I also show that matching estimators and OLS estimators can be viewed as special cases of synthetic control estimators. Furthermore, I demonstrate that the estimator is highly scalable computationally. In Chapter 3, I consider settings where either panel data or repeated cross-sectional data is available. I show that the synthetic control estimator in this setting can yield asymptotically valid standard errors when aggregation is done from individual-level data, unlike the original work of Abadie, Diamond, and Hainmueller (2010). To demonstrate asymptotic properties, two types of asymptotic analysis are carried out: one appropriate when the number of observations at each point in time in each subpopulation tends to infinity, and one suitable for stationary aggregate data and in which the number of pre-intervention periods gets large.

Description

Type of resource text
Form electronic; electronic resource; remote
Extent 1 online resource.
Publication date 2015
Issuance monographic
Language English

Creators/Contributors

Associated with Wong, Laurence
Associated with Stanford University, Department of Economics.
Primary advisor Hong, Han
Thesis advisor Hong, Han
Thesis advisor Imbens, Guido
Thesis advisor Wolak, Frank A
Advisor Imbens, Guido
Advisor Wolak, Frank A

Subjects

Genre Theses

Bibliographic information

Statement of responsibility Laurence Wong.
Note Submitted to the Department of Economics.
Thesis Thesis (Ph.D.)--Stanford University, 2015.
Location electronic resource

Access conditions

Copyright
© 2015 by Laurence Wong
License
This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).

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