Essays in econometrics and industrial organization
Abstract/Contents
- Abstract
- In my dissertation I study econometric methods of causal inference with a particular focus on the use of prediction methods developed by researchers in the fields of statistical learning, machine learning, and pattern recognition. I'm also interested in the application of these methods as well as the more traditional ones to answer relevant policy questions. Chapter 1 (joint with Guido Imbens) considers the synthetic control method developed by Abadie, Diamond, Gardeazabal, and Hainmueller in several influential papers. The method is designed for estimating the effect of a treatment, in the presence of a single treated unit and a number of control units, with pre-treatment outcomes observed for all units. The method constructs a set of weights such that selected covariates and pre-treatment outcomes of the treated unit are approximately matched by a weighted average of the control units (the synthetic control). The weights are restricted to be nonnegative and sum to one. These restrictions are important partly because they make it easier for the procedure to obtain unique weights even when the number of lagged outcomes is modest relative to the number of control units, a common setting in applications. In the chapter we propose a generalization of the synthetic control procedure that allows the weights to be negative, and their sum to differ from one, and that allows for a permanent additive difference between the treated unit and the controls, similar to the difference-in-difference procedures. The weights directly minimize the distance between the lagged outcomes for the treated and the control units, using elastic net regularization to deal with a potentially large number of possible control units. In Chapter 2 (joint with Ali Yurukoglu) we quantify how bargaining power derived from firm size affects the analysis of downstream mergers and the profitability of downstream entry in the multichannel television industry. We estimate an empirical model of the industry which features negotiations between the upstream content producers and the downstream distributors of varying size. We estimate that large distributors like Comcast are able to negotiate about 25% lower content fees than smaller downstream firms such as Cablevision. We evaluate the short-run welfare effects of several recently reviewed mergers taking into account the size effects in negotiations. We also assess the degree to which size based bargaining power creates contracts which are a barrier to entry for new distributors.
Description
| Type of resource | text |
|---|---|
| Form | electronic resource; remote; computer; online resource |
| Extent | 1 online resource. |
| Place | California |
| Place | [Stanford, California] |
| Publisher | [Stanford University] |
| Copyright date | 2018; ©2018 |
| Publication date | 2018; 2018 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Author | Doudchenko, Nikolay |
|---|---|
| Degree supervisor | Benkard, C. Lanier |
| Degree supervisor | Imbens, Guido |
| Thesis advisor | Benkard, C. Lanier |
| Thesis advisor | Imbens, Guido |
| Thesis advisor | Yurukoglu, Ali |
| Degree committee member | Yurukoglu, Ali |
| Associated with | Stanford University, Graduate School of Business. |
Subjects
| Genre | Theses |
|---|---|
| Genre | Text |
Bibliographic information
| Statement of responsibility | Nikolay Doudchenko. |
|---|---|
| Note | Submitted to the Graduate School of Business. |
| Thesis | Thesis Ph.D. Stanford University 2018. |
| Location | electronic resource |
Access conditions
- Copyright
- © 2018 by Nikolay Doudchenko
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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