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Econ_Dissertation_20260206
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Dissertation
THREE ESSAYS ON EMPIRICAL INDUSTRIAL ORGANIZATION AND MACHINE LEARNING
Doctor of Philosophy (PhD), Washington State University
2025
Abstract
This dissertation focuses on two core economic challenges—global public health emergencies andthetransformationofthedigitaleconomy. Bydevelopingandapplyingstate-of-artcompu
tational economics and machine learning methods, it conducts an depth research into market
behavior, policy effectiveness, and mechanism design. The dissertation contains three inde
pendent studies in the fields of emiprical industrial orginazion and econometrics. First pa
per aims to analyze the impact of COVID-19 on airline industry and consumer behavior us
ing high-dimensional econometric techniques. Second paperevaluates the effectiveness of the
U.S. CARES Act on new business applications employing synthetic control method. Third pa
per proposes a machine learning-based approach to design adaptive auction mechanisms in
digital economy.
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Details
- Title
- THREE ESSAYS ON EMPIRICAL INDUSTRIAL ORGANIZATION AND MACHINE LEARNING
- Creators
- Mianfeng Liu
- Contributors
- Felix Munoz-Garcia (Advisor)Jia Yan (Advisor)Ron Mittelhammer (Committee Member)
- Awarding Institution
- Washington State University
- Academic Unit
- School of Economic Sciences
- Theses and Dissertations
- Doctor of Philosophy (PhD), Washington State University
- Number of pages
- 110
- Identifiers
- 99901357896801842
- Language
- English
- Resource Type
- Dissertation