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Essays on Economic Design: Theory and Estimation
Essays on Economic Design: Theory and Estimation
상세정보
- 자료유형
- 학위논문 서양
- 최종처리일시
- 20260202104815
- ISBN
- 9798265408419
- DDC
- 658.816
- 서명/저자
- Essays on Economic Design: Theory and Estimation
- 발행사항
- [Sl] : Harvard University, 2025
- 발행사항
- Ann Arbor : ProQuest Dissertations & Theses, 2025
- 형태사항
- 151 p
- 주기사항
- Source: Dissertations Abstracts International, Volume: 87-05, Section: A.
- 주기사항
- Advisor: Pakes, Ariel.
- 학위논문주기
- Thesis (Ph.D.)--Harvard University, 2025.
- 초록/해제
- 요약This thesis studies optimal economic design choices, both theoretically and empirically, in environments where some market participants themselves make welfare-relevant design choices. In the first two chapters, I study a platform's preferencing mechanism, or rule that assigns the placement of offers on a platform. I theoretically derive a platform's consumer-optimal preferencing rule in a setting in which firms choose prices in a locally envy-free profile, given the preferencing rule, which in special cases, correspond with equilibria in a Generalized Second Price auction. Additionally, I show that Reimers and Waldfogel (2023) empirical test to measure platform bias is valid even under prices endogenous to the preferencing rule in a locally envy-free profile. On Amazon, I measure the extent of platform bias using a large dataset from the platform during the years 2020-2022. I then extend this study to an environment in which firm prices are determined in a non-myopic, dynamic setting, which depends on the platform's preferencing rule. These dynamic pricing strategies result in pricing patterns that closely resemble Edgeworth cycles. I provide a method to estimate the primitives that govern these pricing cycles, which allows me to assess the counterfactual welfare implications associated with various preferencing rules, using a large dataset from the Amazon platform from 2018-2022. The welfare effects of policy proposals in this environment, in particular those that eliminate self-preferencing, significantly differ from those under the static price competition environment. The last chapter studies a class of complete information quantum games, where design choices in quantum versions of classical games, in particular the chosen basis and initial state, determine the set of feasible outcome distributions in a Nash equilibrium in quantum strategies. I derive necessary and sufficient conditions for a Nash equilibrium in quantum strategies to Pareto improve upon classical correlated equilibria in certain classes of quantum games.
- 키워드
- Quantum games
- 기타저자
- Harvard University Economics
- 기본자료저록
- Dissertations Abstracts International. 87-05A.
- 전자적 위치 및 접속
- 로그인 후 원문을 볼 수 있습니다.
MARC
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■007cr#unu||||||||
■020 ▼a9798265408419
■035 ▼a(MiAaPQ)AAI32168233
■040 ▼aMiAaPQ▼cMiAaPQ
■0820 ▼a658.816
■1001 ▼aHartzell, Olivia Reimann.
■24510▼aEssays on Economic Design: Theory and Estimation
■260 ▼a[Sl]▼bHarvard University▼c2025
■260 1▼aAnn Arbor▼bProQuest Dissertations & Theses▼c2025
■300 ▼a151 p
■500 ▼aSource: Dissertations Abstracts International, Volume: 87-05, Section: A.
■500 ▼aAdvisor: Pakes, Ariel.
■5021 ▼aThesis (Ph.D.)--Harvard University, 2025.
■520 ▼aThis thesis studies optimal economic design choices, both theoretically and empirically, in environments where some market participants themselves make welfare-relevant design choices. In the first two chapters, I study a platform's preferencing mechanism, or rule that assigns the placement of offers on a platform. I theoretically derive a platform's consumer-optimal preferencing rule in a setting in which firms choose prices in a locally envy-free profile, given the preferencing rule, which in special cases, correspond with equilibria in a Generalized Second Price auction. Additionally, I show that Reimers and Waldfogel (2023) empirical test to measure platform bias is valid even under prices endogenous to the preferencing rule in a locally envy-free profile. On Amazon, I measure the extent of platform bias using a large dataset from the platform during the years 2020-2022. I then extend this study to an environment in which firm prices are determined in a non-myopic, dynamic setting, which depends on the platform's preferencing rule. These dynamic pricing strategies result in pricing patterns that closely resemble Edgeworth cycles. I provide a method to estimate the primitives that govern these pricing cycles, which allows me to assess the counterfactual welfare implications associated with various preferencing rules, using a large dataset from the Amazon platform from 2018-2022. The welfare effects of policy proposals in this environment, in particular those that eliminate self-preferencing, significantly differ from those under the static price competition environment. The last chapter studies a class of complete information quantum games, where design choices in quantum versions of classical games, in particular the chosen basis and initial state, determine the set of feasible outcome distributions in a Nash equilibrium in quantum strategies. I derive necessary and sufficient conditions for a Nash equilibrium in quantum strategies to Pareto improve upon classical correlated equilibria in certain classes of quantum games.
■590 ▼aSchool code: 0084.
■653 ▼aPricing strategies
■653 ▼aQuantum games
■690 ▼a0501
■690 ▼a0511
■71020▼aHarvard University▼bEconomics.
■7730 ▼tDissertations Abstracts International▼g87-05A.
■790 ▼a0084
■791 ▼aPh.D.
■792 ▼a2025
■793 ▼aEnglish
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T17358962▼nKERIS▼z이 자료의 원문은 한국교육학술정보원에서 제공합니다.
