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Essays on Economics and Algorithms
Essays on Economics and Algorithms
상세정보
- 자료유형
- 학위논문 서양
- 최종처리일시
- 20260202103523
- ISBN
- 9798315798057
- DDC
- 020
- 저자명
- Okumura, Kyohei.
- 서명/저자
- Essays on Economics and Algorithms
- 발행사항
- [Sl] : Northwestern University, 2025
- 발행사항
- Ann Arbor : ProQuest Dissertations & Theses, 2025
- 형태사항
- 250 p
- 주기사항
- Source: Dissertations Abstracts International, Volume: 86-12, Section: A.
- 주기사항
- Advisor: Strulovici, Bruno.
- 학위논문주기
- Thesis (Ph.D.)--Northwestern University, 2025.
- 초록/해제
- 요약This dissertation presents three independent essays in economic theory. Chapter 1 (with Eric Auerbach, Annie Liang, and Max Tabord-Meehan) develops an econometric framework for testing whether a given algorithm is improvable with respect to both accuracy and fairness. The proposed test is simple, broadly applicable, and accommodates a wide range of fairness and accuracy metrics. Chapter 2 (with Kei Ikegami, Atsushi Iwasaki, and Akira Matsushita) proposes a framework for evaluating policy interventions in matching markets with distributional disparities. Using only aggregate-level matching data, the framework enables the computation of welfare-maximizing taxation policies under regional constraints. Chapter 3 addresses the problem of online learning in potentially strategic environments. In light of impossibility results concerning no-external-regret algorithms, I propose alternative design goals and introduce algorithms that satisfy these new criteria.
- 일반주제명
- Information science
- 키워드
- Algorithms
- 키워드
- Accuracy metrics
- 키워드
- Online learning
- 기타저자
- Northwestern University Economics
- 기본자료저록
- Dissertations Abstracts International. 86-12A.
- 전자적 위치 및 접속
- 로그인 후 원문을 볼 수 있습니다.
MARC
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■00520260202103523
■006m o d
■007cr#unu||||||||
■020 ▼a9798315798057
■035 ▼a(MiAaPQ)AAI32039012
■040 ▼aMiAaPQ▼cMiAaPQ
■0820 ▼a020
■1001 ▼aOkumura, Kyohei.
■24510▼aEssays on Economics and Algorithms
■260 ▼a[Sl]▼bNorthwestern University▼c2025
■260 1▼aAnn Arbor▼bProQuest Dissertations & Theses▼c2025
■300 ▼a250 p
■500 ▼aSource: Dissertations Abstracts International, Volume: 86-12, Section: A.
■500 ▼aAdvisor: Strulovici, Bruno.
■5021 ▼aThesis (Ph.D.)--Northwestern University, 2025.
■520 ▼aThis dissertation presents three independent essays in economic theory. Chapter 1 (with Eric Auerbach, Annie Liang, and Max Tabord-Meehan) develops an econometric framework for testing whether a given algorithm is improvable with respect to both accuracy and fairness. The proposed test is simple, broadly applicable, and accommodates a wide range of fairness and accuracy metrics. Chapter 2 (with Kei Ikegami, Atsushi Iwasaki, and Akira Matsushita) proposes a framework for evaluating policy interventions in matching markets with distributional disparities. Using only aggregate-level matching data, the framework enables the computation of welfare-maximizing taxation policies under regional constraints. Chapter 3 addresses the problem of online learning in potentially strategic environments. In light of impossibility results concerning no-external-regret algorithms, I propose alternative design goals and introduce algorithms that satisfy these new criteria.
■590 ▼aSchool code: 0163.
■650 4▼aInformation science
■653 ▼aAlgorithms
■653 ▼aAccuracy metrics
■653 ▼aPolicy interventions
■653 ▼aOnline learning
■690 ▼a0501
■690 ▼a0723
■690 ▼a0509
■690 ▼a0511
■71020▼aNorthwestern University▼bEconomics.
■7730 ▼tDissertations Abstracts International▼g86-12A.
■790 ▼a0163
■791 ▼aPh.D.
■792 ▼a2025
■793 ▼aEnglish
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T17357518▼nKERIS▼z이 자료의 원문은 한국교육학술정보원에서 제공합니다.
