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Essays in FinTech and Macro-Finance
Essays in FinTech and Macro-Finance
상세정보
- 자료유형
- 학위논문 서양
- 최종처리일시
- 20250211151021
- ISBN
- 9798382730813
- DDC
- 658
- 저자명
- Wang, Chenyu.
- 서명/저자
- Essays in FinTech and Macro-Finance
- 발행사항
- [Sl] : Duke University, 2024
- 발행사항
- Ann Arbor : ProQuest Dissertations & Theses, 2024
- 형태사항
- 126 p
- 주기사항
- Source: Dissertations Abstracts International, Volume: 85-11, Section: A.
- 주기사항
- Advisor: Viswanathan, S.
- 학위논문주기
- Thesis (Ph.D.)--Duke University, 2024.
- 초록/해제
- 요약Data collection and analytics are the core of firms' development in digital economies and have an enormous impact on consumer welfare. We build a monopolistic competition model with heterogeneous firms to incorporate both data collection and analytics investment. The model studies how the complementary effect between data collection and analytics affects firms' pricing, profit and consumer welfare. Data is divided into two categories: raw data and effective data. Raw data is a byproduct of production and does not benefit firms on its own. Effective data is a signal on consumers' taste and must be produced with both analytics and raw data. We then find analytics can not only reduce firms' uncertainty but also lower user cost of capital and markup. Lower cost of data analytics can increase consumers' welfare by increasing competition. We allow firms to differ in the size of complementary effect. The model shows that cheaper analytics has asymmetric effects on heterogeneous firms' product quality and profit. Firms with strong complementary effects produce higher quality goods, charge lower price-per-utile and benefit from the cheaper analytics. The opposite is true for firms with weak complementary effects.In the second paper, We build a model to incorporate the buy-now-pay-later (BNPL) platform and study its welfare implication. BNPL platforms lend money to consumers, provide private data to partner firms and charge fee from in-platform merchants. Data can lower production cost. Two types of data are available: public data and private data. Data size of both types increases in the number of firms. Private data is only available for in-platform merchants. We find BNPL platforms can hurt non-platform users. The reason is that the platform fee can decrease the number of firms in the market and reduce public data, which increases out-of-platform firms' product prices. We then study a duopoly model with two platforms competing with each other. The model predicts that competition between platforms benefits non-platform users but can hurt platform users. The intuition is that competition splits the in-platform merchants and reduces private data for both platforms.
- 일반주제명
- Finance
- 키워드
- Data analytics
- 키워드
- Consumer welfare
- 키워드
- Quality goods
- 기타저자
- Duke University Business Administration
- 기본자료저록
- Dissertations Abstracts International. 85-11A.
- 전자적 위치 및 접속
- 로그인 후 원문을 볼 수 있습니다.
MARC
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■006m o d
■007cr#unu||||||||
■020 ▼a9798382730813
■035 ▼a(MiAaPQ)AAI30996544
■040 ▼aMiAaPQ▼cMiAaPQ
■0820 ▼a658
■1001 ▼aWang, Chenyu.
■24510▼aEssays in FinTech and Macro-Finance
■260 ▼a[Sl]▼bDuke University▼c2024
■260 1▼aAnn Arbor▼bProQuest Dissertations & Theses▼c2024
■300 ▼a126 p
■500 ▼aSource: Dissertations Abstracts International, Volume: 85-11, Section: A.
■500 ▼aAdvisor: Viswanathan, S.
■5021 ▼aThesis (Ph.D.)--Duke University, 2024.
■520 ▼aData collection and analytics are the core of firms' development in digital economies and have an enormous impact on consumer welfare. We build a monopolistic competition model with heterogeneous firms to incorporate both data collection and analytics investment. The model studies how the complementary effect between data collection and analytics affects firms' pricing, profit and consumer welfare. Data is divided into two categories: raw data and effective data. Raw data is a byproduct of production and does not benefit firms on its own. Effective data is a signal on consumers' taste and must be produced with both analytics and raw data. We then find analytics can not only reduce firms' uncertainty but also lower user cost of capital and markup. Lower cost of data analytics can increase consumers' welfare by increasing competition. We allow firms to differ in the size of complementary effect. The model shows that cheaper analytics has asymmetric effects on heterogeneous firms' product quality and profit. Firms with strong complementary effects produce higher quality goods, charge lower price-per-utile and benefit from the cheaper analytics. The opposite is true for firms with weak complementary effects.In the second paper, We build a model to incorporate the buy-now-pay-later (BNPL) platform and study its welfare implication. BNPL platforms lend money to consumers, provide private data to partner firms and charge fee from in-platform merchants. Data can lower production cost. Two types of data are available: public data and private data. Data size of both types increases in the number of firms. Private data is only available for in-platform merchants. We find BNPL platforms can hurt non-platform users. The reason is that the platform fee can decrease the number of firms in the market and reduce public data, which increases out-of-platform firms' product prices. We then study a duopoly model with two platforms competing with each other. The model predicts that competition between platforms benefits non-platform users but can hurt platform users. The intuition is that competition splits the in-platform merchants and reduces private data for both platforms.
■590 ▼aSchool code: 0066.
■650 4▼aFinance
■653 ▼aData analytics
■653 ▼aBuy-now-pay-later
■653 ▼aHeterogeneous firms
■653 ▼aConsumer welfare
■653 ▼aQuality goods
■690 ▼a0508
■690 ▼a0310
■690 ▼a0454
■690 ▼a0501
■71020▼aDuke University▼bBusiness Administration.
■7730 ▼tDissertations Abstracts International▼g85-11A.
■790 ▼a0066
■791 ▼aPh.D.
■792 ▼a2024
■793 ▼aEnglish
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T17160450▼nKERIS▼z이 자료의 원문은 한국교육학술정보원에서 제공합니다.
