Essays in Pseudo-Bayesian Learning and Behavioral Macroeconomic Theory
Essays in Pseudo-Bayesian Learning and Behavioral Macroeconomic Theory
상세정보
- 자료유형
- 학위논문 서양
- 최종처리일시
- 20250211152832
- ISBN
- 9798346533443
- DDC
- 519.542
- 저자명
- Furst, Jacob H.
- 서명/저자
- Essays in Pseudo-Bayesian Learning and Behavioral Macroeconomic Theory
- 발행사항
- [Sl] : Harvard University, 2024
- 발행사항
- Ann Arbor : ProQuest Dissertations & Theses, 2024
- 형태사항
- 172 p
- 주기사항
- Source: Dissertations Abstracts International, Volume: 86-05, Section: A.
- 주기사항
- Advisor: Gabaix, Xavier.
- 학위논문주기
- Thesis (Ph.D.)--Harvard University, 2024.
- 초록/해제
- 요약The Kalman filter equations make clear that a realistic agent tracking a distant economic variable period by period (i.e. retaining beliefs but not past data) can neither fully consider nor intuitively update the exceedingly large number of conditional second moments required to continually revise her forecast with statistical accuracy. This dissertation leverages basic results in the behavioral literature to put forth a parameterized specification for behavioral belief evolution that yields sharp testable predictions while remaining consistent with current behavioral working knowledge. I ultimately find that predictable inertia in the mental updating of covariances between variables in a stochastic process can have significant effects on first order beliefs, or the forecasts made by economic agents. In particular, the tendency to pay less and less attention to the interaction between variables the farther apart they exist in a process causes agents to inflate their sensitivity to incoming data, resulting in excess volatility in the agent's forecast of future variables. In addition, variables irrelevant to a rational prediction can, under these behavioral conditions, obtain a non-zero response magnitude, which, while dissipating with distance from a rationally relevant realization, can significantly affect the agent's forecast if highly correlated with the target variable.
- 키워드
- Macroeconomics
- 기타저자
- Harvard University Business Economics
- 기본자료저록
- Dissertations Abstracts International. 86-05A.
- 전자적 위치 및 접속
- 로그인 후 원문을 볼 수 있습니다.
MARC
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■040 ▼aMiAaPQ▼cMiAaPQ
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■1001 ▼aFurst, Jacob H.▼0(orcid)0009-0006-6857-8409
■24510▼aEssays in Pseudo-Bayesian Learning and Behavioral Macroeconomic Theory
■260 ▼a[Sl]▼bHarvard University▼c2024
■260 1▼aAnn Arbor▼bProQuest Dissertations & Theses▼c2024
■300 ▼a172 p
■500 ▼aSource: Dissertations Abstracts International, Volume: 86-05, Section: A.
■500 ▼aAdvisor: Gabaix, Xavier.
■5021 ▼aThesis (Ph.D.)--Harvard University, 2024.
■520 ▼aThe Kalman filter equations make clear that a realistic agent tracking a distant economic variable period by period (i.e. retaining beliefs but not past data) can neither fully consider nor intuitively update the exceedingly large number of conditional second moments required to continually revise her forecast with statistical accuracy. This dissertation leverages basic results in the behavioral literature to put forth a parameterized specification for behavioral belief evolution that yields sharp testable predictions while remaining consistent with current behavioral working knowledge. I ultimately find that predictable inertia in the mental updating of covariances between variables in a stochastic process can have significant effects on first order beliefs, or the forecasts made by economic agents. In particular, the tendency to pay less and less attention to the interaction between variables the farther apart they exist in a process causes agents to inflate their sensitivity to incoming data, resulting in excess volatility in the agent's forecast of future variables. In addition, variables irrelevant to a rational prediction can, under these behavioral conditions, obtain a non-zero response magnitude, which, while dissipating with distance from a rationally relevant realization, can significantly affect the agent's forecast if highly correlated with the target variable.
■590 ▼aSchool code: 0084.
■653 ▼aBayesian learning
■653 ▼aBehavioral economics
■653 ▼aMacroeconomics
■690 ▼a0501
■690 ▼a0511
■71020▼aHarvard University▼bBusiness Economics.
■7730 ▼tDissertations Abstracts International▼g86-05A.
■790 ▼a0084
■791 ▼aPh.D.
■792 ▼a2024
■793 ▼aEnglish
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T17164101▼nKERIS▼z이 자료의 원문은 한국교육학술정보원에서 제공합니다.
