Skip to main content
누빈트
에이전트
더 알아보기
요금제
회사 소개
KO
Home
논문 리뷰
Economics, Econometrics and Finance
Economics, Econometrics and Finance 논문 리뷰
Economics, Econometrics and Finance 분야 주요 연구 논문을 연구 동기·방법·결과로 구조화한 AI 논문 리뷰 목록입니다.
전체
Computer Science
Mathematics
Physics and Astronomy
Engineering
Materials Science
Chemistry
Chemical Engineering
Earth and Planetary Sciences
Environmental Science
Energy
Biochemistry, Genetics and Molecular Biology
Neuroscience
Immunology and Microbiology
Agricultural and Biological Sciences
Medicine
Pharmacology, Toxicology and Pharmaceutics
Health Professions
Economics, Econometrics and Finance
Business, Management and Accounting
Decision Sciences
Social Sciences
Psychology
Arts and Humanities
필터
4,392개의 결과
Linking Economic Complexity, Institutions and Income Inequality
Dominik Hartmann, Miguel Guevara 외 3명
RePEc: Research Papers in Economics
|
2015
|
4 회 인용
Liquidity Constraints and Demand for Healthcare: Evidence from Danish Welfare Recipients
Frederik Plesner Lyngse
arXiv (Cornell University)
|
2020
|
4 회 인용
Local martingale deflators for asset processes stopped at a default time $S^ au$ or right before $S^{ au-}$
Shiqi Song
arXiv (Cornell University)
|
2014
|
4 회 인용
Local search for stable marriage problems
Mirco Gelain, Maria Pini 외 3명
arXiv (Cornell University)
|
2010
|
4 회 인용
Local well-posedness for the great lake equation with transport noise
Dan Crisan, Oana Lang
arXiv (Cornell University)
|
2020
|
4 회 인용
Locality for singular stochastic PDEs
Ismaël Bailleul, Yvain Bruned
arXiv (Cornell University)
|
2021
|
4 회 인용
Localizing Volatilities
Marc Atlan
arXiv (Cornell University)
|
2006
|
4 회 인용
Locally Stable Matching with General Preferences
Martin Hoefer, Lisa Wagner
arXiv (Cornell University)
|
2012
|
4 회 인용
Long-term persistence and multifractality of river runoff records: Detrended fluctuation studies
Eva Koscielny–Bunde, Jan W. Kantelhardt 외 3명
ArXiv.org
|
2003
|
4 회 인용
Long Term Risk: A Martingale Approach
Likuan Qin, Vadim Linetsky
arXiv (Cornell University)
|
2014
|
4 회 인용
299
300
301
302
303
