【主题】Hidden Harmony
【报告人】俞宁（南京审计大学）
南京审计大学社会与经济研究院教授、执行院长
【时间】2021年4月14日（星期三）9:30
【地点】上海财经大学高等研究院楼232室
【摘要】It is difficult to reach a consensus on how to measure a social construct such as the harmony level of a group of people. To circumvent the difficulty, we develop “latent” binary quantile regression for settings in which the binary regressand is unobserved and proxied by multiple indicators (e.g., separate reports of whether a group is harmonious). We demonstrate how to identify and estimate parameters for conditional quantiles of the hidden outcome (e.g., group harmony level), prove the strong consistency of the estimator, and run Monte Carlo experiments to verify its finite-sample performance. Based on such a general-purpose method, we use high-quality survey data to uncover factors affecting the harmony levels within college dormitory rooms. The application is NASA-inspired: a scientific understanding of small group harmony improves the selection process for long-duration spaceflight crews. Among other findings, we discover that sleeping schedule discordance damages relationship.
嘉宾简介
俞宁，男，1984年生，福建霞浦人，国家重要人才计划青年学者、江苏省特聘教授、南京审计大学社会与经济研究院执行院长。上海交通大学管理学学士、硕士和博士；斯坦福大学经济学硕士、博士。曾担任埃默里大学助理教授等职务。在American Economic Review、Journal of Economic Theory、Journal of Econometrics等19种国际期刊上发表论文，为25种国际期刊担任匿名审稿人。获2020年中国信息经济学乌家培奖、江苏省哲学社会科学一等奖等。主持多项国家级科研项目；兼任中国信息经济学会学术委员会委员、理事。
