CCAP成立30周年系列活动——讲座预告 | 康奈尔大学 Chris Barrett 特聘教授学术报告

题   目:Harnessing High Frequency Data to Inform Development and Humanitarian Interventions

报告人:Chris Barrett 特聘教授(康奈尔大学

主持人:黄季焜 教授

时   间:2025年10月29日 星期三 15:30-17:00

报告地点:北京大学王克桢楼107会议室


报告人简介:

Chris Barrett is an agricultural and development economist at Cornell University. He is the Stephen B. and Janice G. Ashley Professor of Applied Economics and Management, and an International Professor of Agriculture at the Charles H. Dyson School of Applied Economics and Management, a Professor in the Jeb E. Brooks School of Public Policy, Faculty Director of the Cornell Collaboration on International Development Economics Research, and a Senior Faculty Fellow of the Cornell Atkinson Center for Sustainability. He is co-editor-in-chief of Food Policy, edits the Palgrave Macmillan book series Agricultural Economics and Food Policy, and serves on the Editorial Board of the Proceedings of the National Academy of Sciences. He is an elected Member of the National Academy of Sciences, and an elected Fellow of the American Association for the Advancement of Science, the Agricultural and Applied Economics Association, and the African Association of Agricultural Economists, and an Honorary Life Member of the International Association of Agricultural Economists.


报告内容:

Strengthening the resilience of vulnerable populations and of the natural systems that support their lives and livelihoods is central to ensuring both can withstand and recover from shocks and to sustainably improving human development. In a polycrisis era, the value of prompt – even anticipatory – response to shocks is increasingly important. The emergence of high frequency data from various sources (surveys, Earth observation, etc.) opens up new opportunities for early warning, for improved targeting and impact evaluation, and for anticipatory financing, as well as the opportunity to advance our understanding of sustainable development and humanitarian programming. This talk will discuss several use cases for high frequency data in improving development and humanitarian interventions.

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