其他
TOP5最新文靶向了中国AI公司, 使用三重差分DDD进行实证评估
凡是搞计量经济的,都关注这个号了
稿件:econometrics666@126.com
正文
关于下方文字内容,作者:翟大业,中国人民大学自然资源管理,通信邮箱:syzhaidaye@163.com
数据密集型创新与国家:来自中国AI公司的证据
Martin Beraja, David Y. Yang, Noam Yuchtman, 2022, Data-intensive Innovation and the State: Evidence from AI Firms in China, The Review of Economic Studies. 关于David Yang,参看:Acemoglu终于对中国学术界的问题下手了! 关于David Yang,其他三篇敏感性文章(建议在社群内部讨论), 1.Curriculum and Ideology(JPE), 2.Protests as Strategic Games: Experimental Evidence from Hong Kong's Anti-Authoritarian Movement(QJE), 3.The Impact of Media Censorship: 1984 or Brave New World? (AER) Developing AI technology requires data. In many domains, government data far exceeds in magnitude and scope data collected by the private sector, and AI firms often gain access to such data when providing services to the state. We argue that such access can stimulate commercial AI innovation in part because data and trained algorithms are shareable across government and commercial uses. We gather comprehensive information on firms and public security procurement contracts in China’s facial recognition AI industry. We quantify the data accessible through contracts by measuring public security agencies’ capacity to collect surveillance video. Using a triple-differences strategy, we find that data-rich contracts, compared to data-scarce ones, lead recipient firms to develop significantly and substantially more commercial AI software. Our analysis suggests a contribution of government data to the rise of China’s facial recognition AI firms, and that states’ data collection and provision policies could shape AI innovation.
解读完整版PDF
原文PDF
关于DID,参看:1.120篇DID双重差分方法的文章合集, 包括代码,程序及解读, 建议收藏!2.空间DID双重差分法运行和操作代码,3.AER未监测的污染, DID和事件研究法运用的典范(附代码),4.AER, 中国大运河上的叛乱: 262年间的证据, 运用DID, CIC, SCM等方法!5.封城的经济代价有多高? 宋铮等用交叠DID, 事件研究法, 结构估计, 引力模型测度,6.QJE: 离婚越容易, 女性生活越幸福!DID证实!
下面这些短链接文章属于合集,可以收藏起来阅读,不然以后都找不到了。
3.5年,计量经济圈近1000篇不重类计量文章,
可直接在公众号菜单栏搜索任何计量相关问题,
Econometrics Circle
数据系列:空间矩阵 | 工企数据 | PM2.5 | 市场化指数 | CO2数据 | 夜间灯光 | 官员方言 | 微观数据 | 内部数据计量系列:匹配方法 | 内生性 | 工具变量 | DID | 面板数据 | 常用TOOL | 中介调节 | 时间序列 | RDD断点 | 合成控制 | 200篇合辑 | 因果识别 | 社会网络 | 空间DID数据处理:Stata | R | Python | 缺失值 | CHIP/ CHNS/CHARLS/CFPS/CGSS等 |干货系列:能源环境 | 效率研究 | 空间计量 | 国际经贸 | 计量软件 | 商科研究 | 机器学习 | SSCI | CSSCI | SSCI查询 | 名家经验计量经济圈组织了一个计量社群,有如下特征:热情互助最多、前沿趋势最多、社科资料最多、社科数据最多、科研牛人最多、海外名校最多。因此,建议积极进取和有强烈研习激情的中青年学者到社群交流探讨,始终坚信优秀是通过感染优秀而互相成就彼此的。