摘要翻译：
知识生产存在正外部性还是负外部性？当前对知识生产的贡献是增加还是减少未来知识的增长？我们使用一个随机的现场实验，将相关内容添加到维基百科中的一些页面，同时保持相似页面不变。我们发现，内容的添加对随后的内容长期增长的影响微乎其微。我们的结果对信息种子和激励捐款有影响，这意味着额外的内容不会通过激励或阻止未来的捐款来产生相当大的外部性。
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英文标题：
《Externalities in Knowledge Production: Evidence from a Randomized Field
  Experiment》
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作者：
Marit Hinnosaar, Toomas Hinnosaar, Michael Kummer, Olga Slivko
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最新提交年份：
2019
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分类信息：

一级分类：Economics        经济学
二级分类：General Economics        一般经济学
分类描述：General methodological, applied, and empirical contributions to economics.
对经济学的一般方法、应用和经验贡献。
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一级分类：Computer Science        计算机科学
二级分类：Computers and Society        计算机与社会
分类描述：Covers impact of computers on society, computer ethics, information technology and public policy, legal aspects of computing, computers and education. Roughly includes material in ACM Subject Classes K.0, K.2, K.3, K.4, K.5, and K.7.
涵盖计算机对社会的影响、计算机伦理、信息技术和公共政策、计算机的法律方面、计算机和教育。大致包括ACM学科类K.0、K.2、K.3、K.4、K.5和K.7中的材料。
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一级分类：Computer Science        计算机科学
二级分类：Computer Science and Game Theory        计算机科学与博弈论
分类描述：Covers all theoretical and applied aspects at the intersection of computer science and game theory, including work in mechanism design, learning in games (which may overlap with Learning), foundations of agent modeling in games (which may overlap with Multiagent systems), coordination, specification and formal methods for non-cooperative computational environments. The area also deals with applications of game theory to areas such as electronic commerce.
涵盖计算机科学和博弈论交叉的所有理论和应用方面，包括机制设计的工作，游戏中的学习（可能与学习重叠），游戏中的agent建模的基础（可能与多agent系统重叠），非合作计算环境的协调、规范和形式化方法。该领域还涉及博弈论在电子商务等领域的应用。
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一级分类：Quantitative Finance        数量金融学
二级分类：Economics        经济学
分类描述：q-fin.EC is an alias for econ.GN. Economics, including micro and macro economics, international economics, theory of the firm, labor economics, and other economic topics outside finance
q-fin.ec是econ.gn的别名。经济学，包括微观和宏观经济学、国际经济学、企业理论、劳动经济学和其他金融以外的经济专题
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英文摘要：
  Are there positive or negative externalities in knowledge production? Do current contributions to knowledge production increase or decrease the future growth of knowledge? We use a randomized field experiment, which added relevant content to some pages in Wikipedia while leaving similar pages unchanged. We find that the addition of content has a negligible impact on the subsequent long-run growth of content. Our results have implications for information seeding and incentivizing contributions, implying that additional content does not generate sizable externalities by inspiring nor discouraging future contributions.
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PDF链接：
https://arxiv.org/pdf/1903.01861