Collaborating with Data Aggregators and the Estimize.com Setting
本文为研究者提供与Estimize等在线平台合作生成新数据、开展实地实验的建议，分享成功与失败经验，并介绍平台数据集及如何利用其特点检验会计理论。
ABSTRACT Our paper aims to assist researchers interested in generating new data and conducting field experiments to devise strategies for collaborating with startups and online platforms such as Estimize.com (Estimize). Specifically, we provide advice on collaborating with data aggregators in general and share past experiences working with Estimize, an online platform that crowdsources forecasts of earnings, revenue, key performance indicators (KPIs), and economic indicators. We inform academics about the opportunities and challenges of collaborating with online platforms such as Estimize by documenting prior successful and unsuccessful collaboration attempts and by sharing Estimize’s responses to our questions regarding what they deem important for collaboration. We also present details on the unique archival datasets currently available through Estimize, discuss important events impacting the platform, explain potential ways to generate new data by collaborating with the platform, highlight how the setting’s distinguishing features can help test accounting theories, and discuss limitations. Data Availability: Data are available from the public and proprietary sources cited in the text. JEL Classifications: M40; B40; C81; C90; C93.