Heterogeneous agent modeling of the personal data economy

该奖项全部或部分由《2021年美国救援计划法案》（公法117-2）资助。该奖项是美国国家科学基金会社会、行为和经济科学博士后研究奖学金（SPRF）计划的一部分。SPRF计划的目标是为学术界、工业界或私营部门和政府的科学事业准备有前途的早期职业博士级科学家。SPRF奖励包括在知名科学家的赞助下进行为期两年的培训，并鼓励博士后进行独立研究。美国国家科学基金会寻求促进科学界各阶层的科学家，包括那些未被充分代表的群体的科学家，参与其研究项目和活动；博士后阶段被认为是实现这一目标的一个重要的专业发展阶段。每个博士后必须解决各自学科领域的重要科学问题。在纽约大学法学院Katherine Strandburg博士的赞助下，该博士后奖学金奖支持一位研究个人数据经济的异构代理建模的早期职业科学家。数字平台已经渗透到社会和经济生活的方方面面。这些服务收集的个人数据的经济通过信用评分机构和公司估值与金融系统交叉。它还通过其在营销中的作用与实体经济交叉。数据的价值和影响部分来自于它如何调解和连接不同的参与者。对这种数据经济进行适当监管是一项紧迫的政治问题。本研究解决了个人数据在社会背景、部门和平台之间流动时的宏观经济属性这一基本科学问题。这项工作将有助于隐私的一般经济理论以及计算经济学和金融学的方法。解决个人数据作为战略地位和可交易资产的混合角色的新建模技术将在开源软件研究工具包中传播。重要的结果将提交给联邦机构，为数字经济的监管提供建议。本研究应用并扩展了宏观经济学和金融研究中常用的异构智能体建模方法。异构智能体建模（HAM）包括理性智能体随机动态规划（SDP）和基于零智能体的模型（ABM）。数据经济案例激发了如何将SDP和ABM综合成一个支持内生信息流的框架的基础研究。个人数据经济中的异质行为者以不同程度的有限理性为特征，包括预测跨期选择后果的能力。它们的相互作用也可能导致未知或未经研究的涌现特性。通过对数据经济的特定方面的调查，例如它与信用体系、产品开发和数据中介治理的交叉点，这项工作将开发建模工具，将HAM与Pearlian因果关系理论、部分可观察马尔可夫决策过程以及Ostrom和Williamson的制度经济学的见解结合起来。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2). This award was provided as part of NSF's Social, Behavioral and Economic Sciences Postdoctoral Research Fellowships (SPRF) program. The goal of the SPRF program is to prepare promising, early career doctoral-level scientists for scientific careers in academia, industry or private sector, and government. SPRF awards involve two years of training under the sponsorship of established scientists and encourage Postdoctoral Fellows to perform independent research. NSF seeks to promote the participation of scientists from all segments of the scientific community, including those from underrepresented groups, in its research programs and activities; the postdoctoral period is considered to be an important level of professional development in attaining this goal. Each Postdoctoral Fellow must address important scientific questions that advance their respective disciplinary fields. Under the sponsorship of Dr. Katherine Strandburg at New York University School of Law, this postdoctoral fellowship award supports an early career scientist investigating heterogeneous agent modeling of the personal data economy. Digital platforms have come to mediate every aspect of social and economic life. The economy of personal data collected by these services intersects the financial system through credit scoring institutions and the valuations of companies. It also intersects the real economy through its role in marketing. Data’s value and impact come in part from how it mediates and connects heterogeneous actors. The proper regulation of this data economy is an urgent political matter. This research addresses the fundamental scientific question of the macroeconomic properties of personal data as it flows between social contexts, sectors, and platforms. The work will contribute to both a general economic theory of privacy as well as methods in computational economics and finance. New modeling techniques that address personal data’s hybrid role as strategic position and tradable asset will be disseminated in open source software research toolkits. Salient results will be presented to federal agencies to advise regulation of the digital economy.This research applies and extends heterogeneous agent modeling (HAM) methods used in macroeconomics and financial research. Heterogeneous agent modeling (HAM) includes both rational agent stochastic dynamic programming (SDP) and zero-intelligence agent based models (ABM). The data economy case motivates fundamental research about how to synthesize SDP and ABM into a framework that supports endogenous information flows. Heterogeneous actors in the economy of personal data are marked by different levels of bounded rationality, including the ability to foresee consequences of intertemporal choice. Their interactions may also result in unknown or uninvestigated emergent properties. Through the investigation of particular aspects of the data economy, such as its intersections with the credit system, product development, and data intermediary governance, this work will develop modeling tools that combine HAM with insights from Pearlian causality theory, Partially Observable Markov Decision Processes, and the institutional economics of Ostrom and Williamson.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.