Doctoral Dissertation Research: Identifying Individuals' Causal Effects (Peer Effects) on Participation in Collective Action

摘要：集体行动或合作行为是经济学和政治学中的一个核心概念。尽管具有这种重要性，但关于个人如何促使他人参与合作企业的证据相对较少。这项研究分析了手机数据：发送/接收短信和电话的时间和地点。分析告诉我们，个体是如何促使同伴加入集体行动的；这如何鼓励更广泛的合作行为；以及这些过程与非集体行动领域的过程有何不同。此外，这项研究还将这一领域引入了手机元数据领域，这是一个非常丰富的数据源，可以帮助我们深入了解一系列政治和社会行为。特别是，它有助于研究技术驱动的通信如何影响经济和政治行为，并将研究置于美国国家科学基金会的十大思想之一，研究人类技术前沿的工作。技术摘要：在本提案中，PI试图调查导致成功集体行动的因果机制。著名的集体行动理论认为，个人选择参与集体行动是基于两组因素：他们自己的偏好和机会成本（独立于他们的同伴）和/或对有多少人会参与的估计，这只受到同伴决策的轻微影响。这些方法与行为经济学中越来越多的实证文献相矛盾，这些文献发现强有力的证据表明，在许多其他非集体行动领域，个人决定了他们的直接同伴的经济选择。PI在两个重要领域为这一研究领域做出了贡献。首先，本项目拟对个体如何引导他人参与集体行动进行大规模实证研究。其次，研究将展示个人层面的影响如何通过沟通网络传播，表现在广泛的行为中。本文对几个国家/地区的匿名手机元数据进行了分析。这些数据记录了个人在集体行动之前和期间与其他个人的通信，以及他们的地理移动（即呼叫/短信发送者，接收者，时间戳和位置）。利用这些数据，PI利用一系列自然实验来评估：(1)个体对其同伴参与集体行动的因果影响；(2)这些个别的因果效应如何聚合成集体行动；(3)这些因果过程在个体之间有何不同？对同龄人的因果影响？非集体行动领域的经济决策。

General Abstract: Collective action, or cooperative behavior, is a central concept in economics and political science. Despite this significance, there is relatively little evidence regarding how individuals cause others to participate in cooperative ventures. This study analyzes cell phone data: the time and location of sent/received text messages and calls. The analysis tells us how individuals cause their peers to join in collective action; how this might encourage broader cooperative behavior; and how these processes differ from that of non-collective action areas. Additionally, this research introduces the field to cell phone metadata -- an exceptionally rich data source that can help provide insight into a range of political and social behavior. In particular, it contributes to studies of how technologically-enabled communication affects economic and political behaviors, and situates the research within one of the NSF's Ten Big Ideas, studying work at the Human-Technology Frontier. Technical Abstract:In this proposal, the PI seeks to investigate the causal mechanisms that lead to successful collective action. Prominent theories of collective action argue that individuals choose to participate in an instance of collective action based on two sets of factors: their own preferences and opportunity costs (independent from their peers) and/or on estimates of how many other people will participate, which is only marginally affected by peers' decisions. These approaches are contradicted by a growing empirical literature in behavioral economics, which finds strong evidence that individuals determine their immediate peers' economic choices in many other non-collective action domains. The PI contributes to this line of research in two important areas. First, the project proposes to develop a large-scale empirical study of how individuals lead others to participate in collective action. Second, the research will show how individual-level effects spread through communication networks, manifesting in widespread behaviors. This dissertation takes analyzes several country-years of anonymized cell phone metadata. This data records individuals' communication with other individuals before and during instances of collective action as well as their geographic movement (i.e. call/SMS sender, recipient, timestamp, and location). Using this data, the PI exploits a series of natural experiments to assess (1) individuals' causal effects on their peers' participation in collective action; (2) how these individual causal effects aggregate into collective action; and (3) how these causal processes differ from individuals? causal effects on their peers? economic decisions in non-collective action domains.