People Power or a One-Shot Deal? A Dynamic Model of Protest
People Power or a One-Shot Deal? A Dynamic Model of Protest
复制标题
人民力量还是一锤定音？
DOI：
10.1111/ajps.12017
复制
发表时间：
2013
影响因子：
4.2
通讯作者：
Joshua A. Tucker
中科院分区：
文献类型：
--
作者：
Adam Meirowitz;Joshua A. Tucker
在阿拉伯之春之后，一个关键的问题是，民众抗议现在是否可能成为中东政治的一个永久性部分，或者过去两年发生的抗议活动更有可能是“一次性交易”。我们从理论的角度考虑这个问题，重点是一个时期的抗议活动的后果与未来抗议活动的动机之间的关系。该模型提供了许多预测，解释为什么我们可能会观察到一种我们称为“一次性交易”的现象：抗议活动一次性发生，但不会在未来发生，尽管其间出现了一段糟糕的治理时期。分析的重点是公民的学习过程。我们认为，公民可能不仅是在发现他们的新政府的类型或质量--正如大多数以前的逆向选择模型所假设的那样--而且公民可能还在了解他们国家潜在政府的宇宙。通过这种方式，一个政府的糟糕表现引发了对可能的继任者的一些悲观情绪。这种建模方法以两种方式扩展了关于选举中逆向选择的正式文献：它认真考虑了罢免政府可能代价高昂的事实，并探索了允许公民/委托人面对潜在分布的不确定性的相关性，可能的政府/代理人类型就是从这些分布中提取的。
In the aftermath of the Arab Spring, a crucial question is whether popular protest is now likely to be a permanent part of Middle Eastern politics or if the protests that have taken place over the past two years are more likely to be a “one-shot deal.” We consider this question from a theoretical perspective, focusing on the relationship between the consequences of protests in one period and the incentives to protest in the future. The model provides numerous predictions for why we might observe a phenomenon that we call the “one-shot deal”: when protest occurs at one time but not in the future despite an intervening period of bad governance. The analysis focuses on the learning process of citizens. We suggest that citizens may not only be discovering the type or quality of their new government—as most previous models of adverse selection assume—but rather citizens may also be learning about the universe of potential governments in their country. In this way, bad performance by one government induces some pessimism about possible replacements. This modeling approach expands the formal literature on adverse selection in elections in two ways: it takes seriously the fact that removing governments can be costly, and it explores the relevance of allowing the citizen/principal to face uncertainty about the underlying distribution from which possible government/agent types are drawn.