“Transparency for Authoritarian Stability: Open Government Information and Contention with Institutions in China” (under review) [SSRN]
It is widely agreed that concern for stability usually leads to the restriction of information in autocracies. However, many non-democratic countries have recently implemented open government information (OGI)—a type of policy transparency measures that allow citizens to identify illegal government behaviors that affect them. I argue, based on the Chinese example, that a regime can promote transparency to redirect popular discontent from the streets to institutional venues, such as the courts, for dispute resolution. Using survey experiments administered online and in the field with low-income rural people about OGI on land-taking compensation, I show that OGI increases citizens’ preference for legal and political institutions and makes them prioritize institutions over protest. Multiple findings suggest that this is because the evidence of local misbehavior increases their perceived fairness of institutions for dispute resolution. Moreover, province-level observational data shows that protest declines with better OGI performance. The study implies that an authoritarian regime can disclose certain negative information to maintain stability.
“Message or Messenger? Source and Labeling Effects in Authoritarian Response to Protest” (with Daniel Arnon and Pearce Edwards, revise and resubmit at Comparative Political Studies )
Authoritarian regimes in the 21st century have increasingly turned to using information control rather than kinetic force to respond to threats to their rule. This paper studies an often overlooked type of information control: strategic labeling and public statements by regime sources in response to protests. Labeling protesters as violent criminals may increase support for repression by signaling that protests are illegitimate and deviant. Regime sources, compared to more independent sources, could increase support for repression even more when paired with such an accusatory label. Accommodative labels should have opposing effects—decreasing support for repression. The argument is tested with a survey experiment in China which labels environmental protests. Accusatory labels increase support for repression of protests. Regime sources, meanwhile, have no advantage over nongovernmental sources in shifting opinion. The findings suggest that negative labels de-legitimize protesters and legitimize repression while the sources matter less in this contentious authoritarian context.
“Data Manipulation and Its Effect on Citizens’ Views: Evidence from A Survey Experiment in China” (with Jennifer Gandhi, under review)
Governments enact a broad array of policies that affect the economy, influencing citizens’ welfare. They also produce and disseminate information about these issues to citizens and, therefore, can lie through the provision of falsified data. We investigate how official growth statistics and the discovery of data manipulation influence citizens’ views of the economy and government through a survey experiment in China that employs a real case of data falsification by a local government. Despite shaping respondents’ beliefs about actual statistics, official statistics have no effect on their assessments of the economy or government. Yet the discovery of the manipulation of these figures reduces trust and satisfaction in government, especially among those in an economically precarious position. While authoritarian governments may falsify data in order to satisfy public opinion, the discovery of this manipulation, in fact, can undermine this endeavor.
“Disinformation and Censorship: Information Strategies of Government Control”
Authoritarian governments frequently use disinformation to persuade citizens of their performance in an attempt to gain public support. They can also impose censorship ex post for repressing skepticism to official news. But the relationship between censorship and disinformation is unclear. I intend to explore these questions by studying the relationship between disinformation and people’s possibility of knowing the truth outside of governmental broadcast. I employ a signaling model with some chance of “truth detection” by the population. The model shows that 1) when the prior belief does not favor the government, without censorship, citizens’ support for good news increases with the probability of truth detection, 2) censorship provides the bad government more control over truth detection probability but may decrease support when truth detection does not occur, it helps with the persuasion of disinformation in some cases but backfires in others, and 3) in most situations, disinformation and censorship substitute each other for the bad government, and the likelihoods of the two strategies decline with the increase of exogenous truth detection probability.
Selected Works in Progress
Monitoring and Manipulation: Authoritarian Transparency and Legal Resistance (Drafted)
Perceptions of Immigrants and Democratization (with Dongshu Liu and Ye Wang, Data Collection)
Political Effect of Economic Data Manipulation (Drafted)