Political Economy and Governance

A growing body of research on large language models (LLMs) has identified various biases, primarily in contexts where biases reflect societal patterns. This article focuses on a different source of bias in LLMs—government censorship. By comparing foundation models developed in China and those from outside China, we find substantially higher rates of refusal to respond, shorter responses, and inaccurate responses to a battery of 145 political questions in China-originating models. These disparities diminish for less-sensitive prompts, showing that technological and market differences cannot fully explain this divergence. While all models exhibit higher refusal to respond rates with Chinese-language prompts than English ones, language differences are less pronounced than disparities between China-originating and non-China-originating models. We caution that our study is observational and cross-sectional and does not establish a causal linkage between regulatory pressures and censorship behaviors of China-originating LLMs, but these results suggest that censorship through government regulation requiring companies to restrict political content may be an important factor contributing to political bias in LLMs.

Why do authoritarian regimes charge political opponents with nonpolitical crimes when they can levy charges directly related to opponents’ political activism? We argue that doing so disguises political repression and undermines the moral authority of opponents, minimizing backlash and mobilization. To test this argument, we conduct a survey experiment, which shows that disguised repression decreases perceptions of dissidents’ morality, decreases people’s willingness to engage in dissent on behalf of the dissident, and increases support for repression of the dissident. We then assess the external validity of the argument by analyzing millions of Chinese social media posts made before and after a large crackdown of vocal government critics in China in 2013. We find that individuals with larger online followings are more likely to be charged with nonpolitical crimes, and those charged with nonpolitical crimes are less likely to receive public sympathy and support.

This article studies whether pure legality, stripped of normative components that are central to the rule of law, can convey perceived legitimacy to governmental institutions and activity. Through a survey experiment conducted among urban Chinese residents, it examines whether such conveyance is possible under current sociopolitical conditions in which the party-state continues to invest in pure legality without imposing legal checks on the party leadership’s political power and without corresponding investment in substantive rights or freedoms. Among survey respondents, government investment in professional and consistent law enforcement conveys meaningful amounts of political legitimacy. In fact, it does so even when it supports government activity, such as censorship of online speech, that is freedom depriving and socially controversial and even when such investment does not necessarily enhance the external predictability of state behavior. However, the legitimacy-enhancing effects of pure legality are likely weaker than those of state investment in procedural justice.

The rise of social media in the digital era poses unprecedented challenges to authoritarian regimes that aim to influence public attitudes and behaviors. To address these challenges, we argue that authoritarian regimes have adopted a decentralized approach to produce and disseminate propaganda on social media. In this model, tens of thousands of government workers and insiders are mobilized to produce and disseminate propaganda, and content flows in a multidirectional, rather than a top-down manner. We empirically demonstrate the existence of this new model in China by creating a novel data set of over five million videos from over 18,000 regime-affiliated accounts on Douyin, a popular social media platform in China. This paper supplements prevailing understandings of propaganda by showing theoretically and empirically how digital technologies are transforming not only the content of propaganda, but also how propaganda materials are produced and disseminated.

China’s total fertility rate declined very little following implementation of the One Child Policy (OCP) in 1979/1980, but then fell sharply, by more than one-third, during the early 1990s. In this paper, we propose that strengthening bureaucratic incentives under the “One Vote Veto” (OVV) policy, which strictly prohibited career promotion for adherence failure, was necessary for more “effective” implementation of the OCP—and for its delayed impact on fertility. We use provincial variation in OVV implementation to estimate event study regression inputs needed to build actual and counterfactual sequential multi-decrement fertility life tables, finding that the policy explains 46% of China’s total fertility rate decline during the 1990s, driving it below replacement level. Use of intrauterine devices (IUDs, the most prevalent form of modern contraception in China) that was “recommended” by party officials increased by 133% under the policy, a relative increase more than four times as large as the increase in “voluntary” use. Overall, our paper suggests that population policy made a larger contribution to low fertility in China than suggested by past research. More generally, our paper highlights the central role of aligning bureaucratic incentives with public policy objectives, even in a centrally-planned economy like China’s.

Policy experiments are crucial for fostering innovation and mitigating risks and can serve as catalysts for transformative changes. This study investigates the governance of policy experiments in China, focusing on how political factors shape their outcomes. It emphasizes the need to consider concurrent trials—related policy trials implemented simultaneously in a locality that can influence outcomes—when selecting comparable cases for analysis. Such consideration is critical, especially when the policy issue spans multiple sectors and the level of difficulty differs across sectors. By comparing five cities engaged in the same three decarbonization pilots between 2010 and 2015, Hangzhou and Xiamen are identified to have had similar initial conditions and goals but achieved divergent outcomes. This research uncovers the critical role of political leadership in achieving varying levels of decarbonization progress and identifies policy coherence with broader local priorities to be the key explanation for continued leadership attention and efforts devoted to decarbonization despite turnover. The study contributes to the literature by addressing the under-studied impact of political factors and concurrent trials, offering a replicable procedure for future research and practical policy applications.

How do state-controlled broadcasters reach foreign publics to engage in public diplomacy in the era of social media? Previous research suggests that features unique to social media, such as the ability to engage in two-way communication with audiences, provide state-controlled broadcasters new opportunities for online public diplomacy. In this paper, we examine what strategies were used by four Chinese state-controlled media outlets on Twitter to reach foreign publics as the Chinese Communist Party worked to expand its public diplomacy and international media outreach efforts. We find that all outlets increased the volume and diversity of content while none engaged in interactive, two-way communication with audiences, and none appeared to artificially inflate their follower count. One outlet, China Global Television Network, made outsized gains in followership, and it differs from the other Chinese outlets in that it was rebranded, it disseminated a relatively lower share of government-mandated narratives pertaining to China, and the tone of its reporting was more negative. These results show that during a period when Chinese state-controlled broadcasters gained followers on Twitter, outlets made limited use of features unique to social media and instead primarily used social media as a broadcast channel.

We study the effect of a victimization narrative on national identity and public opinion in China experimentally. Previous research has suggested that governments can shape public opinion by guiding citizens’ collective memories of historical events, but few studies have established a clear causal link. By conducting an online survey experiment among 1890 urban Chinese citizens, we examine the causal impact of historical narratives on political attitudes. We find that, compared to control conditions, a narrative focusing on China’s humiliating past in the late Qing significantly reinforces respondents’ attachment to the victim side of the Chinese national identity, raises suspicion of the intention of foreign governments in international disputes, stimulates preference for more hawkish foreign policies, and strengthens support for China’s current political system. These effects are particularly strong among respondents without a college degree.

This paper empirically investigates the labor market effects of China’s 2007 VAT reform, which significantly reduced the tax cost of capital investment. Employing city-by-year variation in the reform, we demonstrate that the tax cuts increased the earnings of skilled workers and left the earnings of the unskilled workers unaffected. Moreover, we find limited impacts of the reform on employment for both skill groups. These results suggest that the tax incentives increased the relative demand for skills, thus resulting in a higher income inequality between skilled and unskilled workers.

Government censorship—internet shutdowns, blockages, firewalls—impose significant barriers to the transnational flow of information despite the connective power of digital technologies. In this paper, we examine whether and how information flows across borders despite government censorship. We develop a semi-automated system that combines deep learning and human annotation to find co-occurring content across different social media platforms and languages. We use this system to detect co-occurring content between Twitter and Sina Weibo as Covid-19 spread globally, and we conduct in-depth investigations of co-occurring content to identify those that constitute an inflow of information from the global information ecosystem into China. We find that approximately one-fourth of content with relevance for China that gains widespread public attention on Twitter makes its way to Weibo. Unsurprisingly, Chinese state-controlled media and commercialized domestic media play a dominant role in facilitating these inflows of information. However, we find that Weibo users without traditional media or government affiliations are also an important mechanism for transmitting information into China. These results imply that while censorship combined with media control provide substantial leeway for the government to set the agenda, social media provides opportunities for non-institutional actors to influence the information environment. Methodologically, the system we develop offers a new approach for the quantitative analysis of cross-platform and cross-lingual communication.

Repression research examines the causes and consequences of actions or policies that are meant to, or actually do, raise the costs of activism, protest, and/or social movement activity. The rise of digital and social media has brought substantial increases in attention to the repression of digital activists and movements and/or to the use of digital tools in repression, which is spread across many disciplines and areas of study. We organize and review this growing welter of research under the concept of digital repression by expanding a typology that distinguishes actions based on actor type, whether actions are overt or covert, and whether behaviors are shaped by coercion or channeling. This delineation between broadly different forms of digital repression allows researchers to develop expectations about digital repression, better understand what is “new” about digital repression in terms of explanatory factors, and better understand the consequences of digital repression.