Research project Social media and traditional media in China: Political and economic effects (MediaChina)

This project has received funding from the European Research Council under grant agreement No 742983.

Principal Investigator: David Strömberg

Background

New media are rapidly increasing the amount of information available to citizens and leaders in many autocracies, including China. The consequences for political accountability and regime stability are unclear. The new media can be used to spread information and organize opposition against authoritarian governments. However, autocrats may censor the information, or even use it for surveillance to solidify regime stability. China is leading this development, both because of the enormous popularity of social media and because of their adoption of state-of-the-art censoring and surveillance technologies. The development in China is of huge importance in its own right. However, social media effects in China today may also point to the direction of social-media effects in other non-democracies approaching this juncture in the near future. For example, within a decade or so, several countries with authoritarian governments in Africa may have reached similar level of social-media penetration and technological sophistication as China has today.

Objectives and outline

This project will analyse how economic and political outcomes in China are affected by traditional and social media. It will also use content in these media to measure factors that are otherwise difficult to observe, such as political networks and the trade-off between political and economic goals in Chinese firms. A major impetus for this project is that an explosion of social media use in China has produced an information shock to society and its leaders, also supplying a data shock to researchers, which is magnified by the digitization of traditional media content and coupled with new methods for analysing this type of data, originating from the big-data and machine-learning revolutions. As a result, a large set of previously unanswerable questions are now open for research.

Output

Publications

”Media bias in China” (with Bei Qin and Yanhui Wu) American Economic Review 108.9 (2018): 2442-2476.

This paper examines whether and how market competition affected the political bias of government-owned newspapers in China from 1981 to 2011. We measure media bias based on coverage of government mouthpiece content (propaganda) relative to commercial content. We first find that a reform that forced newspaper exits (reduced competition) affected media bias by increasing product specialization, with some papers focusing on propaganda and others on commercial content. Second, lower-level governments produce less-biased content and launch commercial newspapers earlier, eroding higher-level governments' political goals. Third, bottom-up competition intensifies the politico-economic trade-off, leading to product proliferation and less audience exposure to propaganda.
China newspaper directory: DOI 10.5281/zenodo.3997221.

”Why does China allow freer social media? Protests versus surveillance and propaganda” (with Bei Qin and Yanhui Wu). Journal of Economic Perspectives 31.1 (2017): 117-140.

In this paper, we document basic facts regarding public debates about controversial political issues on Chinese social media. Our documentation is based on a dataset of 13.2 billion blog posts published on Sina Weibo--the most prominent Chinese microblogging platform--during the 2009-2013 period. Our primary finding is that a shockingly large number of posts on highly sensitive topics were published and circulated on social media. For instance, we find millions of posts discussing protests, and these posts are informative in predicting the occurrence of specific events. We find an even larger number of posts with explicit corruption allegations, and that these posts predict future corruption charges of specific individuals. Our findings challenge a popular view that an authoritarian regime would relentlessly censor or even ban social media. Instead, the interaction of an authoritarian government with social media seems more complex.

”Social Media and Collective Action in China” (with Bei Qin and Yanhui Wu), Econometrica, forthcoming.

This paper studies how social media affects the dynamics of protests and strikes in China during 2009-2017. Based on 13.2 billion microblog posts, we use tweets and retweets to measure social media communication across cities and exploit its rapid expansion for identification. We find that, despite strict government censorship, Chinese social media has a sizeable effect on the geographical spread of protests and strikes. Furthermore, social media communication considerably expands the scope of protests by spreading events across different causes (e.g., from anti-corruption protests to environmental protests) and dramatically increases the probability of far-reaching protest waves with simultaneous events occurring in many cities. These effects arise even though Chinese social media barely circulates content that explicitly helps organize protests.

Working papers

”Does Chinese research hinge on US co-authors? Evidence from the China initiative” (with Philippe Aghion, Celine Antonin, Luc Paluskiewicz, Raphael Wargon and Karolina Westin).

Launched in November 2018 by the Trump administration, the China Initiative made administrative procedures more complicated and funding less accessible for collaborative projects between Chinese and US researchers. In this paper, we use information from the Scopus database to analyze how the China Initiative shock affected the volume and quality of Chinese research. We find a negative effect of the Initiative on the average quality of both the publications and the co-authors of Chinese researchers with prior US collaborations compared to Chinese researchers with prior European collaborations. Thus, the Initiative is estimated to have reduced the number of yearly citations for Chinese researchers in the treatment group by 13 percent more than for researchers in the control group. The negative effect of the Initiative has been stronger for Chinese researchers with higher research productivity and/or who worked on US-dominated fields before the shock. Finally, we find no significant effect of the China Initiative on the volume and quality of research of US researchers with prior Chinese collaborations.

”Chinese Microblogs and Drug Quality” (with Bei Qin and Thomas Larsson)

This paper examines the impact of the introduction of Sina Weibo, the most popular microblog in China, on the quality of drugs on the market. Using a unique data set on drug quality and Sina Weibo use, I explore the staggered diffusion of Sina Weibo across prefectures. I find that the number of bad drugs is decreasing in Sina Weibo use: if the Sina Weibo use is doubled, the number of bad drugs found will be reduced by 21 percent. Consistent with the prediction of a simple moral-hazard model, I show that the reduction of bad drugs is driven by two mechanisms: Sina Weibo induces more effort from the Drug Administration and it deters the production of bad drugs. Finally, I show that the diffusion of Sina Weibo has a higher marginal effect for disadvantaged groups, consistent with microblogging being a cheap, accessible media. The results suggest that microblogs can play an important role in monitoring both the public and the private sectors, especially in a context with media censorship.

”The Innovation Cost of Short Political Horizons: Evidence from Local Leaders’ Promotion in China” (Xueping Sun).

This paper examines how politicians’ time horizons affect the choices between policies that yield short-versus long-term growth. I digitize the career histories of Chinese city leaders, link them to economic policies and innovation outcomes, and exploit political connections formed through previous work ties to generate variation in leaders’ promotion expectations. I find that when leaders are connected, they can rationally expect an earlier promotion. Such expectations lead them to pursue a fast-over-slow strategy for growth: higher spending on infrastructure, lower spending on science and technology, and lower effort in promoting innovation. As a result, the local economy has higher short-term growth but lower future patenting and long-term growth.