Venture capital plays an important role in funding and shaping innovation outcomes, characterized by investors’ deep knowledge of the technology, industry, and institutions, as well as their long-running relationships with the entrepreneurship and innovation community. China, in its pursuit of global leadership in AI innovation and technology, has set up government venture capital funds so that both national and local governments act as venture capitalists. These government-led venture capital funds combine features of private venture capital with traditional government innovation policies. In this paper, we collect comprehensive data on China’s government and private venture capital funds. We draw three important contrasts between government and private VC funds: (i) government funds are spatially more dispersed than private funds; (ii) government funds invest in firms with weaker ex-ante performance signals but these firms exhibit growth rates exceeding those of firms in which private funds invest; and (iii) private VC funds follow government VC investments, especially when hometown government funds directly invest on firms with weaker ex-ante performance signals. We interpret these patterns in light of VC funds’ traditional role overcoming information frictions and China’s unique institutional environment, which includes important frictions on mobility and information.

Many governments engage in policy experimentation in various forms to resolve uncertainty and facilitate learning. However, little is understood about the characteristics of policy experimentation, and how the structure of experimentation may affect policy learning and policy outcomes. We describe and explain China’s policy experimentation since 1980, among the largest and most systematic in recent history. We collect comprehensive data on policy experiments conducted in China over the past four decades. We document three facts. First, about 90\% of the experiments exhibit positive sample selection in terms of a locality’s economic development. Second, careerdriven local politicians allocate more resources to ensure the experiments’ success, and such effort is not replicable when policies roll out to the entire country. Third, the central government is not fully sophisticated when interpreting experimentation outcomes. Under certain experimentation objectives, these facts imply that policy learning may be biased and national policies originating from the experimentation may be distorted. Taken together, while China’s bureaucratic and institutional conditions make policy experimentation possible at an unparalleled scale, the complex political environments can also impose limitation on effective policy learning.

Citizens have long taken to the streets to demand change, expressing political views that may otherwise be suppressed. Protests have produced change at local, national, and international scales, including spectacular moments of political and social transformation. We document five new empirical patterns describing 1.2 million protest events across 218 countries between 1980 and 2020. First, autocracies and weak democracies experienced a trend break in protests during the Arab Spring. Second, protest movements also rose in importance following the Arab Spring. Third, protest movements geographically diffuse over time, spiking to their peak, before falling off. Fourth, a country’s year-to-year economic performance is not strongly correlated with protests; individual values are predictive of protest participation. Fifth, the US, China, and Russia are the most over-represented countries by their share of academic studies. We discuss each pattern’s connections to the existing literature and anticipate paths for future work.

Recent scholarship has suggested that artificial intelligence technology and autocratic regimes may be mutually reinforcing. We test for such a mutually reinforcing relationship in the context of facial recognition AI in China. To do so, we gather comprehensive data on AI firms and government procurement contracts, as well as on social unrest across China during the last decade. We first show that autocrats benefit from AI: local unrest leads to greater government procurement of facial recognition AI as a new technology of political control, and increased AI procurement indeed suppresses subsequent unrest. We then show that AI innovation benefits from autocrats’ suppression of unrest: the contracted AI firms innovate more both for the government and commercial markets, and are more likely to export their products; and non-contracted AI firms do not experience detectable negative spillovers. Taken together, these results suggest the possibility of sustained AI innovation under the Chinese regime: AI innovation entrenches the regime, and the regime’s investment in AI for political control stimulates further frontier innovation.

Developing AI technology requires data. In many domains, government data far exceeds in magnitude and scope data collected by the private sector, and AI firms often gain access to such data when providing services to the state. We argue that such access can stimulate commercial AI innovation in part because data and trained algorithms are shareable across government and commercial uses. We gather comprehensive information on firms and public security procurement contracts in China's facial recognition AI industry. We quantify the data accessible through contracts by measuring public security agencies' capacity to collect surveillance video. Using a triple-differences strategy, we find that data-rich contracts, compared to data-scarce ones, lead recipient firms to develop significantly and substantially more commercial AI software. Our analysis suggests a contribution of government data to the rise of China’s facial recognition AI firms, and that states’ data collection and provision policies could shape AI innovation.

Major crises — from terrorist attacks to epidemic outbreaks — bring the trade-off between individual civil liberties and societal well-being into sharp relief. In this paper, we study how willing citizens are to restrict civil liberties to improve public health conditions in the context of the COVID-19 pandemic. We design and conduct representative surveys involving approximately 550,000 responses across 15 countries, including China and the United States, during many months of the COVID-19 pandemic, from March 2020 until January 2021. We document significant heterogeneity across countries and demographic groups in willingness to sacrifice rights for public welfare. Citizens disadvantaged by income, education, or race are less willing to sacrifice rights than their more advantaged peers in every country, as are those with prior experience in communist regimes. Leveraging naturally-occurring variation as well as experimental approaches, we estimate that a one standard deviation increase in health security concerns increases willingness to sacrifice civil liberties by approximately 68%-83% of the difference between the average Chinese and U.S. citizen. Stated preferences correlate with observed behavior including demand for tracing apps, donations, and petitions.

Which fundamental traits are associated with individuals' participation in antiauthoritarian protests? We conduct a series of surveys eliciting participation in Hong Kong's antiauthoritarian movement, covering a period that included protests ranging from tens of thousands to over one million participants. For a sample of university students, we construct a comprehensive profile of fundamental economic preferences: risk and time preferences plausibly affecting an individual’s costs of protest participation; social preferences affecting the benefits. We also elicit other fundamental traits: personality, cognitive abilities, and socioeconomic background. We document several facts about protest participants: (i) fundamental economic preferences, particularly risk tolerance and pro-social preferences, are the strongest predictors of protest participation; (ii) the strongest predictors are the same for modest and massive protests, with larger effects for massive protests; (iii) participation in massive protests is not driven by marginal types, but rather by inframarginal types; (iv) both the distribution of fundamental preferences and their relationship with protest participation are very similar between university students and the broader population; and, (v) willingness to respond honestly to sensitive survey questions is high and stable over the entire sample period. Our findings suggest that economic preferences be considered alongside class background and personality as deeply determined traits driving protest participation and can inform the development of dynamic models of protest movements.

People's perceptions about others play an important role in shaping their own attitudes and behaviors, as well as social norms more broadly. This review presents a meta-analysis of the recent empirical literature that examines perceptions about others in the field, covering over a million observations for a total of 434 elicited perceptions. We document a number of stylized facts. Misperceptions about others are widespread, asymmetric, much larger when about out-group members, and positively associated with one's own attitudes. Experimental treatments to re-calibrate misperceptions generally work as intended; they sometimes lead to meaningful changes in behaviors, though this often occurs only immediately after the treatments. We discuss different conceptual frameworks that could explain the origin, persistence, and rigidity of misperceptions about others. We point to several directions for future research.

We test whether participation in one protest within a political movement increases subsequent protest attendance, and why. To identify an effect of protest participation, we randomly, indirectly incentivize Hong Kong university students into participation in an antiauthoritarian protest. To identify the effects of social interactions, we randomize the intensity of this treatment across major-cohort cells. We find that experimentally-induced protest participation is significantly associated with protest attendance one year later, though political beliefs and preferences are unaffected. Persistent political engagement is greatest among individuals in the cells with highest treatment intensity, suggesting that social interactions sustained persistent political engagement.

We study partisan differences in Americans' response to the COVID-19 pandemic. Political leaders and media outlets on the right and left have sent divergent messages about the severity of the crisis, which could impact the extent to which Republicans and Democrats engage in social distancing and other efforts to reduce disease transmission. We develop a simple model of a pandemic response with heterogeneous agents that clarifies the causes and consequences of heterogeneous responses. We use location data from a large sample of smartphones to show that areas with more Republicans engage in less social distancing, controlling for other factors including public policies, population density, and local COVID cases and deaths. We then present new survey evidence of significant gaps at the individual level between Republicans and Democrats in self-reported social distancing, beliefs about personal COVID risk, and beliefs about the future severity of the pandemic.

How do reported incidence, knowledge, and behaviors regarding coronavirus disease 2019 vary across sociodemographic characteristics in the US? In this survey study, the largest differences in coronavirus disease 2019–related knowledge and behaviors were associated with race/ ethnicity, sex, and age. African American participants, men, and people younger than 55 years were less likely to know how the disease is spread, were less likely to know the symptoms of coronavirus disease 2019, washed their hands less frequently, and left the home more often. These findings suggest that more effort is needed to increase accurate information and encourage appropriate behaviors among minority communities, men, and younger people.

Media censorship is a hallmark of authoritarian regimes. We conduct a field experiment in China to measure the effects of providing citizens with access to an uncensored Internet. We track subjects' media consumption, beliefs regarding the media, economic beliefs, political attitudes, and behaviors over 18 months. We find 4 main results: (i) free access alone does not induce subjects to acquire politically sensitive information; (ii) temporary encouragement leads to a persistent increase in acquisition, indicating that demand is not permanently low; (iii) acquisition brings broad, substantial, and persistent changes to knowledge, beliefs, attitudes, and intended behaviors; and (iv) social transmission of information is statistically significant but small in magnitude. We calibrate a simple model to show that the combination of low demand for uncensored information and the moderate social transmission means China's censorship apparatus may remain robust to a large number of citizens receiving access to an uncensored Internet.

Social scientists have long viewed the decision to protest as strategic, with an individual's participation a function of her beliefs about others' turnout. We conduct a field experiment that re-calibrates individuals' beliefs about others' protest participation, in the context of Hong Kong's ongoing anti-authoritarian movement. We elicit subjects' planned participation in an upcoming protest and their prior beliefs about others' participation, in an incentivized manner. One day before the protest, we randomly provide a subset of subjects with truthful information about others' protest plans, and elicit posterior beliefs about protest turnout, again in an incentivized manner. After the protest, we elicit subjects' actual participation. This allows us to identify the causal effects of positively and negatively updated beliefs about others' protest participation on subjects' own turnout. In contrast with the assumptions of many recent models of protest participation, we consistently find evidence of strategic substitutability. We provide guidance regarding plausible sources of strategic substitutability that can be incorporated into theoretical models of protests.

We study the causal effect of school curricula on students' political attitudes, exploiting a major textbook reform in China between 2004 and 2010. The sharp, staggered introduction of the new curriculum across provinces allows us to identify its causal effects. We examine government documents articulating desired consequences of the reform, and identify changes in textbooks reflecting these aims. A survey we conducted reveals that the reform was often successful in shaping attitudes, while evidence on behavior is mixed. Studying the new curriculum led to more positive views of China's governance, changed views on democracy, and increased skepticism toward free markets.

Migration to another country is one approach to avoiding risks from political turmoil, but many more people stay behind than leave. In part, this may be because the economic costs of uprooting families or businesses are large. We explore the economic calculus behind migration during times of political turmoil through two major episodes in China over the past century: movement from Shanghai to Hong Kong in advance of the possible Communist takeover in the 1940s, and exit from Hong Kong in more recent years as the mainland government increased political control over the city. In each case, we document the extent to which exit decisions are responsive to (i) wealth shocks, as measured by differential real estate appreciation, and (ii) changes in the differential price of moving vs. staying put, using quasi-random destruction of businesses by errant bombs in historical Shanghai and labor market shocks in contemporary Hong Kong. In both episodes, we document a large, positive wealth elasticity of migration and a negative relative price elasticity. Importantly, people became more elastic, not less, when the perception of political turbulence became salient. Economic incentives play an important role in shaping migration decisions even during highly politically uncertain times.

Global innovation and entrepreneurship has traditionally been dominated by a handful of high-income countries, especially the US. This paper investigates the international consequences of the rise of a new hub for innovation, focusing on the dramatic growth of high-potential entrepreneurship and venture capital in China. First, using comprehensive data on global venture activities, we show that as the Chinese venture industry rose in importance, entrepreneurship increased substantially in other emerging markets, particularly in sectors dominated by Chinese companies. Using a broad set of country-level economic indicators, we find that this effect was driven by country-sector pairs most similar to their counterparts in China. Second, turning to mechanisms, we show that the baseline findings are driven by local investors and by new firms that more closely resemble existing Chinese companies. Third, we find that this growth in emerging-market investment had wide-ranging positive consequences, including a rise in serial entrepreneurship, cross-sector spillovers, innovation, and broader measures of socioeconomic well-being. Together, our findings suggest that developing countries benefited from more “appropriate” businesses and technology pioneered by China, and that a system where only rich countries lead in innovation could limit entrepreneurial activity in large parts of the world.

We document three facts about the global diffusion of surveillance AI technology, and in particular, the role played by China. First, China has a comparative advantage in this technology. It is substantially more likely to export surveillance AI than other countries, and particularly so as compared to other frontier technologies. Second, autocracies and weak democracies are more likely to import surveillance AI from China. This bias is not observed in AI imports from the US or in imports of other frontier technologies from China. Third, autocracies and weak democracies are especially more likely to import China’s surveillance AI in years of domestic unrest. Such imports coincide with declines in domestic institutional quality more broadly. To the extent that China may be exporting its surveillance state via trade in AI, this can enhance and beget more autocracies abroad. This possibility challenges the view that economic integration is necessarily associated with the diffusion of liberal institutions.

Can efforts to eradicate inequality in wealth and education eliminate intergenerational persistence of socioeconomic status? The Chinese Communist Revolution and Cultural Revolution aimed to do exactly that. Using newly digitized archival records and contemporary census and household survey data, we show that the revolutions were effective in homogenizing the population economically in the short run. However, the pattern of inequality that characterized the pre-revolution generation re-emerges almost half a century after the revolutions. Individuals whose grandparents belonged to the pre-revolution elite earn 12 percent more income and have completed more than 11 percent additional years of schooling than those from the rest of the population. We find evidence that human capital (such as knowledge, skills, and values) has been transmitted within the elite families. Moreover, the pre-revolution elite either move to opportunities or stay to benefit from the social capital embodied in kinship networks that have survived the revolutions. These channels allow the pre-revolution elite to rebound after the revolutions, and their socioeconomic status persists despite one of the most aggressive attempts to eliminate differences in the population.

US voters exaggerate the differences in attitudes held by Republicans and Democrats on a range of socioeconomic and political issues, and greater perceived polarization is associated with greater political engagement and affective polarization. In this paper, we examine the drivers of such perceived partisan differences. We find that a model of stereotypes, where distortions are stronger for issues that are more salient to voters, captures important features of the data. First, perceived partisan differences are predictable from the actual differences across parties, in particular from the relative prevalence of extreme attitudes. Second, perceived partisan differences are larger on issues that individuals consider more important. Third, issue salience increases the tendency to over-weigh extreme types. Exploiting nationally representative survey data, we show that the end of the Cold War in 1991, which shifted US voters’ attention away from external threats, increased perceived, relative to actual, partisan differences on domestic issues. The rise was stronger for issues with more stereotypical partisan differences. The reverse pattern occurred after the terrorist attacks in 2001, when attention swung back towards external threats. Consistent with the mechanism of salience-modulated stereotyping, beliefs about political groups can shift dramatically even when the underlying partisan differences change little.

Political trust is the foundation of authoritarian regimes’ legitimacy, and it is often sustained by propaganda. When does propaganda reach its limit, and what are the consequences when propaganda is falsified? We study the causal effect of the Great Chinese Famine (1958-1961) on survivors’ political distrust. Policy failures led to the Famine, but the propaganda blamed drought for the disaster. Information that directly contradicted the propaganda -- experiences of severe Famine in the absence of abnormal drought conditions -- was quasi-randomly available to some citizens, but not others. Using a nationally representative survey, we employ a difference-in-differences strategy to compare individuals who were exposed to different intensities of the Famine across regions with different levels of drought during the Famine. The Famine survivors inferred the government’s liability from starvation experiences and the drought conditions, and they were more likely to dismiss the propaganda and blame the government for the Famine if they observed regular weather conditions during the Famine. As a result, these individuals expressed significantly less trust in the government. Costs of falsified propaganda are substantial, since the dampened political trust has turned into a stable political ideology. The distrust persists even half a century after the Famine, has been transmitted to the subsequent generation, and has spilled over to a broad range of political attitudes unrelated to the Famine.

Beliefs about whether effort pays off govern some of the most fundamental choices individual make. This paper uses China’s Cultural Revolution to understand how these beliefs can be affected, how they impact behavior, and how they are transmitted across generations. During the Cultural Revolution, China’s college admission system based on entrance exams was suspended for a decade until 1976, effectively depriving an entire generation of young people of the opportunity to access higher education (the “lost generation”). Using data from a nationally representative survey, we compare cohorts who graduated from high school just before and after the college entrance exam was resumed. We find that members of the “lost generation” who missed out on college because they were born just a year or two too early believe that effort pays off to a much lesser degree, even 40 years into their adulthood. However, they invested more in their children’s education, and transmitted less of their changed beliefs to the next generation, suggesting attempts to safeguard their children from sharing their misfortunes.

Citizens' preference for redistribution determines many key political economy outcomes. In this project, we aim to understand how do ancestors' redistributive experiences affect the descendants' preference for redistribution. We conduct a survey experiment under the historical backdrop of the wealth equalization movements during the Communist Revolution in China (1947-1956). We remind a random subset of respondents of these movements that their ancestors went through. We find that on average, making the historical experiences salient turns the respondents significantly and persistently more favorable towards government redistribution. We show that the treatment effect is not driven by changes in apolitical preferences, beliefs of current inequality, or knowledge of the movements. Salience in history influences the mental framework when respondents think of redistribution: respondents are reminded of the specific family experiences during past redistribution, and they are triggered to project similar redistribution in the future.