Knowledge that Transforms

Recent scholarship has suggested that artificial intelligence (AI) technology and autocratic regimes may be mutually reinforcing. We test for 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 since the early 2010s. 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 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; noncontracted 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.

This article examines the relationship between ethnic-based gender norms and conflict-related sexual violence. We generate a novel dyadic data set that contains information on the ethnic identity of all the actors involved in ethnic civil conflicts around the world between 1989 and 2019 and their use of sexual violence. We exploit ethnographic information to construct a new male dominance index at the ethnicity level that captures deep-rooted gender norms. First, we find that male-dominant armed actors are more likely to be perpetrators of sexual violence. Second, we consider the cultural distance in gender norms between the combatants and show that sexual violence is driven by a specific clash of conceptions on the appropriate role of men and women in society: sexual violence increases when the perpetrator is more male dominant than the victim. Additional analyses suggest that gender norms influence both the strategic use of sexual violence for military purposes and the expressive use of sexual violence for private motivations. These patterns are specific to sexual violence and do not explain general violence in a conflict. Differences in other cultural dimensions unrelated to gender are not associated with conflict-related sexual violence.

We study time-consistent bank resolution mechanisms. The key constraint is that governments cannot avoid bailouts that are ex post efficient. Contrary to common wisdom, we show that the government may still avoid moral hazard and implement the first-best allocation by using the distribution of bailouts across banks to provide incentives. We analyze properties of credible tournament mechanisms that provide support to the best-performing banks and resolve the worst-performing ones. We extend our mechanism and show that it continues to perform well when banks are imperfect substitutes, when they are differentially interconnected as long as bailout funds can be earmarked, and when their risk-taking is driven by overoptimism instead of moral hazard.

We develop a new class of general-equilibrium models with partially unfunded debt to propose a fiscal theory of persistent inflation. In response to business cycle shocks, the monetary authority controls inflation and the fiscal authority stabilizes debt. However, the central bank accommodates unfunded fiscal shocks, causing persistent movements in inflation, output, and real interest rates. In an estimated quantitative model, fiscal inflation accounts for the bulk of inflation dynamics. In the aftermath of the pandemic, unfunded fiscal shocks sustain the recovery but also cause a persistent increase in inflation. The model is able to predict the inflationary effects of the American Rescue Plan Act fiscal stimulus out of sample and with real-time data.

Many school districts with centralized school choice adopt strategy-proof assignment mechanisms to relieve applicants from needing to strategize based on beliefs about their own admissions chances. This article shows that beliefs about admissions chances shape choice outcomes even when the assignment mechanism is strategy-proof by influencing how applicants search for schools and that “smart matching platforms” that provide live feedback on admissions chances help applicants search more effectively. Motivated by a model in which applicants engage in costly search for schools and overoptimism can lead to undersearch, we use data from a large-scale survey of choice participants in Chile to show that learning about schools is hard, beliefs about admissions chances guide the decision to stop searching, and applicants systematically underestimate nonplacement risk. We use RCT and RD research designs to evaluate scaled live feedback policies in the Chilean and New Haven choice systems. Twenty-two percent of applicants submitting applications where risks of nonplacement are high respond to warnings by adding schools to their lists, reducing nonplacement risk by 58% and increasing test score value added at the schools where they enroll by 0.10 standard deviations. Reducing the burden of school choice requires not just strategy-proofness inside the centralized system but also choice supports for the strategic decisions that inevitably remain outside of it.

We use admissions lotteries to estimate the effects of large-scale public preschool in Boston on college-going, college preparation, standardized test scores, and behavioral outcomes. Preschool enrollment boosts college attendance as well as SAT test taking and high school graduation. Preschool also decreases high school disciplinary measures including juvenile incarceration, but has no detectable effect on state achievement test scores. An analysis of subgroups shows that effects on college enrollment, SAT-taking, and disciplinary outcomes are larger for boys than for girls. Our findings illustrate possibilities for large-scale modern, public preschool and highlight the importance of measuring long-term and non–test score outcomes in evaluating the effectiveness of education programs.

A large literature in cognitive science studies the puzzling “Flynn effect” of rising fluid intelligence (reasoning skill) in rich countries. We develop an economic model in which a cohort’s mix of skills is determined by different skills’ relative returns in the labor market and by the technology for producing skills. We estimate the model using administrative data from Sweden. Combining data from exams taken at military enlistment with earnings records from the tax register, we document an increase in the relative labor market return to logical reasoning skill as compared to vocabulary knowledge. The estimated model implies that changes in labor market returns explain 37% of the measured increase in reasoning skill, and can also explain the decline in knowledge. An original survey of parents, an analysis of trends in school curricula, and an analysis of occupational characteristics show evidence of increasing emphasis on reasoning as compared to knowledge.

Using a randomized experiment with an automobile manufacturing firm in China, we measure the effects of letting workers evaluate their managers on worker and firm outcomes. In the treatment teams, workers evaluate their managers monthly. We find that providing feedback leads to significant reductions in worker turnover and increases in team-level productivity. In addition, workers report higher levels of happiness and well-being. The evidence suggests that these results are driven by learning by managers, leading to changes in their behavior and an overall better relationship between managers and workers.

Different agents need to make a prediction. They observe identical data, but have different models: they predict using different explanatory variables. We study which agent believes they have the best predictive ability—as measured by the smallest subjective posterior mean squared prediction error—and show how it depends on the sample size. With small samples, we present results suggesting it is an agent using a low-dimensional model. With large samples, it is generally an agent with a high-dimensional model, possibly including irrelevant variables, but never excluding relevant ones. We apply our results to characterize the winning model in an auction of productive assets, to argue that entrepreneurs and investors with simple models will be overrepresented in new sectors, and to understand the proliferation of “factors” that explain the cross-sectional variation of expected stock returns in the asset-pricing literature.

This article studies external sovereign bonds as an asset class. We compile a new database of 266,000 monthly prices of foreign-currency government bonds traded in London and New York between 1815 (the Battle of Waterloo) and 2016, covering up to 91 countries. Our main insight is that, as in equity markets, the returns on external sovereign bonds have been sufficiently high to compensate for risk. Real ex post returns average more than 6% annually across two centuries, including default episodes, major wars, and global crises. This represents an excess return of 3%–4% above US or UK government bonds, which is comparable to stocks and outperforms corporate bonds. Central to this finding are the high average coupons offered on external sovereign bonds. The observed returns are hard to reconcile with canonical theoretical models and the degree of credit risk in this market, as measured by historical default and recovery rates. Based on our archive of more than 300 sovereign debt restructurings since 1815, we show that full repudiation is rare; the median creditor loss (haircut) is below 50%.