This article studies the macroeconomic implications of imperfect risk sharing implied by a class of New Keynesian models with heterogeneous agents. The models in this class can be equivalently represented as a representative-agent economy with wedges. These wedges are functions of households’ consumption shares and relative wages, and they identify the key cross-sectional moments that govern the impact of households’ heterogeneity on aggregate variables. We measure the wedges using U.S. household-level data and combine them with a representative-agent economy to perform counterfactuals. We find that deviations from perfect risk sharing implied by this class of models account for only 7% of output volatility on average but can have sizable output effects when nominal interest rates reach their lower bound.

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.

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.

Market power of intermediaries contributes to the low incomes of farmers in India. I study the role of spatial competition between intermediaries in determining the prices that farmers receive in India by focusing on a law that restricts farmers to selling their goods to intermediaries in their own state. I show that the discontinuities in market power generated by the law translate into discontinuities in prices. Increasing spatial competition by one standard deviation causes prices received by farmers to increase by 6.4%. I propose and estimate a quantitative spatial model of bargaining and trade to shed light on spatial and aggregate implications. Estimates from the structural model suggest that removing the interstate trade restriction in India would increase competition between intermediaries. Thereby average farmer prices and their output would increase by at least 11% and 7%, respectively. The value of the national crop output would increase by at least 18%. However, there are distributional consequences as well, as some farmers stand to lose due to increased local production.

Books shape how children learn about society and norms, in part through representation of different characters. We use computational tools to characterize representation in children’s books widely read in homes, classrooms, and libraries over the past century and describe economic forces that may contribute to these patterns. We introduce new artificial intelligence methods for systematically converting images into data. We apply these tools, alongside text analysis methods, to measure skin color, race, gender, and age in the content of these books, documenting what has changed and what has endured over time. We find underrepresentation of Black and Latinx people in the most influential books, relative to their population shares, though representation of Black individuals increases over time. Females are also increasingly present but appear less often in text than in images, suggesting greater symbolic inclusion in pictures than substantive inclusion in stories. Characters in these influential books have lighter average skin color than in other books, even after conditioning on race, and children are depicted with lighter skin color than adults on average. We present empirical analysis of related economic behavior to better understand the representation we find in these books. On the demand side, we show that people consume books that center their own identities and that the types of children’s books purchased correlate with local political beliefs. On the supply side, we document higher prices for books that center nondominant social identities and fewer copies of these books in libraries that serve predominantly White communities.

Patterns of state formation have crucial implications for comparative economic development. Diamond (1997) famously argued that “fractured land” was responsible for China’s tendency toward political unification and Europe’s protracted polycentrism. We build a dynamic model with granular geographical information in terms of topographical features and the location of productive agricultural land to quantitatively gauge the effects of fractured land on state formation in Eurasia. We find that topography alone is sufficient but not necessary to explain polycentrism in Europe and unification in China. Differences in land productivity, in particular the existence of a core region of high land productivity in northern China, deliver the same result. We discuss how our results map into observed historical outcomes, assess how robust our findings are, and analyze the differences between theory and data in Africa and the Americas.

We study learning via shared news. Each period agents receive the same quantity and quality of firsthand information and can share it with friends. Some friends (possibly few) share selectively, generating heterogeneous news diets across agents. Agents are aware of selective sharing and update beliefs by Bayes’s rule. Contrary to standard learning results, we show that beliefs can diverge in this environment, leading to polarization. This requires that (i) agents hold misperceptions (even minor) about friends’ sharing and (ii) information quality is sufficiently low. Polarization can worsen when agents’ friend networks expand. When the quantity of firsthand information becomes large, agents can hold opposite extreme beliefs, resulting in severe polarization. We find that news aggregators can curb polarization caused by news sharing. Our results hold without media bias or fake news, so eliminating these is not sufficient to reduce polarization. When fake news is included, it can lead to polarization but only through misperceived selective sharing. We apply our theory to shed light on the polarization of public opinion about climate change in the United States.

We use two-round survey data from 62 elections in 10 countries since 1952 to study the formation of vote choice, beliefs, and policy preferences and assess how televised debates contribute to this process. Our data include 253,000 observations. We compare the consistency between vote intention and vote choice of respondents surveyed at different points before, and then again after, the election, and show that 17% to 29% of voters make up their mind during the final two months of campaigns. Changes in vote choice are concomitant to shifts in issues voters find most important and in beliefs about candidates, and they generate sizable swings in vote shares. In contrast, policy preferences remain remarkably stable throughout the campaign. Finally, we use an event study to estimate the impact of TV debates, in which candidates themselves communicate with voters, and of shocks such as natural and technological disasters which, by contrast, occur independently from the campaign. We do not find any effect of either type of event on vote choice formation, suggesting that information received throughout the campaign from other sources such as the media, political activists, and other citizens is more impactful.

Despite the widespread use of graphs in empirical research, little is known about readers’ ability to process the statistical information they are meant to convey (“visual inference”). We study visual inference in the context of regression discontinuity (RD) designs by measuring how accurately readers identify discontinuities in graphs produced from data-generating processes calibrated on 11 published papers from leading economics journals. First, we assess the effects of different graphical representation methods on visual inference using randomized experiments. We find that bin widths and fit lines have the largest effects on whether participants correctly perceive the presence or absence of a discontinuity. Our experimental results allow us to make evidence-based recommendations to practitioners, and we suggest using small bins with no fit lines as a starting point to construct RD graphs. Second, we compare visual inference on graphs constructed using our preferred method with widely used econometric inference procedures. We find that visual inference achieves similar or lower type I error (false positive) rates and complements econometric inference

Scholars have argued that powerful individuals can exert influence on the path of a nation’s development. Yet the process through which people can have an effect on macro-level political economy outcomes remains unclear. This study uses the deadliest civil war in modern history, the Taiping Rebellion (1850–1864), to elucidate how one person—Zeng Guofan—used his personal elite networks to organize an army to suppress the rebellion, and how these networks would affect the nation’s power distribution. Two findings stand out: (i) counties that already had more prewar elites in Zeng’s networks experienced an increase in soldier deaths after he took power; and (ii) postwar political power shifted significantly toward the home counties of these elites, creating a less balanced national-level power distribution. Our findings highlight how micro-level elite networks can influence national politics and societal power distribution, shedding new light on the relationship between elites, war, and the state.