Suchergebnisse

"In modern times, international borders reflect discontinuous changes in political authority, no matter what the inconveniences are for the individuals that they separate. What explains this fact? Why are the citizens of neighboring regions that happen to lie across an international border often subject to very different governance systems? We argue that the defining feature of the modern territorial state system is the local, bounded, monopoly that states have in governing their citizens. States refuse to violate each other's monopolies, even when they could do so easily. We examine what makes this system stable, when and how it emerged, how it spread, how it has been challenged, what led it to be so resilient over time, and how might it change in the future."

During the Middle Ages, most European polities operated under a norm that gave only the close male relatives of a monarch a privileged place in the order of succession. When no such heirs were available, succession disputes were more likely, with distant relatives and female(-line) heirs laying competing claims to the throne. These disputes often produced conflicts that destroyed existing institutions and harmed subsequent economic development. A shortage of male heirs to a European monarchy in the Middle Ages could thus have harmful effects on the development trajectories of regions ruled by that monarchy. We provide evidence for this by showing that regions that were more likely to have a shortage of male heirs are today poorer than other regions. Our finding highlights the importance of the medieval period in European development and shows how small shocks can work in combination with institutions and norms in shaping long-run development paths.

AbstractThe contemporary world is organized into a system of territorial states in which rulers exercise authority inside clearly defined boundaries and recognize the authority of other rulers outside those boundaries. We develop a model to explain how the major economic and military developments in Europe starting in the fifteenth century contributed to the development of this system. Our model rationalizes the system as an economic cartel in which self‐interested and forward‐looking rulers maintain high tax revenues by reducing competition in the "market for governance."

This article introduces a model of war and peace in which leaders believe that their adversaries might be crazy types who always behave aggressively, regardless of whether it is strategically optimal to do so. In the model, two countries are involved in a dispute that can either end in a peaceful settlement or escalate into 'limited war' or 'total war.' If it is common knowledge that the leaders of the countries are strategically rational, then the only equilibrium outcome of the model is peace. Yet if a leader believes that there is a chance that her adversary is a crazy type, then even a strategically rational adversary may have an incentive to adopt a madman strategy in which he pretends to be crazy. This leads to limited war with positive probability, even when both leaders are strategically rational. The article shows that despite having two-sided incomplete information, the model has a generically unique equilibrium. Moreover, the model identifies two countervailing forces that drive equilibrium behavior: a reputation motive and a defense motive. When the prior probability that a leader is crazy decreases, the reputation motive promotes less aggressive behavior by that leader, while the defense motive pushes for more aggressive behavior. These two forces underlay several comparative statics results. For example, the study analyzes the effect of increasing the prior probability that a leader is crazy, and the effect of changing the relative military strengths of the countries, on the equilibrium behavior of both leaders. The analysis also characterizes the conditions under which the madman strategy is profitable (or not), which contributes to the debate in the literature about its effectiveness. Adapted from the source document.

This article introduces a model of war and peace in which leaders believe that their adversaries might be crazy types who always behave aggressively, regardless of whether it is strategically optimal to do so. In the model, two countries are involved in a dispute that can either end in a peaceful settlement or escalate into 'limited war' or 'total war.' If it is common knowledge that the leaders of the countries are strategically rational, then the only equilibrium outcome of the model is peace. Yet if a leader believes that there is a chance that her adversary is a crazy type, then even a strategically rational adversary may have an incentive to adopt a madman strategy in which he pretends to be crazy. This leads to limited war with positive probability, even when both leaders are strategically rational. The article shows that despite having two-sided incomplete information, the model has a generically unique equilibrium. Moreover, the model identifies two countervailing forces that drive equilibrium behavior: a reputation motive and a defense motive. When the prior probability that a leader is crazy decreases, the reputation motive promotes less aggressive behavior by that leader, while the defense motive pushes for more aggressive behavior. These two forces underlay several comparative statics results. For example, the study analyzes the effect of increasing the prior probability that a leader is crazy, and the effect of changing the relative military strengths of the countries, on the equilibrium behavior of both leaders. The analysis also characterizes the conditions under which the madman strategy is profitable (or not), which contributes to the debate in the literature about its effectiveness.

The lasting effects of slavery on contemporary political attitudes in the American SouthDespite dramatic social transformations in the United States during the last 150 years, the South has remained staunchly conservative. Southerners are more likely to support Republican candidates, gun rights, and the death penalty, and southern whites harbor higher levels of racial resentment than whites in other parts of the country. Why haven't these sentiments evolved or changed? Deep Roots shows that the entrenched political and racial views of contemporary white southerners are a direct consequence of the region's slaveholding history, which continues to shape economic, political, and social spheres. Today, southern whites who live in areas once reliant on slavery—compared to areas that were not—are more racially hostile and less amenable to policies that could promote black progress. Highlighting the connection between historical institutions and contemporary political attitudes, the authors explore the period following the Civil War when elite whites in former bastions of slavery had political and economic incentives to encourage the development of anti-black laws and practices. Deep Roots shows that these forces created a local political culture steeped in racial prejudice, and that these viewpoints have been passed down over generations, from parents to children and via communities, through a process called behavioral path dependence. While legislation such as the Civil Rights Act and the Voting Rights Act made huge strides in increasing economic opportunity and reducing educational disparities, southern slavery has had a profound, lasting, and self-reinforcing influence on regional and national politics that can still be felt today.A groundbreaking look at the ways institutions of the past continue to sway attitudes of the present, Deep Roots demonstrates how social beliefs persist long after the formal policies that created those beliefs have been eradicated

AbstractViewing the relationship between politicians and voters as a principal–agent interaction afflicted by moral hazard, we examine how political careers are shaped by the incentives that voters provide incumbents to work in the public interest. When moral hazard binds, the optimal way for voters to hold politicians accountable is to provide re‐election incentives that evolve dynamically over their careers in office. Under these incentives, first‐term politicians are among the most electorally vulnerable and the hardest‐working; politician effort rises with electoral vulnerability; electoral security increases following good performance and decreases following bad performance; and both effort and electoral vulnerability tend to decline with tenure. In extensions, we study limited voter commitment, voluntary retirement from politics, and adverse selection.

AbstractWe introduce a constrained priority mechanism that combines outcome-based matching from machine learning with preference-based allocation schemes common in market design. Using real-world data, we illustrate how our mechanism could be applied to the assignment of refugee families to host country locations, and kindergarteners to schools. Our mechanism allows a planner to first specify a threshold $\bar g$ for the minimum acceptable average outcome score that should be achieved by the assignment. In the refugee matching context, this score corresponds to the probability of employment, whereas in the student assignment context, it corresponds to standardized test scores. The mechanism is a priority mechanism that considers both outcomes and preferences by assigning agents (refugee families and students) based on their preferences, but subject to meeting the planner's specified threshold. The mechanism is both strategy-proof and constrained efficient in that it always generates a matching that is not Pareto dominated by any other matching that respects the planner's threshold.

AbstractWe introduce a constrained priority mechanism that combines outcome-based matching from machine learning with preference-based allocation schemes common in market design. Using real-world data, we illustrate how our mechanism could be applied to the assignment of refugee families to host country locations, and kindergarteners to schools. Our mechanism allows a planner to first specify a threshold
$\bar g$
for the minimum acceptable average outcome score that should be achieved by the assignment. In the refugee matching context, this score corresponds to the probability of employment, whereas in the student assignment context, it corresponds to standardized test scores. The mechanism is a priority mechanism that considers both outcomes and preferences by assigning agents (refugee families and students) based on their preferences, but subject to meeting the planner's specified threshold. The mechanism is both strategy-proof and constrained efficient in that it always generates a matching that is not Pareto dominated by any other matching that respects the planner's threshold.

Abstract We introduce a constrained priority mechanism that combines outcome-based matching from machine learning with preference-based allocation schemes common in market design. Using real-world data, we illustrate how our mechanism could be applied to the assignment of refugee families to host country locations, and kindergarteners to schools. Our mechanism allows a planner to first specify a threshold $\bar g$ for the minimum acceptable average outcome score that should be achieved by the assignment. In the refugee matching context, this score corresponds to the probability of employment, whereas in the student assignment context, it corresponds to standardized test scores. The mechanism is a priority mechanism that considers both outcomes and preferences by assigning agents (refugee families and students) based on their preferences, but subject to meeting the planner's specified threshold. The mechanism is both strategy-proof and constrained efficient in that it always generates a matching that is not Pareto dominated by any other matching that respects the planner's threshold.

Researchers investigating causal mechanisms in survey experiments often rely on nonrandomized quantities to isolate the indirect effect of treatment through these variables. Such an approach, however, requires a "selection-on-observables" assumption, which undermines the advantages of a randomized experiment. In this paper, we show what can be learned about casual mechanisms through experimental design alone. We propose a factorial design that provides or withholds information on mediating variables and allows for the identification of the overall average treatment effect and the controlled direct effect of treatment fixing a potential mediator. While this design cannot identify indirect effects on its own, it avoids making the selection-on-observable assumption of the standard mediation approach while providing evidence for a broader understanding of causal mechanisms that encompasses both indirect effects and interactions. We illustrate these approaches via two examples: one on evaluations of US Supreme Court nominees and the other on perceptions of the democratic peace.