Insufficient trust in journalists creates space for disinformation. We ask whether institutions can safeguard trust in journalists. Our main finding is that the rule of law is positively and robustly associated with trust in journalists. The rule of law arguably promotes trustworthy behavior by punishing deceit and dishonesty, thereby fostering trust. Robustness checks support this result. Moderation analysis indicates that the relationship between the rule of law and trust in journalists is weaker in low-income countries; this difference vanishes once gross domestic product per capita, a variable strongly correlated with the rule of law yet negatively associated with trust in journalists, is taken into account. A heterogeneous treatment analysis using the COVID-19 pandemic as an exogenous shock to trust levels offers suggestive evidence against reverse causality. Though exploratory, our findings point to the importance of high-quality legal institutions in combatting distrust in journalists.
Migrant domestic workers (MDWs) are highly vulnerable to labor abuse. Using a survey and randomized controlled trial conducted in Hong Kong, this study investigates MDWs' labor experiences and the potential of rights awareness campaigns to mitigate labor abuse. The campaigns increased public knowledge of MDWs' rights and reduced the social acceptability of MDWs' mistreatment. To the extent that improving knowledge about MDWs' rights and decreasing acceptance of mistreatment affect the behaviors of employers and others who can support MDWs, rights awareness campaigns can help reduce labor abuse. However, the campaigns had limited impact on MDWs, who demonstrated high awareness of their rights but often experienced concerning levels of abuse and regarded mistreatment as an unavoidable aspect of their employment. These differences highlight the constrained agency of MDWs to independently improve their labor conditions and emphasize the value of rights awareness initiatives targeting employers of MDWs and the general public.
We examine whether the US Securities Exchange Act of 1934 significantly stabilized the market by introducing mandatory disclosure of information. We argue that mandatory information disclosure can curb stock manipulation by enhancing transparency, thereby reducing excess stock volatility. After a comprehensive assessment of the voluntary disclosure practices of companies listed on the New York Stock Exchange before 1934, we find that those with poor disclosure practices experienced a significantly greater reduction in volatility after the implementation of the act compared with those with good disclosure practices. Further analysis reveals that the liquidity of these companies with poor disclosure practices also improved significantly more than that of companies with better disclosure, and the improvement in liquidity was linked to the decrease in their volatility. Given that one key purpose of the act's legislators was to reduce excess market volatility, our findings provide empirical support for considering this legislative aim successful.
Proponents of recreational marijuana laws (RMLs) argue that expanding legal access to marijuana may serve an important social justice objective by reducing racial disparities in arrest rates. Using data from the Uniform Crime Reports and a generalized difference-in-differences approach, we find support for this claim: RML adoption is associated with a reduction of 498-561 marijuana arrests per 100,000 persons (over 90 percent) among Black adults and a reduction of 128-145 arrests (78-88 percent) among White adults. However, we find no evidence that RML adoption reduces racial disparities in nonmarijuana drug arrests or arrests for property and violent crimes, and post-RML reallocation of policing resources to fight nonmarijuana drug crime and violent crime may, in some circumstances, widen these racial disparities. Finally, RMLs reduce opioid-related mortality among non-Hispanic Whites relative to Blacks and Hispanics, consistent with the hypothesis that those hardest hit at the outset of the US opioid epidemic disproportionately gain from recreational marijuana legalization.
Has automakers' use of artificial intelligence (AI) in advanced driver-assistance systems (ADASs) improved automobile safety? We address this question with a first-of-its-kind trim-level dataset of the universe of registered automobiles and accidents in Texas over a 9-year period. We find that ADASs reduce the risk of a motorist getting in any type of accident by 11 to 14 percent and reduce the risk of a motorist getting in a single-vehicle fatal accident by roughly one-third. Our finding that ADASs have improved automobile safety is especially important because it provides early evidence of the benefits of vehicle automation in actual travel environments. Hopefully, it will spur greater interest in the development and widespread adoption of fully autonomous vehicles and in the potential benefits of other transportation technologies using AI.
Although injunctions serve as a crucial remedy for intellectual property protection, their excessive use has the potential to limit economic growth. We use the 2006 Supreme Court ruling in eBay v. MercExchange, which reduced injunction likelihood for defendants in cases related to information and communications technology patents, as a shock to injunction risk. These defendants launched more new products and became more profitable after the ruling. The increase in treated firms' new product development became more pronounced for firms with more limited financing sources, consistent with a financing channel for these results. Moreover, treated firms' increased profitability is concentrated in firms with less product diversity, under more litigation risk, and under more intensive product-market competition.
Guan Yu worship has been a significant cultural force in China for centuries, shaping norms that foster generalized trust and acting as an informal institution in economic activities. Our findings reveal that regions with a higher historical density of Guan temples tend to have deeper financial development. To address potential endogeneity, we use the distance of each prefecture from Guan Yu's hometown as an instrumental variable. The instrumented results confirm the robustness of our findings. Further analysis indicates that the underlying mechanism driving these outcomes is the enhancement of interpersonal and interfirm trust.
We develop a strong triple-difference design, with variation across crimes and areas, to quantify the impact of Australia's 2001 heroin shortage on crime, providing precise and uniform evidence on both the immediate and long-term effects of drug law enforcement. Applying the design to 25 years of monthly postcode data, we show that crime experiences an 8.4 percent surge in the first month, followed by a 1 percent decrease every 13 months, resulting in a roughly 23 percent reduction in crime by 2019. At long-run levels, this implies an annual reduction in crime costs of around AUD 2.21 billion (2020 AUD), highlighting that the benefits of supply-side drug policies are significant and often underestimated because of their delayed realization. We conclude that supply-side policies have a more substantial role in reducing drug-related harm than is conventionally assumed.
This paper quantifies the impact of terrorism on electoral support for incumbent parties in sub-Saharan Africa, using survey data collected during fieldwork that coincided with terrorist attacks. By comparing respondents surveyed immediately before a local attack with those in the same area surveyed shortly after, we observe a decrease of 5-6 percentage points in incumbent support following attacks. This decline is more pronounced when attacks are proximate, target civilians, or incur higher casualties. The impact is strongest in states with weaker institutions, areas with extensive media coverage, and among politically engaged and educated citizens, though an effective government response can mitigate this adverse effect. Further investigation reveals that the reduction in support stems primarily from a significant erosion of trust in the incumbent party, rather than shifts in counterterrorism policy preferences. These findings underscore terrorism's considerable influence on democratic stability in affected regions.
This paper examines the incentive to appeal. While existing literature focuses on appeals as a mechanism for correcting errors or controlling judicial incentives, we explore individual litigants' incentives in civil and criminal cases by modeling the opportunity cost of the trial court judgment for litigants when deciding whether to appeal. In civil trials, this causes a reluctance to appeal for plaintiffs and a bias in favor of appealing for defendants. The same effect induces a bias toward appeal for defendants convicted in criminal trials. We also model the factors that determine appeals and posttrial settlements. Our model illustrates the importance of litigants' beliefs about their prospects on appeal in driving appeals: If parties are sufficiently pessimistic, appellate courts will play little role in correcting errors or controlling judicial incentives. We also examine the empirical literature on appeals and compare the model's implications to the claims therein.
Contract theorists typically assume that efficient breach opportunities are exogenous and traditionally favor using expectation damages over the disgorgement rule. This paper challenges that assumption by introducing a model in which parties exert search efforts to locate better contractual alternatives. Endogenizing efficient breach opportunities yields a novel perspective on contract remedies. I propose two new rules: conditional disgorgement, which grants the breach surplus to the party who located the better alternative; and partial disgorgement, which divides the surplus by a predetermined share. I show that these novel remedies generally outperform extant regimes in inducing optimal search efforts. Because each party benefits regardless of her breaching status, both selfish and cooperative searches are incentivized. The paper derives conditions for the optimality of each proposed rule and discusses these findings in light of existing contract doctrine and commercial practice.
The Dodd-Frank Act in 2010 increased ex ante downgrade threats without changing credit-rated firms' underlying credit quality. We show that the act had negative impacts on credit-rated firms' acquisition activities, especially among speculative-grade firms as they face greater downgrade-induced costs. The more selective acquisition strategies led to higher announcement returns and greater postacquisition upgrade probabilities. Consistent with firms refraining from taking on overall acquisition risk rather than financial risk, we show significant reductions in both cash-and stock-settled dealmaking after the Dodd-Frank Act. In sum, our study highlights that increased legal stringency on credit rating agencies has important spillover effects on firms' mergers and acquisitions activities.
A decision-maker who aims to find the truth from a suspect delegates to an interrogator with possibly misaligned preferences. The ideal interrogator is always misaligned: sometimes nicer, sometimes tougher. The decision-maker can further improve by conditioning the delegation on the evidence, which is her private information, appointing a nice interrogator when the evidence is weak and a tougher interrogator when the evidence is strong. Dynamic, endogenous, conditional delegation can credibly convey information about the strength of the evidence and implement the overall optimum with full commitment. Moreover, the decision-maker can then retain authority over decisions by relying on the interrogator's recommendations.
We study racial diversity in American law schools and the impact of state-level affirmative action bans. Using novel data on enrollment in every law school since 1980, we find that minority shares of enrollment grew from 11 to 32 percent but still lagged behind minority shares of potential law school candidates, which grew from 16 to 43 percent. Exploiting 12 state-level affirmative action bans, we find that affirmative action bans decrease racial diversity by 17 percent and that all the decrease came from enrolling fewer Black and Hispanic students.
We study a reform to the workers' compensation system in Argentina that, motivated by a large increase in workplace litigiousness, mandates that workers go through a mediating government medical commission after a workplace accident to determine the degree of disability, whether the injury happened in the workplace, and the corresponding compensation before additional legal actions can be taken. Leveraging the staggered implementation of the reform across provinces, we find that the reform substantially reduced workplace lawsuits with no effects on reported accidents. Employment increased in highly exposed industries by more than 5 percent a year after the reform, with no effects on average earnings or the number of active firms.
We study the productivity effects of the world's largest privatization program in China. Relying on a matching and difference-in-differences procedure, we find that privatizations robustly led to large productivity gains. Privatizations improved total factor productivity (TFP) by 13-15 percent, and this estimate is at the high end of the estimates obtained from other transitional countries. Further evidence suggests that productivity gains came from improvements in management quality. The positive effect of privatization on TFP was more pronounced among firms in more competitive industries, which suggests complementarity between competition and privatizations. Privatizations worked less well for large state-owned entities under the oversight of the central government. Our evidence suggests that the privatization program was a key contributor to China's growth in previous decades.
About 52 percent of all shareholder meetings happen in the proxy season, a period that lasts from the fourth week of April until the end of May. This concentration leads to an increased workload for Institutional Shareholder Services (ISS), the largest proxy advisor, during which time it must make recommendations on an average of 303 proposals each day, compared with 28 proposals outside the proxy season. We find that ISS makes fewer negative recommendations in this busy period and that the recommendations are of lower quality. The evidence is consistent with ISS managing its workload by both increasing the threshold that triggers further investigation of proposals and reducing the time its analysts spend on each proposal. These findings suggest that the clustering of annual meetings in the proxy season may hinder the informativeness of proxy recommendations.
Do search engines produce better results because their algorithms are better or because they can access more data from past searches? We document that the algorithm of a small search engine can produce nonpersonalized results that are of similar quality to those of the dominant firm (Google) for certain types of search queries. Overall differences in the quality of search results are explained by searches for rare queries, which constitute 74 percent of the traffic in our data. We conduct an experiment in which we keep the algorithm of a small search engine fixed and only vary the amount of data it uses as input. Our results show that giving small search engines access to more data about rare queries improves the quality of their results. This suggests that mandatory data sharing by large search engines is a necessary condition, yet probably not a sufficient one, to increase competition in the search market.
I analyze court orders issued between 1970 and 1988 that were intended to address jail overcrowding. I find that these court orders led to a 21 percent reduction in jail populations but resulted in a 15 percent increase in homicide rates outside of jails. Recent scholarly work suggests that jail incarceration rates could have been reduced without significantly impacting crime. Thus, my findings suggest that court orders may be an ineffective method for reforming jails.
