A selection of recent journal publications

Collective action problems emerge when individual incentives and group interests are misaligned, as in the case of climate change. Individuals involved in these problems are generally considered to have two options: contribute toward public solutions such as global warming mitigation or free ride. However, many collective action problems today involve a third option of investing in a “private solution” such as local adaptation. The availability of this third option can lead to a private solution trap whereby private solutions are adopted, collectively optimal public solutions are not provided, and existing inequalities are exacerbated. We investigated the private solution trap with a collective action game featuring private and public solutions, wealth inequality determined by luck or merit, and participants from 34 countries. We found that the joint existence of private solutions and wealth inequality had a consistent effect across countries: Participants given a higher endowment adopted private solutions almost twice as often as those given a lower endowment, regardless of whether it was determined by luck or merit, and contributed proportionally less toward public solutions. Wealth inequality increased in every country and those given lower endowments were often left unprotected as public solutions were not provided. Across countries, cultural values of hierarchy and harmony were associated with preferences for private and public solutions, respectively. We also identified two universal pathways toward public solution provision: early contributions and conditional cooperation. Our findings highlight the ubiquity of the private solution trap, its cultural underpinnings, and its potential consequences for global collective action problems.

Despite being often discussed both in practice and academic circles, the sunk cost effect remains empirically elusive. Our model based on reference point dependence suggests that the traditional way of testing it—by assigning discounts—may not produce the desired effect. Motivated by this, we evaluate it across the gain-loss divide in two pre-registered experiments. In an online study with N = 1,806, we randomize the price (low, medium, or high) of a ticket to enter a real-effort task, and observe its effect on play time. Our intervention, which varies the sunk cost by $2 for a 14-minute task, results in a moderate sunk cost effect (0.12 SD or 1.3 min). We further explore the economic applications of the effect in a field experiment on YouTube with N = 11,328 videos in which we randomize whether the time until a pre-video ad becomes skippable is shortened (0 s), default (5 s), or extended (10 s). The intervention has an overall insignificant effect on video engagement. This is driven by a sizable negative effect on the extensive margin, a channel which is not present in the online study. Specifically, more users leave before the video starts in the extended treatment (5.2 pp or 28 % more relative to the shortened treatment). Taking the results of both studies together, we offer evidence of the sunk cost effect in a controlled environment, but its application in policy settings may prove challenging.

Over 2 billion people lack clean drinking water. Existing solutions face high costs (piped water) or low demand (point-of-use chlorine). Using a 60,000 household cluster-randomized experiment, we test an alternative approach: decentralized treatment and home delivery of clean water to the rural poor. At low prices, take-up exceeds 90 percent, sustained throughout the experiment. High prices reduce take-up but are privately profitable. We experimentally recover revealed-preference measures of valuation. Willingness-to-pay is several times higher than prior indirect estimates; willingness-to-accept is larger and exceeds marginal cost. Self-reported health measures improve accordingly. On a cost-per-DALY basis, free water delivery regimes appear highly cost effective.

Managing military operations across and between teams of partner nations remains a first-order challenge to security and development during conflict. NATO, under the umbrella of the International Security Assistance Force (ISAF), brought together troops from 28 countries to help enhance security provision in Afghanistan. ISAF units were given responsibility for specific operational units. The assignment of responsibilities to different national armed forces could lead to coordination problems. We explore whether the provision of security is affected by horizontal frictions (when different countries are responsible for different sides of borders) or vertical frictions (when different countries control different levels of the operational hierarchy). We find that both horizontal frictions and vertical frictions are also associated with higher levels of insurgent violence. They also reduce military support activities, including aid projects and patrol activity. These findings indicate that misalignment between units within military organizations can undermine the effectiveness of security and development interventions during war.

Science aspires to be cumulative. Reproducibility efforts strengthen science by testing the reliability of published findings, promoting self-correction, and informing policy-making. Computational reproductions, whereby independent researchers reproduce the results of published studies, are an essential diagnostic tool. Such efforts should have greater visibility. However, little social science reproduction and robustness has been conducted at scale. Here we reproduced original analyses and conducted robustness checks of 110 articles that were published in leading economics and political science journals with mandatory data and code sharing policies. We found that more than 85% of published claims were computationally reproducible. In robustness checks, our reanalyses showed that 72% of statistically significant estimates remain significant and in the same direction, and the median reproduced effect size is nearly the same as the originally published effect size (that is, 99% of the published effect size). Additionally, 6 independent research teams examined 12 pre-specified hypotheses about determinants of robustness. Research teams with more experience found lower levels of robustness, and robustness did not correlate with author characteristics or data availability.

We introduce and validate a novel approach to identifying good managers. In a preregistered lab experiment, we causally identify managerial contributions by randomly assigning managers to teams and controlling for individual skill. We find that manager contributions are crucial for team success, and that people who self-select into management roles perform worse than randomly assigned managers. Managerial performance is strongly predicted by economic decision-making skill but not by demographic characteristics. Two validation studies support our experimental results. Participants who succeed in the lab receive more real-world promotions and, in a separate study of retail store managers, skill measures strongly predict store sales. A one standard deviation increase in manager quality increases annual per store sales by US$4.1 million (25% increase). Selecting managers on skills rather than demographic characteristics or the desire to lead could substantially improve organizational performance.

A core challenge for healthcare systems is ensuring timely care for critical conditions while efficiently managing lower-complexity cases. Hospitals, often overburdened by both, struggle to balance these demands and allocate resources effectively. Many countries have responded by introducing alternative 24/7 facilities to relieve hospital strain and improve patient outcomes, yet evidence on their impact remains limited. We evaluate the introduction of freestanding Emergency Care Centers (UPAs) within Brazil’s publicly funded health system, leveraging rich administrative data. We find that UPAs reduced hospital outpatient procedures by 30% and hospital admissions for ambulatory-sensitive conditions by 24–37%, enabling hospitals to focus on more complex cases, such as surgeries and obstetric admissions, which increased by 25%. We observe a 13% reduction in inpatient mortality, particularly in intensive care and for conditions best suited to hospital treatment. While some deaths were displaced to UPAs, there was a decline in population-level mortality of 1.8%, although this is not statistically significant. Our findings show how an intermediate tier of emergency care reshapes patient sorting, alleviates hospital congestion, and improves hospital performance in an overstretched public health system.

We identify dynamic impacts on domestic violence (DV) of the staggered imposition and lifting of lockdown across Chile’s 346 municipalities. Lockdown increases DV helpline calls and shelter occupancy without increasing DV police reports. These results are consistent with lockdown raising incidence and creating barriers to reporting. Once lockdown is lifted, shelter occupancy falls and police reports surge, but helpline calls remain elevated in line with state dependence in DV. We identify male job loss as a mechanism driving DV. Our findings accentuate controversy around welfare impacts of lockdown mandates. Adverse impacts of lockdown on DV are mitigated by cash transfers.

In trade models with scale economies import liberalization reduces exports within industries by shrinking real market potential. We find this export destruction mechanism reduced US export growth following the permanent normalization of trade relations with China (PNTR). There was also an offsetting boost to exports from lower input costs. We use our estimates to calibrate a quantitative model and show that scale economies are economically important for trade policy analysis. Although PNTR increased aggregate US exports relative to GDP, exports declined in the most exposed industries. US gains from PNTR are positive, but 30 percent smaller than under constant returns.

Market-based environmental regulations are seldom used in low-income countries, where pollution is highest but state capacity is often low. We collaborated with the Gujarat Pollution Control Board (GPCB) to design and experimentally evaluate the world’s first particulate-matter emissions market, which covered industrial plants in a large Indian city. There are three main findings. First, the market functioned well. Treatment plants, randomly assigned to the emissions market, traded permits to become significant net sellers or buyers. After trading, treatment plants held enough permits to cover their emissions 99% of the time, compared with just 66% compliance with standards under the command-and-control status quo. Second, treatment plants reduced pollution emissions, relative to control plants, by 20%–30%. Third, the market reduced abatement costs by an estimated 11%, holding constant emissions. This cost-savings estimate is based on plant-specific marginal cost curves that we estimate from the universe of bids to buy and sell permits in the market. The combination of pollution reductions and low costs imply that the emissions market has mortality benefits that exceed its costs by at least 25 times.

We provide experimental evidence that using body-worn cameras (BWCs) for police monitoring improves police-citizen interactions. In an intervention carried out in Brazil in 2018, we find that treated incidents show a 61.2% decrease in police use of force and a 47.0% reduction in adverse interactions, including handcuff use and arrests. The use of body-worn cameras also significantly improves the quality of police reporting. The rate of incomplete reports dropped by 5.9%, which is accompanied by a 69.2% increase in reported incidents of domestic violence. We explore various mechanisms that explain why BWCs work and show that the results are consistent with the police changing their behavior in the presence of cameras. Overall, results show that the use of body-worn cameras de-escalates conflicts.

We consider a Bayesian persuasion model in which multiple receivers take one action each. We compare simultaneous procedures with sequential ones. In a simultaneous procedure, all the receivers act simultaneously following the realization of a single public signal. In a sequential procedure, receivers receive information and take actions sequentially. We characterize the conditions under which the optimal sequential procedure leads to a higher payoff and characterize the optimal ordering of actions.

We investigate the importance of subjective expectations of returns to and effort costs of the two principal investments that mothers make in newborns: breastfeeding and stimulation. We find heterogeneity across mothers in rural Pakistan in expected effort costs and expected returns for outcomes in the cognitive, socio-emotional and health domains, and that this contributes to explaining heterogeneity in investments. We find no significant differences across women in preferences for child developmental outcomes. We simulate the impact of alternative policies on investments. Our findings highlight the relevance of interventions designed to address maternal depression and reduce perinatal fatigue alongside interventions that increase perceived returns to investments.

We consider a classical auction setting in which an asset/project is sold to buyers who privately receive signals about expected payoffs, and payoffs are more sensitive to a bidder's signal if he runs the project than if another bidder does. We show that a seller can increase revenues by sometimes allocating cash‐flow rights and control to different bidders, for example, with the highest bidder receiving cash flows and the second‐highest receiving control. Separation reduces a bidder's information rent, which depends on the importance of his private information for the value of his awarded cash flows. As project payoffs are most sensitive to a bidder's information if he controls the project, allocating cash flow to another bidder lowers bidders' informational advantage. As a result, when signals are close, the seller can increase revenues by splitting rights between the top two bidders.

We estimate impacts of male job loss, female job loss, and male unemployment benefits on domestic violence (DV) in Brazil. We merge individual-level employment and welfare registers with different measures of DV: judicial cases brought to criminal courts, the use of public shelters by victims, and mandatory DV notifications by health providers. Leveraging mass layoffs for identification, we first show that both male and female job loss, independently, lead to large, and pervasive increases in DV. Using a regression discontinuity design, we then show that access to unemployment benefits does not reduce DV while benefits are being paid, and it leads to higher DV risk once benefits expire. Our findings can be explained by the negative income shock brought by job loss and by increased exposure of victims to perpetrators, as partners tend to spend more time together after displacement. Although unemployment benefits partially offset the income drop following job loss, they reinforce the exposure shock as they increase unemployment duration. Since our results cannot be explained by prominent DV theories, we propose a simple model formalizing these mechanisms

We provide causal evidence for the role of warfare in the development of medieval constitutionalism. Using novel data on the universe of German cities between 1290 and 1710, we show that military conflicts led to city councils that were larger, more likely to be elected by citizens, and more likely to include representatives of craft guilds. Additionally, these conflicts resulted in a substantial increase in local fiscal and spending capacity. We exploit the gender of the firstborn children of local nobles as a source of exogenous variation in conflicts.

We estimate the impacts of temperature on alleged and substantiated child maltreatment among young children using administrative data from state child protective services agencies. Leveraging short-term weather variation, we find increases in the number of young children involved in cases of alleged and substantiated maltreatment during hot periods. Additional analysis identifies neglect as the temperature-sensitive maltreatment type, and we find some evidence that adaptation via air conditioning mitigates this relationship. Given that climate change will increase exposure to extreme temperatures, our findings speak to additional costs of climate change among the most vulnerable.

This paper assesses the effect of the creation of specialised intimate partner violence (IPV) courts on the reporting of IPV, and the incidence of IPV homicides in Spain. We find that the opening of a specialised IPV court increases the reporting of IPV by nearly 122 offences per 100,000 inhabitants, or 28% in the preferred specification. The rise in reporting is primarily driven by an increase in the reporting of moderate offences. We do not find conclusive evidence on the effects of specialised courts on IPV homicides.

Using two decades of data from 12 low-income countries in West Africa, we show that dust carried by harmattan trade winds increases infant and child mortality. Health investments respond to dust exposure, consistent with compensating behaviours. Despite these efforts, surviving children still exhibit negative health impacts. Our data allow us to investigate differential impacts over time and across countries. We find declining impacts over time, suggesting adaptation. Using national-level measures of macroeconomic conditions and health resources, we find suggestive evidence that both economic development and public health improvements have contributed to this adaptation, with health improvements playing a larger role.

We study the impact of weak identification in discrete choice models, and provide insights into the determinants of identification strength in these models. Using these insights, we propose a novel test that can consistently detect weak identification in commonly applied discrete choice models, such as probit, logit, and many of their extensions. Furthermore, we demonstrate that when the null hypothesis of weak identification is rejected, Wald-based inference can be carried out using standard formulas and critical values. A Monte Carlo study compares our proposed testing approach against commonly applied weak identification tests. The results simultaneously demonstrate the good performance of our approach and the fundamental failure of using conventional weak identification tests for linear models in the discrete choice model context. Lastly, we apply our approach in two empirical examples: married women labor force participation, and US food aid and civil conflicts.

This paper provides an exhaustive characterization of the asymptotic null distribution of Wald-type statistics for testing restrictions given by polynomial functions—which may involve singularities—when the limiting distribution of the parameter estimator is absolutely continuous (e.g., Gaussian). In addition to the well-known finite-sample noninvariance, there is also an asymptotic noninvariance (nonpivotality): with standard critical values, the test may either under-reject or over-reject, and even diverge under the null hypothesis. The asymptotic distribution of the test statistic can vary under the null hypothesis and depends on the true unknown parameter value. All these situations are possible in testing restrictions which arise in the statistical and econometric literatures, for example, for examining the specification of ARMA models, causality at different horizons, indirect effects, zero determinant hypotheses on matrices of coefficients, and other situations where singularities cannot be excluded. We provide the limit distribution and general bounds for the single restriction case. For multiple restrictions, we give a necessary and sufficient condition for the existence of a limit distribution, and its form if it exists.

This paper develops a new approach to detecting electoral fraud. Our context involves repeaters, individuals voting in multiple states in the U.S. during 19th Century Congressional Elections. Given high travel times, and the associated difficulties of voting in multiple states on the same day, we exploit the staggered introduction of holding federal elections on the first Tuesday after the first Monday in November (1T1M). The key finding is that county-level turnout rates fell when the closest neighboring state coordinated on 1T1M. This result is consistent with 1T1M adoption making repeating more difficult. In terms of mechanisms, the pattern is stronger in states that had not yet adopted the secret ballot, consistent with the secret ballot itself reducing voter fraud. The results are also stronger in open-seat elections, which tend to be more competitive. Finally, the pattern is also driven by smaller population counties, consistent with repeaters particularly inflating turnout rates in these places.

We conduct a natural field experiment with a major European party to test whether giving party supporters more voice increases their engagement in the party’s electoral campaign. In the experiment, the party asked a random subset of supporters for their opinions on the importance of different policy areas. Giving supporters opportunities to voice their opinions increases their engagement in the campaign as measured using behavioral data from the party’s smartphone application. Survey data reveals that giving voice also increases other margins of campaign effort as well as perceived voice. Our evidence highlights the importance of voice for increasing political engagement.

We estimate the impact of COVID-19 vaccination on psychological well-being using information from a large-scale panel survey representative of the UK population. Exploiting exogenous variation in the timing of vaccinations, we find that vaccination increases psychological well-being (GHQ-12) by 0.12 standard deviations, compensating for one-half of the deterioration in mental health caused by the pandemic. This improvement persists for at least two months, and is linked to higher engagement in social activities and a decrease in the self-reported likelihood of contracting COVID-19. The main beneficiaries are individuals who became mentally distressed during the pandemic, supporting their prioritization in vaccination roll-outs. Conversely, individuals who harbored concerns about potential vaccine side effects show no improvement in psychological well-being upon vaccination, underscoring the importance of public confidence in vaccine safety and efficacy. Accounting for the improvement in psychological well-being increases the benefits of vaccination by around 50%.

Human beings want autonomy. This study offers longitudinal multicountry evidence (for Australia, Germany, the United Kingdom, and England) on how people feel as they go through their working lives. Job autonomy peaks early and then collapses. From the age of approximately 40 y old, the typical worker endures diminishing feelings of autonomy through the next three decades of their career. Evidence on objective measures of autonomy—including job titles—suggests that these feelings are not an emotional illusion. Perceptions and reality match: “Demotions,” whether formal or informal, are apparently commonplace. The fact that autonomy exhibits this pattern in the modern workplace is, to our knowledge, not known by social and behavioral scientists.

Does the allocation of incentives across the hierarchy of an organization matter for its performance? In an experiment with a large public health organization, we find that health care provision is highly affected by how incentives are allocated between frontline workers and their supervisors. Sharing incentives equally between these two layers raises health visits by 61% compared with unilateral allocations and uniquely improves health service provision and health outcomes. We provide reduced-form and structural evidence that effort complementarities and contractual frictions drive these results and explore the implications for the optimal design of incentive policies in multilayered organizations

We study the use of Temporal-Difference learning for estimating the structural parameters in dynamic discrete choice models. Our algorithms are based on the conditional choice probability approach but use functional approximations to estimate various terms in the pseudo-log-likelihood function. We suggest two approaches: The first—linear semi-gradient—provides approximations to the recursive terms using basis functions. The second—Approximate Value Iteration—builds a sequence of approximations to the recursive terms by solving non-parametric estimation problems. Our approaches are fast and naturally allow for continuous and/or high-dimensional state spaces. Furthermore, they do not require specification of transition densities. In dynamic games, they avoid integrating over other players’ actions, further heightening the computational advantage. Our proposals can be paired with popular existing methods such as pseudo-maximum-likelihood, and we propose locally robust corrections for the latter to achieve parametric rates of convergence. Monte Carlo simulations confirm the properties of our algorithms in practice.

Focusing on the 1989 Canada-United States Free Trade Agreement (CUSFTA), we examine how regional content requirements in Free Trade Areas (FTAs) affect competition and prices in intermediate goods markets. Content requirements in FTAs shelter firms from competition more than an equivalent trade-protection tariff would. We document patterns in US industry-level census data and Canadian product-level export data that align with theoretical predictions: stricter and binding content requirements are linked to higher prices and more firm entry. These results underscore the role of content requirements in shaping market structure and market power, with implications for the choice of preferential trade arrangements.

This paper examines the effect of real-time corporate emissions data disclosure on housing markets, leveraging China’s 2017 “Installing, Erecting, and Networking” (IEN) policy as a quasi-natural experiment. Using a difference-in-difference-in-differences (DDD) analysis on over 35,000 housing transactions near 13 Waste-to-Energy (WtE) incineration plants, we find that the real-time emissions data disclosure significantly attenuates the housing price gradient by approximately 34.7%. This attenuation corresponds to an economic gain equivalent to around 39% of an urban resident’s annual disposable income, reflecting a substantial reduction in residents’ perceived environmental risks. Event study analysis demonstrates that the housing market response emerges rapidly after the introduction of real-time disclosure and remains persistent thereafter. Further heterogeneity analyses indicate that the positive effects of the disclosure are more pronounced in urban areas and are stronger near plants that operate in compliance with emission standards, employ advanced flue gas abatement technologies, and have smaller treatment capacities. Our findings underscore the novel role of real-time emissions data disclosure in mitigating environmental risk perceptions, offering key policy implications for enhancing public acceptance of potentially controversial environmental infrastructure.

We propose two types of Quantile Graphical Models: (i) Conditional Independence Quantile Graphical Models (CIQGMs) characterize the conditional independence by evaluating the distributional dependence structure at each quantile index, as such, those can be used for validation of the graph structure in the causal graphical models; (ii) Prediction Quantile Graphical Models (PQGMs) characterize the statistical dependencies through the graphs of the best linear predictors under asymmetric loss functions. PQGMs make weaker assumptions than CIQGMs as they allow for misspecification. One advantage of these models is that we can apply them to large collections of variables driven by non-Gaussian and non-separable shocks. Because of QGMs’ ability to handle large collections of variables and focus on specific parts of the distributions, we could apply them to quantify tail interdependence. The resulting tail risk network can be used for measuring systemic risk contributions that help make inroads in understanding international financial contagion and dependence structures of returns under downside market movements.

Academics play a vital role in the generation and dissemination of knowledge, ideas and narratives. Social media provide new, more direct ways of science communication. Yet, since not all academics engage with social media, the sample that does so may have an outsized influence on shaping public perceptions of academia through the set topics they engage with and their style and tone of communication. We describe patterns in academics’ expression online using an international dataset covering nearly 100,000 scholars linking their Twitter content to academic records. We document large and systematic variation in politically salient academic expression concerning climate action, cultural and economic concepts. We show that US academics often diverge from the US Twitter population at large in topic focus and style, although academics are not necessarily more extreme in their beliefs. Future work should examine potential impacts on public trust and the reasons why academics express themselves politically on social media.

We study how do-or-die threats ending negotiations affect gridlock and welfare when two opposing parties bargain. Failure to agree on a deal in any period implies a continuation of the negotiation. However, under brinkmanship, agreement failure in any period may precipitate a crisis with a small chance. In equilibrium, such brinkmanship threats improve the probability of an agreement, but also increase the risk of crisis. Brinkmanship reduces welfare when one might think it is most needed: severe gridlock. In this case, despite this global welfare loss, a party has incentives to use brinkmanship strategically to obtain a favorable bargaining position.

Many European countries have raised the minimum legal drinking age (MLDA) from 16 to 18 over the past decades. These policies often comprise a bundle of reforms including restrictions on alcohol sales to minors, venue access limitations, and advertising controls. We provide novel evidence of the impact of MLDA changes on educational outcomes by exploiting their staggered timing across Spanish regions. Alcohol consumption among adolescents aged 14–17 decreased by 7 to 17% and exam performance improved by 4% of a standard deviation. We also observe a 10% decrease in the use of anxiolytics and hypnosedatives, suggesting improved mental health. There are no significant changes in the use of other substances, leisure habits or study effort. These findings are consistent with neurobiological evidence that alcohol directly impairs cognitive development and increases anxiety-related behaviours. Reducing teenage alcohol consumption represents a substantial opportunity to improve educational outcomes in Europe, where youth drinking rates remain notably high.

This article studies the verifiable disclosure of data by an informed expert whose bias direction is unknown to the decision maker. It shows that the expert's disclosure induces the decision maker to choose an action biased in the expert's desired direction. The pattern of manipulation depends on the weighted mass of left and right-biased expert types with the same ideal action. All expert types with bias on the side with lower weighted mass, and a subset of types with bias on the other side, induce the choice of their ideal action; they fully manipulate. All other expert types partially manipulate.

New technologies allow perfect detection of environmental violations at near-zero marginal cost, but take-up is low. We conducted a field experiment to evaluate enforcement of water conservation rules with smart meters in Fresno, CA. Households were randomly assigned combinations of enforcement method (automated or in-person inspections) and fines. Automated enforcement increased households’ punishment rates from 0.1% to 14%, decreased summer water use by 3%, and reduced violations by 17%, while higher fine levels had little effect. However, automated enforcement also increased customer complaints by 1,102%, ultimately causing its cancellation and highlighting that political considerations limit technological solutions to enforcement challenges

Using administrative data on the universe of U.K. taxpayers, we study the contribution of migrants to the rise in U.K. top incomes. We show that migrants are over-represented at the top of the income distribution, with migrants twice as prevalent in the top 0.01% as anywhere in the bottom 97% of taxpayers. These high incomes are predominantly from labor, rather than capital, and migrants are concentrated in only a handful of industries, predominantly finance. All of the observed growth in the U.K. top 1% income share over the past 20 years has accrued to migrants.

We propose a model of elections in which partisans wish to convince themselves that their party is the better choice. They select information sources from a broad array of media outlets with different biases to achieve that goal, but they may not always succeed due to their rationality which acts as a constraint. We explore how asymmetries between the two political sides skew electoral outcomes despite rationality. Here we consider salient examples such as asymmetric exposure or asymmetric trust in media, as well as propaganda, but this notion of partisanship is easily applicable to a wide variety of electoral contexts.

Literature has shown that air pollution can have short- and long-term adverse effects on physiological and cognitive performance. In this study, we estimate the effect of increased pollution levels on the likelihood of accidents at construction sites, a significant factor related to productivity losses in the labor market. Using data from all construction sites and pollution monitoring stations in Israel, we find a strong and significant causal effect of nitrogen dioxide (NO), one of the primary air pollutants, on construction site accidents. We find that a 10-ppb increase in NO levels increases the likelihood of an accident by as much as 25 %. Importantly, our findings suggest that these effects are non-linear. While moderate pollution levels, according to EPA standards, compared to clean air levels, increase the likelihood of accidents by 138 %, unhealthy levels increase it by 377 %. We present a mechanism where the effect of pollution is exacerbated under conditions of high cognitive strain or reduced awareness. Finally, we perform a cost-benefit analysis, supported by a nonparametric estimation calculating the implied number of accidents due to NO exposure, and examine a potential welfare-improving policy to subsidize the closure of construction sites on highly polluted days.

Does low trust in workers discourage firms from hiring? We conduct an experiment in Ghana with real entrepreneurs who have the option to hire anonymous workers for a trivial but tedious task. Shirking attracts no penalty and completion of the task is an indicator of trustworthiness. We elicit employers’ expectations and study how they change with random signals of workers’ previous behavior. We find that employers underestimate workers’ trustworthiness, which reduces hiring and profits. Negative signals lower employers’ expectations, while positive signals do not affect them. This asymmetry can help to sustain an equilibrium with limited experimentation and biased beliefs.

Blind adoption of opinions put forward by political parties and influential figures can sometimes be harmful. Focusing on cases where the partisan gap on policy support has not yet arisen, we investigate whether its formation can be prevented by encouraging prior active engagement with non-partisan information. To address this question, we recruited N=851 Republicans for a study about net neutrality, an issue largely unfamiliar to the electorate, which refers to equal treatment of all internet traffic. In a pre-registered experiment, we randomly changed the order in which the following two types of information were provided: (i) partisan, underscoring Republicans’ opposition and Democrats’ support, and (ii) non-partisan, where the participants evaluated factual arguments about the pros and cons of the policy. Despite holding total information constant, we find that those who saw the non-partisan block first donated 46% more to a charity advocating for net neutrality (p=0.001). The treatment effect persisted in an obfuscated follow-up study, conducted several weeks after the intervention. However, we do not find an effect on donations when repeating the main study with a sample of Democrats.

While many socialist countries suffered from harsh economic crises, studying their impacts on economic and political attitudes is challenging because of the scarcity of reliable data in non-democratic contexts. We study a democratic socialist setting where we have ample information on such attitudes: the Israeli kibbutzim. Exploiting an economic crisis that hit some kibbutzim more than others, we find that the crisis led to reduced support for leftist political parties. This effect persisted for over 20 years after the crisis had ended. We document that the electoral movement was rooted in a rightward shift in economic attitudes, suggesting that economic crises may undermine socialist regimes by silently changing attitudes toward them. In our unique setting, we can also study recovery mechanisms from the crisis. First, we find that while a sharp debt relief arrangement restored trust in the leadership, it did not reverse the impact of the crisis on economic attitudes. Second, as part of their efforts to recover from the crisis, kibbutzim liberalized their labor markets. Analyzing the staggered shift away from equal sharing to market-based wages, we find that this labor market liberalization led kibbutz members to move further rightward in their political voting and economic attitudes.

Free and fair elections should incentivize elected officials to exert effort and enable citizens to select representative politicians and occasionally replace incumbents. However, incumbency advantage and coordination failures possible in multi-party systems may jeopardize this process. We ask whether these two forces compound each other. Using a regression discontinuity design (RDD) in French two-round local and parliamentary elections, we find that close winners are more likely to run again and to win the next election by 33 and 25 percentage points, respectively. Incumbents who run again personalize their campaign communication more and face fewer ideologically close competitors, revealing that parties from the incumbent’s orientation coordinate more effectively than parties on the losing side. A complementary RDD shows that candidates who marginally qualify for the runoff also rally new voters. We conclude that party coordination on the incumbent and voter coordination on candidates who won or gained visibility in a previous election both contribute to incumbents’ future success.

We propose a Bayesian approach to Local Projections (LPs) that optimally addresses the empirical bias-variance trade-off intrinsic in the choice between direct and iterative methods. Bayesian Local Projections (BLPs) regularize LP regressions via informative priors and estimate impulse response functions that capture the properties of the data more accurately than iterative VARs. BLPs preserve the flexibility of LPs while retaining a degree of estimation uncertainty comparable to Bayesian VARs with standard macroeconomic priors. As regularized direct forecasts, BLPs are also a valuable alternative to BVARs for multivariate out-of-sample projections.

In asset pricing models with stochastic volatility, uncertainty about volatility affects risk premia through two channels: aversion to decreasing returns and aversion to increasing volatility. We analyze the identification of and robust inference for structural parameters measuring investors’ aversions to these risks: the return risk price and the volatility risk price. In the presence of a leverage effect (instantaneous causality between the asset return and its volatility), we study the identification of both structural parameters with the price data only, without relying on additional option pricing models or option data. We analyze this identification challenge in a nonparametric discrete-time exponentially affine model, complementing the continuous-time approach of Bandi and Renò (2016). We then specialize to a parametric model and derive the implied minimum distance criterion relating the risk prices to the asset return and volatility’s joint distribution. This criterion is almost flat when the leverage effect is small, and we introduce identification-robust confidence sets for both risk prices regardless of the magnitude of the leverage effect.

Westling and Carone (Ann. Statist. 48 (2020) 1001–1024) proposed a framework for studying the large sample distributional properties of generalized Grenander-type estimators, a versatile class of nonparametric estimators of monotone functions. The limiting distribution of those estimators is representable as the left derivative of the greatest convex minorant of a Gaussian process whose monomial mean can be of unknown order (when the degree of flatness of the function of interest is unknown). The standard nonparametric bootstrap is unable to consistently approximate the large sample distribution of the generalized Grenander-type estimators even if the monomial order of the mean is known, making statistical inference a challenging endeavour in applications. To address this inferential problem, we present a bootstrap-assisted inference procedure for generalized Grenander-type estimators. The procedure relies on a carefully crafted, yet automatic, transformation of the estimator. Moreover, our proposed method can be made “flatness robust” in the sense that it can be made adaptive to the (possibly unknown) degree of flatness of the function of interest. The method requires only the consistent estimation of a single scalar quantity, for which we propose an automatic procedure based on numerical derivative estimation and the generalized jackknife. Under random sampling, our inference method can be implemented using a computationally attractive exchangeable bootstrap procedure. We illustrate our methods with examples and we also provide a small simulation study. The development of formal results is made possible by some technical results that may be of independent interest.

Does self‐governance, a hallmark of democratic societies, foster norms of generalized cooperation? Does this effect persist, and if so, why? I investigate these questions using a natural experiment in Switzerland. In the Middle Ages, the absence of an heir resulted in the extinction of a prominent noble dynasty. As a result, some Swiss municipalities became self‐governing, whereas the others remained under feudalism for another 600 years. Evidence from a behavioral experiment, the World Values Survey and the Swiss Household Panel consistently show that individuals from historically self‐governing municipalities exhibit stronger norms of cooperation today. Referenda data on voter‐turnout allow me to trace these effects on individually costly and socially beneficial actions for over 150 years. Furthermore, norms of cooperation map into prosocial behaviors like charitable giving and environmental protection. Uniquely, Switzerland tracks every family's place of origin in registration data, which I use to demonstrate persistence from cultural transmission in a context of historically low migration.

I study the determinants of childhood lead screening using all Illinois birth records (2001–2014), matched to lead testing records and geocoded housing age data. Housing age measures lead risk, as older houses disproportionally have lead paint. Changes in geographic access to providers provide variation in non-monetary costs of testing. Higher costs reduce screening among low- and high-risk households alike. Thus, self-selection based on screening costs does not appear to improve targeting, even though high-risk households are willing to pay $31-419 more than low-risk households for screening. Screening incentives would be cost-effective for reasonable values of lead poisoning externalities.

We examine a dynamic disclosure model in which the value of a firm follows a random walk. Every period, with some probability, the manager learns the firm's value and decides whether to disclose it. The manager maximizes the market perception of the firm's value, which is based on disclosed information. In equilibrium, the manager follows a threshold strategy with thresholds below current prices. He sometimes reveals pessimistic information that reduces the market perception of the firm's value. He does so to reduce future market uncertainty, which is valuable even under risk-neutrality.

I document a substantial rise in the proportion of job seekers who are classified as out of the labour force in the United States since 1980. I propose an adjusted unemployment rate to account for these searchers; the adjustment increases the unemployment rate by 5.2 percentage points, rids the unemployment rate of its downward trend and decreases volatility by 50%. I also construct a measure of total search effort in the economy, including employed job seekers. Finally, estimates of the Phillips curve using the adjusted unemployment rate or total searcher rate show no sign of a flattening output-inflation relationship in the post-2008 recession period.

We study the role of professional networks in facilitating emigration of Jewish academics dismissed from their positions by the Nazi government. We use individual-level exogenous variation in the timing of dismissals to estimate causal effects. Academics with more ties to early emigres (emigrated 1933–1934) were more likely to emigrate. Early emigres functioned as "bridging nodes" that facilitated emigration to their own destination. We also provide evidence of decay in social ties over time and show that professional networks transmit information that is not publicly observable. Finally, we study the relative importance of three types (family, community, professional) of social networks.

This paper evaluates a large urban public works program randomly rolled out across neighborhoods of Addis Ababa, Ethiopia. We find the program increased public employment and reduced private labor supply among beneficiaries and improved local amenities in treated locations. We then combine a spatial equilibrium model and unique commuting data to estimate the spillover effects of the program on private sector wages across neighborhoods: under full program rollout, wages increased by 18.6 percent. Using our model, we show that welfare gains to the poor are six times larger when we include the indirect effects on private wages and local amenities.

We introduce an adaptive targeted treatment assignment methodology for field experiments. Our Tempered Thompson Algorithm balances the goals of maximizing the precision of treatment effect estimates and maximizing the welfare of experimental participants. A hierarchical Bayesian model allows us to adaptively target treatments. We implement our methodology in Jordan, testing policies to help Syrian refugees and local jobseekers to find work. The immediate employment impacts of a small cash grant, information and psychological support are small, but targeting raises employment by 1 percentage-point (20%). After 4 months, cash has a sizable effect on employment and earnings of Syrians.

We study a model of time preference in which both current consumption and the memory of past consumption enter “experienced utility”—or the felicity—of an individual. An individual derives overall utility from her own felicity and the anticipated felicities of future selves. These postulates permit an agent to anticipate future regret in current decisions, and generate a set of novel testable implications in line with empirical evidence. The model can be applied to disparate phenomena, including present bias, equilibrium savings behavior, anticipation of regret, and career concerns.

We propose a method to allow usual business cycle models to account for the unusual COVID episode. The pandemic and the public and private responses to it are represented by a new shock called the Covid shock, which loads onto wedges that underlie the usual shocks and comes with news about its evolution. We apply our method to a standard medium-scale model, estimating the loadings with 2020q2 data and the evolving news using professional forecasts. The Covid shock accounts for most of the early macroeconomic dynamics, was inflationary and a persistent drag on activity, and the majority of its effects were unanticipated. We also show how the Covid shock can be used to estimate DSGE models with data before, during, and after the pandemic.

We use a randomized experiment to evaluate the impact of providing richer information about prospective jobs to vocational trainees on their employment outcomes. The setting of the study is the vocational training program DDU-GKY in India. We find that including in the training two information sessions about placement opportunities make trainees 18% more likely to stay in the jobs in which they are placed. We provide suggestive evidence that the effect is driven by improved selection into training: as a result of the intervention, trainees that are over-optimistic about placement jobs are more likely to drop out before placement.

This paper estimates the size of the media multiplier, an easily generalizable model-based measure of how far media coverage magnifies the economic response to shocks. We combine monthly aggregated and anonymized credit card activity data from 114 card issuing countries in 5 destination countries with a large corpus of news coverage in issuing countries reporting on violent events in the destinations. To define and quantify the media multiplier we estimate a model in which latent beliefs, shaped by either events or news coverage, drive card activity. According to the model, media coverage can more than triple the economic impact of an event. We document, through our model, that this effect is highly heterogenous and depends on the broader media representation of countries in each others news. We speculate about the role of the media in driving international travel patterns an.

Children exposed to pollutants like lead have lower academic achievement and are more likely to engage in risky behavior. However, little is known about whether lead-exposed children affect the long-run outcomes of their peers. We estimate these spillover effects using unique data on preschool blood lead levels (BLLs) matched to education data for all students in North Carolina public schools. We compare siblings whose school-grade cohorts differ in the proportion of children with elevated BLLs, holding constant school and peers’ demographics. Having more lead-exposed peers is associated with lower high school graduation and SAT-taking rates and increased suspensions and absences.

We investigate the impacts of a perinatal psychosocial intervention on trajectories of maternal mental health and child skills, from birth to age 3. We find improved maternal mental health and functioning (0.17–0.29 SD), modest but imprecisely estimated improvements in parenting (0.07–0.11 SD), and transitory improvements in child socio-emotional development (0.06–0.39 SD). The intervention had negligible influence on physical health and cognition. Estimates of a skill production function reveal the intervention attenuated the negative association between maternal depression and child outcomes, and it narrowed outcome gaps between mothers who were and were not depressed in pregnancy.

Gravity equations are an important tool in empirical international trade research. We study to what extent sector-level parameters can be recovered from aggregate gravity equations estimated via Poisson pseudo maximum likelihood. We show that in the leading case where trade cost regressors do not vary at the sector level, estimates obtained with aggregate data have a clear interpretation as a weighted average of sectoral elasticities. Otherwise the estimates are biased, but researchers may possibly infer the direction of the bias. We illustrate our results by revisiting Baier and Bergstrand’s (2007) influential study of the effects of free trade agreements.

We examine the persistence of teachers' gender biases by following teachers over time in different classes. We find a very high correlation of gender biases for teachers across their classes. We find a substantial impact of gender bias on student performance in university admissions exams, choice of university field of study, and quality of the enrolled program. The effects on university choice outcomes are larger for girls, explaining some gender differences in STEM majors. Teachers with lower value-added are also more likely to be gender biased.

We examine how the evaluation of research studies in economics depends on whether a study yielded a null result. Studies with null results are perceived to be less publishable, of lower quality, less important and less precisely estimated than studies with large and statistically significant results, even when holding constant all other study features, including the sample size and the precision of the estimates. The null result penalty is of similar magnitude among PhD students and journal editors. The penalty is larger when experts predict a large effect and when statistical uncertainty is communicated with p-values rather than standard errors. Our findings highlight the value of a pre-result review.

Seasonal infectious diseases can cause demand and supply pressures that reduce the ability of healthcare systems to provide high-quality care. This may generate negative spillover effects on the health outcomes of patients seeking medical help for unrelated reasons. Separating these indirect burdens from the direct consequences for infected patients is usually impossible due to a lack of suitable data and an absence of population testing. However, this paper finds robust empirical evidence of excess mortality among non-COVID-19 patients in an integrated public healthcare system: the English National Health Service (NHS). Analysing the forecast error in the NHS’ model for predicted mortality, we find at least one additional excess death among patients who sought medical help for reasons unrelated to COVID-19 for every 42 COVID-19-related deaths in the population. We identify COVID-19 pressures as a key driver of non-COVID-19 excess mortality in NHS hospitals during the pandemic, and characterize the hospital populations and medical conditions that were disproportionately affected. Our findings have substantive relevance in shaping our understanding of the wider burden of COVID-19, and other seasonal diseases more generally, and can contribute to debates on optimal public health policy.

In practice mediation operates through shuttle diplomacy: the mediator goes back and forth between parties, meeting them in private. We model shuttle diplomacy as a dynamic procedure. The mediator helps each party to gradually discover (privately) her value from settlement and re-assess her bargaining position, while also proposing the terms of the deal. We show that shuttle diplomacy always allows parties to achieve an ex-post efficient final settlement. In contrast, this is not possible with a static mediation procedure. In addition, if parties have symmetric prior value distributions, shuttle diplomacy guarantees a fair split of the social value from settlement.

This paper examines how natural disasters affect local public finances and their interplay with intergovernmental transfers and external resources. Exploiting the randomized nature of the 2013 Typhoon Haiyan, one of the most devastating natural disasters in recent history, we document its causal effect on the local government fiscal dynamics. Combining data on local government finance with reports on the level of damages and using difference-in-differences with instrumental variable to analyze the data, we show that local public revenue and expenditures remain largely unaffected, except for debt payments. However, we find important heterogeneity in local revenue responses: poorer municipalities raised comparatively lower revenue in the aftermath of the Typhoon. We also provide evidence that external funding did not lead to lower tax collection efforts, but instead leads to higher local expenditures, suggesting that disaster aid does not cause a moral hazard problem in local governments' spending decisions.

A principal incentivizes a group of agents to work by choosing a monitoring structure and a scheme of performance-contingent rewards. The monitoring structure partitions the set of agents into monitoring teams, each delivering a signal of joint performance. We show that unlike under partial implementation, the principal always exhausts her monitoring capacity to optimally implement work as a unique outcome. Optimal monitoring teams are homogeneous between them: equally sized and with agents allocated in an anti-assortative fashion. Higher-effort-cost agents receive lower rents, and they tend to be monitored more closely than lower-effort-cost agents when the principal's allocation is constrained.

Subjects were asked to predict the choice made by a hypothetical individual, based on a small sample of his past choices in identical situations. Each of the alternatives facing the individual has a number of components. When the data is presented explicitly as a distribution of past choices, most subjects use the holistic procedure according to which the prediction is the most common choice made in the past. Nevertheless, a significant minority of subjects use atomistic procedures, which relate to the various components individually. When the distribution is not explicitly presented but can be derived from the data, subjects apply both atomistic procedures and holistic rules of thumb.

This paper explores the implications of voter loss-aversion and imperfect recall for the dynamics of electoral competition in a simple Downsian model of repeated elections. The interplay between the median voter’s reference point and political parties’ choice of platforms generates a dynamic process of (de)polarization, following an initial shift in party ideology. This is consistent with the gradual nature of long-term trends in polarization in the US Congress.

We consider a dynamic principal-agent problem, where the sole instrument the principal has to incentivize the agent is the disclosure of information. The principal aims at maximizing the (discounted) number of times the agent chooses the principal's preferred action. We show that there exists an optimal policy, where the principal recommends its most preferred action and discloses information as a reward in the next period, until either this action becomes statically optimal for the agent or the agent perfectly learns the state.

We present a theory of monopoly protection by means of entry in adjacent markets that have a common customer base (i.e., envelopment). A firm dominant in its market enters a data-rich secondary market and engages in predatory pricing and privacy-policy tying. We define the latter as conditioning service provision to the subscription of a privacy policy that allows bundling of user data across all sources. Acquiring data from the secondary market confers an advantage in the data-intensive primary market that shields the dominant firm from entry, thus harming consumers. We discuss potential remedies, including data unbundling and portability.

Can revenue sharing of resource rents be a source of distributive conflict? Can cohesive institutions avoid such conflicts? We exploit exogenous variation in local government revenues and new data on local democratic institutions in Nigeria to study these questions. We find a strong link between rents and conflict. Conflicts are highly organized and concentrated in districts and time periods with unelected local governments. Once local governments are elected these relationships are much weaker. We argue that elections produce more cohesive institutions that help limit distributional conflict between groups. Throughout, we confirm these findings using individual level survey data.

There has been a phenomenal global increase in the proportion of women in politics in the last two decades, but there is no evidence of how this has influenced economic performance. We investigate this using data on competitive elections to India’s state assemblies, leveraging close elections to isolate causal effects. We find significantly higher growth in economic activity in constituencies that elect women and no evidence of negative spillovers to neighbouring male-led constituencies, consistent with net growth. Probing mechanisms, we find evidence consistent with women legislators being more efficacious, less corrupt and less vulnerable to political opportunism