We develop a Heterogeneous Agents New Keynesian (HANK) model with a job ladder and endogenous on-the-job search (OJS) that challenges the traditional view of a negative relationship between unemployment and inflation. On the one hand, OJS is inflationary, sparking wage competition among firms to attract or retain workers. On the other hand, OJS strengthens workers’ bargaining power, reducing firms’ incentives to post vacancies and thereby increasing unemployment. The model explains the effects of the 2012 Danish tax reform, which influenced OJS differentially across the income distribution, on the employment transitions and wage growth observed in the microdata.

Does anticipation of discrimination (beliefs individuals hold about the behavior of others towards them) undermine cooperation? We develop a new design to isolate the role of anticipation from confounding motives. Using the trust game, we measure anticipation as the double difference between the amount transferred to outgroup vs. ingroup trustees when the trustor’s own identity is revealed vs. concealed. Using the context of affective polarization, we find that anticipation of discrimination undermines cooperation by the same magnitude as taste-based and statistical discrimination. However, anticipation of discrimination is misperceived. Our method can be used to study anticipation of discrimination across societal divisions.

We develop an empirical framework to analyze vertical relationships with manufacturer-retailer bargaining. Our key innovation is the introduction of a novel Nash-in-Nash bargaining model that incorporates uncertainty in retailers’ pricing responses to wholesale prices. This model extends existing Nash-in-Nash frameworks by relaxing assumptions about the timing of wholesale and retail price setting. We show that our model can be microfounded by a two-stage noncooperative game with delegated negotiations. We propose a two-step strategy that separably identifies bargaining and responsiveness parameters and implies a Generalized Method of Moments estimation procedure.

Investors evaluate their entire portfolio, not individual assets, striving to balance returns and risks through effective diversification. This paper introduces a flexible demand system accommodating heterogeneous substitution, cross-asset complementarities, and diverse investment strategies. By relaxing multinomial logit assumptions, our model better captures portfolio allocation decisions, linking portfolio weights to both individual asset and portfolio-wide characteristics. We propose a demandinverse approach for the identification of structural parameters. This approach implies a Generalized Method of Moments estimation procedure with novel instruments addressing cross-asset dependencies. Monte Carlo simulations validate the model, demonstrating improved finite-sample properties over standard multinomial logit frameworks.

China has experienced a remarkable rise in living standards over four decades of economic reforms, alongside a tremendous increase in inequalities. In this context, do Chinese people support redistribution of wealth gained through reform windfalls? To answer this question, we conducted an online survey experiment with a nationally representative sample from China (N = 2, 000). The treatment group was shown examples of wealth acquired through typical reform-era pathways requiring minimal ability or effort. This exposure led to a 0.1 standard deviation decrease in their support for redistribution. We propose a “reform windfall as redistribution” mechanism to explain this reduction : the treated group perceives the reform era as inherently redistributive, providing opportunities to escape systemic inequalities tied to the political system, thereby reducing the perceived need for formal redistribution. This decline in support is not driven by changes in fairness perceptions, as respondents do not attribute the wealth acquisition scenarios to ability or effort, nor do they view them as distinctly fair or unfair. Furthermore, we find limited evidence of heterogeneity, with one exception: individuals reporting higher economic pressure show an even greater reduction in redistributive support when exposed to the treatment. We hypothesize that this occurs because unmet expectations for upward mobility exacerbate their reactions to the treatment scenarios.

We document that inflation risk in the U.S. varies significantly over time and is often asymmetric. To analyze the first-order macroeconomic effects of these asymmetric risks within a tractable framework, we construct the beliefs representation of a general equilibrium model with skewed distribution of markup shocks. Optimal policy requires shifting agents’ expectations counter to the direction of inflation risks. We perform counterfactual analyses using a quantitative general equilibrium model to evaluate the implications of incorporating real-time estimates of the balance of inflation risks into monetary policy communications and decisions.

We study a class of two-way fixed effects index function models with a nonparametric link function and individual- (or time-) specific slopes. Our model alleviates potential misspecification errors due to the common practice of specifying a known link function such as Gaussian and its tail behavior. It also enables to incorporate richer unobserved heterogeneity in the marginal effects of covariates via heterogeneous slopes across individuals. We show the identification of the link function as well as the slopes and fixed effects parameters when both individual and time dimensions are large. We propose a nonparametric consistency result for the fixed effects sieve maximum likelihood estimators. Finally, we apply our method to the study of establishing exportation and illustrate the consequences of imposing Gaussian link function and homogeneity on the slope of distance.

Over the past decades, many European countries have raised the minimum legal drinking age (MLDA) from 16 to 18 years. This study provides novel evidence of the impact of this policy on educational outcomes by exploiting the staggered timing of MLDA changes across Spanish regions. Raising the MLDA decreased alcohol consumption among adolescents aged 14–17 by 8 to 18% and improved their exam performance by 4% of a standard deviation. This effect appears driven by alcohol’s direct impact on cognitive ability, as we find no significant changes in potential mediators like use of other substances or time spent on leisure activities, including socialising, sports, gaming, or internet use. We also observe a decrease in tranquilliser and sleeping pill use, suggesting improved mental health. Our findings indicate that reducing teenage alcohol consumption represents a significant opportunity to improve educational outcomes in Europe, where youth drinking rates remain notably high.

This paper leverages generative AI to build a network structure over 5,000 product nodes, where directed edges represent input-output relationships in production. We layout a two-step ‘build-prune’ approach using an ensemble of prompt-tuned generative AI classifications. The ’build’ step provides an initial distribution of edge predictions, the ‘prune’ step then re-evaluates all edges. With our AI-generated Production Network (AIPNET) in toe, we document a host of shifts in the network position of products and countries during the 21st century. Finally, we study production network spillovers using the natural experiment presented by the 2017 blockade of Qatar. We find strong evidence of such spill-overs, suggestive of on-shoring of critical production. This descriptive and causal evidence demonstrates some of the many research possibilities opened up by our granular measurement of product linkages, including studies of on-shoring, industrial policy, and other recent shifts in global trade.

This study examines the impact of emissions data disclosure on alleviating NIMBYism (Not In My Backyard) concerns surrounding Waste-to-Energy (WtE) incineration plants. Leveraging China’s 2017 “Installing, Erecting, and Networking” (IEN) policy as a quasi-natural experiment, we employ a difference-in-differences (DID) approach to analyze over 35,000 housing transactions near 13 plants. Results indicate that the IEN policy attenuates the housing price gradient by 30.43%, equivalent to 38% of an urban Chinese resident’s annual disposable income. This robust evidence highlights how transparency policies can enhance public trust and thus promote more sustainable urban development.

Talent is a key input in the delivery of public services, yet less is known about what affects the supply of talent for the public sector. This paper studies the role of political corruption in shifting talent allocation across public and private sector careers. I exploit a randomized anti-corruption audit program in Brazil together with comprehensive micro-data on educational and labor market outcomes of college students. Using a generalized difference-in- difference research design, I find that high-ability students in audited municipalities are less likely to choose majors tailored toward public sector careers, such as business administration and law. Moreover, tracking students to the labor market demonstrates that audits also lead to a lower share of high-ability students working as civil servants. Finally, I provide suggestive evidence that the effects of audits on talent allocation can be driven by the perception of lower rent-seeking returns and higher reputation costs. Taken together, these findings highlight an understudied negative consequence of corruption on the economy: the distortion of talent allocation toward rent-seeking in the public sector.

Despite its recognized inefficiency, the persistence of income hiding between spouses remains largely unaddressed in the literature. Our study suggests that one cause of persistency is that this behavior may provide strategic benefits, particularly by affecting labor supply decisions and overall household income. Using a field experiment involving low-income workers in Southeast Asia, we estimate the effects of randomly disclosing spousal income on productivity in a standardized work task. Our findings indicate that income disclosure significantly affects labor productivity compared to a nondisclosure scenario, in which spouses can conceal any income generated. The effects exhibit notable gender differences: when income is disclosed to their spouses, women decrease productivity, while men increase productivity. We introduce a two-stage game model and further empirical tests to demonstrate that these gender differences arise from disparities in bargaining power, with men holding significantly more bargaining power than women. Overall, this study sheds light on the unintended consequences of financial inclusion or pay transparency policies on both productivity and household inequality.

A decision-making agent is usually assumed to be Bayesian rational, or to maximize subjective expected utility, in the context of a completely and correctly specified decision model. Following the discussion in Hammond (2007) of Schumpeter's (1911, 1934) concept of entrepreneurship, and of Shackle's (1953) concept of potential surprise, this paper considers enlivened decision trees whose growth over time cannot be accurately modelled in full detail. An enlivened decision tree involves more severe limitations than model mis-specification, unforeseen contingencies, or unawareness, all of which are typically modelled with reference to a universal state space large enough to encompass any decision model that an agent may consider. We consider three motivating examples based on : (i) Homer's classic tale of Odysseus and the Sirens; (ii) a two-period linear-quadratic model of portfolio choice; (iii) the game of Chess. Though our novel framework transcends standard notions of risk or uncertainty, a form of Bayesian rationality is still possible. Instead of subjective probabilities of different models of a classical finite decision tree, we show that Bayesian rationality and continuity imply subjective expected utility maximization when some terminal nodes have attached real-valued subjective evaluations instead of consequences. Moreover, subjective evaluations lie behind, for example, the kind of Monte Carlo tree search algorithm that has been used by some powerful chess-playing software packages.

In April 2022, consumers in Great Britain (GB) witnessed a 54% increase in the energy price cap, as a result of Russia’s invasion of Ukraine on February 24th, which sent wholesale gas prices spiralling across Europe. We leverage high-frequency data collected by the Smart Energy Research Lab, a representative panel containing daily gas and electricity data for around 13,000 households in Great Britain between January 2021 and December 2023 to investigate the implications. We exploit several datasets linked to the panel data which include time-varying and cross-sectional information. We rely on two price shocks : 1) in October 2021 a wave of energy retail suppliers leaving the industry. At this time over two million consumers on fixed contracts were forced to join a new supplier and pay a variable tariff, and 2) these consumers were exposed to a second price shock caused by the Ukraine-Russia conflict which fed through April 2022’s energy price cap. Exploiting this pseudo-natural experiment, we use a difference-in-difference framework to estimate average treatment effects on this group of consumers and find that they would have consumed an additional 10 percentage points more electricity and 16 percentage points more gas had their prices remained fixed. These estimates are robust to a battery of robustness checks and point towards a significant loss in welfare for consumers on variable tariffs in the early stages of the energy price crisis

We study the impact of foreign exchange interventions during periods of tight credit constraints. Expanding on the Gabaix and Maggiori (2015) model, we predict that long-lived spot interventions have larger effects on exchange rates than short lived swaps, unanticipated interventions are more impactful, and tighter credit constraints amplify effects. Using high-frequency data on Brazilian Central Bank interventions from 1999 to 2023, we find that unanticipated spot sales of USD reserves lead to significant domestic currency appreciation and reduced covered interest parity deviations. Spot interventions outperform swaps, especially when global intermediaries are constrained, and enhance market efficiency by lowering USD borrowing costs.

Which types of human capital influence the adoption of advanced technologies? We study the skill-biased adoption of information and communication technologies (ICT) across two waves in the UK. Specifically, we compare the new wave of cloud and machine learning / AI technologies during the 2010s - pre-LLM - with the previous wave of personal computer adoption in the 1990s and early 2000s. At the area-level we see the emergence of a distinct STEM-biased adoption effect for the second wave of cloud and machine learning / AI technologies (ML/AI), alongside a general skill-biased effect. A one-standard deviation increase in the baseline share of STEM workers in areas is associated with around 0.3 of a standard deviation higher adoption of cloud and ML/AI. We find similar effects at the firm level where we are able to test for the influence of a wide range of skills. In turn, this STEM-biased adoption pattern has encouraged the concentration of these technologies, leading to more acute differences between high-tech and low-tech areas and firms. In contrast with classical technology diffusion, recent cloud and ML/AI adoption in the UK seems more likely to widen inequalities than reduce them

This paper brings together two major research streams in economic theory : information transmission in networks and strategic communication. The model embeds persuasion games of strategic disclosure by Milgrom (1981) into the communication network framework by Jackson and Wolinsky (1996). I find that the unique optimal network is a line in which players are ordered according to their bliss points. This ordered line is also pairwise- stable. This finding stands in sharp contrast to previous results in network studies, that identify stars as the optimal and pairwise-stable networks when communication is non-strategic and subject to technological constraints. While stars are the most centralized minimally-connected networks, the line is the most decentralized one. These results may be especially relevant to political economy applications, such as networks of policymakers, interest groups, or judges

This paper studies natural disasters and the psychological costs of climate change. It presents what we believe to be the first evidence that higher temperature variability and not a higher level of temperature is what predicts natural disasters. This conclusion holds whether or not we control for the (incorrectly signed) impact of temperature. The analysis draws upon long differences regression equations using GDIS data from 1960-2018 for 176 countries and the contiguous states of the USA. Results are checked on FEMA data. Wellbeing impact losses are calculated. To our knowledge, the paper’s results are unknown to natural and social scientists.

We study the process of long-run urban growth using a unique setting of close elections that determined “county seats” (capitals) in the frontier United States. Employing a regression discontinuity design, we show that winning towns rapidly became the economic and population centers of their counties as new migrants coordinated on them as destinations. This coordination was largest in the early years of a county’s history, but limited in later decades. Using generalized random forests, we show that the economic changes were not zero sum locally: specific choices of county seat could increase long- run county population and income. As county administration was limited in this era, the public sector did not play a substantial role in this growth. Instead, these results illustrate how a political process can select spatial equilibria through a shock that is neither related to locational fundamentals nor confers direct productivity advantages on the location.

We study how businesses adjust to significant rises in energy costs. This matters for both the current energy crisis and the longer-term shift towards Net Zero. Using firm-level real-time survey and administrative data backed by a pre-registered analysis plan, we examine how firms respond to the energy price shock triggered by Russia’s invasion of Ukraine along output, price, input, process and survival margins. We find that, on average, firms pass on some cost increases, build up cash reserves, and face higher debt, but do not yet see layoffs or bankruptcies. However, effects are highly heterogeneous by size and industry: for instance, small firms tend to increase cash reserves and prices, while large firms invest more in capital. We estimate separate elasticities for many small industry cells and subsequently use k-means clustering techniques on the estimated effects to identify high- dimensional firm-adaptation archetypes. These estimates can help tailor firm support in the energy transition both in the short and the long term. More generally, the machinery developed in this paper enables policymakers to evaluate and adjust economic policy in near-real time.

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 the signal of the bidder who controls the asset. We show that a seller can increase revenues by sometimes allocating cash-flow rights and control to different bidders, e.g., 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 the information of the bidder who 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.

This study utilizes novel data to investigate the impact of cooking energy sources and indoor air pollution on the happiness, life satisfaction, physical, and mental health of women in Nigeria. The existing body of literature relies on ambient air pollution data, which can be limiting in resource-constrained settings. To address this gap, we employ a direct approach, measuring Carbon Monoxide (CO) levels in participants’ blood using the Rad-57 CO-oximeter. Our analysis reveals strong positive correlations between the utilization of clean cooking energy and women’s reported happiness and life satisfaction. Additionally, the study finds that clean cooking energy usage is associated with a significant reduction in mental health problems among women. These findings highlight a substantial disparity in wellbeing based on access to clean cooking energy sources. Furthermore, exposure to carbon monoxide, as measured in this study, demonstrates a detrimental effect on women’s health and overall well-being. Consequently, policymakers and stakeholders should prioritize initiatives that promote household energy access and facilitate the transition to clean cooking practices, especially in rural areas where the use of polluting fuels and exposure to indoor air pollution remain prevalent concerns.

This paper uncovers if and how insurance companies react to shocks to collateral in their portfolio of securitized assets. We address this question in the context of commercial real estate cash flow shocks, which are informationally opaque to holders of commercial mortgage-backed securities (CMBS). Using detailed micro data, we show that cash flow shocks during the COVID-19 pandemic predict CRE mortgage delinquency, especially those stemming from lease expiration of offices, reflecting lower demand for these properties. Insurers react to such cash flow shocks by selling more exposed CMBS—mirrored by a surge in small banks holding CMBS—and the composition of their CMBS portfolio affects their trading behavior in other assets. Our results indicate that institutional investors actively monitor underlying asset risk, and even gain an informational advantage over some banks.

We analyze the impact of evaluator and candidate gender on the language used in academic evaluations using data on 295,000 evaluation reports for applicants seeking professorial promotion across all academic fields in Italy. In this context, candidates are assessed by a national-level committee composed of five randomly selected evaluators from the corresponding field. We observe that the language used in evaluation reports varies significantly with applicants’ productivity and professional ties to evaluators, but we find no indication that the language of the assessments depends on the gender of either the candidates or the evaluators.

Announcing a large fiscal stimulus may signal the government’s pessimism about the severity of a recession to the private sector, impairing the stabilizing effects of the policy. Using a theoretical model, we show that these signaling effects occur when the stimulus exceeds expectations and are more noticeable during periods of high economic uncertainty. Analysis of a new dataset of daily stock prices and fiscal news in Japan supports these predictions. We introduce a method to identify fiscal news with different degrees of signaling effects and find that such effects weaken or, in extreme cases, even completely undermine the stabilizing impact of fiscal policy.

This paper studies the impact of relative assessment on performance using a quasiexperiment: club-level swimming competitions in the US. By exploiting the age group structure, where swimmers are assessed against peers within their age group and experience a significant shift in relative standing upon aging up, we identify the causal effects of being assessed against better-performing peers. Using a regression discontinuity design, we find that swimmers, on average, swim significantly slower after aging up. This effect is similar across genders and is most pronounced among swimmers in the middle and top of the ability distribution, while those in the bottom third show no significant change. Our findings highlight the importance of considering the psychological impacts of relative assessment in competitive environments.

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, World Values Survey, and Swiss Household Panel consistently shows 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.

Can inequality in rewards result in an erosion in broad-based support for meritocratic norms? We hypothesize that unequal rewards between the successful and the rest, drives a cognitive gap in their meritocratic beliefs, and hence their social preferences for redistribution. Two separate experiments (one in the UK and the other in the USA) show that the elite develop and maintain “meritocratic bias” in the redistributive taxes they propose, even when not applied to their own income: lower taxes on the rich and fewer transfers to the poor, including those who failed despite high effort. These social preferences at least partially reflect a self-serving meritocratic illusion that their own high income was deserved. A Wason Card task confirms that individuals maintain their illusion of being meritocratic, by not expending cognitive effort to process information that may undermine their self-image even when incentivized to do otherwise.

Support for right-wing populist parties is characterised by considerable regional heterogeneity and especially concentrated in regions that have experienced economic decline. It remains unclear, however, whether the spatial externalities of local decline, including homelessness and crime, boost support for populist parties, even among those not directly affected by such decline. In this paper, we contribute to filling this gap in two ways. First, we gather novel data on a particularly visible form of local decline, high-street vacancies, that comprise 83,000 premises in England and Wales. Second, we investigate the influence of local decline on support for the right-wing populist UK Independence Party (UKIP) between 2009 and 2019. We find a significant positive association between high-street vacancy rates and UKIP support. These results enhance our understanding of how changes in the lived environment shape political preferences and behaviour, particularly in relation to right-wing populism.

We study the choice of multiple advisors, balancing political alignment, competence, and diverse perspectives. An imperfectly informed leader can consult one or two advisors. One has views closely aligned with the leader’s, but his information is imprecise or correlated with the leaders own. The other is more biased but has independent or more precise information. We identify a trade-off between consulting the more aligned or the better informed expert, even when this entails small costs. Subtle comparative statics emerge : When the leader consults both advisors, increasing the bias of the more biased expert may result in the dismissal of the other advisor. The leader may opt to delegate consulting and decision-making, but only to the advisor who collects superior information in equilibrium. We then study the uncertain trade-off case where the most informed advisor is not necessarily also more biased. We find that reducing the probability that the better-informed expert is more biased may lead to hiring also the other advisor. The leader may delegate to the advisor with uncertain bias, although he is more biased in expectation, because he more easily aggregates information in equilibrium.

This paper develops a novel method to identify the causal contribution of managers to team performance. The method requires repeated random assignment of managers to multiple teams and controls for individuals’ skills. A good manager is someone who consistently causes their team to produce more than the sum of their parts. Good managers have roughly twice the impact on team performance as good workers. People who nominate themselves to be in charge perform worse than managers appointed by lottery, in part because self-promoted managers are overconfident, especially about their social skills. Managerial performance is positively predicted by economic decision-making skill and fluid intelligence – but not gender, age, or ethnicity. Selecting managers on skills rather than demographics or preferences for leadership could substantially increase organizational productivity.

How does social influence affect consumer ratings? Using a dataset from the popular Steam gaming platform I investigate how quality judgements depend on pre-existing consumer assessments. In 2019, Steam introduced a new review system which decreased the exposure of users to previous ratings. Firstly, I find that user ratings are dependent on average ratings. A 10 percent increase in average rating increases the probability a review is positive by 5.4% before the policy change, but only by 2.8% after. The result is not due to selection, and is robust to a wide range of alternative specifications. Secondly, the effect is heavily asymmetric: individual reviewers are more negative when exposed to a lower average rating, but do not respond to a higher one. This negativity compounds and inflates the gap between lower rated and higher rated games. Overall, these social influence effects are driven by less experienced users on the platform. Finally, using estimates of owner data, I run a structural model of game choice. A 1% increase in rating is equivalent to a 2.5 dollar price reduction. This suggests social influence has large implications for buyers and sellers.

The widening income gap between older and younger individuals is a key topic in political and academic discussions. Research often focuses on labor earnings, neglecting other income sources and cross-country comparisons. This paper fills these gaps by analyzing disposable income trends in 2004-2018 across 32 countries using the Luxembourg Income Study Database. Key findings: (1) The age-income gap has increased in richer countries but decreased in poorer ones; (2) Higher employment rates among older individuals drive this disparity in richer countries; (3) Increased female labor market participation mildly affected the employment margin, while rising education and later retirement did not.

This paper investigates the association between sets of inputs and the educational outcomes of English adolescents. By linking the Longitudinal Study of Young People in England and Ofsted data, the paper employs the Context-Input-Process-Outcome model to compare the correlation of students and school inputs with their cognitive and non-cognitive outcomes. Using Nonlinear Canonical Correlation Analysis, the paper compares the characteristics of the high achievers to those of the low achievers revealing consistency with current findings in the literature. The results reveal that student inputs exert a greater influence than school inputs in revealing these characteristics. Specifically, unlike low achievers high achievers tend to exhibit positive attitudes toward school, benefit from supportive home learning environments, express greater eagerness to pursue university education, and belong to higher socio-economic backgrounds.

Hedge fund activists often aim to convince other shareholders to vote for a particular corporate policy, while majority shareholders recognize that activist recommendations serve their own interests, not necessarily maximizing firm value. We show how an activist can increase the likelihood of a favorable vote by delegating the tasks of acquiring information and making recommendations to another activist. This choice balances motivating the delegated activist to acquire costly information against ensuring shareholders trust the recommendation. We characterize how the hedge fund activist’s bias affects the delegation bias, information acquisition, recommendation and shareholder voting decisions, and firm value.

Does markets exposure foster or erode civic values and rules necessary to constrain opportunistic behavior? Using a natural experiment on market location from Ethiopia, I compare individuals who are from the same clan and attend the same market but vary in their exposure to that market. I find a positive effect of market exposure on civic values and rule formation. This result arises because individuals trade primarily in livestock, which is prone to cooperation problem from asymmetric information and weak state capacity. I use vignette studies to show that societies develop different types of exchange structures to mitigate this problem, which then shapes civic values and rules. In societies far from markets, there is no need for civic values and rules, as individuals rarely attend markets and sell livestock eponymously within their social network. In societies near markets, ephemeral and impersonal nature of market exchange creates a demand for civic values and community sanctioning as lubricants to conclude exchange, otherwise individuals end up losing gains from trade. Exposure to markets without asymmetric information has no effect on civic values and rules, suggesting that prosperity and contact hypothesis are not the channels.

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 reduce military support activities, including aid projects. They are also associated with higher levels of insurgent violence. These findings indicate that misalignment between units within military organizations can undermine the effectiveness of security and development interventions during war, with broader implications for managing complex teams under risk.

We leverage recent advancements in machine learning to develop an integrated method to solve globally and estimate models featuring agent heterogeneity, nonlinear constraints, and aggregate uncertainty. Using simulated data, we show that the proposed method accurately estimates the parameters of a nonlinear Heterogeneous Agent New Keynesian (HANK) model with a zero lower bound (ZLB) constraint. We further apply our method to estimate this HANK model using U.S. data. In the estimated model, the interaction between the ZLB constraint and idiosyncratic income risks emerges as a key source of aggregate output volatility.

We examine bidders’ behaviour in auction sales of the iPhone4 on eBay in the context of a significant shortage of the product at listed price, leading to achieved prices significantly above the posted price, on average. We examine the behaviour of sellers then test the direct prediction of the successive auctions model that bidders increase their bids over successive auctions and are influenced by the effects of information gained from previous auctions, finding that bidders indeed react both to their direct experience and to experience gained from studying previous auctions. In addition, the results are suggestive of bidders being reluctant to reveal their true valuation of the product initially but that they do so only over time. Our results are novel in being able to track individual bidders’ behaviour rather than simply auction outcomes.

As the world experiences a fourth industrial revolution - in Information Technology - we look back at how things turned out in the first Industrial Revolution, which began when Adam Smith was writing The Wealth of Nations. For the historical record, we draw on the recent study of Power and Progress by Daron Acemoglu and Simon Johnson, who describe how the benefits of innovation were – or were not - spread across society in Britain at that time. This paper focuses on the case of India under colonial rule, however, where two themes emerge. First, how the transfer of technology under the control of a private company – based in London and granted monopoly powers by the British government - was enough to stymie the ‘virtuous spiral of Smithian growth’ for a century or more. Second, how two centuries of colonial control also deprived the indigenous population of what Amartya Sen has claimed is the key insurance against famine - namely democratic accountability. The paper end with brief remarks on how industrial policy in India of today could help spread the benefits of the current IT revolution.

What contributed to the decline in employment-to-employment (EE) transition rate in the UK in recent decades? This paper empirically examines potential channels that caused the sluggish EE mobility from 2000-2019. First, I break down the observed fall in EE mobility relative to unemployed-to-employment (UE) transition into changes in relative search intensity and worker’s acceptance rate. I find the vast majority of the persistent decline after 2010 was due to fall in job acceptance. Second, I estimate a dynamic job ladder model using UK survey data to examine the relative importance of changes in employment and job offer distribution in reducing job acceptance. Results reveal that the falling job acceptance in the 2000s was attributed to workers moving up the job ladder; while acceptance remained low in the 2010s as a result of deterioration in offer qualities. Counterfactual exercise shows that if the attractiveness of poaching offers did not deteriorate after 2010, the EE mobility would have returned to levels in early 2000s. Finally, I test the contribution of composition changes to the fall in EE rate by implementing a between-within decomposition using a structural framework, which accounts for both worker heterogeneity and sectoral compositions. Results rule out demographic changes or structural transformation as main drivers of the fall in EE rates.

Climate action requires significant public- and private sector investment to achieve meaningful reductions in carbon emissions. This paper documents that large-scale austerity, coupled with barriers to flows of data and a lack of (digital) skills in (local) government, may have been a significant barrier to delivering climate action in the form of retrofitting. Decomposing heterogeneity in estimated treatment effects of a large-scale energy efficiency savings program that was rolled out through a regression discontinuity design in the early 2010s, we find that both the extent of austerity-induced local budget cuts and poor digital connectivity – may be responsible for up to 30% fewer retrofit installations that counterfactually would have taken place had it not been for austerity

Do opinion polls sway turnout and shape political competition in majoritarian systems? Can they strengthen the persistence of safe seats? Analysing national opinion polls during UK general elections and the perceived safeness of constituencies, we find that pre-election polls significantly affect voter turnout. Non-competitive elections predicted by national polls suppress turnout, especially in areas with low perceived electoral competition. This reinforces the advantage of trailing parties in their strongholds, potentially fuelling party demand for safe seats that may give rise to demands for gerrymandering. This can exacerbate spatial polarization of the electoral landscape, with implications for governance regarding opinion polling.

Combining longitudinal postcode-level data on charitable donations made through a UK giving portal with publicly available data on local crime and neighborhood characteristics, we study the relationship between local crime and local residents’ charitable giving and we investigate the possible mechanisms underlying this relationship. An increase in local crime corresponds to a sizeable increase in the overall size of unscheduled charitable donations. This effect is mainly driven by the responses of female and gender unclassified donors. Donation responses also reflect postcode variation in socio-economic characteristics, levels of mental health, and political leanings, but mainly so for female and gender-unidentified donors.

Politicians often use red herrings to distract voters from scandals. When do such red herrings succeed? I develop a model in which an incumbent runs for re-election and potentially faces a scandal. Some incumbents enjoy telling “tales” (attention-grabbing stories) while others use tales to distract voters from the scandal. Multiple equilibria can arise: one with a norm of tale-telling in which red herrings succeed and another with a norm against tale-telling in which they fail. Increased media attention to tales has a nonmonotonic effect, facilitating red herrings at low attention levels, but serving a disciplinary function at high levels.

We study the relationship between exposure to historical conflict involving heavy weaponry and male-favoring gender norms. We argue that the physical nature of such conflict produced cultural norms favoring males and male offspring. We focus on spatial variation in gender norms across India, a dynamic developing economy in which gender inequality persists. We show robust evidence that areas with high exposure to pre-colonial conflict are significantly more likely to exhibit male favoring gender norms as measured by male-biased sex ratios and crimes against women. We document how conflict-related gender norms have been transmitted over time via male-favoring folkloric traditions, the gender identity of temple gods, and male-biased marriage practices, and have been transmitted across space by migrants originally from areas with high conflict exposure.

A substantial body of literature has shown that women shy away from competition against men, which has been put forward as an explanation for the significant gender differences observed in career promotions and salary negotiations. It is therefore of crucial importance to understand the conditions under which the gender gap in competitiveness can be reduced. In this study, we explore the role of priming. Our findings replicate previous work showing that, in the absence of primes, women compete less than men. By contrast, introducing a priming task can eliminate gender disparities in competitiveness, ceteris paribus; however, the effects are stronger when neutral primes are used. We perform sentiment analysis and attribute this to the more negative emotions triggered in the neutral priming condition, making women more competitive. Overall, our results indicate that costless and simple tools such as priming can be adopted by organisations aiming at reducing gender inequalities in the workplace.

We develop a model of strategic voting in a spatial setting with multiple candidates when voters have both expressive and instrumental concerns. The model endogenizes the strategic coordination of voters, yet is flexible enough to allow the analysis of political platform competition by policy-motivated candidates. We characterize all strategic voting equilibria in a three-candidate setting. Highlighting the utility of our approach, we analyze a setting with two mainstream and a spoiler candidate, showing that the spoiler can gain from entering, even though she has no chance of winning the election and reduces the winning probability of her preferred mainstream candidate

In this paper, we estimate the causal effect of transitory individual-level health shocks on schooling outcomes in Brazil. We focus on dengue fever, which, despite putting half of the world’s population at risk, has received relatively little attention, possibly due to its low mortality. We link individual register data on dengue infections with detailed individual records from the Brazilian school census and use a fixed effects estimation strategy to estimate the effect of dengue infections on grade retention and dropout. We find that dengue infections during the school year have a substantial negative effect on measures of student success, with an increase in grade retention of 3.5 percent and an increase in dropout of 4.6 percent. Using information on monthly attendance from the monitoring system of conditionalities of the Brazilian cash transfer Bolsa Famılia, we provide evidence that infections reduce school attendance.

Formal conceptions of state capacity have mostly focused on indirect measures of state capacity – by, for instance, using the state’s fiscal or extractive capacity as a proxy for its overall capacity. Yet, this input or extractive view of state capacity falls short, especially since cross-country empirical evidence suggests that similar levels of fiscal capacity, measured by tax revenues as a percentage of GDP, can produce starkly different outputs – both in classic economic terms and in broader terms that citizens would recognize as desirable outcomes, including quality of life, health, security, equality of opportunity, and intergenerational mobility. This paper argues that a central step towards addressing these shortcomings of the conventional view is to account for a crucial and largely ignored boundary of the state or dimension of state capacity: its capacity to gather, process, and deploy information in its conduct of fiscal policy. Specifically, we study how the presence or lack of such informational capacity constrains governments in responding to crises, such as the recent energy price shock. Our framework provides the analytical toolkit to examine how the informational boundary of the state shapes the incentives for policymakers to resort to untargeted and/or distortionary policy instruments, as opposed to targeted and non-distortionary ones, in responding to crises. The policy response to the energy crisis following the invasion of Ukraine provides the empirical context upon which we bring this theoretical framework to bear on data, though the latter can be straightforwardly extended to other recent crises.