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Electoral violence remains a significant challenge worldwide. It not only threatens to undermine the legitimacy and fairness of electoral outcomes, but often has serious repercussions on political stability broadly. The ability to prevent electoral violence is critical for safeguarding democracy and ensuring peaceful transitions of political power. Predicting which elections are at risk of violence is a crucial step in effective prevention. In this study, we develop a set of machine-learning models to forecast the likelihood of electoral violence worldwide. Using diverse data sources, which include economic indicators, the history of electoral violence, political instability, and digital vulnerability, we predict the risk of electoral violence on a scale ranging from no violence to severe violence. Our final forecasts are produced by combining constituent models into an ensemble using a genetic algorithm. Out-of-sample evaluation of the system shows that the final model accurately distinguishes between different levels of risk. After validating our system on historical data, we generate out-of-sample probabilistic forecasts for national-level elections in 2025 and 2026. This research contributes to the field of political violence prediction by providing a medium-term data-driven forecasting tool for electoral violence.

How does the deployment and withdrawal of UN peacekeepers affect local economic development in civil war countries? This study provides a large-N subnational analysis across UN peacekeeping operations that assesses their impact on the local economy both during deployment and after their withdrawal. We expect a positive association between UN peacekeeping and economic development. Besides providing a sizeable cash injection into the economy, peacekeepers can safeguard both the resumption of everyday economic exchanges at the grassroots level and the influx of aid and development projects. To test this, we combine subnational data on peacekeeping deployments with high-resolution data on nightlight emissions. Results from two-way fixed effects models, using matching, show that a more sizable peacekeeping presence can help boost economic activity in their area of operation. Importantly, we identify a slow but positive economic development in areas of deployment after peacekeepers withdraw, which is confirmed in a DiD estimation approach.

Across the world, many citizens go to the polls amidst armed threats from both state and non-state actors. How do militarized elections affect citizens’ willingness to accept restrictions on democratic rights? We argue that when forming opinions about appropriate limits to state powers, citizens navigate competing threats from state and non-state actors. The display of state coercive force should make citizens more protective of civil and political rights. Yet, if it occurs in the context of threat posed by non-state actors, citizens may become more likely to accept that rights are restricted. We embed a vignette experiment with a selective information prime in a 2019 post-election survey of 1,080 Indian citizens across two states affected by armed insurgency. We find that being primed on a heavy state-military presence makes citizens more reluctant to accept restrictions on civil and political rights, but the effect is only found among politically marginalized groups. In the presence of violent non-state threats, however, citizens become more likely to support policies that curtail democratic rights.

Much research examines citizens' beliefs in misinformation and whether these beliefs can be corrected, but we know far less about how misinformation impacts social attitudes. We propose that misinformation can induce affective shifts that increase out-group animosity and fuel polarization. Politicians amplify these effects by embedding misinformation into larger narratives of threat from out-groups. We conduct a preregistered vignette experiment following the 2021 elections in West Bengal, India, exposing respondents to a misinformation message that invokes salient identity cleavages. We randomize whether citizens are asked about intergroup attitudes before or after exposure to misinformation and find that treated respondents report more hostile out-group attitudes. Corrective information fails to mitigate these negative effects, suggesting that the effects of misinformation may not operate through citizens' factual beliefs. While it is known that directional motives aid the proliferation of misinformation on social media, our study shows that misinformation itself can exacerbate social cleavages.

The detrimental impacts of wars on human development are well documented across research domains, from public health to micro-economics. However, these impacts are studied in compartmentalized silos, which limits a comprehensive understanding of the consequences of conflicts, hampering our ability to effectively sustain human development. This article takes a first step in addressing this gap by reviewing the literature on conflict impacts through the lens of an inter-disciplinary theoretical framework. We review the literature on the consequences of conflicts across 9 dimensions of human development: health, schooling, livelihood and income, growth and investments, political institutions, migration and displacement, socio-psychological wellbeing and capital, water access, and food security. The study focuses on both direct and indirect impacts of violence, reviews the existing evidence on how impacts on different dimensions of societal wellbeing and development may intertwine, and suggests plausible mechanisms to explain how these connections materialize. This exercise leads to the identification of critical research gaps and reveals that systematic empirical testing of how the impacts of war spread across sectors is severely lacking. By streamlining the literature on the impacts of war across multiple domains, this review represents a first step to build a common language that can overcome disciplinary silos and achieve a deeper understanding of how the effects of war reverberate across society. This multidisciplinary understanding of conflict impacts may eventually help to reconcile divergent estimates and enable forward-looking policies that minimize the costs of war.

In many elections across the world, the regime in power uses violence to influence electoral dynamics and outcomes. What is the effect of such violence on citizens' attitudes to democracy? We argue that the effect of government-perpetrated electoral violence on citizens' democratic commitment will diverge depending on whether the individual supports the ruling or opposition party. While those affiliated with the opposition should become more likely to support democracy in the wake of government violence, we expect those affiliated with the incumbent to support more power concentrated in the hands of the executive. We examine these expectations using cross-national, geo-referenced survey data from the Afrobarometer, alongside event data on electoral violence. We find that while incumbent supporters generally display lower baseline support for democracy in the absence of violence, violent elections do not further erode their democratic commitment. Violence is, however, associated with increased support for democracy amongst opposition supporters.

This study presents new theory and evidence on the repertoire of electoral intimidation, suggesting that threats can be used to deter rival party supporters from voting but also to mobilize citizens to vote for a particular party. We expect these strategies to unfold in the same electoral context, but differ in targeting and incidence; while threats to demobilize are concentrated in closely contested areas and occur more frequently overall, threats to mobilize target fewer voters and are centered in parties’ own strongholds. Recognizing the difficulty of surveying citizens about sensitive experiences, we combine qualitative material from local news with evidence from a list experiment embedded in an original survey conducted after the 2019 elections in the Indian state of West Bengal. Our empirical findings corroborate our expectations: areas without overt violence may nevertheless be highly coercive, underlining the importance of studying the full repertoire of electoral violence.

List experiments encourage survey respondents to report sensitive opinions they may prefer not to reveal. But, studies sometimes find that respondents admit more readily to sensitive opinions when asked directly. Often this over-reporting is viewed as a design failure, attributable to inattentiveness or other nonstrategic error. This paper conducts an exploratory analysis of such a ‘failed’ list experiment measuring vote buying in the 2019 Nigerian presidential election. We take this opportunity to explore our assumptions about vote buying. Although vote buying is illegal and stigmatized in many countries, a significant literature links such exchanges to patron-client networks that are imbued with trust, reciprocity and long-standing benefits, which might create incentives for individuals to claim having been offered to participate in vote buying. Submitting our data to a series of tests of design, we find that over-reporting is strategic: respondents intentionally reveal vote buying and it’s likely that those who reveal vote buying have in fact being offered to participate in vote buying. Considering reasons for over-reporting such as social desirability and network benefits, and the strategic nature of over-reporting, we suggest that “design failure" is not the only possible conclusion from unexpected list experiment results. With this paper we show that our theoretical assumptions about sensitivity bias affect the conclusions we can draw from a list experiment.

Drawing on collective experience from ten collaborative research projects focused on the Global South, we identify three major challenges that impede the translation of research on sustainability and resilience into better-informed choices by individuals and policy-makers that in turn can support transformation to a sustainable future. The three challenges comprise: (i) converting knowledge produced during research projects into successful knowledge application; (ii) scaling up knowledge in time when research projects are short-term and potential impacts are long-term; and (iii) scaling up knowledge across space, from local research sites to larger-scale or even global impact. Some potential pathways for funding agencies to overcome these challenges include providing targeted prolonged funding for dissemination and outreach, and facilitating collaboration and coordination across different sites, research teams, and partner organizations. By systematically documenting these challenges, we hope to pave the way for further innovations in the research cycle.

How do violent elections affect the willingness of citizens to defend democratic institutions? We argue that in the wake of violent elections, support for democratic constraints on the executive will diverge amongst ruling and opposition party supporters. To protect their position, ruling party supporters become more likely to endorse weakening constraints on executive power, even if it violates democratic principles. Opposition supporters, on the other hand, become more likely to reject democratic transgressions that de facto render them more vulnerable to political abuse. We examine these expectations using a vignette experiment embedded in a nationally representative 2019 post-election survey of 2400 Nigerians. Our findings suggest that incumbent supporters are overall more likely to endorse weaker constraints on the executive, but these attitudes are not reinforced by information about election violence. Opposition supporters, in contrast, become less likely to accept transgressions when informed about election violence.