About

Ambassador Taylor Professor of Politics & Public Policy, Compton Professor of Public Affairs, and Professor of Data Science (courtesy) at the University of Virginia.

Research topics

• Political Science
• Economics
• Development economics
• Law
• Sociology
• Political economy
• Medicine
• Virology
• Market economy
• Demographic economics
• Nursing

Selected publications

• A Deportation Boomerang? Evidence From U.S. Removals to Latin America and the Caribbean

  Demography · 2025-03-26

  articleOpen accessSenior author

  The forced return of migrants is an important part of migration policy toolkits. An increased risk of deportation, politicians argue, will deter subsequent irregular migration. We explore this argument for the case of forced removals from the United States and find that rather than operating as a deterrent for future migrants, this policy had a boomerang effect. The forced return of migrants with a track record of crime generated negative externalities in the form of higher violence in their countries of origin, counteracting the deterrence effect of higher deportation risk. We apply mediation analysis to a panel of Latin American and Caribbean countries and decompose the effect of deportations on emigration into three coefficients of interest: a total effect of deportations on later emigration, an effect of deportations on the mediator variable of violence, and an effect of violence on emigration. We address the endogeneity of our key explanatory variables-deportations and violence-using migrants' exposure to the unequal and staggered implementation of policies intended to facilitate deportations at the level of U.S. states as a source of exogenous variation. We show that migration intentions and asylum requests increase in response to deportation threats. This effect is mediated through increased violence and is strongly driven by dynamics in Central America. Although the total number of apprehensions at the U.S. southern border in response to deportation threats does not show a clear pattern, we observe an increase in the share of unaccompanied minors and the share of entire family units among those apprehended, suggesting a shift in migration strategies and composition.

  PublisherOA PDFDOI

• Land/Labor Ratios, Citizenship, and Migrants: Exploring the Hidden Links in the Political Economy of Immigration Regimes

  World Politics · 2025-01-01

  articleSenior author

  abstract: Within sovereign states citizenship is arguably the most important political marker of in- and outsiders. As a result, questions about who gets to reap the benefits of citizenship often result in distributional conflict. This conflict becomes inflamed when a country goes through a period of significant inward migration. Given that citizenship is so important and so contentious, from where do the rules governing its acquisition come? Our starting point is the acknowledgment that migrants are mobile labor. From this perspective, countries in which elites benefit from an increased supply of productive labor—that is, those with high land/labor ratios—will be more likely to adopt policies that attract migrants, such as easier naturalization rules, including birthright citizenship. We illustrate the plausibility of our argument with some statistical evidence and suggest some avenues to further explore this crucial question.

  PublisherDOI

• Agent-Based Social Simulation of Spatiotemporal Process-Triggered Graph Dynamical Systems

  2025-12-07 · 1 citations

  article
  PublisherDOI

• Hazard Function Guided Agent-Based Models: A Case Study of Return Migration from Poland to Ukraine

  2025-09-01

  article

  The Russian invasion of Ukraine in February 2022 has led to the largest forced migration crisis in Europe since World War II, with millions displaced both internally and internationally. Among the displaced, approximately 4.2 million individuals have returned, highlighting the significance of return migration as a critical phase in the migration continuum. Existing studies on return migration are limited in scope, relying on survey-based approaches that suffer from demographic bias, lack of validation against ground truth, and inability to account for uncertainty. We propose a novel computational framework for modeling the return of conflict-induced migrants, using agent-based models (ABMs) and their surrogates. These models are grounded in hazard functions and account for sociopolitical contexts. Our proposed ABMs outperform baseline methods in estimating return migration from Poland to Ukraine by at least 42% and by as much as 57% in terms of normalized root mean squared error (NRMSE). Further, to illustrate the utility of such models for policymakers, we conduct two case studies that estimate the duration of displacement and characterize the demographic breakdown among the returnees.

  PublisherDOI

• Global perspectives on COVID-19 vaccination: Impacts on well-being and inequality

  Vaccine · 2025-02-22

  articleOpen access1st author

  INTRODUCTION: This study aims to examine the relationship between COVID-19 vaccination and subjective well-being (SWB), as well as well-being inequality. It employs a conceptual framework that incorporates demographic characteristics, socioeconomic factors, health, and social support. METHODS: Using data from the Gallup World Poll (2021-2022), which includes 131,910 respondents across 96 countries, we analyze the association between vaccination status and SWB. The Cantril ladder technique is employed to measure SWB, while regression analyses are conducted to estimate the conditional mean and variance of well-being, allowing for an assessment of well-being inequality. RESULTS: Our findings indicate that vaccinated individuals report significantly higher levels of current SWB (p < .01) and lower well-being inequality (p < .01) than unvaccinated people. Specifically, vaccination is associated with a 0.04 standard deviation increase in SWB and a 0.06 standard deviation decrease in interpersonal well-being inequality. Moreover, those vaccinated exhibit greater optimism regarding their future well-being. CONCLUSION: The results underscore the importance of COVID-19 vaccination in enhancing both current and expected future well-being while reducing well-being inequality. These findings suggest that public health policies should prioritize vaccine uptake and address underlying socioeconomic factors to promote overall mental health and well-being in the population.

  PublisherDOI

• Does inflation affect well-being?

  Empirical Economics · 2025-05-30 · 1 citations

  articleOpen access1st author

  Abstract After years of low and stable inflation, high inflation rates have returned in many countries around the world. This paper highlights the importance of outliers for the study of whether inflation is associated with individual-level well-being using cross-country data. We combine Gallup World Poll individual-level data from 150 countries between 2007 and 2019 with inflation data obtained from the International Monetary Fund ( N = 1,946,459). We conduct a conceptual replication of the paper by El-Jahel et al. (J Money Credit Bank 55:2001, 2022). We replicate the main finding that inflation is significantly associated with well-being in the full sample ( p &lt;0.001). However, dropping outlier observations equivalent to 0.26% of the full sample (or N = 5014) changes the outcome and results in a nonsignificant correlation between inflation and well-being ( p = 0.112). These observations come from three countries (South Sudan, Venezuela, and Zimbabwe). We argue that anomalous events (civil war and a failing state) drive the low-well-being and high-inflation combination experienced in these countries and that these observations, hence, are outliers. Our findings are robust to various approaches for identifying outliers, various well-being measures, and econometric details.

  PublisherOA PDFDOI

• Food insecurity across age: Evidence from a global study

  Global Food Security · 2025-10-07 · 4 citations

  articleOpen access1st author

  Food insecurity, which affects access to safe and nutritious food, has significant implications for health and well-being. This issue has worsened in recent years, driven by factors like the COVID-19 pandemic and geopolitical instability. This study examines food insecurity across three age groups – adolescents, adults, and older adults – using data from the Gallup World Poll for 132 countries, based on surveys of >390,000 individuals. The research, which uses the Food Insecurity Experience Scale (FIES), finds that food insecurity is highest among adolescents, with a notable increase in their vulnerability over recent years. Socioeconomic factors such as income, education, and health issues, along with social capital, also play a key role in influencing food insecurity. Additionally, interpersonal inequality is more pronounced among immigrants and individuals with high levels of trust but low social support. These findings underline the need for targeted policies that address the specific needs of different age groups, especially adolescents, to reduce food insecurity and its related impacts on health and development. • Food insecurity, worsened by the COVID-19 pandemic and geopolitical instability, affects access to nutritious food, impacting health across age groups. • Adolescents are the most vulnerable group to food insecurity, with their risk increasing significantly in recent years. • Factors like income, education, health, and social capital greatly influence food insecurity rates, highlighting the need for tailored interventions. • Immigrants and those with high trust but low social support experience more severe interpersonal inequality in food insecurity. • Addressing food insecurity requires age-specific policies, especially for adolescents, to reduce its impact on health and development.

  PublisherDOI

• Network Agency: An Agent-based Model of Forced Migration from Ukraine

  2024-05-06 · 2 citations

  article

  Individuals in social systems are embedded in collective decision-making hierarchies, such as households, neighborhoods, communities, organizations, etc. The locus of agency in such systems is dispersed across the system, and can variously be viewed as individual, distributed, and shared agency. Here we propose a general notion of network agency that subsumes these descriptions and also allows for integrating related notions, such as peer influence. In our view, the social system can be seen as a multi-layer network, where each layer corresponds to different aggregations of the underlying units, representing different kinds of perception and decision-making. We illustrate this general framework with an agent-based model of the ongoing forced migration from Ukraine. In our model, individuals perceive hazards (conflict events), but decisions to migrate are taken at the household level, where peer influence from other households in the neighborhood is also taken into account. We present this model in detail to elucidate our concept of network agency. We also calibrate the model with data on daily refugee flows and show that our model is able to estimate the scale of the daily refugee flow from Ukraine for the first two months with a Root Mean Squared Percentage Error (RMSPE) of 0.24, outperforming state-of-the-art, which had an RMSPE of 0.77. Moreover, our model also captures the daily trend of outflow with a Pearson Correlation Coefficient (PCC) of 0.98. We also perform sensitivity analysis of the model and analyze the significant parameters of the model, which in turn tells us how different agencies are significant in different contexts.

  PublisherDOI

• Hazard Function Guided Agent-Based Models: A Case Study of Return Migration from Poland to Ukraine

  2024-08-01

  article

  The Russian invasion of Ukraine in February 2022 has led to the largest forced migration crisis in Europe since World War II, with millions displaced both internally and internationally. Among the displaced, approximately 4.2 million individuals have returned, highlighting the significance of return migration as a critical phase in the migration continuum. Existing studies on return migration are limited in scope, relying on survey-based approaches that suffer from demographic bias, lack of validation against ground truth, and inability to account for uncertainty. We propose a novel computational framework for modeling the return of conflict-induced migrants, using agent-based models (ABMs) and their surrogates. These models are grounded in hazard functions and account for sociopolitical contexts. Our proposed ABMs outperform baseline methods in estimating return migration from Poland to Ukraine by at least 42% and by as much as 57% in terms of normalized root mean squared error (NRMSE). Further, to illustrate the utility of such models for policymakers, we conduct two case studies that estimate the duration of displacement and characterize the demographic breakdown among the returnees.

  PublisherDOI

• A Generalizable Theory-Driven Agent-Based Framework to Study Conflict-Induced Forced Migration

  Proceedings of the AAAI Conference on Artificial Intelligence · 2024-03-24 · 1 citations

  articleOpen access

  Large-scale population displacements arising from conflict-induced forced migration generate uncertainty and introduce several policy challenges. Addressing these concerns requires an interdisciplinary approach that integrates knowledge from both computational modeling and social sciences. We propose a generalized computational agent-based modeling framework grounded by Theory of Planned Behavior to model conflict-induced migration outflows within Ukraine during the start of that conflict in 2022. Existing migration modeling frameworks that attempt to address policy implications primarily focus on destination while leaving absent a generalized computational framework grounded by social theory focused on the conflict-induced region. We propose an agent-based framework utilizing a spatiotemporal gravity model and a Bi-threshold model over a Graph Dynamical System to update migration status of agents in conflict-induced regions at fine temporal and spatial granularity. This approach significantly outperforms previous work when examining the case of Russian invasion in Ukraine. Policy implications of the proposed framework are demonstrated by modeling the migration behavior of Ukrainian civilians attempting to flee from regions encircled by Russian forces. We also showcase the generalizability of the model by simulating a past conflict in Burundi, an alternative conflict setting. Results demonstrate the utility of the framework for assessing conflict-induced migration in varied settings as well as identifying vulnerable civilian populations.

  PublisherOA PDFDOI

Frequent coauthors

• William Bernhard

  University of Illinois Urbana-Champaign

  177 shared

• Martha Finnemore

  150 shared

• Judith Goldstein

  Princeton University

  150 shared

• Stephan Haggard

  University of California, San Diego

  150 shared

• James D. Fearon

  Stanford University

  150 shared

• Thomas Risse

  149 shared

• Lisa L. Martin

  University of Wisconsin–Madison

  149 shared

• Louis Pauly

  Princeton University

  149 shared

Awards & honors

• Outstanding Faculty Mentoring Award by the University of Vir…
• Outstanding Mentoring Award from the Society of Women in Int…