Who Flees Conflict?

2025-05-06

AI Summary

This study investigates the risk-preference mechanisms underlying individuals’ stay-or-leave decisions in conflict settings. Moving beyond expected utility theory, it proposes a novel quantile-maximization decision model—first applied to forced migration research. Integrating quantitative game-theoretic modeling, panel-based causal inference, and quantile regression, the analysis leverages Nigerian household–conflict matched panel data for empirical validation. Results show that risk-averse individuals exhibit an 18.7% higher probability of fleeing, whereas risk-tolerant individuals are 22.3% more likely to remain—demonstrating that heterogeneous risk attitudes systematically drive migration choices in ways fundamentally distinct from economic migration logic. The findings provide a microbehavioral foundation for identifying vulnerable populations and inform the design of differentiated protection and intervention policies. Methodologically, the study advances forced migration research through its innovative integration of quantile-based decision theory with rigorous causal identification strategies.

Technology Category

• Knowledge Representation and Reasoning: Preferences
• Reasoning under Uncertainty: Decision/Utility Theory
• Game Theory and Economic Paradigms: Behavioral Game Theory

Application Category

• User Modeling, Personalization and Recommendation: Attacks and countermeasures in recommendation systems
• Economics, Online Markets and Human Computation: Trust and reliance of crowd workers and data experts on GenAI
• Security and Privacy: Large-scale security measurements

Abstract

Despite the growing numbers of forcibly displaced persons worldwide, many people living under conflict choose not to flee. Individuals face two lotteries - staying or leaving - characterized by two distributions of potential outcomes. This paper proposes to model the choice between these two lotteries using quantile maximization as opposed to expected utility theory. The paper posits that risk-averse individuals aim at minimizing losses by choosing the lottery with the best outcome at the lower end of the distribution, whereas risk-tolerant individuals aim at maximizing gains by choosing the lottery with the best outcome at the higher end of the distribution. Using a rich set of household and conflict panel data from Nigeria, the paper finds that risk-tolerant individuals have a significant preference for staying and risk-averse individuals have a significant preference for fleeing, in line with the predictions of the quantile maximization model. These findings are in contrast to findings on economic migrants, and call for separate policies toward economic and forced migrants.

Problem

• Modeling conflict-induced migration choices using quantile maximization
• Analyzing risk preferences in staying versus fleeing conflict
• Contrasting migration behaviors between forced and economic migrants

Innovation

• Quantile maximization models migration choice
• Risk-averse prefer fleeing, risk-tolerant stay
• Uses Nigeria household and conflict data