Behavioral therapy with cash grants led to significant fall in crime, drug use, and violence among high-risk urban men.
People may under-report sensitive and risky behaviors such as violence or substance abuse in surveys. Misreporting correlated with treatment is especially worrisome in causal analysis. We develop and test a survey validation technique that uses intensive qualitative work to check for measurement error in random subsamples of respondents. Trained local researchers spent several days speaking with and observing respondents within a few days of their survey, validating six behaviors: four potentially sensitive (crime, drug use, homelessness, gambling) and two non-sensitive (phone charging and video club expenditures). Subjects were enrolled in a randomized trial designed to reduce poverty and anti-social behaviors. We find no evidence of underreporting of sensitive behaviors, partly because (we discovered) stigma in this population is low. Nonsensitive expenditures were underreported, however, especially by the control group, probably because of strategic behavior and recall bias. The main contribution is a replicable validation method for observable, potentially sensitive behaviors.
Dispute resolution institutions facilitate agreements and preserve the peace whenever property rights are imperfect. In weak states, strengthening formal institutions can take decades, and so state and aid interventions also try to shape informal practices and norms governing disputes. Their goal is to improve bargaining and commitment, thus limiting disputes and violence. Mass education campaigns that promote alternative dispute resolution (ADR) are common examples of these interventions. We studied the short-term impacts of one such campaign in Liberia, where property disputes are endemic. Residents of 86 of 246 towns randomly received training in ADR practices and norms; this training reached 15% of adults. One year later, treated towns had higher resolution of land disputes and lower violence. Impacts spilled over to untrained residents. We also saw unintended consequences: more extrajudicial punishment and (weakly) more nonviolent disagreements. Results imply that mass education can change high-stakes behaviors, and improving informal bargaining and enforcement behavior can promote order in weak states.
Conflict early warning remains an important but elusive goal in Liberia. If outbreaks of violence could be predicted before they occur, early responders could focus their energies and scarce resources on the highest-risk communities. Is such a goal realistic? Early warning requires a simple system for generating reliable predictions—a system that is not only accurate, but is also consistent over time and across counties and communities. This is a difficult, maybe impossible, task. In this report we describe results from a two-year study that suggest prediction may be more promising than we initially expected. We use fine-grained quantitative data from a survey of 247 rural Liberian towns and villages to assess whether statistical analysis can be used to predict conflict over time. To our surprise, we find that models built on fewer than 10 risk factors measured in 2008 accurately predict up to 75% of all conflicts two years later. We began this exercise skeptical, and these accuracy rates are far higher than we anticipated.
Policymakers in Liberia face a dearth of evidence to guide their ambitious agenda of security sector reform, strengthening of property rights and the rule of law, and reconciliation. This lack of data is especially acute outside the capital and in areas where UN and police presence is limited.
How can new democracies and societies emerging from conflict encourage tolerance and dialogue, strengthen conflict resolution systems, and increase understanding of human rights?