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Predicting Local Violence: Evidence from a Panel Survey in Liberia

87 Pages Posted: 22 Oct 2016  

Robert A. Blair

Brown University

Christopher Blattman

University of Chicago, Harris School of Public Policy; National Bureau of Economic Research (NBER)

Alexandra Hartman

University College of London

Date Written: October 20, 2016

Abstract

Riots, murders, lynchings and other forms of local violence are costly to security forces and society at large. Identifying risk factors and forecasting where local violence is most likely to occur should help allocate scarce peacekeeping and policing resources. Most forecasting exercises of this kind rely on structural or event data, but these have many limitations in the poorest and most war-torn states, where the need for prediction is arguably most urgent. We adopt an alternative approach, applying machine learning techniques to original panel survey data from Liberia to predict collective, interpersonal and extrajudicial violence two years into the future. We first train our models to predict 2010 local violence using 2008 risk factors, then generate forecasts for 2012 before collecting new data. Our models achieve out-of-sample AUCs ranging from 0.65 to 0.74, depending on our specification of the dependent variable. The models also draw our attention to risk factors different from those typically emphasized in studies aimed at causal inference alone. For example, we find that while ethnic heterogeneity and polarization are reliable predictors of local violence, adverse economic shocks are not. Surprisingly, we also find that the risk of local violence is higher rather than lower in communities where minority and majority ethnic groups share power. These counterintuitive results illustrate the usefulness of prediction for generating new stylized facts for future research to explain. Ours is one of just two attempts to forecast local violence using survey data, and we conclude by discussing how our approach can be replicated and extended as similar datasets proliferate.

Keywords: forecasting, violence, machine learning, surveys, Africa

Suggested Citation

Blair, Robert A. and Blattman, Christopher and Hartman, Alexandra, Predicting Local Violence: Evidence from a Panel Survey in Liberia (October 20, 2016). Available at SSRN: https://ssrn.com/abstract=2856479

Robert A. Blair

Brown University ( email )

Box 1860
Providence, RI 02912
United States

Christopher Blattman (Contact Author)

University of Chicago, Harris School of Public Policy ( email )

1101 East 58th Street
Chicago, IL 60637
United States

National Bureau of Economic Research (NBER) ( email )

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

Alexandra Hartman

University College of London ( email )

29-30 Tavistock Sq
School of Public Policy
London, WC1H 9QU
United Kingdom

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