Temporal Patterns in Migration Flows Evidence from South Sudan

Abstract

What explains the variation in migration flows over time and space? Existing work has contributed to a rich understanding of the factors that affect why and when people leave. What is less understood are the dynamics of migration flows over time. Existing work typically focuses on static variables at the country-year level and ignores the temporal dynamics. Are there recurring temporal patterns in migration flows? And can we use these patterns to improve our forecasts of the number of migrants? Here, we introduce new methods to uncover temporal sequences—motifs—in the number of migrants over time and use these motifs for forecasting. By developing a multivariable shape similarity-based model, we show that temporal patterns do exist. Moreover, using these patterns results in better out-of-sample forecasts than a benchmark of statistical and neural networks models. We apply the new method to the case of South Sudan.