作者：Lee, Kwok Hao; Tan, Brandon Joel
作者单位：National University of Singapore; Harvard University
摘要：We propose a quantitative spatial model featuring heterogeneous worker groups and their travel to consume nontradable goods and services. We consider the opening of the Downtown Line in Singapore, which connected regions where high-income households have residential amenities to where nontraded sectors are productive. Leveraging transit farecard data, we show that high-income workers saw large welfare gains but low-income workers gained little. Everyone enjoyed improved access to consumption o...
作者：Heller, Sara B.; Jakubowski, Benjamin; Jelveh, Zubin; Kapustin, Max
作者单位：University of Michigan System; University of Michigan; National Bureau of Economic Research; New York University; University System of Maryland; University of Maryland College Park; Cornell University
摘要：Using Chicago police data, we train a machine learning model to predict the risk of being shot in the next 18 months. Out-of-sample accuracy is strikingly high. A central concern with using police data is baking in bias, or overestimating risk for groups likelier to interact with police conditional on behavior. Our predictions, however, accurately recover risk across demographic groups. Legal, ethical, and practical barriers should prevent using victimization predictions to target law enforcem...
