Heterogenous impacts of adverse labour market shocks
Previous research has shown that plant closures have large and persistent negative effects on earnings and employment. However, the impacts of plant closures and other adverse labour market shocks are very heterogeneous. In this project we use machine learning methods to learn about this heterogeneity. The goal is to learn why some cope rather well with negative shocks while others suffer large and persistent negative effects. We examine a wide range of factors which may explain the heterogeneous impacts, including human capital, family, occupation, location and industry characteristics. We also examine how these different factors interact.