Learning from the past: a machine-learning approach for predicting the resilience of locked-in regions after a natural shock
研究利用机器学习方法，预测2016年意大利中部地震对133个农村和内城地区劳动力市场的长期影响，填补了针对锁定和欠发达地区韧性研究的空白。
Italy has been affected by many different shocks in recent years, from the Great Recession to many natural hazards. While many studies have analysed the effects of natural and socio-economic shocks on urbanized and developed areas, very few have focused on locked-in and less developed regions. In this study we focus on the pernicious effects of three earthquakes that have affected the labour markets of rural and inner municipalities of Central Italy during the last 20 years. We adopt a machine-learning technique that allows us to provide a scenario five to seven years after the earthquake for 133 municipalities affected by the Central Italy earthquake in 2016.