Econometric Analysis of Pandemic Disruption and Recovery Trajectory in the U.S. Rail Freight Industry
美国铁路货运业疫情冲击与复苏轨迹的计量分析
To measure the impacts on U.S. rail and intermodal freight by economic disruptions of the 2007-09 Great Recession and the COVID-19 pandemic, this paper uses time series analysis with the AutoRegressive Integrated Moving Average (ARIMA) family of models and covariates to model intermodal and commodity-specific rail freight volumes based on pre-disruption data. A framework to construct scenarios and select parameters and variables is demonstrated. By comparing actual freight…