Panel data nowcasting
提出在即时预测中使用面板数据方法，从国家层面转向区域层面，通过混合频率面板VAR模型和偏差校正估计量，对美国各州季度实际GDP增长进行即时预测，并展示了跨州信息整合的收益。
This article promotes the use of panel data methods in nowcasting. This shifts the focus of the literature from national to regional nowcasting of variables like gross domestic product (GDP). We propose a mixed-frequency panel VAR model and a bias-corrected least squares estimator which attenuates the bias in fixed effects dynamic panel settings. Simulations show that panel forecast model selection and combination methods are successfully adapted to the nowcasting setting. Our novel empirical application of nowcasting quarterly U.S. state-level real GDP growth highlights the success of state-level nowcasting, as well as the gains from pooling information across states.