Adaptive nowcasting of arrivals during health crises
提出一种自适应方法，利用“必要旅行条件”作为障碍，结合疫情前趋势和流行病学模型，即时预测健康危机期间的到达人数。
This paper develops a new methodology to nowcast the number of arrivals during health-related crises such as Covid-19. The methodology is adaptive, so that the relevance of different determinants varies over time by employing hurdles that work as ‘necessary travelling conditions’. It starts with a baseline series built upon a pre-Covid-19 trend. This series is adjusted by each hurdle. The first hurdle is the market closure; epidemiological models are applied to anticipate the dates of re-opening. The second hurdle deals with key travelling determinants such as the income effect. The third hurdle is the lack of confidence; this depends on the length of the recovery, and the expected path to follow.