This paper is to produce different scenarios in forecasts for international tourism demand, in light of the COVID-19 pandemic. By implementing two distinct methodologies (the Long Short Term Memory neural network and the Generalized Additive Model), based on recent crises, we are able to calculate the expected drop in the international tourist arrivals for the next 12 months. We use a rolling-window testing strategy to calculate accuracy metrics and show that even though all models have comparable accuracy, the forecasts produced vary significantly according to the training data set, a finding that should be alarming to researchers. Our results indicate that the drop in tourist arrivals can range between 30.8% and 76.3% and will persist at least until June 2021.

中文翻译：

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COVID-19 旅游业复苏的好、坏和丑陋

鉴于 COVID-19 大流行，本文将在国际旅游需求预测中产生不同的情景。通过实施两种不同的方法（长短期记忆神经网络和广义加性模型），基于最近的危机，我们能够计算出未来 12 个月国际游客人数的预期下降。我们使用滚动窗口测试策略来计算准确度指标，并表明即使所有模型都具有可比的准确度，但根据训练数据集产生的预测差异很大，这一发现应该让研究人员感到震惊。我们的结果表明，游客人数下降幅度在 30.8% 到 76.3% 之间，并且至少会持续到 2021 年 6 月。