基于分段组合VARX模型的中国出境游客数量预测  

Forecasting Chinese Outbound Tourism with Segmented Combined VARX Models

作　　者：王雯 李丰 Wen Wang;Feng Li(School of Statistics and Mathematics,Central University of Finance and Economics;Guanghua School of Management,Peking University)

机构地区：[1]中央财经大学统计与数学学院 [2]北京大学光华管理学院

出　　处：《经济管理学刊》2025年第1期255-284,共30页Quarterly Journal of Economics and Management

基　　金：国家社会科学基金一般项目(22BTJ028)。

摘　　要：本文对结构性变化的旅游需求进行研究,基于带有外生变量的向量自回归(VARX)模型,提出了一种分段组合预测的方法。与既有研究普遍采用的基于完整数据集构建组合预测模型不同,本文创新性地将时间因素纳入组合预测考量,通过将不同时间段的变量视为独立的单元,构建出分段时间序列数据集的组合预测模型。该方法以游客的网络搜索行为作为外生变量用于预测旅游人数,并捕捉这些外生变量在不同时间节点上对旅游人数产生的差异化影响,特别是在新冠疫情等突发冲击下的动态变化。实证结果显示,VARX模型的分段组合在预测中国出境旅游人数时展现出更高的准确性,其预测精度因考虑了外生变量在不同时间段的特异性影响而得以提升。事后分析进一步显示,特别是针对2024年中国出境旅游趋势的外样本预测结果,随着全球旅游市场的逐步复苏,中国出境旅游人数将呈现积极向上的增长态势。这一结论与现有公开文献中的趋势分析相吻合,进一步印证了本文预测方法的实践应用价值。The tourism industry has experienced sustained growth in recent years.However,the COVID-19 pandemic led to a sharp decline in global tourism in 2020.As the impact of the virus wanes and epidemic management becomes more standardized,the tourism sector is gradually rebounding.China,the world's largest outbound tourism market,has significantly contributed to the global recovery of tourism through its policy approach to COVID-19 normalization.Forecasting tourist numbers enables more strategic allocation and adjustment of tourism resources,enhancing service quality.The pandemic has influenced tourism demand,making it essential to analyze these shifting patterns for the sustainable growth of the industry.Research in tourism forecasting has yielded several insights:①Tourism demand forecasts benefit from incorporating relevant external factors,such as online search indices,to boost accuracy and interpretability.②Combining forecasting methods can enhance,or at least maintain,the accuracy of single forecasts.③Unforeseen events like COVID-19 outbreaks can compromise the accuracy of traditional methods,necessitating specialized forecasting approaches during crises.However,existing methods often overlook the varying impact of exogenous factors on tourism demand over different periods,assuming a stable relationship between explanatory and target variables even in crisis conditions.In reality,the pandemic altered tourists'risk perceptions,which,in turn,influenced their demand and consumption preferences,impacting their travel behavior.This indicates that an explanatory variable's effect on tourism demand may differ across pre-pandemic,pandemic,and post-pandemic periods,meaning that variables from distinct periods may need to be treated as independent new variables.This research primarily employed a Vector Autoregression model with exogenous variables(VARX),an adaptation of the Vector Autoregression(VAR)model that allows for the simultaneous analysis of endogenous and exogenous variables.The study began by gathering data o

关 键 词：带有外生变量的向量自回归模型 分段组合 旅游预测 

分 类 号：F590[经济管理—旅游管理] F064.1[经济管理—产业经济] O212.4[理学—概率论与数理统计]