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ABSTRACT This study explores the dynamic interaction between Climate Policy Uncertainty (CPU), Economic Policy Uncertainty (EPU), and the performance of the U.S. tourism sector through a novel multi‐layered analytical framework. Using advanced econometric and machine learning techniques, we examine monthly data spanning 2005 to 2021 across three interrelated dimensions: tourist arrivals, tourism revenues, and stock market performance of tourism firms. Our findings reveal a temporal and contextual divergence in the effects of CPU and EPU: CPU has a stronger influence on revenue streams, while EPU predominantly shapes tourist arrivals, particularly during global crises such as the COVID‐19 pandemic and the U.S.‐China trade tensions. Moreover, we show that these core tourism metrics significantly moderate the transmission of policy uncertainties to tourism‐related firm performance, with more pronounced effects in small and medium‐sized firms. These findings have significant implications for policymakers, investors, and tourism managers, emphasizing the need for differentiated strategies to enhance resilience across firm types during periods of environmental and economic uncertainty. Our findings contribute to the literature by showing that CPU and EPU represent distinct but interconnected uncertainty channels that cascade from tourism demand and revenues to financial‐market valuation, with heterogeneous effects across firm‐size categories.
Elbialy et al. (Mon,) studied this question.