Balcilar, MehmetUsman, OjonugwaÖzkan, Oktay2023-11-102023-11-102023https://hdl.handle.net/11467/6992https://doi.org/10.1080/13683500.2023.2245109This study presents evidence on how tourism development affects U.S. energy security risks from 1997 to 2020 using a Kernel-based regularized least squares (KRLS) machine learning approach. Our empirical results demonstrate that tourism development amplifies the U.S. energy security-related risks. Also, while technological innovation and urbanization dampen the pressure on energy security-related risks, economic policy-based uncertainty and industrial production increase energy security risks. These results survive in the disaggregated models except for the environmental-related risks sub-index which decreases as a result of tourism development. Our findings, therefore, provide useful insights for policymakers to minimize energy security-related risks.eninfo:eu-repo/semantics/embargoedAccessU.S energy security risks; tourism development; policy uncertainty; technology innovation; KRLS machine learningReviewQ1WOS:001045332800001N/A2-s2.0-8516783638610.1080/13683500.2023.2245109