The nonlinear interaction of oil prices, inflation, the exchange rate, institutional quality, and trade balance on tourist arrivals in Bangladesh is scrutinized in this study. The technique utilized in this study, Nonlinear Autoregressive Distributed Lag (NARDL), is a novel co-integrating strategy. The yearly time series data used in this study spanned 1995 to 2019. The NARDL bound test is performed to assess if variables like oil prices, inflation, the exchange rate, institutional quality, and trade balance on tourist arrivals are co-integrated. Oil prices and exchange rates, according to the findings, have a long-run negative and significant impact on tourism demand, whereas improvements in institutional quality are positively associated with tourist arrivals. Moreover, the study’s findings revealed a nonlinear kinship between the trade balance, inflation, and tourism demand across time. The asymmetric results obtained could enable Bangladeshi policymakers to make more precise decisions.

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