We propose a time-varying framework for tail risk contagion based on conditional higher co-moments (Co-HCM), derived from a DCC-GARCH-MGH model that provides closed-form expressions for dynamic co-moments. Applying this CoHCM approach, we construct tail contagion networks across Belt and Road Initiative (BRI) stock markets. Our ffndings indicate that covariance-based metrics underestimate the ex-tent of epidemic transmission, while the CoHCM metrics reveal China’s pivotal role in spreading outbreaks and identify a distinct cluster of core transmission hubs, particularly during the 2015 Chinese stock market crisis. Dynamic contagion further exhibits cross-country heterogeneity that the Southeast Asian markets synchronize tightly with China during crises, while smaller and resource-driven markets display more inter-mittent contagion patterns. These ffndings highlight the importance of higher co-moment dependence for monitoring systemic risk in interconnected emerging markets.

The study aims to explain the economic impact of Internet implication in tourism sector by taking sample of mega project listed countries (which provide big pitch to boost tourism business). Our work find the volatility cause of tourism revenue at country i, by examining the inbound tourist expenditures as a factor of technological infrastructure. We deploy data ranging from 1990 to 2017 and uses error correction model as representative of Autoregressive-Distributed Lag (ARDL) model after addressing diagnostic tests (for data reliability concern). We found long- and short-run association between tourism expenditure and information and communication technology (ICT) proxies in case of developed economies, while only short-run association in underdeveloped countries. The startling scenario about underdeveloped economies are also confirmed by one-way causation in our analysis. After sensitive analysis at each slot, the study concludes that tourism revenue is streaming low across those boundaries where tourists a