Development of G-causality by utilising hybridisation of bootstrap method for assessing tourism impacts in Malaysia

This study aims to develop and examine the causality direction of non-economic short and long-term factors in the Malaysian tourism industry using a new hybrid Bootstrap-Granger Model. The proposed method was validated with non-economic factor dataset from the World Bank (tourist arrival, population, air transport, and carbon dioxide emission) in the tourism industry. The model effectiveness was tested and analysed by comparing it against the actual Granger model using statistical tests such as unit root, Johansen cointegration, and Granger causality tests. The empirical results revealed that compared to the Granger model, the proposed counterpart generated smaller mean square error and root mean square error values for non-economic factor datasets. Furthermore, the results also revealed that tourist arrival and other determinants were co-integrated. In other words, the proposed model enhanced Granger causality accuracy and proved to be more robust, precise, and accurate results towards the promotion of overall economic activities.