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

Authors: Anton Abdulbasah Kamil; Muhamad Safiih Lola

Addresses: Faculty of Economics, Administrative and Social Sciences, Istanbul Gelisim University, 34310 Avcilar/Istanbul, Turkiye ' Faculty of Ocean Engineering Technology and Informatics, Universiti Malaysia Terengganu, 21030, Kuala Nerus, Terengganu, Malaysia

Abstract: 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.

Keywords: bootstrap method; Granger Causality; hybridisation; tourism impact and non-economy factors; Malaysia.

DOI: 10.1504/IJDATS.2026.151639

International Journal of Data Analysis Techniques and Strategies, 2026 Vol.18 No.1, pp.57 - 81

Accepted: 20 Nov 2023
Published online: 11 Feb 2026 *

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