The effect of tourism on economic growth: a production function approach / Cheam Chai Li, Nik Nor Hashimah Nik Ismail and Mazlina Mamat

Tourism is one of the largest and fastest growing industries in the world. The upsurge of interest in the role of tourism for economic growth is due to its contribution to the host country in terms of foreign exchange earnings, employment, multiplier effects, etc. This turns the sector into a potent...

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Bibliographic Details
Main Authors: Cheam, Chai Li, Nik Ismail, Nik Nor Hashimah, Mazlina Mamat, Mazlina
Format: Research Reports
Language:English
Published: 2013
Subjects:
Online Access:https://ir.uitm.edu.my/id/eprint/61713/1/61713.pdf
https://ir.uitm.edu.my/id/eprint/61713/
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Summary:Tourism is one of the largest and fastest growing industries in the world. The upsurge of interest in the role of tourism for economic growth is due to its contribution to the host country in terms of foreign exchange earnings, employment, multiplier effects, etc. This turns the sector into a potential strategic factor for economic growth. Tourism in Malaysia follows the same trend. As far as the study is concerned, even there is a huge increased in tourism industry worldwide, the empirical results with regards to Granger causality are mixed between tourism and economic growth. Moreover, not much attention has been given to the issue of tourism and growth within neoclassical growth theory in Malaysia. Long term economic growth rates are conditioned by physical capital and human capital thus reflecting the important of production functions to an economy. Therefore the link between economic growth, tourism and production functions is an important issue that needs to be analyzed in depth. With the above mentioned reasons, it has inspired the study to venture into this area within the Malaysian context and the objectives of the study are set to determine: 1) long run relationships, 2) the directions of Granger causality, and 3) the interaction of triangular relationships. The study employs econometric techniques such as unit roots, Johansen cointegration and multivariate Granger causality in vector error correction model (VECM).