Investigating Nepal’s Gross Domestic Product from Tourism: Vector Error Correction Model Approach
American Journal of Theoretical and Applied Statistics
Volume 5, Issue 5, September 2016, Pages: 311-316
Received: Aug. 31, 2016;
Accepted: Sep. 9, 2016;
Published: Sep. 28, 2016
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Basanta Dhakal, Central Department of Statistics, Tribhuvan University, Kathmandu, Nepal
Azay Bikram Sthapit, Central Department of Statistics, Tribhuvan University, Kathmandu, Nepal
Shankar Prasad Khanal, Central Department of Statistics, Tribhuvan University, Kathmandu, Nepal
This study tries to examine long run and short run relationship of foreign exchange earnings from tourism and average expenditure of international tourists towards share of gross domestic product (GDP) of Nepalese tourism by using Vector Error Correction Model (VECM). A multivariate time series analysis has been applied from the period of 1991 to 2014 tourism data of Nepal. The results of Johansen test of co-integration indicates there is one co-integrated vector under 4 lags of length among the share of gross domestic product of Nepalese tourism, foreign exchange earnings from tourism and average expenditure of international tourist. The long run relationship based on vector error correction model has indicated that coefficient of GDP elasticity with respect to average expenditure per visitor is more elastic as compare to coefficient of GDP elasticity with respect to foreign exchange earnings from tourism. The results of Granger causality analysis have depicted that there exists bidirectional causal relationship between GDP and expenditure per visitor and unidirectional causal relationship exists between GDP and foreign exchange earnings from tourism.
Azay Bikram Sthapit,
Shankar Prasad Khanal,
Investigating Nepal’s Gross Domestic Product from Tourism: Vector Error Correction Model Approach, American Journal of Theoretical and Applied Statistics.
Vol. 5, No. 5,
2016, pp. 311-316.
Copyright © 2016 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/
) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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