The determinants of tourism demand in South Africa using a dynamic panel data approach

2.50
Hdl Handle:
http://hdl.handle.net/10547/594733
Title:
The determinants of tourism demand in South Africa using a dynamic panel data approach
Authors:
Durbarry, Ramesh; Nicolas, J.F.; Seetanah, Boopen
Abstract:
This article models inbound tourism demand for South Africa using a theoretical framework that is based on the gravity model and provides elasticity estimates that are useful for policy purposes. It uses a well-established gravity model following Anderson and van Wincoop's model (2003) to explain tourism flows. The article departs from most of the existing work estimating tourism demand and builds on the recent work of Durbarry, but employs a dynamic panel data setting. The results show that tourists are not too sensitive to changes in the tourism price of South Africa, indicating that it offers a unique product and experience to tourists. In fact, evidence tends to suggest that competing destinations may imploy tourism products that are unique to their destinations in the region. The level of development and tourism infrastructure also affect arrivals. It is also found that distance negatively affects arrivals, but common border and language play an important role. The dynamic model supports the presence of repeat tourism and positive word-of-mouth, particularly from European and American origins.
Citation:
Durbarry, R., Nicolas, J.F., Seetanah, B. (2009) 'The Determinants of Tourism Demand in South Africa Using a Dynamic Panel Data Approach' Tourism Analysis 14 (3):375
Publisher:
Cognizant Communication Corporation
Journal:
Tourism Analysis
Issue Date:
1-Oct-2009
URI:
http://hdl.handle.net/10547/594733
DOI:
10.3727/108354209789704968
Additional Links:
http://openurl.ingenta.com/content/xref?genre=article&issn=1083-5423&volume=14&issue=3&spage=375
Type:
Article
Language:
en
ISSN:
1083-5423
Appears in Collections:
INTOUR Institute for Tourism Research

Full metadata record

DC FieldValue Language
dc.contributor.authorDurbarry, Rameshen
dc.contributor.authorNicolas, J.F.en
dc.contributor.authorSeetanah, Boopenen
dc.date.accessioned2016-01-25T10:47:40Zen
dc.date.available2016-01-25T10:47:40Zen
dc.date.issued2009-10-01en
dc.identifier.citationDurbarry, R., Nicolas, J.F., Seetanah, B. (2009) 'The Determinants of Tourism Demand in South Africa Using a Dynamic Panel Data Approach' Tourism Analysis 14 (3):375en
dc.identifier.issn1083-5423en
dc.identifier.doi10.3727/108354209789704968en
dc.identifier.urihttp://hdl.handle.net/10547/594733en
dc.description.abstractThis article models inbound tourism demand for South Africa using a theoretical framework that is based on the gravity model and provides elasticity estimates that are useful for policy purposes. It uses a well-established gravity model following Anderson and van Wincoop's model (2003) to explain tourism flows. The article departs from most of the existing work estimating tourism demand and builds on the recent work of Durbarry, but employs a dynamic panel data setting. The results show that tourists are not too sensitive to changes in the tourism price of South Africa, indicating that it offers a unique product and experience to tourists. In fact, evidence tends to suggest that competing destinations may imploy tourism products that are unique to their destinations in the region. The level of development and tourism infrastructure also affect arrivals. It is also found that distance negatively affects arrivals, but common border and language play an important role. The dynamic model supports the presence of repeat tourism and positive word-of-mouth, particularly from European and American origins.en
dc.language.isoenen
dc.publisherCognizant Communication Corporationen
dc.relation.urlhttp://openurl.ingenta.com/content/xref?genre=article&issn=1083-5423&volume=14&issue=3&spage=375en
dc.rightsArchived with thanks to Tourism Analysisen
dc.subjectdynamic panel dataen
dc.subjectSouth Africaen
dc.subjecttourism demanden
dc.titleThe determinants of tourism demand in South Africa using a dynamic panel data approachen
dc.typeArticleen
dc.identifier.journalTourism Analysisen
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