期刊名称：South African Journal of Economic and Management Sciences
印刷版ISSN：2222-3436
出版年度：2014
卷号：17
期号：4
页码：379-395
出版社：University of Pretoria
摘要：ABSTRACT The core of South Africa tourism industry is based on wildlife tourism. Private game reserves and game farms which forms part of wildlife tourism constitute most of the wildlife products in South Africa. On these private reserves and game farms, hunting is one of the major income generators for product owners. The aim of this study is to analyse the economic impact of hunting on the regional economies of three of South Africa's most important hunting provinces. The study used economic multipliers, input-output analysis, and related modelling processes through input-output (supply-use) tables and social accounting matrices (SAM). The results differed significantly for the three provinces, with Limpopo receiving the biggest impact (R2.6 billion) and the Free State having the highest multiplier (2.08). The geographical location of the game farms, the number of farms per province and the species available all influenced the magnitude of the economic impact of hunters over and above the traditional determinants of economic impact analysis. The implication of the research is that it will help product owners in the development of game farms or hunting products, contribute to policy formulation, especially for government decisions on what products to offer where, and how to create more jobs.
其他摘要：ABSTRACT The core of South Africa tourism industry is based on wildlife tourism. Private game reserves and game farms which forms part of wildlife tourism constitute most of the wildlife products in South Africa. On these private reserves and game farms, hunting is one of the major income generators for product owners. The aim of this study is to analyse the economic impact of hunting on the regional economies of three of South Africa's most important hunting provinces. The study used economic multipliers, input-output analysis, and related modelling processes through input-output (supply-use) tables and social accounting matrices (SAM). The results differed significantly for the three provinces, with Limpopo receiving the biggest impact (R2.6 billion) and the Free State having the highest multiplier (2.08). The geographical location of the game farms, the number of farms per province and the species available all influenced the magnitude of the economic impact of hunters over and above the traditional determinants of economic impact analysis. The implication of the research is that it will help product owners in the development of game farms or hunting products, contribute to policy formulation, especially for government decisions on what products to offer where, and how to create more jobs.
