Impact of Tourism on the Environment and Economic Growth: Evidence from Sub-Saharan Africa

Transcription

1 Impact of Tourism on the Environment and Economic Growth: Evidence from Sub-Saharan Africa B O S T O N U N I V E R S I T Y M E T R O P O L I T A N C O L L E G E J U N G W A N L E E, P H. D.

2 Purposes of This Research For past decades, there was quite a lot time series approach to analyze the relationship between tourism and economic growth, But there was no systematic time series approach to analyze the relationship between tourism, carbon dioxide emissions and economic growth for sub-saharan Africa. The research question here is whether tourism is the cause of the increase in carbon dioxide emissions and economic growth in the region. Our research on the link between tourism, carbon dioxide emissions and economic growth is different from prior research in the following two points: first, that this study employs multivariate panel regression models for research method, not using the environmental Kuznets curve model nor computable general equilibrium models; second, that we categorize sub-sahara African countries into two groups: oil producing countries versus non-oil producing countries. 2

3 Statements of the Problems The major challenge in the minds of sub-sahara Africa is first, how to develop policy responses to counter the effects of the current environmental problems and second, lay the foundations for robust and sustainable development that generates employment and at the same time reduces the carbon dioxide emissions from industries. Facing this challenge, the increase of economic importance of tourism raises new questions and pressures to governments regarding the best policy frameworks to encourage continued economic growth and the reduction of carbon dioxide emissions. 3

4 Related Literature Total 52 articles are cited in text, and fully listed at References. Those articles were selected mainly from Environmental studies, Tourism research, Ecological economics, and Econometrics Web of Science listed journals (mainly SSCI) such as Tourism Management, Annals of Tourism Research, Journal of Ecological Economics, and Journal of Econometrics, etc. 4

5 Hypotheses H1: Tourism directly affects economic growth. H2: Economic growth positively affects carbon dioxide emissions. H3: Tourism directly affects carbon dioxide emissions. H4: There is a long-run equilibrium relationship between tourism, economic growth and carbon dioxide emissions. 5

6 Data 6 The International Monetary Fund lists 47 countries under Sub-Saharan Africa. At the first stage of data screening, 19 countries were excluded, and at the second stage, 14 additional countries were excluded because the data of tourism receipts, energy use or carbon dioxide emissions are entirely or partly missing. As a result, only 14 countries that have full information in terms of their longitudinal data availability were employed. Finally, the sample of 14 countries includes Angola, Botswana, Cameroon, Ivory Coast, Ethiopia, Ghana, Kenya, Mauritius, Mozambique, Nigeria, Senegal, South Africa, Sudan and Tanzania. The sample of 23 observations in each country is restricted to the period in which annual data are available from 1988 to 2010.

7 Summary Statistics of the Sample Country GDP Growth Energy Use CO 2 Emissions Tourism/GDP Angola Botswana Cameroon Ivory Coast Ethiopia Ghana Kenya Mauritius Mozambique Nigeria Senegal South Africa Sudan Tanzania Statistics Mean Median St. Deviation Minimum Maximum

8 Results of Panel Unit Root Test 8 Variables GDP CO 2 Energy Use Tourism Method Level 1st diff. Level 1st diff. Level 1st diff. Level 1st diff. Levin, Lin, & Chu *** *** *** *** *** Breitung *** *** *** *** *** Im, Pesaran, & Shin *** *** *** *** *** Fisher-ADF *** *** *** *** *** Fisher-PP *** *** *** *** ***

9 Results of Fisher-type Johansen Panel Cointegration Test 9 GDP = f(tourism, Energy Use) CO 2 = f(tourism, Energy Use, GDP) Number of cointegration (r) r = 0 r 1 r 2 r 3 Trace test statistic Max-eigenvalue test statistic Trace test statistic Max-eigenvalue test statistic 48.35*** 39.89** *** *** *** 40.28**

10 Results of Panel Regression Models [Oil producers¹] Variables GDP = f(tourism, Energy Use) t-statistic in [ ] Tourism 0.431[10.567]*** 0.067[1.372] CO 2 = f(tourism, Energy Use, GDP) t-statistic in [ ] Energy Use 1.029[6.975]*** 0.502[3.303]*** GDP 0.325[4.189]*** Constant [10.655] [-1.878] Dependent variable GDP CO 2 R-squared Adjusted R-squared F-statistic *** *** Durbin-Watson stat Estimation method Random Effects Model Random Effects Model ¹Oil producers: Angola, Cameroon, Ivory Coast, Mozambique, Nigeria and Sudan. 10

11 Results of Panel Regression Models [Non-oil producers²] Variables GDP = f(tourism, Energy Use) t-statistic in [ ] CO 2 = f(tourism, Energy Use, GDP) t-statistic in [ ] Tourism 0.307[3.377]*** 0.077[2.717]*** Energy Use 0.859[2.691]*** 0.976[10.480]*** GDP 0.009[0.459] Constant [3.399] 0.083[0.087] Dependent variable GDP CO 2 R-squared Adjusted R-squared F-statistic *** *** Durbin-Watson stat Estimation method Random Effects Model Random Effects Model ²Non-oil producers: Botswana, Ethiopia, Ghana, Kenya, Mauritius, Senegal, South Africa and Tanzania. 11

12 Findings and Discussions[1/2] 1. Detailed plans or strategies. Governments especially in the non-oil producing countries should take a greater role in promoting the awareness of the benefits associated with sustainable tourism growth. Putting a price on environmental problems through cost mechanisms such as taxes or tradable permit systems could be available options for policymakers. 2. Greening technology support policies. 12 Greening technology support policies for energy use may be appropriate since energy use is a highly significant factor in predicting economic growth and CO2 emissions. Better responsiveness of businesses and consumers will promote environmental awareness among all the stakeholders and thus educate and motivate them to conduct their activity in an environmentally responsible manner and guide tourists to act in environmentally friendly ways.

13 Findings and Discussions[2/2] 3. Altering tourism consumption patterns. Alternatively, implementing new policies as well as altering tourism consumption patterns could be more effective. These include economic incentives for tourism firms undertaking low carbon technologies in their tourism operation, such as transportation, accommodation and waste management Strengthened international support networks. The recommendations made in Agenda 21. It is a product of the 1992 UN Conference on Environment and Development held in Rio de Janeiro, Brazil. These undertakings can be encouraged through strengthened international support networks such as international cooperation to provide information on weather patterns and climatic conditions or to fashion new and collaborative financing systems for implementing the necessary actions. The New Partnership for Africa s Development also calls for African communities to engage actively in sustainable tourism, including adventure tourism, ecotourism and cultural tourism.

14 Conclusions The current research discovers both long-run equilibrium and short-run dynamics between economic growth, tourism, energy use and carbon emissions in sub-saharan Africa. o o 14 Tourism shows highly significant direct impact on economic growth. Tourism and economic growth yield a highly significant positive effect on carbon emissions. Sub-Saharan African countries from both oil and non-oil producing countries need support in enhancing and promoting policy coherence, and integrating climate change mitigation concerns into priority development policies and programs.