The Influence of Economic Factors and Policies on Deforestation in Tanzania
Corresponding Author(s) : thadei sagamiko
Journal of Humanities & Social Science (JHSS),
Vol. 9 No. 2 (2020): SPECIAL ISSUE OF SCIENCE, 2020
Abstract
In this paper we analysed the influence of economic factors and policy on the rate of
deforestation in Tanzania. A multiple linear regression model was formulated and the
effects of each factor on deforestation were tested. The ordinary least squares method was
used to estimate the model parameters. Correlation analysis revealed that per capita
income, per capita purchasing power, and electricity consumption have positive
relationship with deforestation rate; while inflation rate and poverty rate have a negative
relationship with deforestation rate. All factors were found to be significant and were used
for regression analysis. By considering the p-value at 5% level, the coefficient of
determination from regression analysis indicated that 87% of deforestation rate is caused
by explanatory variables captured in the model; and all explanatory variables had positive
impact on deforestation. Thus, it is suggested that policy and decision-making should link
with the country’s desire for economic growth and environmental management.
Keywords
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- Economics, 82(3): 409–412.
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- Structure, Estimation, and Application. Amsterdam Academic Press, Amsterdam.
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- Government of the United Republic of Tanzania, TZA-NBS-2011-V01.
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- Bongor, Indonesia. PhD Thesis, Georg-August-University of Göttingen.
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References
Blomquist, S. 1980. A Note on the Use of the Coefficient of Determination. Scandinavian Journal of
Economics, 82(3): 409–412.
Buongiorno, J., S. Zhu, D. Zhang, J. Turner & D. Tomberlin. 2003. The Global Forest Products Model:
Structure, Estimation, and Application. Amsterdam Academic Press, Amsterdam.
Cronk, B. C., 2012. How to Use SPSS: A Step-By-Step Guide To Analysis and Interpretation (7th
Edition) Glendale, CA: Pyrczak Publishing.
Daniel, G., 2007. Forest Management Gender and Food Security of Rural Poor in Africa UNU-WIDER,
(ISSN 1810–2611).
Food and Agriculture Organization (FAO). 2001. State of the World’s Forest 2001 Food and
Agriculture Organization. Rome: FAO.
Food and Agriculture Organization (FAO). 2010. Global Forest Resource Assessment, Country
Report, URT. Rome: FAO.
Kaale, B. K., 2005. Baseline Study on Biomass Energy Conservation in Tanzania. SADC Program for
Biomass Energy Conservation. Ministry of Energy and Minerals, Dar Es Salaam, Tanzania.
Kaimowitz, D. & A. Angelsen. 1998. Economic Models of Tropical Deforestation a Review, Center
for International Forestry Research, Bogor, Indonesia.
Kooten, G. C. & E. H. Bulte. 2000. The Economics of Nature; Managing Biological Assets. Blackwell
Publishers, Oxford, UK.
Kindermann, G. E., M. Obersteiner, E Rametsteiner & Mccallum. 2006. Predicting the DeforestationTrend Under Different Carbon-Prices. Carbon Balance and Management 1(15).
Le Cessie, S. & J. V. Houwelingen. 1992. Ridge Estimators in Logistic Regression. Applied Statistics
(1): 191–201.
Ministry of Natural Resources and Tourism (MNRT). 1999. Tanzania Forestry Action Plan 1994/95 –
/08, Update, Draft.
National Forestry Resources Monitoring and Assessment (NAFORMA). 2014. Draft Report on
NAFORMA Dar es Salaam. Tanzania Forest Services.
National Bureau of Statistics (NBS). 2014. Household Budget Survey 2011–2014, Sixth Round,
Government of the United Republic of Tanzania, TZA-NBS-2011-V01.
Nkonoki, S. R, 1983. The Poor Man’s Energy Crisis. A Report of the Tanzania Rural Energy
Consumption Survey Dar Es Salaam, Tanzania.
Reetz, S. W. H, 2012. Effects of Land Use, Market Integration and Poverty on Tropical Deforestation,
Bongor, Indonesia. PhD Thesis, Georg-August-University of Göttingen.
Scrieciu, S. S. 2001. Economic Causes of Tropical Deforestation - A Global Empirical Application.
Manchester, UK. (18):108–118.
Slingenberg, A., B. Leon, W. Henny, R. Koen, E. Lisa & T. Kerry. 2006. Understanding the Cause of
Biodiversity Loss and Policy Assessment Framework, ECORYS, Netherland.