Brian A., Jingwa and Simplice A., Asongu (2012): The Role of Human Development on Deforestation in Africa: A Modelling-Based Approach.
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Abstract
The rate of deforestation in Africa is of paramount concern not only to the future of Africa, but also to the world. This study uses country-level data to model changes in forest area over an 18 year period (1990-2007) in 35 African countries and investigates the role played by important development indicators of human development. The results reveal that the net loss of forests was 0.19% every year between 1990 and 2007. This implies a total of 3.42% of forest was lost in the 18 year period. This is more in line with estimates obtained by the Food and Agricultural Organization (0.56% between1990-2000 and 0.49% between 2000-2010). Human development which involves life expectancy, education and income is found to have a positive effect on forest growth and conservation, while cutting down trees for wood fuel is a significant cause of deforestation. Using generalized linear mixed models and generalised estimating equations, we were able to calculate expected estimates of forest area for 2010, 2020 and 2030 under the assumption that nothing is done to change observed trends. In many countries, progress has been made in reforestation, forest protection and conservation. However, if indiscriminate cutting down of trees is not checked, many countries will lose most or all of their forests by 2030.
Item Type: | MPRA Paper |
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Original Title: | The Role of Human Development on Deforestation in Africa: A Modelling-Based Approach |
Language: | English |
Keywords: | Deforestation; Environment; Human development index; Agriculture; Data modelling; Africa |
Subjects: | Q - Agricultural and Natural Resource Economics ; Environmental and Ecological Economics > Q2 - Renewable Resources and Conservation > Q23 - Forestry C - Mathematical and Quantitative Methods > C3 - Multiple or Simultaneous Equation Models ; Multiple Variables > C39 - Other C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C50 - General I - Health, Education, and Welfare > I0 - General O - Economic Development, Innovation, Technological Change, and Growth > O1 - Economic Development > O13 - Agriculture ; Natural Resources ; Energy ; Environment ; Other Primary Products C - Mathematical and Quantitative Methods > C3 - Multiple or Simultaneous Equation Models ; Multiple Variables > C33 - Panel Data Models ; Spatio-temporal Models |
Item ID: | 35898 |
Depositing User: | Brian A. Jingwa |
Date Deposited: | 12 Jan 2012 16:22 |
Last Modified: | 27 Sep 2019 01:51 |
References: | Achard F, Eva H., Stibig H. Mayaux P., Gallego J., Richards T. and Malingreau J. (2002) Determination of deforestation rates of the world’s humid tropical forests. Science, 298, 999-1002. Akaike, H. (1974) A New Look at the Statistical Model Identification. IEEE Trans. Autom. Control, AC (19), 716-723. Anderson J., Ball J., Bourke I., Braatz S., Clément J., Dembner S., Morell M., Palmberg-Lerche C., Perlis A., Russo L., and Warner K. (1999) Non-wood forest products and income generation. Unasylva,FAO , 198 Arild Angelsen and David Kaimowit (1999) Rethinking the Causes of Deforestation: Lessons from Economic Models. The World Bank Research Observer.14, 73-98 Asongu S. and Jingwa B. (2011) Population growth and forest sustainability in Africa. MPRA Paper No. 35179. Brown, S., and G. Gaston. (1996) Tropical Africa: Land Use, Biomass, and Carbon Estimates for 1980. ORNL/CDIAC-92, NDP-055. Dorothy D. Dunlop (1994) Regression for Longitudinal Data: A Bridge from Least Squares Regression. The American Statistician, 48(4), 299-303. Easterly W. (2007) How the millennium development goals are unfair to Africa. Global Economy and Development, Working Paper 14. Giesbrecht F. and Burns J. (1985) Two-Stage Analysis Based on a Mixed Model: Large-Sample Asymptotic Theory and Small-Sample Simulation Results. Biometrics, 41(2), 477-487. FAO (2006) Regional strategic framework for Africa (2010-2015). FAO (1996). Forest resources assessment 1990 - Survey of tropical cover and study of change processes. FAO Forestry Paper 130. Rome. 152 pp. FAO (2001). Global forest resources assessment 2000. Main Report. FAO Forestry Paper 140. Rome. 479 pp Food and Agricultural Organisation of the United Nations (2010). State of the World’s Forests 2010. FAO Corporate Document Repository, Rome. Food and Agricultural Organisation of the United Nations (2011). State of the World’s Forests 2011. FAO Corporate Document Repository, Rome. Foster, J., Lopez-Calva, L., and Szekely, M. (2005) Measuring the distribution of human development: methodology and an application to Mexico. Journal of Human Development, 6(1), 5-29. Hedeker, D. (2004) An introduction to growth modeling. In D. Kaplan (Ed.), Quantitative Methodology for the Social Sciences. Thousand Oaks CA: Sage Publications. http://wwf.panda.org/about_our_earth/about_forests/deforestation/forestdegradation/ (accessed 10/12/2011). Jha S. and Bawa K. (2006) Population growth, human development, and deforestation in biodiversity hotspots. Conservation Biology, 20(3), 906-912. Kelatwang S. and Garzuglia M. (2006) Changes in forest area in Africa 1990-2005. International Forestry Review, 5(1), 21-30. Kenneth M. Chomit, Piet Buys, Giacomo De Luca, Timothy S. Thomas, and Sheila Wertz-Kanounnikoff.( 2006) At Loggerheads? Agricultural Expansion, Poverty Reduction, and Environment in the Tropical Forests. A World Bank Policy Research Report The World Bank. Kung-Yee Liang and Scott L. Zeger (1986) Longitudinal data analysis using generalized linear models. Biometrika, 73(1) 13-22. Lanly, P. 1982. Tropical forestry resources. FAO Study: Forests 30. Rome. 113 pp Molenberghs G. and Verbeke G. (2005).Models for Discrete Longitudinal Data. Springer Science + Business Media Inc. Nan M. Laird and James H. Ware (1982) Random-Effects for Longitudinal Data. Biometrics, 38 (4), 963-974. Neyman J. and Pearson E. (1928) On the use and interpretation of certain test criteria for purposes of statistical inference Part I. Biometrika, 20A (1/2), 175-240. Pan wei (2001) Akaike’s information criterion in Generalized Estimating Equations. Biometrics, 57, 120-125. Raghu N. Kackar and David A. Harville (1981) Unbiasedness of two-stage estimation and prediction procedures for mixed linear models. Communications in statistics-theory and methods, 10(13), 1249-1261. The World Bank (2010) African Development Indicators. The world Bank. The World Bank (2011) African Development Indicators 2011. The International Bank for Reconstruction and Development/ the World Bank, Washington DC. UNDP Human Development Report (2010). The Real Wealth of Nations: Pathways to Human Development. 20th Anniversary ed. UNDP. United Nations (2005). Resolution adopted by the general assembly. Dist. General. Vecchia A., Pini G., Sorani F. and Tarchiani V. (2005) KEITA: The impact on environmental and livelihood status of 20 years fight against desertification actions. Viterbo. Verbeke G. and Molenberghs G. (2009). Linear Mixed Models for Longitudinal data. Springer, New York, Inc. |
URI: | https://mpra.ub.uni-muenchen.de/id/eprint/35898 |