The Effect of Socio-Economic Dimensions on Deforestation: Application of Spatial Econometrics

مجله اقتصاد و توسعه کشاورزی

Article 1, Volume 36, Issue 2 - Serial Number 55, July 2022, Pages 115-128   

Document Type: Research Article-en

DOI: 10.22067/jead.2022.17787.0

Authors

H. Amirnejad^{* 1}; A. Mehrjo¹; M.H. Eskandari Nasab²

¹Department of Agricultural Economics, Sari Agricultural Sciences and Natural Resources University, Sari, Iran

²Department of Agricultural Economics, Faculty of Agriculture, Tarbiat Modares University (T.M.U), Tehran, Iran

Abstract

In the second half of the twenty-first century, economic change, population growth and globalization were the main factors driving the deforestation in the South Asian countries. To identify the effects due to socio-economic factors affecting deforestation in such countries, this study applied the spatial econometrics model based on data from 18 selected countries for the period between 2005 and 2015. The spatial correlation tests were showing that ignoring the effects of spatial correlation cause bias in results. The results of the model also confirmed the environmental Kuznets curve hypothesis for the selected countries with a turning point of $ 5,107. Our findings illustrated that increasing GDP per capita in neighbouring countries through interregional mobility of inputs of production will increase deforestation in the target country. The increase in the exchange rate in neighbouring countries due to the increase in imports of forest products and the non-cutting of domestic forest resources will reduce deforestation in the target country. Increased population density and unemployment in neighbouring countries due to reduced job opportunities and increased migration to the target country, followed by increased demand for food and increased land demand, led to increased deforestation in the target country. Finally, increasing the human development index variable has reduced deforestation in the target country. However, changing this variable in neighbouring countries has not affected the deforestation of the target country. Therefore, in a world with increasing economic growth, it is suggested that to prevent deforestation by improving the human development index, eradicating the problem of unemployment, and eradicating poverty redouble efforts. As the results of this study showed, the population had a direct and significant effect on deforestation in selected countries. Due to the increase in population growth in different years, it is recommended that the population issue be given more attention by looking at the requirements of sustainable development to reduce environmental degradation, mainly deforestation. Because according to the results of this study, the lack of rapid population growth reduces deforestation in selected countries.

Keywords

Deforestation; Spatial econometrics; Spatial Kuznets curve; Sustainable economic development

References

1. Ahmed , Shahbaz M., Qasim A., and Long W. 2015. The linkages between deforestation, energy and growth for environmental degradation in Pakistan. Ecological Indicators 49: 95-103. https://doi.org/10.1016/j.ecolind.2014.09.040.
2. Alishiri , Sajjadifar S.H., and Mohammadbagheri A. 2017. Environmental Kuznets curve hypothesis assessment (case study of water pollution). Water and Wastewater Magazine 1(28): 57-64. (In Persian)
3. Allen , and Douglas B. 1985. The causes of deforestation in developing countries. Annuals of Association of American Geographers 75(2): 163–184. https://doi.org/10.1111/j.1467-8306.1985.tb00079.x.
4. Angelsen 1999. Agricultural expansion and deforestation: modeling the impact of population, market forces and property rights. Journal of Development Economics 58(1): 185-218. https://doi.org/10.1016/S0304-3878(98)00108-4.
5. Anselin L. 1988. Spatial Econometrics: Methods and Models. p. 310-330.
6. Anselin , and Bera A.K. 1998. Spatial dependence in linear regression models with an introduction to spatial econometrics. Statistics Textbooks and Monographs 155: 237-290.
7. Atella V., Belotti F., Depalo D., and Piano Mortari A. 2014. Measuring spatial effects in the presence of institutional constraints: The case of Italian Local Health Authority expenditure. Regional Science and Urban Economics 49: 232-241. https://doi.org/10.1016/j.regsciurbeco.2014.07.007.
8. Balado-Naves R., Baños-Pino J.F., and Mayor M. 2018. Do countries influence neighbouring pollution? A spatial analysis of the EKC for CO₂ Energy Policy 123: 266-279. https://doi.org/10.1016/j.enpol.2018.08.059.
9. Bera , Saha S., and Bhattacharjee S. 2020. Forest cover dynamics (1998 to 2019) and prediction of deforestation probability using binary logistic regression (BLR) model of Silabati watershed, India. Trees, Forests and People, 2, 100034. https://doi.org/10.1016/j.tfp.2020.100034.
10. Bohn , and Deacon R. 2000. Ownership Risk, Investment, and the Use of Natural Resources. The American Economic Review 90(3): 526-549. https://doi.org/10.1257/aer.90.3.526.
11. Boubacar 2012. Neighboring effects of deforestation: a spatial econometric approach. Environmental Economics (3, Iss. 3): 72-81.
12. Caravaggio 2020. A global empirical re-assessment of the Environmental Kuznets curve for deforestation. Forest Policy and Economics 119: 102282. https://doi.org/10.1016/j.forpol.2020.102282.
13. Cochard , Nguyen V.H.T., Ngo D.T., and Kull C.A. 2020. Vietnam’s forest cover changes 2005–2016: Veering from transition to (yet more) transaction? World Development 135: 105051. https://doi.org/10.1016/j.worlddev.2020.105051.
14. Culas 2007. Deforestation and the environmental Kuznets curve: An institutional perspective. Ecological Economics 61(3): 429-437. https://doi.org/10.1016/j.ecolecon.2006.03.014.
15. Daryani 2015. Investigating the effects of economic and demographic factors on environmental pollution in OPEC member countries. Thesis in Humanities, Persian Gulf University. (In Persian with English abstract)
16. FAO, Food and Agriculture Organization of the United Nations, Rome. 2015. Global Forest Resources Assessment. How are the world’s forests changing? Second edition. Available at http://www.fao.org//.
17. FAO, Food and Agriculture Organization. 1992. Forest Resources Assessment, Tropical Countries, Forestry. Paper, 112. Available at http://www.fao.org//.
18. FAO, Food and Agriculture Organization. 1997. State of the World's Forests. FAO, Rome. Available at http://www.fao.org//.
19. FAO, Rome, Food and Agriculture Organization. 2003. State of the World's Forests. FAO: Rome, Available at http://www.fao.org//.
20. FAO, Rome, Food and Agriculture Organization. 2005. State of the World's Forests. FAO: Rome, Available at http://www.fao.org//.
21. Faria , and Almeida A. 2016. Relationship between Openness to Trade and Deforestation: Empirical Evidence from the Brazilian Amazon. Ecological Economics 5(121): 85-97. https://doi.org/10.1016/j.ecolecon.2015.11.014.
22. Ferreira 2004. Deforestation, Property Rights, and International Trade. Land Economics 80(2): 174-193. https://doi.org/10.2307/3654737.
23. Florax , Folmer H., and Rey S. 2003. Specification searches in spatial econometrics: The relevance of Hendry’s methodology. Regional Science and Urban Economics 33(5): 557-579. https://doi.org/10.1016/S0166-0462(03)00002-4.
24. Hamidi 2015. Investigating the Convergence of Energy Intensity among OPEC Countries in the Presence of Structural Failures (A Bilateral Approach). M.Sc. Thesis, Urmia University. (In Persian with English abstract)
25. Hao, Liu Y., Weng J.H., and Gao Y. 2016. Does the environmental Kuznets curve for coal consumption in China exist? New evidence from spatial econometric analysis. Energy 114: 1214-1223. https://doi.org/10.1016/j.energy.2016.08.075.
26. Heerink , Mulatu A., and Bulte E. 2001. Income inequality and environment: Aggregation bias in environmental Kuznets curves: Evidence from automobile lead emissions. Journal of Environmental Economics and Management 35(2): 126-141. https://doi.org/10.1016/S0921-8009(01)00171-9.
27. Hoseini , Karimzadeh S., and Bakhtiari S. 2018. The relationship between financial development, economic growth and energy consumption in a selection of developing countries. Financial Economy (Financial Economy and Development) 12(45): 167-191. (In Persian with English abstract)
28. Humphreys 2004. Redefining the Issues: NGO Influence on International Forest Negotiations. Global Environmental Politics, 4(2): 51-74. https://doi.org/10.1162/152638004323074192.
29. Khezri, , Heshmati, A., and Khodaei, M. 2021. The role of R&D in the effectiveness of renewable energy determinants: A spatial econometric analysis. Energy Economics, 99, 105287. https://doi.org/10.1016/j.eneco.2021.105287.
30. Koop, , and Toole, L. 1999. Is there an environmental Kuznets curve for deforestation? Journal of Development Economics 58(1): 231–244. https://doi.org/10.1016/S0304-3878(98)00110-2.
31. LeSage J., and Pace RK. Introduction to spatial econometrics. Boca Raton: CRC PressTaylor & Francis Group.
32. Lewis L., Edwards D.P., and Galbraith D. 2015. Increasing human dominance of tropical forests. Science 349(6250): 827-832. https://doi.org/10.1126/science.aaa9932.
33. Lopez , and Galinato G. 2005. Trade policies, economic growth, and the direct causes of deforestation. Land Economics 81(2): 145-169. https://doi.org/10.3368/le.81.2.145.
34. Lv, and Li S. 2021. How financial development affects CO₂ emissions: a spatial econometric analysis. Journal of Environmental Management 277: 111397. https://doi.org/10.1016/j.jenvman.2020.111397.
35. Mahapatra , and Kant S. 2005. Tropical deforestation: A multinomial logistic model and some country-specific policy prescriptions. Forest Policy and Economics 7(1): 1-24. https://doi.org/10.1016/S1389-9341(03)00064-9.
36. Mahmodpor , Saeidpor L., and Alidost N. 2018. Investigating the effect of economic openness on knowledge-based economy, Parliamentary Quarterly and Strategy 25(96): 297-320. (In Persian with English abstract)
37. Mansorabadi , and Khodaparast Shirzadi J. 2019. The Impact of Natural Resources on Economic Growth and the Role of Institutional Quality, Agricultural Economics Research 11(1): 75-92. (In Persian)
38. Mendelsohn 1994. Property rights and tropical deforestation. Oxford Economic Papers 46(1): 750-756. https://www.jstor.org/stable/2663497.
39. Miyamoto 2020. Poverty reduction saves forests sustainably: Lessons for deforestation policies. World Development 127: 104746. https://doi.org/10.1016/j.worlddev.2019.104746.
40. Morita , and Matsumoto K. 2017. REDD+ financing to enhance climate change mitigation and adaptation and biodiversity co-benefits: lessons from the Global Environment Facility. AGRIVITA, Journal of Agricultural Science 40(1): 118-130.
41. Nasirnia , and Esmaeili A. 2009. Socio-economic factors affecting deforestation of selected countries: Application Kuznets Environmental Theory. Agricultural Science and Technology and Natural Resources 13(48): 367-374. (In Persian)
42. Nasirnia F., and Esmaeili A. 2008. Investigation of Deforestation in Iran and Neighboring Countries: Application Kuznets Model. Agricultural Economics 3(10): 17-31. (In Persian)
43. Reddya S., Saranyaa K.R.L., Vazeed S.P., Satisha K.V., Jhaa C.S., Diwakara P.G., Dadhwala V.K.C., Raoa P.V.N., and Krishna Y.V.N.M. 2018. Assessment and monitoring of deforestation and forest fragmentation in south Asia since the 1930s. Global and Planetary Change 161(3): 132-148. https://doi.org/10.1016/j.gloplacha.2017.10.007.
44. Sadeghi Saadat, R. 2004. Population growth, economic growth and environmental impacts in Iran (A causal analysis). Journal of Economic Research 64: 163-180. (In Persian with English abstract)
45. Salimifar , and Dehnavi J. 2010. Comparison of the condense environmental curve in OECD member states and developing countries: Panel-Based Analysis. Journal of Knowledge and Development 16(29): 182-200. (In Persian with English abstract)
46. Santiago R., and do Couto H.T.Z. 2020. Socioeconomic development versus deforestation: Considerations on the sustainability of economic and social growth in most Brazilian municipalities. Environmental Development 35: 100520. https://doi.org/10.1016/j.envdev.2020.100520.
47. Stern, , and Stern, N. H. 2007. The economics of climate change: the Stern review: cambridge University press.
48. Ullah M.A., Tsuchiya J., Asahiro K., and Tani M. 2022. Exploring the socioeconomic drivers of deforestation in Bangladesh: The case of Teknaf Wildlife Sanctuary and its surrounding community. Trees, Forests and People 7: 100167. https://doi.org/10.1016/j.tfp.2021.100167.
49. Van der Werf R., Morton D.C., Defries R.S., Olivier J.G., Kasibhatla P.S., Jackson R.B., and Randerson J.T. 2009. CO₂ emissions from forest loss. Nature Geoscience 2(11): 737-738.
50. Wheeler , Hamme D., Kraft R., Dasgupta S., and Blankspoor B. 2013. Economic Dynamics and Forest Clearing: A Spatial Econometric Analysis for Indonesia. Ecological Economics 85: 85-96. https://doi.org/10.1016/j.ecolecon.2012.11.005.
51. World Bank, World Development Indicators. 2016. World Bank Publications, cop, Washington, DC. Available at: http://documents.worldbank.org/curated/en/805371467990952829/World-development-indicators-2016.
52. World Bank, World Development Indicators. 2020. World Bank Publications, cop, Washington, DC. Available at: http://documents.worldbank.org/curated/en/805371467990952829/World-development-indicators-2020.