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Environmental Science and Pollution Research

, Volume 26, Issue 31, pp 32311–32321 | Cite as

A non-linear assessment of the urbanization and climate change nexus: the African context

  • Sofien TibaEmail author
Research Article
  • 61 Downloads

Abstract

The climate change issue becomes more challenging with the increasing pace of urbanization in Africa. For this purpose, we attempt to examine the relationship urbanization and CO2 emissions by applying the panel smooth transition regression model for 47 African countries during the spanning time 1990–2014. Our results reveal that the nexus between urbanization and CO2 emissions is non-linear. Our highlights recorded a monotonic nexus confirming the existence of the EKC hypothesis for the urbanization. In addition, our empirical results determine the threshold of the transition which takes the value of 42.01. Moreover, the estimated slope parameter implies that the nexus between urbanization and CO2 emissions smoothly switches from one regime to another regime but relatively rapid. Hence, it is extremely important to understand this nexus to take seriously climate change vulnerabilities. Indeed, the African economies are invited to establish efficiently the low-carbon and reduce the spatial heterogeneity to generate the green development path and provide effective structures for a platform for sustainable cities.

Keywords

Urbanization CO2 emissions PSTR model Africa 

Notes

References

  1. Ameli A, Bahrami S, Khazaeli F, Haghifam M-R (2014) A multiobjective particle swarm optimization for sizing and placement of DGs from DG owner's and distribution company's viewpoints. IEEE Trans Power Deliv 29:1831–1840Google Scholar
  2. Apergis N, Payne JE (2009) CO2 emissions, energy usage, and output in Central America. Energy Policy 37:3282–3286Google Scholar
  3. Bahrami S, Amini MH (2018) A decentralized trading algorithm for an electricity market with generation uncertainty. Appl Energy 218:520–532Google Scholar
  4. Behera SR, Dash DP (2017) The effect of urbanization, energy consumption, and foreign direct investment on the carbon dioxide emission in the SSEA (South and Southeast Asian) region. Renew Sust Energ Rev 70:96–106Google Scholar
  5. Colletaz G, Hurlin C (2006) Threshold effect in the public capital productivity: an international panel smooth transition approach. University of Orleans working paper. Growth, Investment And Real Rates. Carneige-Rochester Conf Series on Public Policy 39:95–140Google Scholar
  6. De Hoyos R, Sarafidis V (2006) Testing for cross-sectional dependence in panel data models. Stata J 6:482–496Google Scholar
  7. Du L, Wei C, Cai S (2012) Economic development and carbon dioxide emissions in China: provincial panel data analysis. China Econ Rev 23:371–384Google Scholar
  8. Du LM, Hanley A, Zhang N (2016) Environmental technical efficiency, technology gap and shadow price of coal-fuelled power plants in China: a parametric meta-frontier analysis. Resour Energy Econ 43:14–32Google Scholar
  9. González, A., Teräsvirta, T., vanDijk, D., 2005. Panel smooth transition regression models. SEE/EFI Working Paper Series in Economics and Finance, No. 604.Google Scholar
  10. Granger, C., Teräsvirta, T., 1993. Modelling non-linear economic relationships. Oxford University Press.Google Scholar
  11. Han F, Xie R, Lu Y, Fang J, Liu Y (2018) The effects of urban agglomeration economies on carbon emissions: evidence from Chinese cities. J Clean Prod 172:1096–1110Google Scholar
  12. Hansen B (1996) Inference when a nuisance parameter is not identified under the null hypothesis. J Econ 64:413–430Google Scholar
  13. Huang W, Gao Q-X, Cao G, Ma Z-Y, Zhang W-D, Chao Q-C (2016) Effect of urban symbiosis development in China on GHG emissions reduction. Adv Clim Chang Res 7:247–252Google Scholar
  14. Ibarra R, Trupkin D, 2011. The relationship between inflation and growth: a panel smooth transition regression approach. Research Network and Research Centers Program of Banco Central del Uruguay (Working Paper).Google Scholar
  15. Im KS, Pesaran MH, Shin Y (2003) Testing for unit roots in heterogeneous panels. J Econ 115:53–74Google Scholar
  16. IPCC, 2007. Climate Change 2007 Synthesis Report, Intergovernmental Panel on Climate Change [Core Writing Team IPCC.  https://doi.org/10.1256/004316502320517344 Google Scholar
  17. Jansen E, Teräsvirta T (1996) Testing parameter constancy and super exogeneity in econometric equations. Oxf Bull Econ Stat 58:735–763Google Scholar
  18. Jayanthakumaran K, Verma R, Liu Y (2012) CO2 emissions, energy consumption, trade and income: a comparative analysis of China and India. Energy Policy 42:450–460Google Scholar
  19. Kasman A, Duman YS (2015) CO2 emissions, economic growth, energy consumption, trade and urbanization in new EU member and candidate countries: a panel data analysis. Econ Model 44:97–103Google Scholar
  20. Kayani AS, Muddassir M, Khalid MW, Shah AH (2018) Impacts of climate change on agricultural land productivity: an evidence from Punjab province of Pakistan. J AnimPlant Sci 28:584–588Google Scholar
  21. Lean HH, Smyth R (2010) CO2 emissions, electricity consumption and output in ASEAN. Appl Energy 87:1858–1864Google Scholar
  22. Li K, Lin BQ (2015) Impacts of urbanization and industrialization on energy consumption/CO2 emissions: does the level of development matter? Renew Sust Energ Rev 52:1107–1122Google Scholar
  23. Liddle B, Lung S (2010) Age-structure, urbanization, and climate change in developed countries: revisiting STIRPAT for disaggregated population and consumption-related environmental impacts. Popul Environ 31:317–343Google Scholar
  24. Lin SF, Zhao DT, Marinova D (2009) Analysis of the environmental impact of China based on STIRPAT model. Environ Impact Asses 29:341–347Google Scholar
  25. Lin SF, Sun J, Marinova D, Zhao DT (2017) Effects of population and land urbanization on china's environmental impact: empirical analysis based on the extended STIRPAT model. Sustain-Basel 9:1–25Google Scholar
  26. Liu T, Ma Z, Huffman T, Ma L, Jiang H, Xie H (2016a) Gaps in provincial decision maker’s perception and knowledge of climate change adaptation in China. Environ Sci Pol 58:41–51Google Scholar
  27. Liu X, Bae J (2018) Urbanization and industrialization impact of CO 2 emissions in China. J Clean Prod 172:178–186Google Scholar
  28. Liu Y, Xiao HW, Zhang N (2016b) Industrial carbon emissions of China's regions: a spatial econometric analysis. Sustainability-Basel 8:210Google Scholar
  29. Liu Y, Xiao H, Lv Y, Zhang N (2017) The effect of new-type urbanization on energy consumption in China: a spatial econometric analysis. J Clean Prod 163:S299–S305Google Scholar
  30. Luukkonen R, Saikkonen P, Teräsvirta T (1988) Testing linearity against smooth transition autoregressive models. Biometrika 75:491–499Google Scholar
  31. Mudombi S, Fabricius C, Van Zyl-Bulitta V, Patt A (2017) The use of and obstacles to social learning in climate change adaptation initiatives in South Africa. Jàmbá J Disaster Risk Stud 9:1–8Google Scholar
  32. Omay T, Kan EO (2010) Re-examining the threshold effects in the inflation-growth nexus: OECD evidence. Econ Model 27(5):996–1005Google Scholar
  33. Omay T, Apergis N, Özçelebi H (2015) Energy consumption and growth: new evidence from a non-linear panel and a sample of developing countries. Singapore Econ Rev 60(02):1–30Google Scholar
  34. Omay T, Eyden R, Gupta R (2018) Inflation-growth nexus in Africa: evidence from a pooled CCE multiple regime panel smooth transition model. Empir Econ 54(3):913–944Google Scholar
  35. Peng J, Tian L, Liu YX, Zhao MY, Hu YN, Wu JS (2017) Ecosystem services response to urbanization in metropolitan areas: thresholds identification. Sci Total Environ 607:706–714Google Scholar
  36. Pesaran MH, 2004. General diagnostic tests for cross section dependence in panels. Cambridge Working Papers in Economics 0435. Faculty of Economics, University of Cambridge.Google Scholar
  37. Sadorsky P (2009) Renewable energy consumption, CO2 emissions and oil prices in theG7 countries. Energy Econ 31:456–462Google Scholar
  38. Shahbaz M, Loganathan N, Muzaffar AT, Ahmed K, Jabran MA (2016) How urbanization affects CO2 emissions of STIRPAT model in Malaysia? The application. Renew Sust Energ Rev 57:83–93Google Scholar
  39. Teräsvirta T (1994) Specification estimation and evaluation of smooth transition autoregressive models. J Am Stat Assoc 89:208–218Google Scholar
  40. The U.S. Energy Information Administration: available at: https://www.eia.gov/. Accessed on December 2018
  41. Tiba S (2019) Exploring the nexus between oil availability and economic growth: insights from non-linear model. Environ Model Assess.  https://doi.org/10.1007/s10666-019-09659-9 Google Scholar
  42. Tiba S, Frikha M (2019a) EKC and macroeconomics aspects of well-being: a critical vision for a sustainable future. J Knowl Econ.  https://doi.org/10.1007/s13132-019-00600-9
  43. Tiba S, Frikha M (2019b) Sustainability challenge in the agenda of African countries: evidence from simultaneous equations models. J Knowl Econ.  https://doi.org/10.1007/s13132-019-00605-4
  44. Tiba S, Frikha M (2019c) The controversy of the resource curse and the environment in the SDGs background: the African context. Res Policy 62:437–452Google Scholar
  45. Tiba S, Omri A, Frikha M (2015) The four-way linkages between renewable energy, environmental quality, trade and economic growth: a comparative analysis between high and middle-income countries. Energy Systems 7:103–144Google Scholar
  46. Ucar N, Omay T (2009) Testing for unit root in nonlinear heterogeneous panels. Econ Lett 104:5–8Google Scholar
  47. Wang Y, Li L, Kubota J, Han R, Zhu XD, Lu GF (2016) Does urbanization lead to more carbon emission? Evidence from a panel of BRICS countries. Appl Energy 168:375–380Google Scholar
  48. World Development Indicator Database (2019) (CD ROM-2019).Google Scholar
  49. Xu Q, Dong Y-X, Yang R (2018) Urbanization impact on carbon emissions in the Pearl River Delta region: Kuznets curve relationships. J Clean Prod 180:514–523Google Scholar
  50. Yousaf B, Liu G, Abbas Q, Wang R, Ubaid Ali M, Ullah H, Liu R, Zhou C (2017) Systematic investigation on combustion characteristics and emission-reduction mechanism of potentially toxic elements in biomass- and biochar-coal co-combustion systems. Appl Energy 208:142–157Google Scholar
  51. Zhang CG, Lin Y (2012) Panel estimation for urbanization, energy consumption and CO2 emissions: a regional analysis in China. Energ Policy 49:488–498Google Scholar
  52. Zhang N, Yu KR, Chen ZF (2017) How does urbanization affect carbon dioxide emissions? A cross-country panel data analysis. Energ Policy 107:678–687Google Scholar
  53. Zhang WJ, Xu HZ (2017) Effects of land urbanization and land finance on carbon emissions: a panel data analysis for Chinese provinces. Land Use Policy 63:493–500Google Scholar
  54. Zhou WJ, Zhu B, Chen DJ, Griffy-Brown C, Ma YY, Fei WY (2012) Energy consumption patterns in the process of China’s urbanization. Popul Environ 33:202–220Google Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Faculty of Economics and ManagementUniversity of SfaxSfaxTunisia

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