Testing Porter and pollution haven hypothesis via economic variables and CO2 emissions: a cross-country review with panel quantile regression method

Abstract

Nowadays, determining the factors influencing carbon dioxide emissions is a crucial issue for policymakers. So, this study examines Porter and pollution haven’s hypothesis via foreign direct investment, financial development, and energy consumption in 14 countries of the MENA region during 2004–2016, using panel quantile regression that estimated the impact of these factors in quantiles of 0.1, 0.25, 0.5, 0.75, and 0.9. Also, the effect of population, trade openness, and economic growth variables has been investigated as controlling variables on CO2 emissions. The results of the research show that the impact of energy consumption, economic growth, and total population on all quantiles of carbon dioxide emission is positive and significant. Still, the effect of direct foreign investment on the amount of CO2 emissions is negative and only significant at 0.1, 0.5, and 0.75 quantiles, which supports Porter's hypothesis. Based on this hypothesis, the foreign direct investment entrance helps reduce the environmental pollution of the host country. Also, the effect of financial development on 0.25, 0.5, 0.75, and 0.9 quantile carbon dioxide emissions is negative and significant. Finally, the trade openness variable has a positive and significant effect on the quantiles of 0.1 and 0.9 CO2 emissions.

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References

  1. Abdouli M, Hammami S (2017) Economic growth, FDI inflows and their impact on the environment: an empirical study for the MENA countries. Qual Quant 51(1):121–146. https://doi.org/10.1007/s11135-015-0298-6

    Article  Google Scholar 

  2. Abokyi E, Appiah-Konadu P, Abokyi F, Oteng-Abayie EF (2019) Industrial growth and emissions of CO2 in Ghana: the role of financial development and fossil fuel consumption. Energy Rep 5:1339–1353. https://doi.org/10.1016/j.egyr.2019.09.002

    Article  Google Scholar 

  3. Ahmad M, Zhao ZY (2018) Empirics on linkages among industrialization, urbanization, energy consumption, CO2 emissions and economic growth: a heterogeneous panel study of China. Environ Sci Pollut Res 25:30617. https://doi.org/10.1007/s11356-018-3054-3

    CAS  Article  Google Scholar 

  4. Ahmad M, Zhao ZY, Rehman A, Shahzad M, Li H (2019) Revealing long- and short-run empirical interactions among foreign direct investment, renewable power generation, and CO2 emissions in China. Environ Sci Pollut Res 26:22220–22245. https://doi.org/10.1007/s11356-019-05543-x

    CAS  Article  Google Scholar 

  5. Alexander M, Harding M, Lamarche C (2011) Quantile regression for time-series-cross-section data. Int J Stat Manag Syst 6(1–2):47–72

    Google Scholar 

  6. Appiah K, Du J, Yeboah M et al (2019) Causal correlation between energy use and carbon emissions in selected emerging economies—panel model approach. Environ Sci Pollut Res 26:7896–7912. https://doi.org/10.1007/s11356-019-04140-2

    Article  Google Scholar 

  7. Arouri MEH, Youssef AB, M'henni H, Rault C (2012) Energy consumption, economic growth and CO2 emissions in Middle East and North African countries. Energy Policy 45:342–349. https://doi.org/10.1016/j.enpol.2012.02.042

    Article  Google Scholar 

  8. Asghari M, Salarnazar RS (2013) The Impact of Foreign Direct Investment Inflow on Selected MENA Countries’ Environmental Quality. Econ Dev Res 3(9):1–30

    Google Scholar 

  9. Baltagi BH (2008) Econometric analysis of panel data. John Wiley, Chichester

  10. 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 70:96–106. https://doi.org/10.1016/j.rser.2016.11.201

    CAS  Article  Google Scholar 

  11. Bilgili F, Koçak E, Bulut Ü (2016) The dynamic impact of renewable energy consumption on CO2 emissions: a revisited environmental Kuznets curve approach. Renew Sust Energ Rev 54:838–845. https://doi.org/10.1016/j.rser.2015.10.080

    Article  Google Scholar 

  12. Breitung J (1999) The local power of some unit root tests for panel data. Discussion Papers, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes

  13. Çetin M, Ecevit E (2015) Urbanization, energy consumption and CO2 emissions in sub Saharan countries: a panel cointegration and causality analysis. J Econ Dev Stud 3(2):66–76. https://doi.org/10.15640/jeds.v3n2a7

    Article  Google Scholar 

  14. Çetin M, Ecevit E (2017) The impact of financial development on carbon emissions under the structural breaks: empirical evidence from Turkish economy. J Econ Manag Perspect 11(1):64–78

    Google Scholar 

  15. Cheng C, Ren X, Wang Z, Shi Y (2018) The impacts of non-fossil energy, economic growth, energy consumption, and oil price on carbon intensity: evidence from a panel quantile regression analysis of EU 28. Sustainability 10(11):4067. https://doi.org/10.3390/su10114067

    CAS  Article  Google Scholar 

  16. Choi I (2001) Unit root tests for panel data. J Int Money Financ 20(2):249–272. https://doi.org/10.1016/S0261-5606(00)00048-6

    Article  Google Scholar 

  17. Coondoo D, Dinda S (2002) Causality between income and emission: a country group-specific econometric analysis. Ecol Econ 40(3):351–367

    Article  Google Scholar 

  18. Copeland BR, Taylor MS (2003) Trade and the environment. Princeton University Press

  19. Daly HE (1991) Steady-state economics: with new essays. Island Press

  20. Damette O, Delacote P (2012) On the economic factors of deforestation: what can we learn from quantile analysis? Econ Model 29(6):2427–2434. https://doi.org/10.1016/j.econmod.2012.06.015

    Article  Google Scholar 

  21. Davino C, Furno M, Vistocco D (2013) Quantile regression: theory and applications (988). John Wiley & Sons ISBN: 978-1-119-97528-1

  22. Dogan E, Inglesi-Lotz R (2020) The impact of economic structure to the environmental Kuznets curve (EKC) hypothesis: evidence from European countries. Environ Sci Pollut Res 27:1–8. https://doi.org/10.1007/s11356-020-07878-2

    Article  Google Scholar 

  23. Dogan E, Seker F (2016) The influence of real output, renewable and non-renewable energy, trade and financial development on carbon emissions in the top renewable energy countries. Renew Sust Energ Rev 60:1074–1085. https://doi.org/10.1016/j.rser.2016.02.006

    Article  Google Scholar 

  24. Dogan E, Turkekul B (2016) CO2 emissions, real output, energy consumption, trade, urbanization and financial development: testing the EKC hypothesis for the USA. Environ Sci Pollut Res 23(2):1203–1213. https://doi.org/10.1007/s11356-015-5323-8

    Article  Google Scholar 

  25. Dong K, Hochman G, Zhang Y, Sun R, Li H, Liao H (2018) CO2 emissions, economic and population growth, and renewable energy: empirical evidence across regions. Energy Econ 75:180–192. https://doi.org/10.1016/j.eneco.2018.08.017

    Article  Google Scholar 

  26. El Montasser G, Ajmi AN, Nguyen DK (2018) Carbon emissions—income relationships with structural breaks: the case of the Middle Eastern and North African countries. Environ Sci Pollut Res 25:2869–2878. https://doi.org/10.1007/s11356-017-0725-4

    CAS  Article  Google Scholar 

  27. Farhani S (2013) Renewable energy consumption, economic growth and CO2 emissions: evidence from selected MENA countries. Energy Econ Lett 1(2):24–41

    Google Scholar 

  28. Frankel JA, Romer DH (1999) Does trade cause growth? Am Econ Rev 89(3):379–399. https://doi.org/10.1257/aer.89.3.379

    Article  Google Scholar 

  29. Ghorashi N, Alavi Rad A (2018) Impact of financial development on CO2 emissions: panel data evidence from Iran’s economic sectors. J Commun Health Res 7(2):127–133

    Google Scholar 

  30. Gorus MS, Aydin M (2019) The relationship between energy consumption, economic growth, and CO2 emission in MENA countries: causality analysis in the frequency domain. Energy 168:815–822. https://doi.org/10.1016/j.energy.2018.11.139

    Article  Google Scholar 

  31. Hadri K (2000) Testing for stationarity in heterogeneous panel data. Econ J 3(2):148–161. https://doi.org/10.1111/1368-423X.00043

    Article  Google Scholar 

  32. Hao Y, Liu YM (2015) Has the development of FDI and foreign trade contributed to China’sCO2emissions? An empirical study with provincial panel data. Nat Hazards 76(2):1079–1091. https://doi.org/10.1007/s11069-014-1534-4

    Article  Google Scholar 

  33. Huang Y, Chen X, Zhu H, Huang C, Tian Z (2019) The heterogeneous effects of FDI and foreign trade on CO2 emissions: evidence from China. Math Probl Eng 2019:1–14. https://doi.org/10.1155/2019/9612492

    CAS  Article  Google Scholar 

  34. Im KS, Pesaran MH, Shin Y (2003) Testing for unit roots in heterogeneous panels. J Econ 115(1):53–74. https://doi.org/10.1016/S0304-4076(03)00092-7

    Article  Google Scholar 

  35. Jensen V (1996) The Pollution Haven Hypothesis and the Industrial Flight Hypothesis: Some Perspectives on Theory and Empirics (Working Paper 1996.5). Centre for Development and the Environment, University of Oslo, Oslo

  36. Jiang C, Ma X (2019) The impact of financial development on carbon emissions: a global perspective. Sustainability 11(19):5241. https://doi.org/10.3390/su11195241

    Article  Google Scholar 

  37. Kahia M, Ben Jebli M, Belloumi M (2019) Analysis of the impact of renewable energy consumption and economic growth on carbon dioxide emissions in 12 MENA countries. Clean Techn Environ Policy 21(4):871–885. https://doi.org/10.1007/s10098-019-01676-2

    CAS  Article  Google Scholar 

  38. Kao C (1999) Spurious regression and residual-based tests for cointegration in panel data. J Econ 90(1):1–44. https://doi.org/10.1016/S0304-4076(98)00023-2

    Article  Google Scholar 

  39. Kim S (2019) CO2 emissions, foreign direct investments, energy consumption, and GDP in developing countries: a more comprehensive study using panel vector error correction model. Kor Econ Rev 35:5–24

    Google Scholar 

  40. Koçak E, Şarkgüneşi A (2018) The impact of foreign direct investment on CO2 emissions in Turkey: new evidence from cointegration and bootstrap causality analysis. Environ Sci Pollut Res 25(1):790–804. https://doi.org/10.1007/s11356-017-0468-2

    CAS  Article  Google Scholar 

  41. Koenker R (2004) Quantile regression for longitudinal data. J Multivar Anal 91(1):74–89. https://doi.org/10.1016/j.jmva.2004.05.006

    Article  Google Scholar 

  42. Koenker R, Bassett G Jr (1978) Regression quantiles. Econometrica:33–50

  43. Lamarche C (2011) Measuring the incentives to learn in Colombia using new quantile regression approaches. J Dev Econ 96(2):278–288

    Article  Google Scholar 

  44. Lancaster T (2000) The incidental parameter problem since 1948. J Econ 95(2):391–413

    Article  Google Scholar 

  45. Le TH, Le HC, Taghizadeh-Hesary F (2020) Does financial inclusion impact CO2 emissions? Evid Asia Financ Res Lett 101451:101451. https://doi.org/10.1016/j.frl.2020.101451

    Article  Google Scholar 

  46. Levin A, Lin C, Chu C-J (2002) Unit root tests in panel data: asymptotic and finite-sample properties. J Econ 108:1–24. https://doi.org/10.1016/S0304-4076(01)00098-7

    Article  Google Scholar 

  47. Li P, Ouyang Y (2019) The dynamic impacts of financial development and human capital on CO2 emission intensity in China: an ARDL approach. J Bus Econ Manag 20(5):939–957. https://doi.org/10.3846/jbem.2019.10509

    Article  Google Scholar 

  48. Lin B, Xu B (2018) Factors affecting CO2 emissions in China's agriculture sector: a quantile regression. Renew Sust Energ Rev 94:15–27. https://doi.org/10.1016/j.rser.2018.05.065

    Article  Google Scholar 

  49. List JA, Millimet DL, Fredriksson PG, McHone WW (2003) Effects of environmental regulations on manufacturing plant births: evidence from a propensity score matching estimator. Rev Econ Stat 85(4):944–952. https://doi.org/10.1162/003465303772815844

    Article  Google Scholar 

  50. Maddala GS, Wu S (1999) A comparative study of unit root tests with panel data and a new simple test. Oxf Bull Econ Stat 61(S1):631–652. https://doi.org/10.1111/1468-0084.0610s1631

    Article  Google Scholar 

  51. Maeso-Fernandez F, Osbat C, Schnatz B (2006) Towards the estimation of equilibrium exchange rates for transition economies: methodological issues and a panel cointegration perspective. J Comp Econ 34(3):499–517. https://doi.org/10.1016/j.jce.2006.05.003

    Article  Google Scholar 

  52. Magazzino C, Cerulli G (2019) The determinants of CO2 emissions in MENA countries: a responsiveness scores approach. Int J Sustain Dev World Ecol 26(6):522–534. https://doi.org/10.1080/13504509.2019.1606863

    Article  Google Scholar 

  53. Mahmood H, Maalel N, Zarrad O (2019) Trade openness and CO2 emissions: evidence from Tunisia. Sustainability 11(12):3295. https://doi.org/10.3390/su11123295

    Article  Google Scholar 

  54. Mansoor A, Sultana B (2018) Impact of population, GDP and energy consumption on carbon emissions: evidence from Pakistan using an analytic tool IPAT. Asian J Econ Empir Res 5(2):183–190. https://doi.org/10.20448/journal.501.2018.52.183.190

    Article  Google Scholar 

  55. Menyah K, Wolde-Rufael Y (2010) Energy consumption, pollutant emissions and economic growth in South Africa. Energy Econ 32(6):1374–1382. https://doi.org/10.1016/j.eneco.2010.08.002

    Article  Google Scholar 

  56. Mitić P, Munitlak Ivanović O, Zdravković A (2017) A cointegration analysis of real GDP and CO2 emissions in transitional countries. Sustainability 9(4):568. https://doi.org/10.3390/su9040568

    Article  Google Scholar 

  57. Nasir MA, Huynh TLD, Tram HTX (2019) Role of financial development, economic growth & foreign direct investment in driving climate change: a case of emerging ASEAN. J Environ Manag 242:131–141. https://doi.org/10.1016/j.jenvman.2019.03.112

    Article  Google Scholar 

  58. Naz S, Sultan R, Zaman K, Aldakhil AM, Nassani AA, Abro MMQ (2019) Moderating and mediating role of renewable energy consumption, FDI inflows, and economic growth on carbon dioxide emissions: evidence from robust least square estimator. Environ Sci Pollut Res 26(3):2806–2819. https://doi.org/10.1007/s11356-018-3837-6

    CAS  Article  Google Scholar 

  59. Nazir MR, Nazir MI, Hashmi SH, Fareed Z (2018) Financial development, income, trade, and urbanization on Co2 emissions: new evidence from Kyoto annex countries. J Innov SustainRISUS ISSN 2179-3565 9(3):17–37. https://doi.org/10.24212/2179-3565.2018v9i3p17-37

    Article  Google Scholar 

  60. Neequaye NA, Oladi R (2015) Environment, growth, and FDI revisited. Int Rev Econ Financ 39:47–56. https://doi.org/10.1016/j.iref.2015.06.002

    Article  Google Scholar 

  61. Newell P (2001) Managing multinationals: the governance of investment for the environment. J Int Dev 13(7):907–919. https://doi.org/10.1002/jid.832

    Article  Google Scholar 

  62. Neyman J, Scott EL (1948) 1. Econometrica 16(1):1–32. https://doi.org/10.2307/1914288

    Article  Google Scholar 

  63. Omri A (2013) CO2 emissions, energy consumption and economic growth nexus in MENA countries: evidence from simultaneous equations models. Energy Econ 40:657–664. https://doi.org/10.1016/j.eneco.2013.09.003

    Article  Google Scholar 

  64. Pedroni P (2001) Purchasing power parity tests in cointegrated panels. Rev Econ Stat 83(4):727–731. https://doi.org/10.1162/003465301753237803

    Article  Google Scholar 

  65. Peng H, Tan X, Li Y, Hu L (2016) Economic growth, foreign direct investment and CO2 emissions in China: a panel granger causality analysis. Sustainability 8(3):233. https://doi.org/10.3390/su8030233

    CAS  Article  Google Scholar 

  66. Phuc Nguyen C, Schinckus C, Dinh Su T (2019) Economic integration and CO2 emissions: evidence from emerging economies. Clim Dev 12:1–16. https://doi.org/10.1080/17565529.2019.1630350

    Article  Google Scholar 

  67. Ponomareva M (2010) Quantile regression for panel data models with fixed effects and small T: identification and Estimation. University of Western Ontario

  68. Powell JL (1984) Least absolute deviations estimation for the censored regression model. J Econ 25(3):303–325. https://doi.org/10.1016/0304-4076(84)90004-6

    Article  Google Scholar 

  69. Rasoulinezhad E, Saboori B (2018) Panel estimation for renewable and non-renewable energy consumption, economic growth, CO2 emissions, the composite trade intensity, and financial openness of the commonwealth of independent states. Environ Sci Pollut Res 25:17354. https://doi.org/10.1007/s11356-018-1827-3

    CAS  Article  Google Scholar 

  70. Rosen AM (2012) Set identification via quantile restrictions in short panels. J Econ 166(1):127–137. https://doi.org/10.1016/j.jeconom.2011.06.011

    Article  Google Scholar 

  71. Salahuddin M, Alam K, Ozturk I, Sohag K (2018) The effects of electricity consumption, economic growth, financial development and foreign direct investment on CO2 emissions in Kuwait. Renew Sust Energ Rev 81:2002–2010. https://doi.org/10.1016/j.rser.2017.06.009

    Article  Google Scholar 

  72. Sarkodie SA, Strezov V (2019) Effect of foreign direct investments, economic development and energy consumption on greenhouse gas emissions in developing countries. Sci Total Environ 646:862–871. https://doi.org/10.1016/j.scitotenv.2018.07.365

    CAS  Article  Google Scholar 

  73. Song M, Guo X, Wu K, Wang G (2015) Driving effect analysis of energy-consumption carbon emissions in the Yangtze River Delta region. J Clean Prod 103:620–628. https://doi.org/10.1016/j.jclepro.2014.05.095

    Article  Google Scholar 

  74. Soytas U, Sari R, Ewing BT (2007) Energy consumption, income, and carbon emissions in the United States. Ecol Econ 62(3–4):482–489. https://doi.org/10.1016/j.ecolecon.2006.07.009

    Article  Google Scholar 

  75. Stern DI (2004) A multivariate cointegration analysis of the role of energy in the US macro economy. Energy Econ 22:267–283. https://doi.org/10.1016/s0140-9883(99)00028-6

    Article  Google Scholar 

  76. Wasti SKA, Zaidi SW (2020) An empirical investigation between CO2 emission, energy consumption, trade liberalization and economic growth: a case of Kuwait. J Build Eng 28:101104. https://doi.org/10.1016/j.jobe.2019.101104

    Article  Google Scholar 

  77. World Bank (2017) World development indicators. World Bank, Washington D.C

    Google Scholar 

  78. Xu B, Lin B (2016) A quantile regression analysis of China's provincial CO2 emissions: where does the difference lie? Energy Policy 98:328–342. https://doi.org/10.1016/j.enpol.2016.09.003

    CAS  Article  Google Scholar 

  79. Zhang C, Zhou X (2016) Does foreign direct investment lead to lower CO2 emissions? Evidence from a regional analysis in China. Renew Sust Energ Rev 58:943–951. https://doi.org/10.1016/j.rser.2015.12.226

    Article  Google Scholar 

  80. Zhang YJ, Jin YL, Chevallier J, Shen B (2016) The effect of corruption on carbon dioxide emissions in APEC countries: a panel quantile regression analysis. Technol Forecast Soc Chang 112:220–227. https://doi.org/10.1016/j.techfore.2016.05.027

    Article  Google Scholar 

  81. Zheng J, Sheng P (2017) The impact of foreign direct investment (FDI) on the environment: market perspectives and evidence from China. Economies 5(1):8

    Article  Google Scholar 

  82. Zheng H, Hu J, Wang S, Wang H (2019) Examining the influencing factors of CO2 emissions at city level via panel quantile regression: evidence from 102 Chinese cities. Appl Econ 51:3906–3919. https://doi.org/10.1080/00036846.2019.1584659

    Article  Google Scholar 

  83. Zhou Y, Sirisrisakulchai J, Liu J, Sriboonchitta S (2018) The impact of economic growth and energy consumption on carbon emissions: evidence from panel quantile regression. J Phys Conf Ser 1053(1):012118. https://doi.org/10.1088/1742-6596/1053/1/012118

    CAS  Article  Google Scholar 

  84. Zhu H, Duan L, Guo Y, Yu K (2016) The effects of FDI, economic growth and energy consumption on carbon emissions in ASEAN-5: evidence from panel quantile regression. Econ Model 58:237–248. https://doi.org/10.1016/j.econmod.2016.05.003

    Article  Google Scholar 

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Acknowledgments

We would like to thank the Agrimetsoft team (www.agrimetsoft.com) for the perfect consultations and tools in facilitating the statistical processes in this research.

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Salehnia, N., Karimi Alavijeh, N. & Salehnia, N. Testing Porter and pollution haven hypothesis via economic variables and CO2 emissions: a cross-country review with panel quantile regression method. Environ Sci Pollut Res 27, 31527–31542 (2020). https://doi.org/10.1007/s11356-020-09302-1

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Keywords

  • Environmental degradation
  • Air pollution
  • Panel data
  • Mediterranean climate
  • Stationary
  • Economic growth

JEL Classification

  • Q53
  • Q40
  • C22