DOI: https://doi.org/10.14710/jwl.11.3.310-326

Hubungan antara Perdagangan, Investasi, PDB, Korupsi, dan Deforestasi di Asia Tenggara: Menguji Hipotesis Environmental Kuznets Curve (EKC)

*Mohamad Egi Destiartono  -  Fakultas Ekonomika dan Bisnis, Universitas Diponegoro, Semarang, Indonesia, Indonesia
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Abstract
Mencapai pembangunan berkelanjutan seperti net zero deforestation adalah agenda penting. Studi ini bermaksud mengungkap hubungan antara pertumbuhan ekonomi, keterbukaan perdagangan, investasi, pengendalian terhadap korupsi, dan deforestasi di Asia Tenggara periode 2000 – 2020 dengan mengadopsi kerangka Environmental Kuznets Curve (EKC). Metode Pooled Mean Group (PMG) dan uji kausalitas Dumitrescu-Hurlin (DH) diaplikasikan untuk mengestimasi hubungan dinamis jangka pendek dan panjang, serta arah kausalitas. Uji akar unit dan kointegrasi juga ditambahkan dalam penelitian ini. Seluruh variabel terintegrasi pada ordo pertama, I(1), dan mereka terkointegrasi. Hasil menunjukkan bahwa hubungan antara PDB per kapita dan deforestasi mengikuti kurva N, bukan EKC tradisional. Deforestasi akan terus berlangsung karena PDB per kapita Asia Tenggara telah melewati titik balik kedua (3.074 USD per capita).Selain itu, foreign direct investment (FDI) dan keterbukaan perdagangan terdeteksi sebagai pendorong deforestasi. Sebaliknya, indeks pengendalian korupsi memiliki pengaruh negatif pada deforestasi. Mendorong pembangunan sekaligus mengurangi laju deforestasi memungkinkan untuk dicapai karena uji DH menunjukkan kausalitas satu arah dari PDB per kapita menuju deforestasi. Studi ini menyarankan untuk memperkuat perdagangan hijau, investasi bersih, penguatan tata kelola, dan pembangunan berkelanjutan dengan tujuan mengurangi laju deforestasi.

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Keywords: Asia Tenggara; deforestasi; EKC; keterbukaan perdagangan; korupsi; PDB

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  2. Adams, C., Rodrigues, S. T., Calmon, M., & Kumar, C. (2016). Impacts of large-scale forest restoration on socioeconomic status and local livelihoods: what we know and do not know. Biotropica, 48(6), 731–744. https://doi.org/https://doi.org/10.1111/btp.12385
  3. Adila, D., Nuryartono, N., & Oak, M. (2021). The environmental kuznets curve for deforestation in Indonesia. Economics and Finance in Indonesia, 67(2), 195. https://doi.org/10.47291/efi.v67i2.671
  4. Ahmad, S., Khan, D., & Magda, R. (2022). Assessing the influence of financial inclusion on environmental degradation in the ASEAN region through the panel PMG-ARDL approach. Sustainability (Switzerland), 14(12). https://doi.org/10.3390/su14127058
  5. Ahmed, K., Shahbaz, M., Qasim, A., & Long, W. (2015). The linkages between deforestation, energy and growth for environmental degradation in Pakistan. Ecological Indicators, 49(2014), 95–103. https://doi.org/10.1016/j.ecolind.2014.09.040
  6. Ajanaku, B. A., & Collins, A. R. (2021). Economic growth and deforestation in African countries: Is the environmental kuznets curve hypothesis applicable? Forest Policy and Economics, 129, 102488. https://doi.org/10.1016/j.forpol.2021.102488
  7. Ansari, M. A. (2022). Re-visiting the environmental kuznets curve for ASEAN: A comparison between ecological footprint and carbon dioxide emissions. Renewable and Sustainable Energy Reviews, 168, 112867. https://doi.org/https://doi.org/10.1016/j.rser.2022.112867
  8. Ari, I., & Şentürk, H. (2020). The relationship between GDP and methane emissions from solid waste: A panel data analysis for the G7. Sustainable Production and Consumption, 23, 282–290. https://doi.org/10.1016/j.spc.2020.06.004
  9. Avnimelech, G., & Zelekha, Y. (2014). The impact of corruption on entrepreneurship. International Business Ethics and Growth Opportunities, 42(2), 282–294. https://doi.org/10.4018/978-1-4666-7419-6.ch013
  10. Caravaggio, N. (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
  11. Caravaggio, N. (2022). Economic growth and forest transition in Latin America. Forest Policy and Economics, 135, 102667. https://doi.org/https://doi.org/10.1016/j.forpol.2021.102667
  12. Carodenuto, S., Merger, E., Essomba, E., Panev, M., Pistorius, T., & Amougou, J. (2015). A methodological framework for assessing agents, proximate drivers and underlying causes of deforestation: Field test results from Southern Cameroon. Forests, 6(1), 203–224. https://doi.org/10.3390/f6010203
  13. Defries, R. S., Rudel, T., Uriarte, M., & Hansen, M. (2010). Deforestation driven by urban population growth and agricultural trade in the twenty-first century. Nature Geoscience, 3(3), 178–181. https://doi.org/10.1038/ngeo756
  14. Dumitrescu, E. I., & Hurlin, C. (2012). Testing for Granger non-causality in heterogeneous panels. Economic Modelling, 29(4), 1450–1460. https://doi.org/10.1016/j.econmod.2012.02.014
  15. Ekananda, M. (2022). Role of macroeconomic determinants on the natural resource commodity prices: Indonesia futures volatility. Resources Policy, 78, 102815. https://doi.org/10.1016/j.resourpol.2022.102815
  16. Espoir, D. K., Sunge, R., & Bannor, F. (2023). Exploring the dynamic effect of economic growth on carbon dioxide emissions in Africa: evidence from panel PMG estimator. Environmental Science and Pollution Research, 30(52), 112959–112976. https://doi.org/10.1007/s11356-023-30108-4
  17. FAO. (2007). Manual on deforestation, degradation, and fragmentation using remote sensing and GIS. In strengthening monitoring, assessment and reporting on sustainable forest management in Asia (GCP/INT/988/JPN) MAR-SFM) (MAR-SFM Working Paper 5 / 2007). http://www.fao.org/3/a-ap163e.pdf
  18. FAO. (2020). Global forest resources assessment 2020: Main report. https://doi.org/10.4060/ca9825en
  19. Faria, W. R., & Almeida, A. N. (2016). Relationship between openness to trade and deforestation: Empirical evidence from the Brazilian Amazon. Ecological Economics, 121, 85–97. https://doi.org/10.1016/j.ecolecon.2015.11.014
  20. Gandhi, S., & Jones, T. G. (2019). Identifying mangrove deforestation hotspots in South Asia, Southeast Asia and Asia-Pacific. Remote Sensing, 11(6), 1–27. https://doi.org/10.3390/RS11060728
  21. Habiba, U., Xinbang, C., & Anwar, A. (2022). Do green technology innovations, financial development, and renewable energy use help to curb carbon emissions? Renewable Energy, 193, 1082–1093. https://doi.org/https://doi.org/10.1016/j.renene.2022.05.084
  22. Hosonuma, N., Herold, M., De Sy, V., De Fries, R. S., Brockhaus, M., Verchot, L., Angelsen, A., & Romijn, E. (2012). An assessment of deforestation and forest degradation drivers in developing countries. Environmental Research Letters, 7(4), 1–12. https://doi.org/10.1088/1748-9326/7/4/044009
  23. Im, K. S., Pesaran, M. H., & Shin, Y. (2003). Testing for unit roots in heterogeneous panels. Journal of Econometrics, 115(1), 53–74. https://doi.org/10.1016/S0304-4076(03)00092-7
  24. Islam, M. S. (2022). Do personal remittances cause environmental pollution? Evidence from the top eight remittance-receiving countries. Environmental Science and Pollution Research, 29(24), 35768–35779. https://doi.org/10.1007/s11356-021-18175-x
  25. IUCN. (2021). Issues brief: Deforestation and forest degradation. https://www.iucn.org/resources/issues-brief/deforestation-and-forest-degradation
  26. Kao, C. (1999). Spurious regression and residual-based tests for cointegration in panel data. Journal of Econometrics, 90(1), 1–44. https://doi.org/10.1016/S0304-4076(98)00023-2
  27. Levin, A., Lin, C. F., & Chu, C. S. J. (2002). Unit root tests in panel data: Asymptotic and finite-sample properties. Journal of Econometrics, 108(1), 1–24. https://doi.org/10.1016/S0304-4076(01)00098-7
  28. Lim, C. L., Prescott, G. W., De Alban, J. D. T., Ziegler, A. D., & Webb, E. L. (2017). Untangling the proximate causes and underlying drivers of deforestation and forest degradation in Myanmar. Conservation Biology, 31(6), 1362–1372. https://doi.org/https://doi.org/10.1111/cobi.12984
  29. Lopez, L., & Weber, S. (2017). Testing for granger causality in panel data. Stata Journal, 17(4), 972–984. https://doi.org/10.1177/1536867X1801700412
  30. Lorente, D. B., & Alvarez-Herranz, A. (2016). An approach to the effect of energy innovation on environmental kuznets curve: An introduction to inflection point. Bulletin of Energy Economics, September, 225–233. https://www.researchgate.net/profile/Daniel-Lorente-2/publication/311172976_An_Approach_to_the_Effect_of_Energy_Innovation_on_Environmental_Kuznets_Curve_An_Introduction_to_Inflection_Point/links/584ae1b908aecb6bd8bef8fb/An-Approach-to-the-Effect-of-Energ
  31. Margono, B. A., Potapov, P. V, Turubanova, S., Stolle, F., & Hansen, M. C. (2014). Primary forest cover loss in Indonesia over 2000–2012. Nature Climate Change, 4(8), 730–735. https://doi.org/10.1038/nclimate2277
  32. Miyamoto, M., Mohd Parid, M., Noor Aini, Z., & Michinaka, T. (2014). Proximate and underlying causes of forest cover change in Peninsular Malaysia. Forest Policy and Economics, 44, 18–25. https://doi.org/https://doi.org/10.1016/j.forpol.2014.05.007
  33. Nathaniel, S. P., & Bekun, F. V. (2020). Environmental management amidst energy use, urbanization, trade openness, and deforestation: The Nigerian experience. Journal of Public Affairs, 20(2). https://doi.org/10.1002/pa.2037
  34. Pablo-Romero, M. P., Sánchez-Braza, A., & Gil-Pérez, J. (2023). Is deforestation needed for growth? Testing the EKC hypothesis for Latin America. Forest Policy and Economics, 148, 102915. https://doi.org/https://doi.org/10.1016/j.forpol.2023.102915
  35. Pachmann, A. (2018). Corruption and deforestation in Indonesia. Regional Formation and Development Studies, 25(2), 55–62. https://doi.org/10.15181/rfds.v25i2.1745
  36. Pedroni, P. (2004). Panel cointegration: Asymptotic and finite sample properties of pooled time series tests with an application to the PPP hypothesis. Econometric Theory, 20(3), 597–625. https://doi.org/10.1017/S0266466604203073
  37. Pendrill, F., Persson, U. M., Godar, J., & Kastner, T. (2019). Deforestation displaced: Trade in forest-risk commodities and the prospects for a global forest transition. Environmental Research Letters, 14(5). https://doi.org/10.1088/1748-9326/ab0d41
  38. Pendrill, F., Persson, U. M., Godar, J., Kastner, T., Moran, D., Schmidt, S., & Wood, R. (2019). Agricultural and forestry trade drives large share of tropical deforestation emissions. Global Environmental Change, 56, 1–10. https://doi.org/https://doi.org/10.1016/j.gloenvcha.2019.03.002
  39. Pesaran, M. H. (2007). A simple panel unit root test in the presence of cross-section dependence. JourJournal of Applied Econometrics, 22(2), 265–312. https://doi.org/https://www.jstor.org/stable/25146517
  40. Pesaran, M. H., Shin, Y., Smith, R. P., & Hashem, M. (1999). Pooled mean group estimation of dynamic heterogeneous panels. Source: Journal of the American Statistical Association, 94(446), 621–634. https://doi.org/10.2307/2670182
  41. Pichler, M., Bhan, M., & Gingrich, S. (2021). The social and ecological costs of reforestation. territorialization and industrialization of land use accompany forest transitions in Southeast Asia. Land Use Policy, 101, 105180. https://doi.org/https://doi.org/10.1016/j.landusepol.2020.105180
  42. Puspitaningrum, R., Sukmana, R., & Mawardi, I. (2018). The linkage between economic growth and deforestation in OIC (The Organization of Islamic Cooperation) Countries. Advances in Social Science, Education and Humanities Research (ASSEHR), 98(Icpsuas 2017), 320–325. https://doi.org/10.2991/icpsuas-17.2018.68
  43. Rahman, D.-S., Chen, S., Saud, S., Saleem, N., & Bari, M. W. (2019). Nexus between financial development, energy consumption, income level, and ecological footprint in CEE countries: do human capital and biocapacity matter? Environmental Science and Pollution Research, 26. https://doi.org/10.1007/s11356-019-06343-z
  44. Rashid Gill, A., Viswanathan, K. K., & Hassan, S. (2018). The environmental kuznets curve (EKC) and the environmental problem of the day. Renewable and Sustainable Energy Reviews, 81, 1636–1642. https://doi.org/https://doi.org/10.1016/j.rser.2017.05.247
  45. Richards, D. R., & Friess, D. A. (2016). Rates and drivers of mangrove deforestation in Southeast Asia, 2000-2012. Proceedings of the National Academy of Sciences of the United States of America, 113(2), 344–349. https://doi.org/10.1073/pnas.1510272113
  46. Samejima, H. (2020). Tropical Timber Trading from Southeast Asia to Japan BT - Anthropogenic Tropical Forests: Human–Nature Interfaces on the Plantation Frontier (N. Ishikawa & R. Soda (eds.); pp. 517–541). Springer Singapore. https://doi.org/10.1007/978-981-13-7513-2_25
  47. Shahbaz, M., Nwani, C., Bekun, F. V., Gyamfi, B. A., & Agozie, D. Q. (2022). Discerning the role of renewable energy and energy efficiency in finding the path to cleaner consumption and production patterns: New insights from developing economies. Energy, 260, 124951. https://doi.org/https://doi.org/10.1016/j.energy.2022.124951
  48. Tarascina, A. (2018). How does foreign direct investment impact deforestation in Indonesia ? Journal of International Economics, 79(1), 42–53
  49. Taubert, F., Fischer, R., Groeneveld, J., Lehmann, S., Müller, M. S., Rödig, E., Wiegand, T., & Huth, A. (2018). Global patterns of tropical forest fragmentation. Nature, 554(7693), 519–522. https://doi.org/10.1038/nature25508
  50. Turner, E. C., & Snaddon, J. L. (2023). Chapter 16 - Deforestation in Southeast Asia. In R. Sivanpillai & J. F. B. T.-B. and E. H. Shroder risks, and disasters (Second Edition) (Eds.), Hazards and Disasters Series (pp. 319–334). Elsevier. https://doi.org/https://doi.org/10.1016/B978-0-12-820509-9.00004-6
  51. Turubanova, S., Potapov, P. V, Tyukavina, A., & Hansen, M. C. (2018). Ongoing primary forest loss in Brazil, Democratic Republic of the Congo, and Indonesia. Environmental Research Letters, 13(7), 74028. https://doi.org/10.1088/1748-9326/aacd1c
  52. Usman, O., Iorember, P. T., & Olanipekun, I. O. (2019). Revisiting the environmental kuznets curve (EKC) hypothesis in india: The effects of energy consumption and democracy. Environmental Science and Pollution Research, 26(13), 13390–13400. https://doi.org/10.1007/s11356-019-04696-z
  53. Waluyo, E. A., & Terawaki, T. (2016). Environmental kuznets curve for deforestation in Indonesia: An ARDL bounds testing approach. Journal of Economic Cooperation and Development, 37(3), 87–108. https://jecd.sesric.org/pdf.php?file=ART15031901-2.pdf
  54. Wehkamp, J., Koch, N., Lübbers, S., & Fuss, S. (2018). Governance and deforestation — a meta-analysis in economics. Ecological Economics, 144, 214–227. https://doi.org/10.1016/j.ecolecon.2017.07.030
  55. Westerlund, J. (2005). New simple tests for panel cointegration. Econometric Reviews, 24(3), 297–316. https://doi.org/10.1080/07474930500243019
  56. World Bank, W. D. I. (2020). Forest Cover (% of Land Area). https://data.worldbank.org/indicator/AG.LND.FRST.ZS?locations=ID
  57. Yameogo, C. E. W. (2021). Globalization, urbanization, and deforestation linkage in Burkina Faso. Environmental Science and Pollution Research, 28(17), 22011–22021. https://doi.org/10.1007/s11356-020-12071-6
  58. Zeraibi, A., Ahmed, Z., Shehzad, K., Murshed, M., Nathaniel, S. P., & Mahmood, H. (2022). Revisiting the EKC hypothesis by assessing the complementarities between fiscal, monetary, and environmental development policies in China. Environmental Science and Pollution Research, 29(16), 23545–23560. https://doi.org/10.1007/s11356-021-17288-7

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