Main Article Content
Corruption, democracy, military expenditure, , carbon dioxide emission, ASEAN countries
Purpose of the study: The current study aims to examine the relationship between corruption, democracy, military expenditure and environmental degradation in a panel of six ASEAN countries including Malaysia, Indonesia, Philippines, Thailand, Singapore and Vietnam using a panel data from 1995 to 2017.
Methodology: In addition, the current study is unique in applying the sophisticated methods of panel Fully Modified Ordinary Least Square (FMOLS) and Dynamic Ordinary Least Square (DOLS) that have been adopted in several earlier quality research.
Main Findings: The results of panel estimations conclude that corruption, military expenditure, and democracy have a noteworthy and significant impact on carbon dioxide emission in ASEAN countries. The results of FMOLS and DOLS confirm that there is a positive and significant impact of military expenditure and corruption on carbon dioxide emission. However, we found a negative and significant impact of democracy on carbon dioxide emission in all selected ASEAN countries.
Implications: In general, the consequences of both statistical estimations affirm that corruption, democracy, and military expenditure are the critical and noteworthy determinants of carbon dioxide emission in ASEAN nations.
2. Alkali, M.Y. and M.I. Imam, 2016. Accountability and environmental sustainability: Nigerian maritime experience. Asian Journal of Economics and Empirical Research, 3(1): 1-5.Available at: https://doi.org/10.20448/journal.501/2016.3.1/501.1.1.5.
3. Ametorwo, A.M., 2016. Managing work family conflict among female entrepreneurs in Ghana for development. International Journal of Economics, Business and Management Studies, 3(1): 21-35.
4. Bae, J.H., D.D. Li and M. Rishi, 2017. Determinants of CO2 emission for post-soviet union independent countries. Climate Policy, 17(5): 591-615.Available at: https://doi.org/10.1080/14693062.2015.1124751.
5. Bildirici, M., 2017a. CO 2 emissions and militarization in G7 countries: Panel cointegration and trivariate causality approaches. Environment and Development Economics, 22(6): 771-791.Available at: https://doi.org/10.1017/s1355770x1700016x.
6. Bildirici, M., 2018. Impact of military on biofuels consumption and GHG emissions: The evidence from G7 countries. Environmental Science and Pollution Research, 25(14): 13560-13568.Available at: https://doi.org/10.1007/s11356-018-1545-x.
7. Bildirici, M.E., 2017b. The causal link among militarization, economic growth, CO 2 emission, and energy consumption. Environmental Science and Pollution Research, 24(5): 4625-4636.Available at: https://doi.org/10.1007/s11356-016-8158-z.
8. Bildirici, M.E., 2017c. The effects of militarization on biofuel consumption and CO2 emission. Journal of Cleaner Production, 152: 420-428.Available at: https://doi.org/10.1016/j.jclepro.2017.03.103.
9. Clark, B., A.K. Jorgenson and J. Kentor, 2010. Militarization and energy consumption: A test of treadmill of destruction theory in comparative perspective. International Journal of Sociology, 40(2): 23-43.Available at: https://doi.org/10.2753/ijs0020-7659400202.
10. Cossiga, G.A., 2018. Signals from the world of economics. The price constant and the democratic issue. International Journal of Social and Administrative Sciences, 3(1): 1-21.
11. Diekmann, A. and A. Franzen, 2019. Environmental concern: A global perspective. In Einstellungen und Verhalten in der empirischen Sozialforschung. Wiesbaden: Springer. pp: 253-272.
12. Duong, N.T., 2016. The linkage between corruption and carbon dioxide emission: Evidence from Asian countries.
13. Frhd, N.B., O.U. Grace and V.C. Iwuoha, 2012. Military operations associated with internal security and special rules for opening fire in Armed conflicts. International Journal of Asian Social Science, 2(7): 1151-1160.
14. Ghodrati, S., J. Harati and A. Nazari, 2018. The democracy and environment quality in selected countries: An application of panel data. Iranian Economic Review, 22(1): 21-49.
15. Gibson, J.A., 2016. Elementary school male aggression: Framing aggression reduction programs for effectiveness. Asian Journal of Education and Training, 2(1): 7-10.
16. Habib, S., S. Abdelmonen and M. Khaled, 2018. The effect of corruption on the environmental quality in African countries: A panel quantile regression analysis. Journal of the Knowledge Economy. pp: 1-17.
17. Im, K.S., M.H. Pesaran and Y. Shin, 2003. Testing for unit roots in heterogeneous panels. Journal of Econometrics, 115(1): 53-74.Available at: https://doi.org/10.1016/s0304-4076(03)00092-7.
18. Jorgenson, A.K., B. Clark and J.E. Givens, 2012. The environmental impacts of militarization in comparative perspective: An overlooked relationship. Nature and Culture, 7(3): 314-337.Available at: https://doi.org/10.3167/nc.2012.070304.
19. Joshi, P. and K. Beck, 2018. Democracy and carbon dioxide emissions: Assessing the interactions of political and economic freedom and the environmental Kuznets Curve. Energy Research & Social Science, 39: 46-54.Available at: https://doi.org/10.1016/j.erss.2017.10.020.
20. Kao, C., 2003. Spurious regression and residual-based tests for cointegration in panel data. Journal of Econometrics, 90(1): 1-44.
21. Khalid, M.A. and A.B. Mustapha, 2014. Long-run relationships and causality tests between military expenditure and economic growth in India. The Economics and Finance Letters, 1(4): 49-58.Available at: https://doi.org/10.18488/journal.29/2014.1.4/220.127.116.11.
22. Khan, S.N. and E.I.E. Ali, 2017. The moderating role of intellectual capital between enterprise risk management and firm performance: A conceptual review. American Journal of Social Sciences and Humanities, 2(1): 9-15.Available at: https://doi.org/10.20448/801.21.9.15.
23. Levin, A., C.-F. Lin and C.-S.J. Chu, 2002. Unit root tests in panel data: Asymptotic and finite-sample properties. Journal of Econometrics, 108(1): 1-24.Available at: https://doi.org/10.1016/s0304-4076(01)00098-7.
24. Mao, Y., 2018. Does democratic transition reduce carbon intensity? Evidence from Indonesia using the synthetic control method. Environmental Science and Pollution Research, 25(20): 19908-19917.Available at: https://doi.org/10.1007/s11356-018-2165-1.
25. Masron, T.A. and Y. Subramaniam, 2018. The environmental Kuznets Curve in the presence of corruption in developing countries. Environmental Science and Pollution Research. pp: 1-16.
26. Mohamed, B.M., G.A. Rasheli and L.R. Mwagike, 2018. Marginal effects of factors influencing procurement records management: A survey of selected procuring entities in Tanzania. International Journal of Social and Administrative Sciences, 3(1): 22-34.
27. Mungwari, T., 2018. Media framing of ZANU PF internal succession struggles: Mnangagwa and the military factor. American Journal of Social Sciences and Humanities, 3(1): 1-21.Available at: https://doi.org/10.20448/801.31.1.21.
28. Nekooei, M.H., R. Zeinalzadeh and Z. Sadeghi, 2015. The effects of democracy on environment quality index in selected OIC countries. Iranian Journal of Economic Studies, 4(2): 113-133.
29. Okoli, A.C., 2017. Disarmament, demobilization and reintegration (DDR) in Rwanda, 1997-2008: A desk exegesis and agenda for praxis. International Journal of Emerging Trends in Social Sciences, 1(1): 1-8.Available at: https://doi.org/10.20448/2001.11.1.8.
30. Okon, E.O., 2016. Business development in Nasarawa State: Effect of poor sanitation and waste management system. International Journal of Economics, Business and Management Studies, 3(1): 36-46.
31. Oluwaseun, P. and O. Samuel, 2018. Military regimes and Nigeria’s economic development, 1966-1999. Journal of Social Economics Research, 5(1): 29-38.Available at: https://doi.org/10.18488/journal.35.2018.51.29.38.
32. Özmaden, M., F. Soter and H. Özmaden, 2018. The physical education and sport studies in the framework of social demands-institutional structuring and teacher training the developments before and during Turkey training community alliance period (1922-1936). Asian Journal of Education and Training, 4(3): 170-175.Available at: https://doi.org/10.20448/journal.522.2018.43.170.175.
33. Parks, B.C. and J.T. Roberts, 2010. Climate change, social theory and justice. Theory, Culture & Society, 27(2-3): 134-166.
34. Pedroni, P., 1999. Critical values for cointegration tests in heterogeneous panels with multiple regressors. Oxford Bulletin of Economics and statistics, 61(S1): 653-670.Available at: https://doi.org/10.1111/1468-0084.61.s1.14.
35. Pedroni, P., 2001. Purchasing power parity tests in cointegrated panels. Review of Economics and Statistics, 83(4): 727-731.Available at: https://doi.org/10.1162/003465301753237803.
36. Pedroni, P., 2001a. Fully modified OLS for heterogeneous cointegrated panels. Advances in Econometrics, 15: 93–130.Available at: https://doi.org/10.1016/s0731-9053(00)15004-2.
37. Pedroni, P., 2001b. Fully modified OLS for heterogeneous cointegrated panels. In nonstationary panels, panel cointegration, and dynamic panels. Emerald Group Publishing Limited. pp: pp. 93-130.
38. 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.
39. Phillips, P.C. and B.E. Hansen, 1990. Statistical inference in instrumental variables regression with I (1) processes. The Review of Economic Studies, 57(1): 99-125.Available at: https://doi.org/10.2307/2297545.
40. Rehman, F.U., M. Nasir and F. Kanwal, 2012. Nexus between corruption and regional Environmental Kuznets Curve: The case of South Asian countries. Environment, Development and Sustainability, 14(5): 827-841.Available at: https://doi.org/10.1007/s10668-012-9356-6.
41. Rosli, A. and T.I. Siong, 2018. Determinants of customers satisfaction towards services provided by agencies in urban transformation centre (UTC). International Journal of Economics, Business and Management Studies, 5(1): 9-15.Available at: https://doi.org/10.20448/802.51.9.15.
42. Sharif, A., S.A. Raza, I. Ozturk and S. Afshan, 2019. The dynamic relationship of renewable and nonrenewable energy consumption with carbon emission: A global study with the application of heterogeneous panel estimation. Renewable Energy, 133: 685-691.Available at: https://doi.org/10.1016/j.renene.2018.10.052.
43. Shin, S.J. and J. Zhou, 2003. Transformational leadership, conservation, and creativity: Evidence from Korea. Academy of Management Journal, 46(6): 703-714.Available at: https://doi.org/10.2307/30040662.
44. Sundström, A., 2013. Corruption in the commons: Why bribery hampers enforcement of environmental regulations in South African fisheries. International Journal of the Commons, 7(2): 454-472.Available at: https://doi.org/10.18352/ijc.370.
45. Ul-Haq, I., S. Zhu and M. Shafiq, 2016. Empirical investigation of environmental Kuznets Curve for carbon emission in Morocco. Ecological Indicators, 67: 491-496.Available at: https://doi.org/10.1016/j.ecolind.2016.03.019.
46. Wang, Z., B. Zhang and B. Wang, 2018. The moderating role of corruption between economic growth and CO2 emissions: Evidence from BRICS economies. Energy, 148: 506-513.Available at: https://doi.org/10.1016/j.energy.2018.01.167.
47. Winbourne, S., 2002. Corruption and the environment. Management Systems International and USAID, Washington.
48. You, W.-H., H.-M. Zhu, K. Yu and C. Peng, 2015. Democracy, financial openness, and global carbon dioxide emissions: Heterogeneity across existing emission levels. World Development, 66: 189-207.Available at: https://doi.org/10.1016/j.worlddev.2014.08.013.
49. Zhang, Y.-J., Y.-L. Jin, J. Chevallier and B. Shen, 2016. The effect of corruption on carbon dioxide emissions in APEC countries: A panel quantile regression analysis. Technological Forecasting and Social Change, 112: 220-227.Available at: https://doi.org/10.1016/j.techfore.2016.05.027