IDEAS home Printed from https://ideas.repec.org/a/eee/tefoso/v112y2016icp220-227.html
   My bibliography  Save this article

The effect of corruption on carbon dioxide emissions in APEC countries: A panel quantile regression analysis

Author

Listed:
  • Zhang, Yue-Jun
  • Jin, Yan-Lin
  • Chevallier, Julien
  • Shen, Bo

Abstract

The relationship between corruption and CO2 emissions has been receiving increased attention in recent years, but little work has been conducted for the Asia-Pacific Economic Cooperation (APEC) countries even if they have determined to fight against corruption and address climate change. Using the quantile regression approach, this paper develops a panel data model for the effect of corruption on CO2 emissions in APEC countries. The empirical results show that, first of all, the effect of corruption on CO2 emissions is heterogeneous among APEC countries. Specifically, there is significant negative effect in lower emission countries, but insignificant in higher emission countries. Second, there exists an inverted U-shaped Environmental Kuznets Curve (EKC) between corruption and CO2 emissions, and the per capita GDP at the turning point of the EKC may increase when CO2 emissions increase. Finally, corruption may have not only a negative direct effect on CO2 emissions, but also a positive indirect effect through its effect on per capita GDP. The total effect appears positive, which indicates corruption may worsen environmental quality overall in APEC countries.

Suggested Citation

  • Zhang, Yue-Jun & Jin, Yan-Lin & Chevallier, Julien & Shen, Bo, 2016. "The effect of corruption on carbon dioxide emissions in APEC countries: A panel quantile regression analysis," Technological Forecasting and Social Change, Elsevier, vol. 112(C), pages 220-227.
    • Handle: RePEc:eee:tefoso:v:112:y:2016:i:c:p:220-227
    DOI: 10.1016/j.techfore.2016.05.027
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S004016251630107X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.techfore.2016.05.027?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Callen, Michael & Long, James D., 2015. "Institutional corruption and election fraud: evidence from a field experiment in Afghanistan," LSE Research Online Documents on Economics 102931, London School of Economics and Political Science, LSE Library.
    2. Damette, Olivier & Delacote, Philippe, 2012. "On the economic factors of deforestation: What can we learn from quantile analysis?," Economic Modelling, Elsevier, vol. 29(6), pages 2427-2434.
    3. Hausman, Jerry, 2015. "Specification tests in econometrics," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 38(2), pages 112-134.
    4. Koenker, Roger, 2004. "Quantile regression for longitudinal data," Journal of Multivariate Analysis, Elsevier, vol. 91(1), pages 74-89, October.
    5. Michael Callen & James D. Long, 2015. "Institutional Corruption and Election Fraud: Evidence from a Field Experiment in Afghanistan," American Economic Review, American Economic Association, vol. 105(1), pages 354-381, January.
    6. Peter Pedroni, 2000. "Fully Modified OLS for Heterogeneous Cointegrated Panels," Department of Economics Working Papers 2000-03, Department of Economics, Williams College.
    7. Damania, Richard & Fredriksson, Per G. & List, John A., 2003. "Trade liberalization, corruption, and environmental policy formation: theory and evidence," Journal of Environmental Economics and Management, Elsevier, vol. 46(3), pages 490-512, November.
    8. Aparicio, Sebastian & Urbano, David & Audretsch, David, 2016. "Institutional factors, opportunity entrepreneurship and economic growth: Panel data evidence," Technological Forecasting and Social Change, Elsevier, vol. 102(C), pages 45-61.
    9. Kwabena Gyimah-Brempong & Samaria de Gyimah-Brempong, 2006. "Corruption, Growth, and Income Distribution: Are there Regional Differences?," Economics of Governance, Springer, vol. 7(3), pages 245-269, August.
    10. Abhijit V. Banerjee, 1997. "A Theory of Misgovernance," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 112(4), pages 1289-1332.
    11. Lee, Jen-Sin & Huang, Gow-Liang & Kuo, Chin-Tai & Lee, Liang-Chien, 2012. "The momentum effect on Chinese real estate stocks: Evidence from firm performance levels," Economic Modelling, Elsevier, vol. 29(6), pages 2392-2406.
    12. Katariina Nilsson Hakkala & Pehr-Johan Norbäck & Helena Svaleryd, 2008. "Asymmetric Effects of Corruption on FDI: Evidence from Swedish Multinational Firms," The Review of Economics and Statistics, MIT Press, vol. 90(4), pages 627-642, November.
    13. Rock, Michael T. & Bonnett, Heidi, 2004. "The Comparative Politics of Corruption: Accounting for the East Asian Paradox in Empirical Studies of Corruption, Growth and Investment," World Development, Elsevier, vol. 32(6), pages 999-1017, June.
    14. Lalountas, Dionisios A. & Manolas, George A. & Vavouras, Ioannis S., 2011. "Corruption, globalization and development: How are these three phenomena related?," Journal of Policy Modeling, Elsevier, vol. 33(4), pages 636-648, July.
    15. Biswas, Amit K. & Farzanegan, Mohammad Reza & Thum, Marcel, 2012. "Pollution, shadow economy and corruption: Theory and evidence," Ecological Economics, Elsevier, vol. 75(C), pages 114-125.
    16. Zhang, Yue-Jun & Da, Ya-Bin, 2015. "The decomposition of energy-related carbon emission and its decoupling with economic growth in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 41(C), pages 1255-1266.
    17. Timmons, Jeffrey F. & Garfias, Francisco, 2015. "Revealed Corruption, Taxation, and Fiscal Accountability: Evidence from Brazil," World Development, Elsevier, vol. 70(C), pages 13-27.
    18. Cole, Matthew A., 2007. "Corruption, income and the environment: An empirical analysis," Ecological Economics, Elsevier, vol. 62(3-4), pages 637-647, May.
    19. Harry Seldadyo & Jakob De Haan, 2011. "Is Corruption Really Persistent?," Pacific Economic Review, Wiley Blackwell, vol. 16(2), pages 192-206, May.
    20. Fisman, Raymond & Svensson, Jakob, 2007. "Are corruption and taxation really harmful to growth? Firm level evidence," Journal of Development Economics, Elsevier, vol. 83(1), pages 63-75, May.
    21. Jetter, Michael & Agudelo, Alejandra Montoya & Hassan, Andrés Ramírez, 2015. "The Effect of Democracy on Corruption: Income is Key," World Development, Elsevier, vol. 74(C), pages 286-304.
    22. Jeffrey M. Wooldridge, 2001. "Applications of Generalized Method of Moments Estimation," Journal of Economic Perspectives, American Economic Association, vol. 15(4), pages 87-100, Fall.
    23. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
    24. Arvind K. Jain, 2001. "Corruption: A Review," Journal of Economic Surveys, Wiley Blackwell, vol. 15(1), pages 71-121, February.
    25. van Soest, Daan & Stoop, Jan & Vyrastekova, Jana, 2016. "Toward a delineation of the circumstances in which cooperation can be sustained in environmental and resource problems," Journal of Environmental Economics and Management, Elsevier, vol. 77(C), pages 1-13.
    26. Fredriksson, Per G. & Vollebergh, Herman R. J. & Dijkgraaf, Elbert, 2004. "Corruption and energy efficiency in OECD countries: theory and evidence," Journal of Environmental Economics and Management, Elsevier, vol. 47(2), pages 207-231, March.
    27. Grooms, Katherine K., 2015. "Enforcing the Clean Water Act: The effect of state-level corruption on compliance," Journal of Environmental Economics and Management, Elsevier, vol. 73(C), pages 50-78.
    28. Lamarche, Carlos, 2011. "Measuring the incentives to learn in Colombia using new quantile regression approaches," Journal of Development Economics, Elsevier, vol. 96(2), pages 278-288, November.
    29. Lopez, Ramon & Mitra, Siddhartha, 2000. "Corruption, Pollution, and the Kuznets Environment Curve," Journal of Environmental Economics and Management, Elsevier, vol. 40(2), pages 137-150, September.
    30. Paolo Mauro, 1995. "Corruption and Growth," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 110(3), pages 681-712.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Sekrafi Habib & Snoussi Abdelmonen & Mili Khaled, 2020. "The Effect of Corruption on the Environmental Quality in African Countries: a Panel Quantile Regression Analysis," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 11(2), pages 788-804, June.
    2. Ren, Yi-Shuai & Ma, Chao-Qun & Apergis, Nicholas & Sharp, Basil, 2021. "Responses of carbon emissions to corruption across Chinese provinces," Energy Economics, Elsevier, vol. 98(C).
    3. YunSeop Hwang & Chang-Bong Kim & Cheon Yu, 2024. "The Effect of Corruption on Environmental Quality: Evidence from a Panel of CIS Countries," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 15(1), pages 2836-2855, March.
    4. Román-Aso, Juan A. & Bellido, Héctor & Olmos, Lorena, 2024. "Does corruption pollute the wheel? An analysis for OECD countries," Ecological Economics, Elsevier, vol. 223(C).
    5. Arminen, Heli & Menegaki, Angeliki N., 2019. "Corruption, climate and the energy-environment-growth nexus," Energy Economics, Elsevier, vol. 80(C), pages 621-634.
    6. Jeong Hwan Bae & Dmitriy D. Li & Meenakshi Rishi, 2017. "Determinants of CO emission for post-Soviet Union independent countries," Climate Policy, Taylor & Francis Journals, vol. 17(5), pages 591-615, July.
    7. Bin Dong & Benno Torgler, 2010. "The Consequences of Corruption: Evidence from China," Working Papers 2010.73, Fondazione Eni Enrico Mattei.
    8. Dincer, Oguzhan C. & Fredriksson, Per G., 2018. "Corruption and environmental regulatory policy in the United States: Does trust matter?," Resource and Energy Economics, Elsevier, vol. 54(C), pages 212-225.
    9. Salvatore Bimonte & Arsenio Stabile, 2019. "The Effect of Growth and Corruption on Soil Sealing in Italy: A Regional Environmental Kuznets Curve Analysis," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 74(4), pages 1497-1518, December.
    10. Bin Dong & Benno Torgler, 2010. "The Consequences of Corruption: Evidence from China," Working Papers 2010.73, Fondazione Eni Enrico Mattei.
    11. Hbib Sekrafi & Asma Sghaier, 2018. "Examining the Relationship Between Corruption, Economic Growth, Environmental Degradation, and Energy Consumption: a Panel Analysis in MENA Region," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 9(3), pages 963-979, September.
    12. Maurizio Lisciandra & Carlo Migliardo, 2017. "An Empirical Study of the Impact of Corruption on Environmental Performance: Evidence from Panel Data," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 68(2), pages 297-318, October.
    13. Frantisek Cech & Jozef Barunik, 2017. "Measurement of Common Risk Factors: A Panel Quantile Regression Model for Returns," Working Papers IES 2017/20, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Sep 2017.
    14. Ming Zhong & Jingjing Yu & Syed Anees Haider Zaidi, 2024. "Investigating the Impact of Financial Inclusion on Energy Consumption: Does Corruption Matter?," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 15(2), pages 8797-8814, June.
    15. Wu, Tao & Delios, Andrew & Chen, Zhaowei & Wang, Xin, 2023. "Rethinking corruption in international business: An empirical review," Journal of World Business, Elsevier, vol. 58(2).
    16. Per G. Fredriksson & Eric Neumayer, 2016. "Corruption and Climate Change Policies: Do the Bad Old Days Matter?," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 63(2), pages 451-469, February.
    17. You, Wanhai & Guo, Yawei & Zhu, Huiming & Tang, Yong, 2017. "Oil price shocks, economic policy uncertainty and industry stock returns in China: Asymmetric effects with quantile regression," Energy Economics, Elsevier, vol. 68(C), pages 1-18.
    18. Panteli Maria & Delipalla Sofia, 2022. "The Impact of Institutions on Economic and Environmental Performance: Evidence From Europe," South East European Journal of Economics and Business, Sciendo, vol. 17(2), pages 125-141, December.
    19. Halkos, George E. & Tzeremes, Nickolaos G., 2014. "Public sector transparency and countries’ environmental performance: A nonparametric analysis," Resource and Energy Economics, Elsevier, vol. 38(C), pages 19-37.
    20. Haiqing Hu & Di Chen & Chun‐Ping Chang & Yin Chu, 2021. "The Political Economy Of Environmental Consequences: A Review Of The Empirical Literature," Journal of Economic Surveys, Wiley Blackwell, vol. 35(1), pages 250-306, February.

    More about this item

    Keywords

    Corruption; CO2 emissions; APEC; Panel quantile regression;
    All these keywords.

    JEL classification:

    • D73 - Microeconomics - - Analysis of Collective Decision-Making - - - Bureaucracy; Administrative Processes in Public Organizations; Corruption
    • Q57 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Ecological Economics
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:tefoso:v:112:y:2016:i:c:p:220-227. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.sciencedirect.com/science/journal/00401625 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.