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The impact of corruption on deforestation: a cross-country evidence

Author

Listed:
  • Cuneyt Koyuncu
  • Rasim Yilmaz

    (Dumlupinar University, Turkey
    Namik Kemal University, Turkey)

Abstract

We hypothesized that corruption could contribute to deforestation. The present study, therefore, try to identify such a relation between corruption and deforestation. By using three different corruption indices, we found a statistically significant strong positive relation between corruption and deforestation for different periods across different countries. This finding remains valid in both univariate and multivariate models. Also, the model takes the potential heteroscedasticity problem, common in cross-section studies, into account and makes correction if necessary. To our best knowledge, this study is the first cross-country study addressing to the issue by utilizing all available corruption indices, namely Corruption Perception Index (CPI), International Country Risk Guide (ICRG) index, and Business Intelligence (BI) index. Policies and measures taken towards reducing corruption, therefore, may help to decrease illegal forest activities (e.g. illegal logging and timbering, smuggling of forest products etc.) and in turn depletion of forests.

Suggested Citation

  • Cuneyt Koyuncu & Rasim Yilmaz, 2009. "The impact of corruption on deforestation: a cross-country evidence," Journal of Developing Areas, Tennessee State University, College of Business, vol. 42(2), pages 213-222, January-M.
    • Handle: RePEc:jda:journl:vol.42:year:2009:issue2:pp:213-222
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    Cited by:

    1. Andrew Hargrove & Feng Hao & Jamie Marie Sommer, 2022. "Governing trade: a cross-national study of governance, trade, and CO2 emissions," Journal of Environmental Studies and Sciences, Springer;Association of Environmental Studies and Sciences, vol. 12(4), pages 727-738, December.
    2. Muhammad Haseeb & Muhammad Azam, 2021. "Dynamic nexus among tourism, corruption, democracy and environmental degradation: a panel data investigation," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(4), pages 5557-5575, April.
    3. Dasgupta, Shouro & De Cian, Enrica, 2016. "Institutions and the Environment: Existing Evidence and Future Directions," MITP: Mitigation, Innovation and Transformation Pathways 240747, Fondazione Eni Enrico Mattei (FEEM).
    4. Eleni Stathopoulou & Dimitrios Varvarigos, 2013. "Corruption, Entry and Pollution," Discussion Papers in Economics 13/21, Division of Economics, School of Business, University of Leicester.
    5. Carr, Jamie A. & Petrokofsky, Gillian & Spracklen, Dominick V. & Lewis, Simon L. & Roe, Dilys & Trull, Nicholas & Vidal, Adriana & Wicander, Sylvia & Worthington-Hill, John & Sallu, Susannah M., 2021. "Anticipated impacts of achieving SDG targets on forests - a review," Forest Policy and Economics, Elsevier, vol. 126(C).
    6. Schwerhoff, Gregor & Wehkamp, Johanna, 2018. "Export tariffs combined with public investments as a forest conservation policy instrument," Forest Policy and Economics, Elsevier, vol. 95(C), pages 69-84.
    7. Abman, Ryan, 2018. "Rule of Law and Avoided Deforestation from Protected Areas," Ecological Economics, Elsevier, vol. 146(C), pages 282-289.
    8. Mustafa ÜNVER & Julide Yalçýnkaya KOYUNCU, 2016. "The Impact of Poverty on Corruption," Journal of Economics Library, KSP Journals, vol. 3(4), pages 632-642, December.
    9. Timothy Cadman & Lauren Eastwood & Federico Lopez-Casero Michaelis & Tek N. Maraseni & Jamie Pittock & Tapan Sarker, 2015. "The Political Economy of Sustainable Development," Books, Edward Elgar Publishing, number 15773, March.
    10. Moreira-Dantas, Ianna Raissa & Söder, Mareike, 2022. "Global deforestation revisited: The role of weak institutions," Land Use Policy, Elsevier, vol. 122(C).
    11. Cuneyt Koyuncu & Rasim Yilmaz, 2013. "Deforestation, corruption, and private ownership in the forest sector," Quality & Quantity: International Journal of Methodology, Springer, vol. 47(1), pages 227-236, January.
    12. Dimitrios Varvarigos, 2013. "Economic Growth, Health, and the Choice of Polluting Technologies: The Role of Bureaucratic Corruption," Discussion Papers in Economics 13/22, Division of Economics, School of Business, University of Leicester.
    13. Yi-Bin Chiu, 2012. "Deforestation and the Environmental Kuznets Curve in Developing Countries: A Panel Smooth Transition Regression Approach," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 60(2), pages 177-194, June.
    14. Halkos, George & Sundström, Aksel & Tzeremes, Nickolaos, 2013. "Environmental performance and quality of governance: A non-parametric analysis of the NUTS 1-regions in France, Germany and the UK," MPRA Paper 48890, University Library of Munich, Germany.
    15. Mawusse K.N. Okey, 2016. "Corruption And Emigration Of Physicians From Africa," Journal of Economic Development, Chung-Ang Unviersity, Department of Economics, vol. 41(2), pages 27-52, June.
    16. Ullah, Asad & Ali, Amjad, 2024. "Investigating Corruption, Income Inequality, and Environmental Degradation in Pakistan: A Time Series Analysis," MPRA Paper 121291, University Library of Munich, Germany.
    17. George Halkos & Aksel Sundström & Nickolaos Tzeremes, 2015. "Regional environmental performance and governance quality: a nonparametric analysis," Environmental Economics and Policy Studies, Springer;Society for Environmental Economics and Policy Studies - SEEPS, vol. 17(4), pages 621-644, October.
    18. Sverker C. Jagers & Marina Povitkina & Martin Sjöstedt & Aksel Sundström, 2016. "Paradise Islands? Island States and Environmental Performance," Sustainability, MDPI, vol. 8(3), pages 1-24, March.
    19. Salahodjaev, Raufhon, 2016. "Intelligence and deforestation: International data," Forest Policy and Economics, Elsevier, vol. 63(C), pages 20-27.

    More about this item

    Keywords

    Deforestation; Corruption; Heteroscedasticity;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • O13 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Agriculture; Natural Resources; Environment; Other Primary Products
    • Q23 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Forestry

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