Analysis of the Responsiveness of Environmental Sustainability to Non-Performing Loans in Africa
This study draws on Sustainable Development Goal 12 to analyze the responsiveness of environmental sustainability to non-performing loans (NPLs) in Africa over the period 2000–2016. We explore (1) how environmental sustainability reacts to shocks from NPLs and (2) heterogeneous responses of environmental sustainability to NPLs. We employed Generalized Method of Moment (GMM) style panel Vector Autoregressive and panel quantile regression models to investigate the phenomenon. Our results revealed that conditioning on other sustainability determinants, environmental sustainability responds negatively to NPLs. The impulse response function revealed that the impact of one standard deviation shock in rising NPLs on environmental sustainability is negative from year 1 to year 6 and equal to zero from years 7 to 10. Besides, the quantile regression revealed heterogeneous responses indicating that compared with countries distributed along a high environmentally sustainable path, countries on a low environmentally sustainable path suffer more environmental issues resulting from rising NPLs.
Abrigo, M.R.M., & Love, I. (2016). Estimation of panel vector autoregression in Stata: A package of programs (Working Papers 201602). Hawaii: Department of Economics, University of Hawaii at Manoa.
Al-Moulani, A.J. (2016). Banking sector depth & long-term economic growth in the GCC states: Relationship nature, sector development status & policy implications (Doctoral Thesis, Cranfield University, United Kingdom). Retrieved from https://dspace.lib.cranfield.ac.uk/handle/1826/10492.
Amuakwa-Mensah, F., Marbuah, G., & Ani-Asamoah Marbuah, D. (2017). Re-examining the determinants of non-performing loans in Ghana’s banking industry: Role of the 2007–2009 financial crisis. Journal of African Business, 18(3), 357-379.
Andrews, D.W.K., & Lu, B. (2001). Consistent model and moment selection procedures for GMM estimation with application to dynamic panel data models. Journal of Econometrics, 101(1), 123-164.
Arcand, J.-L., Berkes, E., & Panizza, U. (2012). Too much finance? (IMF Working Paper No. 12/161). Washington, DC: International Monetary Fund.
Arellano, M., & Bover, O. (1995). Another look at the instrumental variable estimation of error component models. Journal of Econometrics, 68(1), 29–51.
Balcilar, M., Ozdemir, Z. A., Tunçsiper, B., Ozdemir, H., & Shahbaz, M. (2019). On the nexus among carbon dioxide emissions, energy consumption and economic growth in G-7 countries: New insights from the historical decomposition approach. Environment, Development and Sustainability, 2019, 1-38.
Barajas, A., Chami, R., & Yousefi, S. (2011). The impact of financial development on growth in the Middle East and North Africa. In International Monetary Fund, Middle East and Central Asia Regional Economic Outlook (Chapter 3.3). Washington, DC: International Monetary Fund.
Caldecott, B., & McDaniels, J. (2014). Financial dynamics of the environment: Risks, impacts, and barriers to resilience (Working Paper for the UNEP Inquiry July, 2014). Oxford: Smith School of Enterprise and the Environment, University of Oxford.
Canova, F., & Ciccarelli, M. (2013). Panel vector autoregressive models: A survey (CEPR Discussion Papers No.9380). London: Centre for Economic Policy Research.
Caprio, G., & Klingebiel, D. (2002). Episodes of systemic and borderline banking crises. In D. Klingebiel & L. Laeven (Eds.), Managing the real and fiscal effects of banking crises (pp. 31-49). Washington, DC: The World Bank.
Chaffin, J. (2010, April 1). Economic crisis cuts European carbon emissions. Financial Times. Retrieved from https://www.ft.com/content/b26d579e-3d99-11df-bdbb-00144feabdc0
Charfeddine, L., & Khediri, K. B. (2016). Financial development and environmental quality in UAE: Cointegration with structural breaks. Renewable and Sustainable Energy Reviews, 55, 1322-1335.
Charfeddine, L., & Kahia, M. (2019). Impact of renewable energy consumption and financial development on CO2 emissions and economic growth in the MENA region: A panel vector autoregressive (PVAR) analysis. Renewable Energy, 139, 198-213.
Choi, I. (2001). Unit root tests for panel data. Journal of International Money and Finance, 20(2), 249-272.
Choi, I. (2002). Combination unit root tests for cross-sectionally correlated panels. In D. Corbae, S. N. Durlauf, & B. Hansen (Eds.), Econometric theory and practice: Frontiers of analysis and applied research, essays in honor of Peter C. B. Phillips (pp. 311–333). Cambridge: Cambridge University Press.
Cialani, C. (2013). CO2 emissions, GDP and trade: A panel cointegration approach (Working Paper No. 2013:12). Falun: Dalarna University.
Dafermos, Y., Galanis, G., & Nikolaidi, M. (2015). A new ecological macroeconomic model: Analysing the interactions between the ecosystem, the financial system and the macroeconomy. London: New Economics Foundation.
Dhaene, G., & Jochmans, K. (2015). Split-panel jackknife estimation of fixed-effect models. The Review of Economic Studies, 82(3), 991-1030.
Dufrenot, G., Mignon, V., & Tsangarides, C. (2009). The trade-growth nexus in the developing countries: A quantile regression approach (CEPII WP No. 2009-04). Paris: The Centre d'Études Prospectives et d'Informations Internationales.
Enkvist, P. A., Dinkel, J., & Lin, C. (2010). Impact of the financial crisis on carbon economics: version 2.1 of the global greenhouse gas abatement cost curve. Washington, DC: McKinsey & Company.
European Central Bank (2016). What are non-performing loans (NPLs)? Retrieved from https://www.ecb.europa.eu/explainers/tell-me/html/npl.en.html
Galeotti, M. (2007). Economic growth and the quality of the environment: Taking stock. Environment, Development and Sustainability, 9(4), 427-454.
Gertler, M., & Kiyotaki, N. (2010). Financial intermediation and credit policy in business cycle analysis. In B. M. Friedman & M. Woodford (Eds.), Handbook of monetary economics (Vol. 3, pp. 547-599). Amsterdam: Elsevier.
Ghosh, S. (2016). Political transition and bank performance: How important was the Arab Spring? Journal of Comparative Economics, 44(2), 372-382.
Global Footprint Network (2019). Data and methodology. Retrieved from www.data.footprintnetwork.org
Hamadi, H., & Bassil, C. (2015). Financial development and economic growth in the MENA Region. Comparative Economic Studies, 57(4), 598–622.
Im, K. S., Pesaran, M. H., & Shin, Y. (2003). Testing for unit roots in heterogeneous panels. Journal of Econometrics, 115(1), 53–74.
Jamel, L., & Maktouf, S. (2017). The nexus between economic growth, financial development, trade openness, and CO2 emissions in European countries. Cogent Economics and Finance, 5(1), 1341456.
Khan, K., Su, C. W., Tao, R., & Hao, L. N. (2019). Urbanization and carbon emission: causality evidence from the new industrialized economies. Environment, Development and Sustainability, 2019, 1-21.
Kim, J., & Park, K. (2016). Financial development and deployment of renewable energy technologies. Energy Economics, 59, 238–250.
Kireyev, A. P. (2000). Comparative macroeconomic dynamics in the Arab World: A panel var approach (IMF Working Papers 00/54). Washington, DC: International Monetary Fund.
Lata, R. S. (2014). Non-performing loan and its impact on profitability of state-owned commercial banks in Bangladesh: An empirical study. Proceedings of 11th Asian Business Research Conference (pp.1-13). Dhaka: BIAM Foundation.
Love, I., & Zicchino, L. (2006). Financial development and dynamic investment behavior: Evidence from panel VAR. The Quarterly Review of Economics and Finance, 46(2), 190-210.
Lutkepohl, H. (2005). New introduction to multiple time series analysis. New York: Springer.
Machado, J. A. F., & Santos Silva, J. M. C. (2019). Quantiles via moments. Journal of Econometrics, 213(1), 145-173.
Maddala, G., & Wu, S. (1999). A comparative study of unit root tests and a new simple test. Oxford Bulletin of Economics and Statistics, 61, 631–652.
Mbah, A. K., & Paothong, A. (2015). Shapiro–Francia test compared to other normality test using expected p-value. Journal of Statistical Computation and Simulation, 85(15), 3002-3016.
Moghadam, H. E., & Dehbashi, V. (2018). The impact of financial development and trade on environmental quality in Iran. Empirical Economics, 54(4), 1777-1799.
Montt, G., Fraga, F., & Harsdorff, M. (2018). The future of work in a changing natural environment: Climate change, degradation and sustainability (ILO Research Paper Series). Geneva: International Labour Office.
Moon, H. R., & Perron, B. (2004). Testing for a unit root in panel with dynamic factors. Journal of Econometrics, 122(1), 81–126.
Morakinyo, A., & Sibanda, M. (2016). Non-performing loans and economic growth in Nigeria: a dynamic analysis. SPOUDAI-Journal of Economics and Business, 66(4), 61-81.
Mpofu, T. R., & Nikolaidou, E. (2019). Macroeconomic and bank-specific determinants of non-performing loans in sub-Saharan Africa (School of Economics Macroeconomic Discussion Paper Series 2019-02). Cape Town: School of Economics, University of Cape Town.
Nasreen, S., Anwar, S., & Ozturk, I. (2017). Financial stability, energy consumption and environmental quality: Evidence from South Asian economies. Renewable and Sustainable Energy Reviews, 67, 1105-1122.
Nieto, M. (2017). Banks and environmental sustainability: Some reflections from the perspective of financial stability. Brussels: Centre for European Policy Studies.
Nizam, E., Ng, A., Dewandaru, G., Nagayev, R., & Nkoba, M. A. (2019). The impact of social and environmental sustainability on financial performance: A global analysis of the banking sector. Journal of Multinational Financial Management, 49, 35-53.
Ntarmah, A. H., Kong, Y., & Gyan, M. K. (2019). Banking system stability and economic sustainability: A panel data analysis of the effect of banking system stability on sustainability of some selected developing countries. Quantitative Finance and Economics, 3(4), 709-738
Omri, A., Euchi, J., Hasaballah, A. H., & Al-Tit, A. (2019). Determinants of environmental sustainability: Evidence from Saudi Arabia. Science of The Total Environment, 657, 1592-1601.
Persyn, D., & Westerlund, J. (2008). Error correction based cointegration tests for panel data. Stata Journal, 8(2), 232-241.
Pesaran, M. H. (2004). General diagnostic tests for cross section dependence in panels: CESifo (Working Paper No. 1229). Cambridge: Cambridge University.
Pesaran, M. H. (2007). A simple panel unit root test in the presence of cross section dependence. Journal of Applied Econometrics, 22(2), 265–312.
Rakić, S., Mitić, P., & Anđelić, G. (2015). Social and environmental management systems in banking sector. Journal of Applied Quantitative Methods, 2015, 51-58.
Richard, P. (2010). Financial market instability and CO2 emissions (GREDI Working Paper No. 10-20). Quebec: University of Sherbrooke.
Rios-Avila, F. (2020). MMQREG: Stata module to estimate quantile regressions via Method of Moments. Statistical Software Components S458750. Boston College Department of Economics.
Romero, J. C., & Linares, P. (2013). Strong versus weak sustainability indexes in a conurbation context. A case example in Spain. Retrieved from http://hdl.handle.net/11531/14299
Saeed, M. Y., Ramzan, M., & Hamid, K. (2020). Causal and dynamic link between the banking sector and economic growth in Pakistan. Applied Economics Journal, 27(1), 102-126.
Salahuddin, M., Gow, J., & Ozturk, I. (2015). Is the long-run relationship between economic growth, electricity consumption, carbon dioxide emissions and financial development in Gulf Cooperation Council Countries robust? Renewable and Sustainable Energy Reviews, 51, 317–326.
Salim, R. A., & Rafiq, S. (2012). Why do some emerging economies proactively accelerate the adoption of renewable energy? Energy Economics, 34, 1051–1057.
Schmidt-Traub, G., & Shah, A. (2015). Investment needs to achieve the Sustainable Development Goals. Paris and New York: Sustainable Development Solutions Network.
Shahbaz, M. (2010). Does financial instability increase environmental pollution in Pakistan? (MPRA Paper No. 31360). Retrieved from https://mpra.ub.uni-muenchen.de/id/eprint/31360
Shahbaz, M. (2013). Does financial instability increase environmental degradation? Fresh evidence from Pakistan. Economic Modelling, 33, 537–544.
Sherwood, B., & Wang, L. (2016). Partially linear additive quantile regression in ultra-high dimension. The Annals of Statistics, 44(1), 288-317.
Sims, C. A. (1980). Macroeconomics and Reality. Econometrica, 48(1), 1-48.
Tamazian, A., Chousa, J., & Vadlamannati, K. (2009). Does higher economic and financial development lead to environmental degradation: Evidence from BRIC countries? Energy Policy, 37, 246–253.
Tamazian, A., & Rao, B. B. (2010). Do economic, financial and institutional developments matter for environmental degradation? Evidence from transitional economies. Energy Economics, 32(1), 137–145.
United Nations Environment Programme [UNEP] (2015). Aligning the financial system with sustainable development: Insights from practice. Geneva: UNEP.
Vodová, P. (2003). Credit risk as a cause of banking crises. Paper presented at the 5th International Conference Aidea Giovani, Milan.
Westerlund, J. (2007). Testing for panel cointegration with multiple structural breaks. Oxford Bulletin of Economics and Statistics, 68(1), 101–132.
World Bank (2019). World development indicators 2019. Washington, DC: World Bank.
World Bank (2020). World development indicators 2020. Washington, DC: World Bank.
Wyman, O. (2015). Post-crisis changes in the stability of the US banking system evidence from US bank holding companies from 2004 to 2014. New York: Oliver Wyman Inc.
Yang, B., Ali, M., & Nazir, M. R. (2020). Financial instability and CO2 emissions: Cross-country evidence. Air Quality, Atmosphere and Health, 13(2), 459-468.
Zeng, S. (2012). Bank non-performing loans (NPLS): A dynamic model and analysis in China. Modern Economy, 3(1), 100-110.
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. Economic Modelling, 58, 237–248.
Copyright (c) 2020 Applied Economics Journal
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Submission of a manuscript to Applied Economics Journal will be taken to imply that the author(s) guarantee that the paper is an original work, has not been published, and is not being considered for publication elsewhere either in printed or electronic form. The author(s) have obtained permission from the copyright holder to reproduce in the article material not owned by them, that author(s) have acknowledged the source, and that this article contains no violation of any existing copyright or other third party right or any material of an obscene, indecent, libelous or otherwise unlawful nature and that the article does not infringe the rights of others. The author(s) will indemnify and keep indemnified the editors and Applied Economics Journal, Center for Applied Economics Research (CAER), Faculty of Economics, Kasetsart University against all claims and expenses. The author(s) agree that the publisher may arrange for the article to be published and sold or distributed on its own, or with other related materials, and could reproduce and/or distribute in printed, electronic or any other medium whether now known or hereafter devised, in all languages, and to authorize third parties to do the same.