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Wednesday 26 April 2017

Economic Growth and Environmental Degradation in Nigeria: Beyond the Environmental Kuznets Curve

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Abstract: The Environmental Kuznets Curve (EKC) hypothesis is a presumption that environmental degradation follows an inverted U-shaped trajectory in relation to economic growth. The thorny question of whether economic growth could provide a cure to environmental degradation has sparked off a large body of empirical studies in the last decade. The conclusions have been mixed. This study contributes to the debate on the existence and policy relevance of the EKC for Nigeria by applying autoregressive distributed lag (ARDL) framework to annual time series data from 1960 to 2008. The traditional EKC model is extended by including (in addition to the level, square and cubed values of the income variable), trade openness as well as the shares of manufacturing, agriculture and service sectors in Nigeria’s GDP. Using Co2 emissions per capita to proxy environmental degradation, our findings do not support the existence of the EKC hypothesis. Rather our results show that Nigeria’s situation when confronted with data is exemplified by an N-shaped relationship with a turning point at $77.27 that lies below the data set used for the study. Based on these findings, the paper posit that the hypothesized EKC serves as a dangerous policy guide to solving environmental problems in Nigeria. The conclusion is that to ensure sustainability, there exist an urgent need to look beyond the EKC by adopting courageous policy measures of environmental preservation in Nigeria irrespective of the country’s level of income.
Keywords: Environmental DegradationARDLEnvironmental Kuznets CurveNigeria (search for similar items in EconPapers)
JEL-codes: C32 O43 Q24 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-afrnep-agrnep-ene and nep-env
Date: 2011-04-27
References: View references in EconPapers View complete reference list from CitEc
Citations View citations in EconPapers (4) Track citations by RSS feed
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