Open AccessESTIMATING ATMOSPHERIC CARBON DIOXIDE EMISSIONS THRESHOLD FOR NIGERIA: A GUIDE FOR ENVIRONMENTAL POLICY
Author(s) -
Aliyu Alhaji Jibrilla
Publication year - 2018
Publication title -
international journal of research - granthaalayah
Language(s) - English
Resource type - Journals
eISSN - 2394-3629
pISSN - 2350-0530
DOI - 10.29121/granthaalayah.v6.i9.2018.1219
Subject(s) - cointegration , distributed lag , urbanization , short run , economics , granger causality , econometrics , error correction model , carbon dioxide , structural break , population , per capita , greenhouse gas , natural resource economics , environmental science , macroeconomics , ecology , economic growth , biology , demography , sociology
This study empirically evaluates whether Green House Gases (GHGs) significantly increase with the rising population and urban growth in Nigeria. In addition, the study examine whether the energy demand also influences Nigerian contribution of global pollution emissions. The results of the Autoregressive Distributed Lag (ARDL) cointegration test indicated long-run and stable relationships among the variables. For affluence, we find evidence that, in the long run, domestic per capita income significantly increases carbon dioxide emissions and then falls after a certain extreme point, providing evidence of an inverted EKC hypothesis in Nigeria. The EKC finding was further supported by appropriate inverted U test. The results also demonstrated that both urbanisation and population change do not have a long term effect on emissions; although urbanisation seems to significantly raise emissions in the short-run. Energy demand has been found to have a significantly positive elasticity effect on carbon dioxide emissions both in the long- and short-run. The short-run Granger causality results indicate that, all variables make a short-run adjustment to correct any deviation from the long-run equilibrium. In addition, analysis of the error correction models reveals that all of the variables contribute to their stable long-run relationship.