Author(s)

Md. Sharif Hossain

Department of Accounting and Information Systems, Faculty of Business Studies, University of Dhaka, Dhaka, Bangladesh.

Nowadays, the impact of climate change on the global mean sea level variations is becoming an important issue to the researchers and policy makers as a general concern about environmental degradation is making their way into global policy agenda. That is why, in this paper the principal purpose has been made to investigate the dynamic cointegration and causality relationships between global mean sea level (GMSL) and its determinants. Also another purpose has been made to examine empirically the short-run and long-run effects of climate change, carbon dioxide emissions, energy consumption, trade openness and urbanization on global mean sea level based on the time series data from 1970-2019. From the Augmented Dickey-Fuller (ADF), Phillips-Perron (PP) and Kwiatkowski-Phillips-Schmidt-Shin (KPSS) tests results it is found that all the variables are integrated of order one i.e. I(1). From the bounds test approach, it is found that there exits only one cointegration relationship when GMSL is the dependent variable. From the Granger causality test results of VEC model, it is found that the short-run unidirectional causalities are running from carbon dioxide emissions and energy consumption to global mean sea level, from energy consumption and trade openness to carbon dioxide emissions and from trade openness to energy consumption. It has also been found that the error correction term is statistically significant at any significance level when global mean sea level is treated as endogenous variable indicating that there exists a long-run relationship among the variables in the form of Equation (1). It has also been found that in the short-run the variables temperature, carbon dioxide emissions, and urbanization have significant positive effects while energy consumption and trade openness have significant negative effects on global mean sea level at any significance level. The coefficient of ECM (-1) is statistically significant at any significance level, indicates that speed of adjustment for short-run to research in the long-run equilibrium is statistically significant and within the first year, when global mean sea level is above or below its equilibrium level, it adjusts 66.52%. It has also been found that in the long-run the variables temperature, carbon dioxide emissions, and urbanization have significant positive effects on global mean sea level at any significance level but the variable energy consumption has significant negative effects at 5% significance level. It is also found that over time higher temperature, and carbon dioxide emissions will increase global mean sea level rapidly. The CUSUM and CUSUMSQ tests results support that the VEC model is stable and can be applied for policy formulation and decision making purposes.

Global Mean Sea Level, Climate Change, Short-Run and Long-Run Effects, Unit Root Tests, Cointegration and Granger Causality Tests

Hossain, M. (2021) Global Mean Sea Level Nexus Climate Change: A Dynamic Cointegration and Causality Analyses. Low Carbon Economy, 12, 151-172. doi: 10.4236/lce.2021.124008.