An empirical investigation between CO2 emission, energy consumption, trade liberalization and economic growth: A case of Kuwait
By Syed Khurram Arslan Wasti, Shumaila Waqar Zaidi. 2020
163 citations recorded by the source corpus.
Abstract The purpose of the present study is to investigate the link among CO2 emissions, energy consumption, gross domestic product, and trade liberalization as related to Kuwait. The study used annual data, starting from 1971 to 2017, which was obtained from a world development indicator of the World Bank. For the empirical analysis, the study adopted Augmented Dicky Fuller and Phillips-Perron methods to review stationarity among the data sets. Their results explained a mixed trend, some variables followed the I (1) process, and few are I (0). Based on the findings, a well-defined Autoregressive Distributed Lag Model was applied to the data sets and the outcome was in support of the long and short-run relationship between variables. Carbon dioxide and energy consumption accelerate economic growth; an increase in CO2 emission also plays a significant role in increasing energy consumption. Furthermore, the Granger Causality test shows evidence of bi-directional causality existing between CO2 emissions and energy consumption. A unidirectional causality is running from the gross domestic product to CO2 emissions and energy consumption to trade liberalization.
Subfields: Economics and Econometrics, Pollution, Renewable Energy, Sustainability and the Environment
View Paper: https://www.semanticscholar.org/paper/7a741f8eca03f8db5646c06fc87758ae197cec82
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In Economics and Econometrics
In Pollution
In Renewable Energy, Sustainability and the Environment
Citations in the corpus
- Does the inflow of remittances and energy consumption increase CO2 emissions in the era of globalization? A global perspective (2020, methodology): “Wasti and Zaidi (2020) examine the influence of trade openness and economic growth on CO2 emissions in Kuwait based on Augmented Dicky Fuller and the Phillips-Perron method and the annual time series data for the period of 1971-2017.”