Dynamic impact of household consumption on its CO2 emissions in Malaysia

Abstract

This article aims to measure the dynamic impact of household consumption (final household consumption expenditure, LHC) on CO 2 emission from household's energy consumption in Malaysia from 1971 to 2010. The estimation of autoregressive distributed lag (ARDL) bounds test confirms a non-monotonic relationship between LHC and residential CO 2 emission. In the long run, there is a positive relationship between LHC and CO 2 emission as well as a negative relationship between quadratic forms of LHC and CO 2 emission which indicates the existence of an inverted U-shaped relationship between these two variables. The analysis also found a similar relationship in both the short and long run. To confirm the non-monotonous relationship, the U test of Sasabuchi-LindMehlum (2010) approach has followed to obtain the sufficient conditions for the existence of inverted U relationship. Moreover, the U test of Sasabuchi-Lind-Mehlum (2010) found that CO 2 emission increases with increasing LHC up to 6.5 units, but it declines with an additional increase of LHC which is also found by the ARDL model. However, the existence of environmental Kuznets curve implies that in the long run, household CO 2 emission declines with the additional increase of household consumption in the Malaysian economy.

Remittance inflows affect the ecological footprint in BICS countries: do technological innovation and financial development matter?

“…Similarly, Töbelmann and Wendler (2020) found an adverse impact of technological innovations on environmental degradation due to increases in the usage of renewable energy in the energymix structure and also improve environmental quality. Many studies have explored the relationship between technological innovations and environmental degradation across the globe and found a negative influence on environmental degradation (Chen and Lee 2020; Yu and Du 2019; Brandão Santana et al 2015;Zhou et al 2016;Gerlagh 2007;Sagar and Holdren 2002;Canadell et al 2007;Sohag et al 2015;Kverndokk et al 2004;Costantini et al 2017;Ang 2009;Fei et al 2014). Other studies explored that technological innovations may degrade the environmental quality due to a lack of research and development (R&D) investment so the desired level of TE has not been attained so for Cheng et al 2019, Gu and Wang (2018), Kivyiro and Arminen (2014), and Yongping 2011).…”

“…Technological innovation (TE) is one of the most authentic ways to reduce environmental degradation and also improve economic growth (Chen and Lee 2020;Yu and Du 2019;Brandão Santana et al 2015;Zhou et al 2016;Gerlagh 2007;Canadell et al 2007;Sohag et al 2015). The 12th BRICS summit was held on November 17, 2020, virtually meeting due to the coronavirus disease 2019 (COVID-19) pandemic and has done many agreements in the field of science, technology, and innovation sectors.…”

“…The 12th BRICS summit was held on November 17, 2020, virtually meeting due to the coronavirus disease 2019 (COVID-19) pandemic and has done many agreements in the field of science, technology, and innovation sectors. 2 High TE could lead to faster implementation of renewable energy to meet the energy demand and change the structure of energy utilization, i.e., the conventional energy source to clean energy source (Sohag et al 2015). The COVID-19 pandemic has enhanced tentatively and burdens on organizations/firms and households universally.…”

Investigating the relevance of Environmental Kuznets curve hypothesis in Saudi Arabia: towards energy efficiency and minimal carbon dioxide emission

“…A similar report was published by Pao and Tsai ( 2011 ) for Brazil, Alam et al ( 2017 ) for India, Lotfalipour et al ( 2010 ) for Iran, and Ang ( 2008 ) and Azlina and Mustapha ( 2012 ) for Malaysia. However, several studies have reported conflicting results, claiming that the relation between CO 2 emissions and production scale depicts an inverted U-shaped EKC for upper-middle-income and high-income countries (Al-Mulali et al 2015 ), Italy and Denmark (Ozturk and Acaravci 2010 ), Tunisia (Shahbaz et al 2014 ), Malaysia (Saboori et al 2012 ; Sohag et al 2015 ).…”

CO2 Emissions in China’s Yangtze River Economic Zone: A Dynamic Vector Autoregression Approach

“…The last is econometric models. The ARDL model was applied by Sohag et al [19] to explore the effect of Malaysia's resident consumption structure on carbon emissions. The stochastic copula autoregressive model was used by Marimoutou and Soury [20] to study the impact of energy price on CO 2 emissions.…”