ArticleEnvironmental science and pollution research international2020
The effects of total factor of productivity, natural resources and green taxation on CO
Article in Environmental science and pollution research international, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed, 58 citations in OpenAlex.
- Ecological footprint in Bangladesh: Identifying the intensity of economic complexity and natural resources.Heliyon · 2023Article
- Article
- Regional Differences and Convergence of Inter-Provincial Green Total Factor Productivity in China under Technological Heterogeneity.International journal of environmental research and public health · 2022Article
- Impact of innovation in renewable energy generation, transmission, or distribution-related technologies on carbon dioxide emission in the USA.Environmental science and pollution research international · 2022Article
- Do international collaborations in environmental-related technology development in the U.S. pay off in combating carbon dioxide emissions? Role of domestic environmental innovation, renewable energy consumption, and trade openness.Environmental science and pollution research international · 2022Article
- A critical review of the current research mainstreams and the influencing factors of green total factor productivity.Environmental science and pollution research international · 2021Review
- The environmental Kuznets curve hypothesis for Bangladesh: the importance of natural gas, liquefied petroleum gas, and hydropower consumption.Environmental science and pollution research international · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 4 institutions in 3 countries.
Funding
Abstract
This study attempts to investigate the environment cleanness between the total factor productivity, natural resources and green taxation on Malaysia's clean environment. Using the environmental Kuznets curve (EKC) hypothesis, this study employs the bootstrap quantile estimates based on the annual data series covering the period of 1970-2018 to analyse the quantile effect factors affecting environment cleanness in Malaysia. The empirical estimates of this study reject the EKC hypothesis throughout the quantile levels, while the green taxation shows a negative sign which indicated government fiscal policies are reducing carbon emission in the upper quantiles. There is also homogeneity slope equality effect between total factor of productivity and green taxation on carbon emissions in the middle and upper quantile levels, while natural resources are indication heterogeneity effect on all quantile levels. From the policy point of view, if Malaysia wants to get environment cleanness, there is a need for comprehensive policies of total factor of productivity with environment innovation-friendly and technological improvement in all major economic sectors of the country.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.