Causal nexus between energy consumption and carbon dioxide emission for Malaysia using maximum entropy bootstrap approach

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• 作者：Sehrish Gul ; Xiang Zou ; Che Hashim Hassan…
• 关键词：Carbon dioxide emission ; Energy consumption ; Maximum entropy bootstrap approach ; Malaysia ; Code ; Q43
• 刊名：Environmental Science and Pollution Research
• 出版年：2015
• 出版时间：December 2015
• 年：2015
• 卷：22
• 期：24
• 页码：19773-19785
• 全文大小：748 KB
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• 作者单位：Sehrish Gul (1)
  Xiang Zou (2)
  Che Hashim Hassan (3)
  Muhammad Azam (4)
  Khalid Zaman (5)
  
  1. Department of Management Sciences, COMSATS Institute of Information Technology, Abbottabad, Pakistan
  2. Institute of Graduate Studies, University of Malaya, 50603, Kuala Lumpur, Malaysia
  3. Unit for the Enhancement of Academic Performance, University of Malaya, Lembah Pantai, 50603, Kuala Lumpur, Malaysia
  4. School of Economics, Finance and Banking College of Business, University Utara Malaysia, Sintok, Malaysia
  5. Department of Economics, University of Sargodha, Canal Campus, Lahore, Pakistan
  
• 刊物类别：Earth and Environmental Science
• 刊物主题：Environment
  Environment
  Atmospheric Protection, Air Quality Control and Air Pollution
  Waste Water Technology, Water Pollution Control, Water Management and Aquatic Pollution
  Industrial Pollution Prevention
  
• 出版者：Springer Berlin / Heidelberg
• ISSN：1614-7499

文摘

This study investigates the relationship between energy consumption and carbon dioxide emission in the causal framework, as the direction of causality remains has a significant policy implication for developed and developing countries. The study employed maximum entropy bootstrap (Meboot) approach to examine the causal nexus between energy consumption and carbon dioxide emission using bivariate as well as multivariate framework for Malaysia, over a period of 1975-013. This is a unified approach without requiring the use of conventional techniques based on asymptotical theory such as testing for possible unit root and cointegration. In addition, it can be applied in the presence of non-stationary of any type including structural breaks without any type of data transformation to achieve stationary. Thus, it provides more reliable and robust inferences which are insensitive to time span as well as lag length used. The empirical results show that there is a unidirectional causality running from energy consumption to carbon emission both in the bivariate model and multivariate framework, while controlling for broad money supply and population density. The results indicate that Malaysia is an energy-dependent country and hence energy is stimulus to carbon emissions. Keywords Carbon dioxide emission Energy consumption Maximum entropy bootstrap approach Malaysia