2017InTech eBooksOpen access

Export, Import, Economic Growth, and Carbon Emissions in Bangladesh: A Granger Causality Test under VAR (Restricted) Environment

Farhana Ferdousi, Md. Qamruzzaman

Open full text 12 citations

Abstract

Purpose: This paper examines the causal and cointegrating relationship between economic growth and CO2 emissions in a multivariate framework by including imports and exports as others control variables for an emerging economy like Bangladesh. Design/methodology: The paper applied vector error correction model (VECM) Granger casualty test for assessing the direction of causality and variance decomposition to explain the magnitude of the forecast error variance determined by the shocks to each of the explanatory variables over time. LB (Q-stat) test is to determine data properties and WILD test is to assess short run causality from independent variables to dependent variable. Findings: The study results revealed that variables are integrated in the same order. The results of Johansen Juselius cointegration tests indicate that there is a unique long-term or equilibrium relationship among variables. Again, Granger causality test revealed that short run unidirectional causality are running from carbon dioxide emission to exports, GDP to import, and from import to carbon dioxide emissions. Variance decomposition function shows that the positive shocks in error term will produce positive effects on all variables in the long run. Therefore, a concerted effort from all national and international stakeholders, i.e., enterprises, consumers, and governments are expected to take measures to offset carbon emission and pursue environment-friendly trade plan for better managing the cities and regions in order to fight against global warming and climate change risk.

Open-access reader

About this research paper

What this paper is about

Purpose: This paper examines the causal and cointegrating relationship between economic growth and CO2 emissions in a multivariate framework by including imports and exports as others control variables for an emerging economy like Bangladesh. Design/methodology: The paper applied vector error correction model (VECM) Granger casualty test for assessing the direction of causality and variance decomposition to explain the magnitude of the forecast error variance determined by the shocks to each of the explanatory variables over time. LB (Q-stat) test is to determine data properties and WILD test is to assess short run causality from independent variables to dependent variable. Findings: The study results revealed that variables are integrated in the same order. The results of Johansen Juselius cointegration tests indicate that there is a unique long-term or equilibrium relationship among variables. Again, Granger causality test revealed that short run unidirectional causality are running from carbon dioxide emission to exports, GDP to import, and from import to carbon dioxide emissions. Variance decomposition function shows that the positive shocks in error term will produce positive effects on all variables in the long run. Therefore, a concerted effort from all national and international stakeholders, i.e., enterprises, consumers, and governments are expected to take measures to offset carbon emission and pursue environment-friendly trade plan for better managing the cities and regions in order to fight against global warming and climate change risk.

Why it matters

OpenAlex reports 12 citations for this work. Citation counts describe recorded attention and do not establish research quality.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

Purpose: This paper examines the causal and cointegrating relationship between economic growth and CO2 emissions in a multivariate framework by including imports and exports as others control variables for an emerging economy like Bangladesh. Design/methodology: The paper applied vector error correction model (VECM) Granger casualty test for assessing the direction of causality and variance decomposition to explain the magnitude of the forecast error variance determined by the shocks to each of the explanatory variables over time. LB (Q-stat) test is to determine data properties and WILD test is to assess short run causality from independent variables to dependent variable. Findings: The study results revealed that variables are integrated in the same order. The results of Johansen Juselius cointegration tests indicate that there is a unique long-term or equilibrium relationship among variables. Again, Granger causality test revealed that short run unidirectional causality are running from carbon dioxide emission to exports, GDP to import, and from import to carbon dioxide emissions. Variance decomposition function shows that the positive shocks in error term will produce positive effects on all variables in the long run. Therefore, a concerted effort from all national and international stakeholders, i.e., enterprises, consumers, and governments are expected to take measures to offset carbon emission and pursue environment-friendly trade plan for better managing the cities and regions in order to fight against global warming and climate change risk.

Key concepts: Variance decomposition of forecast errors, Granger causality, Cointegration, Johansen test, Error correction model, Vector autoregression, Econometrics, Economics

Related papers

Back to paper searchBrowse research topicsOriginal source
Export, Import, Economic Growth, and Carbon Emissions in Bangladesh: A Granger Causality Test under VAR (Restricted) Environment — Research Paper | ScholarLens