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Economic Development, Globalization, Political Risk and CO2 Emission: The Case of Vietnam KCI 등재 SCOPUS

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  • URLhttps://db.koreascholar.com/Article/Detail/403125
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한국유통과학회 (Korea Distribution Science Association)
초록

This study investigates the dynamic effects of economic development, international cooperation, electricity consumption, and political risk on the escalation of CO2 emission in Vietnam. We adopted autoregressive distributed lag model and Granger causality method to examine the interaction between CO2 and various economic and political factors, including foreign direct investment, trade openness, economic growth, manufacture, electricity consumption, and political risk in Vietnam since the economic revolution in 1986. The findings reflect opposite influence between these factors and the level of CO2 in the intermediate and long-term durations. Accordingly, foreign direct investment and CO2 emission have a bidirectional relationship, in which foreign direct investment accelerates short-term CO2 emission, but reduces it in the long run through an interactive mechanism. Moreover, economic development increases the volume of CO2 emission in both short and long run. There was also evidence that political risk has a negative effect on the environment. Overall, the findings confirm lasting negative environmental effects of economic growth, trade liberalization, and increased electricity consumption. These factors, with Granger causality, mutually affect the escalation of CO2 in Vietnam. In order to control the level of CO2, more efforts are required to improve administrative transparency, attract high-quality foreign investment, and decouple the environment from economic development.

목차
Abstract
1. Introduction
2. Literature Review
3. The ARDL Approach and the GrangerCausality Analysis
    3.1. Modeling Procedure
    3.2. Variables Selection and Data Description
    3.3. Model Specification
4. The Results and Discussions
    4.1. The Result of the Unit Root Test
    4.2. The Cointegration Test Results
    4.3. The Long-Run and Short-Term ConnectionsAmong Variables
    4.4. Granger Causality in VECM and ImpulseResponse Analysis
5. Conclusions
References
저자
  • Thi Van VU(Institute of Industrial Economics, School of Business, Hohai University, Nanjing, Jiangsu, China.)
  • De Chun HUANG(Institute of Industrial Economics, School of Business, Hohai University, Nanjing, Jiangsu, China) Corresponding Author