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How Can Blue Economy Contribute to Inclusive Growth and Ecosystem Resources in Asia? A Comparative analysis of Economic, Environmental, and Social Indicators Among 19 Asian Cooperation Dialogue Members
Geng, B.; Wu, D.; Zhang, C.; Xie, W.; Mahmood, M.A.; Ali, Q. How Can the Blue Economy Contribute to Inclusive Growth and Ecosystem Resources in Asia? A Comparative Analysis. Sustainability2024, 16, 429.
Geng, B.; Wu, D.; Zhang, C.; Xie, W.; Mahmood, M.A.; Ali, Q. How Can the Blue Economy Contribute to Inclusive Growth and Ecosystem Resources in Asia? A Comparative Analysis. Sustainability 2024, 16, 429.
Geng, B.; Wu, D.; Zhang, C.; Xie, W.; Mahmood, M.A.; Ali, Q. How Can the Blue Economy Contribute to Inclusive Growth and Ecosystem Resources in Asia? A Comparative Analysis. Sustainability2024, 16, 429.
Geng, B.; Wu, D.; Zhang, C.; Xie, W.; Mahmood, M.A.; Ali, Q. How Can the Blue Economy Contribute to Inclusive Growth and Ecosystem Resources in Asia? A Comparative Analysis. Sustainability 2024, 16, 429.
Abstract
This study investigates how a range of economic, environmental, and social indicators have influenced the concept of inclusive growth in 19 member countries of the Asian Cooperation Dialogue over the period spanning from 1995 to 2021. To analyze these relationships, the research employs the Driscoll Kraay's Standard Errors regression technique, designed to account for factors such as cross-sectional dependence, hetero-scedasticity, and autocorrelation within the data. Furthermore, various preliminary tests were conducted to assess the data for cross-sectional dependence, slope heterogeneity, heteroscedasticity, and autocorrelation. Additionally, the Westerlund cointegration test was employed to evaluate the potential long-term equilibrium relationships among the variables. The findings reveal that the influence of independent variables on the dependent variable, which in this case is the level of inclusive growth (ING), differs significantly among three distinct income categories: lower-middle-income countries (LMYCs), upper-middle-income countries (UMYCs), and high-income countries (HYCs). Notably, the results underscore the overall statistical significance and robust fit of the regression model for all three income groups. One of the primary contribu-tions of this research is the provision of empirical evidence concerning the role played by fishery and aquaculture production in fostering inclu-sive growth in the Asian context. This research also highlights the trade-offs between economic development and environmental sustainability in terms of trade openness, agriculture, forestry and fishing, ecological footprint, and renewable energy utilization. Enhancing inclusive growth in Asia requires improving fishery and aquaculture management, diversifying economic activities, reducing ecological footprint, and increasing renewable energy utilization. The paper suggests some future work directions for extending the analysis to other regions and indicators, as well as incorporating dynamic panel data models and causality tests. The paper also suggests some policy implications for fostering inclusive growth in Asia through regional cooperation, capacity building, technology transfer and green financing.
Keywords
Inclusive growth; economic; environmental; and social indicators; asian cooperation dialogue; Driscoll Kraay’s standard errors regression; fishery and aquaculture production; tradeoffs between development and sustainability; renewable energy utilization
Subject
Business, Economics and Management, Econometrics and Statistics
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
