Hari Nugroho

Economic Growth and Greenhouse Gas Emissions in Asia: A Dynamic Panel Analysis Across Income Groups

Introduction

Economic growth and greenhouse gas emissions in asia: a dynamic panel analysis across income groups. Analyzes economic growth and greenhouse gas emissions in 41 Asian countries (1990-2022) across income groups using dynamic panel GMM. Reveals varied drivers and calls for tailored environmental policies.

Abstract

Research Originality: This study contributes to environmental economics by examining the relationship between economic growth and greenhouse gas emissions across Asian countries, while accounting for differences in income levels. Using a dynamic STIRPAT framework, the analysis also incorporates urbanization, energy intensity, and carbon intensity to understand how emission drivers vary across stages of development. Research Objectives: The study aims to explore the dynamic link between economic growth and greenhouse gas emissions and to identify how demographic and technological factors influence emission patterns in lower-middle-, upper-middle-, and high-income Asian economies. Research Methods: The analysis uses panel data from 41 Asian countries during 1990–2022 and applies a dynamic panel estimation method, the two-step System Generalized Method of Moments (System-GMM). Empirical Results: Economic growth and urbanization generally increase greenhouse gas emissions. However, the main drivers differ by income level. In lower-middle-income countries, emissions are mainly driven by economic growth and carbon intensity. In upper-middle-income countries, urbanization and energy intensity play a larger role, while in high-income countries, the link between growth and emissions becomes weaker. Implications: These findings suggest that environmental policies should be tailored to each stage of economic development. JEL Classification: C23, Q56, O44, Q43

Review

This study offers a timely and relevant contribution to the environmental economics literature by investigating the intricate relationship between economic growth and greenhouse gas emissions in Asia, a region characterized by significant economic dynamism and environmental challenges. The research's originality lies in its dynamic panel analysis, which adeptly accounts for income-level disparities across 41 Asian countries from 1990–2022. By integrating a dynamic STIRPAT framework and employing the robust two-step System Generalized Method of Moments (System-GMM), the authors are well-positioned to uncover how demographic and technological factors influence emission patterns, providing a nuanced understanding that moves beyond aggregated regional analyses. This comprehensive approach promises valuable insights into the heterogeneous drivers of emissions across different stages of economic development. The methodological rigor of employing System-GMM is a significant strength, effectively addressing potential endogeneity and dynamic relationships inherent in such macroeconomic panels. The study's objectives are clearly defined, aiming to dissect the dynamic link between growth and emissions, while also identifying the roles of urbanization, energy intensity, and carbon intensity within lower-middle-, upper-middle-, and high-income Asian economies. The empirical results reveal crucial differentiations: while economic growth and urbanization generally escalate emissions, their primary drivers vary considerably by income group. Specifically, lower-middle-income countries are propelled by economic growth and carbon intensity, upper-middle-income countries by urbanization and energy intensity, and high-income countries exhibit a weaker growth-emission nexus. These findings underscore the importance of disaggregated analysis for understanding environmental impacts. The implications drawn from this research are particularly salient for policy formulation, advocating for environmental strategies that are precisely tailored to the specific stage of economic development. This targeted policy recommendation is a direct and valuable outcome of the study's nuanced findings, challenging one-size-fits-all approaches. While the study provides a robust macro-level analysis, future research could potentially delve into specific country case studies within each income group to provide qualitative depth and examine the role of institutional quality, green technology adoption rates, or international environmental agreements more explicitly. Nevertheless, this paper makes a substantial contribution by providing a data-driven, methodologically sound framework for understanding the complex interplay of economic development and environmental degradation in a critical global region, offering actionable insights for policymakers.

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