The Influx of Green Innovation and Green Investment in South Asia: Sustenance Efforts Impacting Environmental Protection
Abstract/Description
As environmental challenges intensify, the South Asian region characterized by rapid industrialization, high population density, and fragile ecological systems faces a growing urgency to transition toward sustainable development pathways. This study investigates the role of green finance in mitigating environmental pollution while promoting sustainable growth in seven South Asian countries: Pakistan, India, Bangladesh, Bhutan, Maldives, Nepal, and Sri Lanka. Covering the period from 2000 to 2022, the analysis centers on evaluating both the short-run and long-run dynamics between carbon dioxide (CO₂) emissions and several key economic and environmental indicators.
Environmental pollution is proxied by CO₂ emissions (in kilotons), while natural resource depletion (NR), expressed as a percentage of Gross National Income (GNI), serves as an indicator of ecological stress. Green finance (GIFN) is operationalized as expenditure in US dollars toward environmental sustainability, environmental-friendly investments (EFI) are measured through investments in renewable energy, and green technology innovation (GTI) is captured via the number of environment-related patents filed. Additionally, GDP per capita, the Human Development Index (HDI), and population growth are incorporated as control variables. All data are sourced from the World Development Indicators (WDI) and the OECD.
The empirical methodology applies the Panel Auto Regressive Distributed Lag (ARDL) model, which allows for the distinction between short-run fluctuations and long-run equilibrium relationships across the selected countries. Three estimators are utilized: Pooled Mean Group (PMG), Mean Group (MG), and Dynamic Fixed Effects (DFE). These estimators facilitate cross-country comparisons while accounting for potential heterogeneity in economic structures and environmental responses. Stationarity of the panel data series is tested using both first-generation (Levin, Lin & Chu [LLC]; Im, Pesaran & Shin [IPS]) and second-generation unit root tests (ADF-Fisher and PP-Fisher).
The results of the unit root tests reveal a mix of I (0) and I (1) series, validating the appropriateness of the panel ARDL framework. The Hausman test is employed to determine the most efficient estimator, with results indicating that the PMG estimator is preferable due to its efficiency in long-run estimation under homogeneity constraints. The error correction term (ECT) in the PMG model is negative and statistically significant, confirming the existence of long-run cointegration among the variables.
Empirical findings reveal that green finance and green technology innovation have a significant negative effect on CO₂ emissions in the long run, indicating their critical role in reducing environmental pollution. Environmental-friendly investments also contribute positively to emission reductions, though with varying intensities across countries. GDP per capita exhibits a nonlinear relationship with CO₂ emissions, reflecting the Environmental Kuznets Curve (EKC) hypothesis in some countries. HDI is found to correlate negatively with emissions, suggesting that improvements in education, health, and standard of living may foster environmentally conscious behavior. Population growth, however, exerts upward pressure on emissions, underscoring demographic challenges to sustainability.
In the short run, results from the MG estimator reveal heterogeneous impacts across countries, influenced by varying policy implementations, institutional capacities, and stages of economic development. The findings underscore that while green finance mechanisms are effective, their outcomes are context-dependent and moderated by socio-economic factors.
This study contributes to the literature by integrating environmental, financial, and developmental perspectives using a comprehensive econometric approach. It provides actionable insights for policymakers, financial institutions, and environmental agencies aiming to leverage green finance and innovation for sustainable development. The evidence supports the formulation of region-specific green finance strategies, investment in renewable energy technologies, and reforms in governance to enhance institutional readiness for climate action. Ultimately, the study affirms that aligning financial flows with environmental goals is not only desirable but imperative for South Asia’s low-carbon transition and the achievement of long-term sustainability targets.
Keywords
Green Innovation, Green Investment, South Asia, Environmental Protection
Track
Finance
Session Number/Theme
Finance - Session III
Session Chair
Dr. Javed Iqbal
Start Date/Time
14-6-2025 10:55 AM
End Date/Time
14-6-2025 12:35 PM
Location
MCC 10 Ground Floor, AMAN CED Building
Recommended Citation
Shamim, D., & Omer, M. (2025). The Influx of Green Innovation and Green Investment in South Asia: Sustenance Efforts Impacting Environmental Protection. IBA SBS 4th International Conference 2025. Retrieved from https://ir.iba.edu.pk/sbsic/2025/program/113
COinS
The Influx of Green Innovation and Green Investment in South Asia: Sustenance Efforts Impacting Environmental Protection
MCC 10 Ground Floor, AMAN CED Building
As environmental challenges intensify, the South Asian region characterized by rapid industrialization, high population density, and fragile ecological systems faces a growing urgency to transition toward sustainable development pathways. This study investigates the role of green finance in mitigating environmental pollution while promoting sustainable growth in seven South Asian countries: Pakistan, India, Bangladesh, Bhutan, Maldives, Nepal, and Sri Lanka. Covering the period from 2000 to 2022, the analysis centers on evaluating both the short-run and long-run dynamics between carbon dioxide (CO₂) emissions and several key economic and environmental indicators.
Environmental pollution is proxied by CO₂ emissions (in kilotons), while natural resource depletion (NR), expressed as a percentage of Gross National Income (GNI), serves as an indicator of ecological stress. Green finance (GIFN) is operationalized as expenditure in US dollars toward environmental sustainability, environmental-friendly investments (EFI) are measured through investments in renewable energy, and green technology innovation (GTI) is captured via the number of environment-related patents filed. Additionally, GDP per capita, the Human Development Index (HDI), and population growth are incorporated as control variables. All data are sourced from the World Development Indicators (WDI) and the OECD.
The empirical methodology applies the Panel Auto Regressive Distributed Lag (ARDL) model, which allows for the distinction between short-run fluctuations and long-run equilibrium relationships across the selected countries. Three estimators are utilized: Pooled Mean Group (PMG), Mean Group (MG), and Dynamic Fixed Effects (DFE). These estimators facilitate cross-country comparisons while accounting for potential heterogeneity in economic structures and environmental responses. Stationarity of the panel data series is tested using both first-generation (Levin, Lin & Chu [LLC]; Im, Pesaran & Shin [IPS]) and second-generation unit root tests (ADF-Fisher and PP-Fisher).
The results of the unit root tests reveal a mix of I (0) and I (1) series, validating the appropriateness of the panel ARDL framework. The Hausman test is employed to determine the most efficient estimator, with results indicating that the PMG estimator is preferable due to its efficiency in long-run estimation under homogeneity constraints. The error correction term (ECT) in the PMG model is negative and statistically significant, confirming the existence of long-run cointegration among the variables.
Empirical findings reveal that green finance and green technology innovation have a significant negative effect on CO₂ emissions in the long run, indicating their critical role in reducing environmental pollution. Environmental-friendly investments also contribute positively to emission reductions, though with varying intensities across countries. GDP per capita exhibits a nonlinear relationship with CO₂ emissions, reflecting the Environmental Kuznets Curve (EKC) hypothesis in some countries. HDI is found to correlate negatively with emissions, suggesting that improvements in education, health, and standard of living may foster environmentally conscious behavior. Population growth, however, exerts upward pressure on emissions, underscoring demographic challenges to sustainability.
In the short run, results from the MG estimator reveal heterogeneous impacts across countries, influenced by varying policy implementations, institutional capacities, and stages of economic development. The findings underscore that while green finance mechanisms are effective, their outcomes are context-dependent and moderated by socio-economic factors.
This study contributes to the literature by integrating environmental, financial, and developmental perspectives using a comprehensive econometric approach. It provides actionable insights for policymakers, financial institutions, and environmental agencies aiming to leverage green finance and innovation for sustainable development. The evidence supports the formulation of region-specific green finance strategies, investment in renewable energy technologies, and reforms in governance to enhance institutional readiness for climate action. Ultimately, the study affirms that aligning financial flows with environmental goals is not only desirable but imperative for South Asia’s low-carbon transition and the achievement of long-term sustainability targets.
