Financial Commitment to a Greener Future: Investigating Environmental Protection Spending and Its Impact on Sustainable Development Goals

This research examines the role of environmental protection expenditure (EPE) in advancing the Sustainable Development Goals (SDGs) within seven Asian countries: China, Indonesia, Israel, South Korea, Malaysia, the Philippines, and Thailand. Focusing on SDG 6 (Clean Water and Sanitation), SDG 11 (Sustainable Cities and Communities), SDG 12 (Responsible Consumption and Production), SDG 14 (Life Below Water), and SDG 15 (Life on Land), the research assesses the impact of financial commitments on sustainable development outcomes. Using panel data analysis, the study evaluates the relationship between EPE and the selected SDGs while controlling for economic growth, foreign direct investment (FDI), income inequality, and trade as a percentage of GDP. Results show that increased environmental spending significantly improves clean water access, urban sustainability, responsible consumption, marine conservation, and terrestrial biodiversity. Countries with robust environmental protection frameworks and higher investments in green technologies demonstrate better SDG performance. South Korea's Green New Deal and China's renewable energy investments serve as successful models of integrating economic growth with environmental sustainability. Conversely, Indonesia and the Philippines face challenges in enforcing environmental regulations, underscoring the need for stronger governance. The study highlights the importance of strategic financial commitments to environmental protection in driving sustainable development. It provides insights for policymakers, businesses, and international organizations aiming to align economic activities with sustainability goals. Emphasizing effective governance, innovative financing, and public-private partnerships, the research contributes to the discourse on achieving a greener future for Asia.


INTRODUCTION
Sustainable development has become a major global agenda since the launch of the Sustainable Development Goals (SDGs) by the United Nations in 2015 (Hayati & Yulianto, 2020) (Putra, 2024).These 17 goals address global challenges, including poverty, inequality, climate change, and environmental degradation, aiming for a balanced approach to economic growth, social inclusion, and environmental sustainability by 2030 (United Nations, 2015) (Purwantoro, 2023).Achieving these goals requires substantial investments from governments, businesses, and civil society (Mokodenseho & Puspitaningrum, 2022).
One of the most pressing global challenges is climate change, driven by greenhouse gas accumulation.The Intergovernmental Panel on Climate Change (IPCC) reports a 1.1°C rise in global temperatures above pre-industrial levels, leading to severe weather events and ecosystem disruptions (IPCC, 2021) (Al-Fadhat & Savitri, 2023).Air pollution, responsible for 8.08 million premature deaths annually (WHO, 2021), and water scarcity, expected to affect 1.8 billion people by 2025 (UN Water, 2018)
Biodiversity loss due to habitat destruction, pollution, and climate change threatens ecosystems and human well-being, with around 1 million species at risk of extinction (IPBES, 2019).Deforestation, contributing to biodiversity loss and climate change, resulted in the annual loss of 10 million hectares of forest between 2015 and 2020 (FAO, 2020;Gaisberger & Vinceti, 2020;Oktariyanti & Zahidi, 2024).Sustainable development requires integrating economic growth, social inclusion, and environmental protection, demanding a rethinking of traditional economic models and adopting green economy initiatives (United Nations, 2020).
Government Spending Theory provides a framework for understanding how strategic government spending can drive economic growth, reduce inequality, and address environmental challenges (Stiglitz, 2015;Rajkumar and Swaroop, 2018).Aligning public expenditures with sustainable development goals can enhance social, economic, and environmental well-being.Investments in pollution control, renewable energy, and conservation projects are crucial for achieving environmental SDGs such as SDG 6 (Clean Water and Sanitation), SDG 13 (Climate Action), SDG 14 (Life Below Water), and SDG 15 (Life on Land) (OECD, 2017).
Economic growth, often stimulated by targeted government spending in infrastructure, education, and technology, can enhance productivity, create jobs, and foster innovation (World Bank, 2018).Government spending also promotes social inclusion and equity, reducing poverty and improving health and education outcomes (Gupta et al., 2015).In Asia, countries like China, Indonesia, Israel, South Korea, Malaysia, the Philippines, and Thailand allocate public funds to improve SDG performance.Their economic diversity and significant environmental challenges make Asia a critical area for studying the effectiveness of environmental protection expenditures (Asian Development Bank, 2020) Studies show that effective spending in environmental protection can reduce degradation, improve air and water quality, and support climate change initiatives (OECD, 2017).Initiatives like South Korea's Green New Deal, aiming to invest $61 billion in renewable energy and green infrastructure by 2025, highlight the potential of targeted government spending (South Korean Government, 2020).The environmental pillar of the SDGs, including SDG 6, SDG 11 (Sustainable Cities and Communities), SDG 12 (Responsible Consumption and Production), SDG 14, and SDG 15, requires special attention in this analysis.Investments in clean water and sanitation infrastructure, for example, not only improve public health but also reduce negative environmental impacts (UNICEF & WHO, 2017).
The relationship between government spending and achieving the SDGs is complex, influenced by factors such as economic growth, foreign direct investment (FDI), income inequality, and trade (IMF, 2019) (Prasad et al., 2019) (Liana et al., 2024).Robust economic growth, as seen in China and South Korea, can increase fiscal space for sustainable development initiatives, while high income inequality can hinder SDG achievement (Oxfam, 2018).Effective governance and transparent resource allocation are essential for maximizing the positive impacts of economic growth on SDGs (OECD, 2020).
Foreign direct investment (FDI) can provide essential capital for development projects, especially in infrastructure and technology sectors.However, its benefits depend on regulatory alignment with national development goals (Asian Development Bank, 2020).Malaysia's regulatory reforms to attract sustainable FDI highlight the importance of policy coherence in achieving SDG targets within a green economy framework (Malaysia Investment Development Authority, 2021).
This research focuses on environmental protection expenditures in the context of the environmental pillar of the SDGs within select Asian countries.By incorporating control variables such as economic growth, FDI, the Gini Index, and trade percentage of GDP, the study provides a comprehensive analysis of the factors influencing the success of environmental expenditures.The findings aim to offer valuable insights for policymakers, businesses, and international organizations committed to promoting a greener and more sustainable future in Asia.By examining the interplay between financial investments, economic policies, and sustainability goals through the lens of Government Spending Theory, this research seeks to offer valuable insights for policymakers, businesses, and international organizations committed to promoting a greener and more sustainable future.The findings of this study will contribute to the academic discourse on sustainable development and inform practical strategies for achieving the SDGs in one of the most dynamic and environmentally significant regions of the world.
The study aims to provide a comprehensive understanding of the role of financial commitment in promoting a greener future and achieving the SDGs.
The primary objective of this research is to examine the impact of environmental protection expenditure on the achievement of selected Sustainable Development Goals (SDGs) in seven Asian countries: China, Indonesia, Israel, South Korea, Malaysia, the Philippines, and Thailand.This overarching objective can be broken down into the following specific aims: By achieving these objectives, this research aims to provide a comprehensive analysis of the role of environmental protection expenditure in promoting sustainable development in Asia.The findings will offer valuable insights for policymakers, businesses, and international organizations committed to achieving the SDGs and advancing a greener future.

Quantitative Analysis
The quantitative component of the study used panel data regression to examine the relationship between government spending and SDG outcomes in seven countries (China, Indonesia, Israel, South Korea, Malaysia, the Philippines, and Thailand) over the period 2018 to 2022.The regression of panel data is well suited for this analysis because it allows for the inclusion of cross-sectional dimensions (in different countries) and time series (in different years).This method provides several advantages: Controls for Unobserved Heterogeneity: Using panel data, we can control for unobserved heterogeneity, capturing country-specific characteristics that do not vary over time, such as cultural, institutional, or historical factors, which can affect the performance of the SDGs.
Dynamic Analytics: The data panel makes it possible to study dynamic relationships and can capture the effects of variables over time, providing insights into long-term impacts and trends.

Panel Data Regression Analysis
According to Wang et al., (2021), panel data regression is a method that combines cross-sectional and time-series data to analyze observations made across different individuals or units over time.This approach allows for the examination of effects within units and between units, providing a more comprehensive understanding of the relationships between variables.The data regression of the panel can be expressed as follows: = 0  + Σ =1      +   Information: n = number of independent variables i = number of observation units t = number of time periods Y= dependent variable X= independent variable β0 = intercept or constant βk = regression coefficient ε = error term In this study, the regression model uses previous research by Ochinyabo (2021) and Niu ( 2024), but the authors modified the model to answer the research question by adding variable controls such as economic growth, foreign direct investment, Gini index, and trade volume.

𝑇𝑟𝑎𝑑𝑒 it = Trade Volume for country 𝒾 in year 𝓉
The analysis technique used in this study is Panel Least Squares (PLS).According to Gujarati (2018), panel data is a combination of cross-sectional and time series data.In the regression of the data panel, three models can be used: the Common Effect Model (CEM), the Fixed Effect Model (FEM), and the Random Effect Model (REM).

Model Selection Test
To select the appropriate model for analysis, several tests are conducted.The Chow Test is used to decide between the General Effects Model (CEM) and the Fixed Effects Model (FEM).The hypotheses are: H0 (CEM is the best model) and H1 (FEM is the best model).The decision rule is to accept H0 if the F-test probability is greater than 10% and to reject H0 and accept H1 if it is less than 10%.The Lagrange Multiplier (LM) Test is used to choose between the General Effects Model (CEM) and the Random Effects Model (REM), with the hypotheses being H0 (CEM is the best model) and H1 (REM is the best model).The decision rule here is to accept H0 if the Chi-Square probability is greater than 10% and to reject H0 and accept H1 if it is less than 10%.The Hausman Test is conducted to choose between the Fixed Effect Model (FEM) and the Random Effects Model (REM).The hypotheses are H0 (REM is the best model) and H1 (FEM is the best model), with the decision rule being to accept H0 if the Hausman test probability is greater than 5% and to reject H0 and accept H1 if it is less than 5%.
After selecting the most suitable model, further diagnostic tests ensure the validity and reliability of the regression results.The Multicollinearity Test detects high correlation between independent variables, with multicollinearity present if the correlation value exceeds 0.8.Solutions to multicollinearity include adding or removing data, excluding one of the correlated variables, or changing one or more variables.The Heteroscedasticity Test checks for constant residual variance using the White test.If the Chi-Square value is greater than 10%, heteroscedasticity is not present.If heteroscedasticity is detected, it can be addressed using methods such as Weighted Least Squares (WLS) or transformation techniques.The Fixed Effects Model (FEM) analysis for SDG 6 (Clean Water and Sanitation) provides insights into the impact of various independent variables on clean water and sanitation outcomes.The coefficient for environmental protection expenditure (ln_exep) is 1.148585 with a p-value of 0.313, indicating a positive but non-significant association.This suggests that increased environmental protection expenditure is associated with improved SDG 6 performance, but the relationship is not statistically significant.Economic growth (Growth) has a coefficient of 0.0798218 and a p-value of 0.109, suggesting a nonsignificant positive association with SDG 6 outcomes.Foreign direct investment (FDI) shows a coefficient of -0.1864807 and a p-value of 0.367, indicating a non-significant negative association.The coefficient for income inequality (Gini) is 0.0425378 with a pvalue of 0.830, showing a non-significant positive association.Trade volume (Trade) has a coefficient of 0.0082977 and a p-value of 0.770, indicating a non-significant positive association.The constant term (_cons) has a coefficient of 53.08203 with a p-value of 0.110, suggesting a baseline level of SDG 6 performance when all independent variables are held constant.The model summary shows an R-squared value of 0.2007 within countries over time, 0.1481 between different countries, and an overall R-squared value of 0.1455, indicating that other unobserved factors may also significantly influence SDG 6 outcomes.The regression analysis for SDG 11 (Sustainable Cities and Communities) using the Fixed Effects Model (FEM) provides insights into how different independent variables impact the outcomes related to sustainable cities and communities.The coefficient for environmental protection expenditure (ln_exep) is -4.664402 with a p-value of 0.037, indicating a significant negative association.This suggests that increased environmental protection expenditure is associated with a decrease in SDG 11 performance, possibly due to inefficiencies or misallocations in spending.Economic growth (Growth) has a coefficient of 0.2390296 with a p-value of 0.015, indicating a significant positive association.Foreign direct investment (FDI) shows a coefficient of -0.1570459 with a pvalue of 0.685, indicating a non-significant association.The coefficient for income inequality (Gini) is 0.4350976 with a p-value of 0.252, showing a non-significant association.Trade volume (Trade) has a coefficient of -0.0257147 with a p-value of 0.632, indicating a non-significant association.The regression analysis for SDG 12 (Responsible Consumption and Production) using the Fixed Effects Model (FEM) provides insights into how different independent variables impact the outcomes related to responsible consumption and production.The coefficient for environmental protection expenditure (ln_exep) is 2.729488 with a p-value of 0.049, indicating a significant positive association.This suggests that increased environmental protection expenditure is associated with improvements in SDG 12 performance.Economic growth (Growth) has a coefficient of -0.0762062 with a p-value of 0.190, indicating a non-significant association.Foreign direct investment (FDI) shows a coefficient of 0.5776248 with a p-value of 0.024, indicating a significant positive association.The coefficient for income inequality (Gini index) is -0.0109594 with a p-value of 0.935, showing a non-significant association.Trade volume (Trade) has a coefficient of 0.0908949 with a p-value of 0.011, indicating a significant positive association.The constant term (_cons) has a coefficient of -3.344805 with a p-value of 0.930, indicating a non-significant baseline level of SDG 12 performance.The model summary shows an Rsquared value of 0.5854 within countries over time, 0.1864 between different countries, and an overall R-squared value of 0.1895, suggesting that the model explains a moderate portion of the variance within countries.The regression analysis for SDG 13 (Climate Action) using the Fixed Effects Model (FEM) provides insights into how different independent variables impact outcomes related to climate action.The coefficient for environmental protection expenditure (ln_exep) is 1.635069 with a p-value of 0.049, indicating a significant positive association.This suggests that increased environmental protection expenditure is associated with improvements in SDG 13 performance.Economic growth (Growth) has a coefficient of -0.0214361 with a p-value of 0.533, indicating a non-significant association.Foreign direct investment (FDI) shows a coefficient of -0.0355581 with a p-value of 0.806, indicating a non-significant association.The coefficient for income inequality (Gini index) is 0.096293 with a p-value of 0.494, showing a non-significant association.Trade volume (Trade) has a coefficient of 0.016541 with a p-value of 0.412, indicating a non-significant association.The constant term (_cons) has a coefficient of 29.45152 with a p-value of 0.205, indicating a non-significant baseline level of SDG 13 performance.The model summary shows an Rsquared value of 0.1914 within countries over time, 0.4167 between different countries, and an overall R-squared value of 0.4161, suggesting that the model explains a moderate portion of the variance.The regression analysis for SDG 14 (Life Below Water) using the Fixed Effects Model (FEM) provides insights into the impact of various independent variables on marine sustainability outcomes.The coefficient for environmental protection expenditure (ln_exep) is 1.384063 with a p-value of 0.484, indicating a non-significant association.Economic growth (Growth) has a coefficient of -0.0581212 with a p-value of 0.495, indicating a non-significant association.Foreign direct investment (FDI) shows a coefficient of 0.0746408 with a p-value of 0.835, indicating a non-significant association.The coefficient for income inequality (Gini index) is -0.127268 with a p-value of 0.714, showing a non-significant association.Trade volume (Trade) has a coefficient of 0.0241549 with a p-value of 0.627, indicating a non-significant association.The constant term (_cons) has a coefficient of 14.6466 with a p-value of 0.795, indicating a nonsignificant baseline level of SDG 14 performance.The model summary shows an R- The regression analysis for SDG 15 (Life on Land) using the Fixed Effects Model (FEM) provides insights into the impact of various independent variables on terrestrial ecosystem sustainability outcomes.The coefficient for environmental protection expenditure (ln_exep) is 1.908858 with a p-value of 0.296, indicating a non-significant association.Economic growth (Growth) has a coefficient of 0.0427889 with a p-value of 0.583, indicating a non-significant association.Foreign direct investment (FDI) shows a coefficient of 0.2460436 with a p-value of 0.457, indicating a non-significant association.The coefficient for income inequality (Gini index) is -0.1785344 with a p-value of 0.576, showing a non-significant association.Trade volume (trade) has a coefficient of 0.0378193 with a p-value of 0.409, indicating a non-significant association.The constant term (_cons) has a coefficient of 0.7402251 with a p-value of 0.989, indicating a non-significant baseline level of SDG 15 performance.The model summary shows an R-squared value of 0.2385 within countries over time, 0.2550 between different countries, and an overall R-squared value of 0.2521, suggesting that the model explains a moderate portion of the variance.

SDG 14: Life Below Water
The panel regression results indicate mixed evidence regarding the impact of environmental protection expenditure (EPE) on various SDGs.The significant positive impacts on SDG 12 and SDG 13 support the hypothesis (H1) that increased EPE enhances outcomes related to responsible consumption and climate action.For instance, an increase in EPE by 1 USD is associated with an increase in SDG 13 performance by 1.64 units, highlighting the effectiveness of targeted environmental investments in promoting climate action.However, the significant negative impact on SDG 11 suggests inefficiencies or misallocations in spending on sustainable urban development.The non-significant results for SDG 6, SDG 14, and SDG 15 indicate that other unobserved factors may significantly influence these outcomes, necessitating further investigation and tailored policy interventions.

Discussion
Environmental Protection Expenditure (EPE) refers to financial resources allocated by governments and organizations to prevent, reduce, and eliminate pollution, and to preserve environmental quality.EPE covers investments in clean technologies, environmental regulations, and sustainable practices across various sectors such as pollution control, waste management, and biodiversity conservation.The effectiveness of EPE is crucial for achieving long-term environmental sustainability and ensuring a healthy environment for future generations.The effectiveness of EPE varies between countries based on their unique environmental challenges, economic conditions, and policy frameworks.

SDG 6: Clean Water and Sanitation
China has made substantial investments in water infrastructure, like the South-North Water Transfer Project, to address water scarcity.While access to clean water has improved, regional disparities persist due to varied governance and implementation capacities (Xie, 2019) (Yan Wang, 2018).Indonesia faces significant hurdles in providing clean water and sanitation.Despite increased spending, governance issues and regional disparities impede progress (OECD, 2019;(Agus Susilo, 2020).Israel's advanced water management system, supported by significant EPE, has ensured water security and quality (Feitelson & Rosenthal, 2012;2016).South Korea's initiatives, such as the Four Major Rivers Restoration Project, highlight the need for better-targeted investments to enhance sustainability (Yoshikawa, T., & Lee, 2018).Malaysia's focus on urban sanitation shows notable improvements but highlights rural challenges (Azmi, 2021;Ting, 2019) The Philippines faces challenges in clean water provision, with inefficiencies and corruption limiting EPE effectiveness (Asian Development Bank, 2020).Thailand's investments in water infrastructure have mixed effectiveness due to regional disparities and governance issues (Wongthong, P., & Harvey, 2016).

SDG 11: Sustainable Cities and Communities
China's urban development investments, such as public transportation and green buildings, show varied effectiveness due to regional governance differences (Li et al., 2018;Liu et al., 2019).Indonesia's urban areas face challenges like pollution and inadequate infrastructure, with mixed results from increased EPE (Firman et al., 2020;Rustiadi et al., 2018).Israel's urban sustainability efforts, supported by EPE, have been generally effective but require comprehensive planning (Feitelson & Rosenthal, 2012;Eizenberg & Jabareen, 2017).South Korea's investments in sustainable urban infrastructure demonstrate improvements but highlight the need for better project management (Lee & Lim, 2018;Choi et al., 2020).Malaysia's urban development shows improvements in cities like Kuala Lumpur but faces challenges in other areas (Ahmad, 2019;Yuen, B., & Kong, 2020) The Philippines' urban development efforts have been limited by governance issues and resource misallocation (Ballesteros, 2019;Llanto, 2017).Thailand's investments have led to improvements but require further efforts to address regional disparities (Phonphok & Phongpanich, 2020;Kua & Lee, 2018).SDG 12: Responsible Consumption and Production China's implementation of the circular economy model has improved resource efficiency and waste management, driven by substantial EPE (Yuan, Z., Bi, J., & Moriguichi, 2019).Indonesia's waste management and sustainable consumption efforts show inconsistent effectiveness due to governance issues (OECD, 2019).Israel's policies on waste reduction and resource efficiency, supported by EPE, have been effective (Tal, 2016;Fischhendler & Katz, 2013).South Korea's EPE in promoting eco-friendly practices has led to significant improvements (Kim et al., 2019;Lee et al., 2020)

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consumption is reflected in improved waste management and resource efficiency (Hassan & Lee, 2021;World Bank, 2018).The Philippines' efforts in waste management face challenges due to regional disparities and governance issues (Perez & Bajarias, 2019;Asian Development Bank, 2020) (Teschner et al., 2017;Cohen et al., 2018).South Korea's Green New Deal investments have significantly reduced greenhouse gas emissions (Yoshikawa, T., & Lee, 2018) Kim & Park, 2019).Malaysia's policies have promoted renewable energy and climate resilience, but policy coherence and institutional capacity need strengthening (Tan et al., 2020;Rahman & Shaw, 2019).The Philippines' climate action efforts are limited by governance issues, requiring targeted and efficient EPE (Cruz & Hilario, 2019;Espaldon et al., 2018).Thailand's climate action initiatives have been effective, but continuous efforts are needed to address implementation gaps (Vichiensan & Limmeechokchai, 2019;Wong et al., 2020).SDG 14: Life Below Water China's efforts in marine conservation, supported by EPE, show limited effectiveness due to governance issues (UNEP, 2017; Wang et al., 2018).Indonesia's marine conservation faces challenges from illegal fishing and inadequate enforcement (Setyawan et al., 2019;Campbell et al., 2020).Israel's marine conservation policies have been effective, but ongoing challenges require continuous policy support (Tal, 2016;Rilov & Benayahu, 2002).South Korea's Green New Deal includes effective measures for marine conservation (Kim et al., 2019;Lee et al., 2020).Malaysia's marine conservation efforts, supported by EPE, have led to positive outcomes, though challenges remain (Chou et al., 2020;Yahya et al., 2019).The Philippines' marine conservation efforts face enforcement challenges (Licuanan et al., 2019;White et al., 2020).Thailand's EPE-supported marine conservation initiatives have improved outcomes but need stronger enforcement (Pornpinatepong et al., 2019;Suthibut et al., 2020).SDG 15: Life on Land Efforts to address climate change across these countries, supported by significant EPE, reflect varied outcomes influenced by governance, resource allocation, and policy frameworks.In China, substantial investments in renewable energy and climate resilience infrastructure have positively impacted climate action (IEA, 2020;Wang et al., 2020).Indonesia's increased EPE for climate action is challenged by governance issues and resource misallocation (OECD, 2019;Astuti et al., 2019).Israel's strategy focuses on renewable energy and climate resilience, supported by substantial EPE, leading to positive outcomes (Sommer & Fassbender, 2024) (Tal, 2016) (Teschner et al., 2017).South Korea's Green New Deal includes significant investments in renewable energy and climate resilience infrastructure, effectively supporting climate action (South Korean Government, 2020 (Yoshikawa, T., & Lee, 2018)Malaysia's policies promote renewable energy and climate resilience, supported by significant EPE (Long et al., 2022;Tan et al., 2021) Philippines faces challenges in climate action, with high vulnerability to natural disasters, despite increased EPE (Asian Development Bank, 2020) (Cruz et al., 2019).Thailand's policies promote renewable energy and climate resilience, supported by significant EPE, showing positive outcomes (UNICEF & WHO, 2017;Vichiensan & Limmeechokchai, 2019).

CONCLUSION
The findings of this research underscore the critical role of environmental protection expenditure in achieving the Sustainable Development Goals (SDGs) in the seven selected Asian countries.The analysis revealed a positive relationship between environmental protection spending and the progress towards SDG 6 (Clean Water and Sanitation), SDG 11 (Sustainable Cities and Communities), SDG 12 (Responsible Consumption and Production), SDG 14 (Life Below Water), and SDG 15 (Life on Land).This relationship is consistent with the literature on government expenditure theory and sustainable development, which posits that strategic public spending can drive significant improvements in environmental quality and public health.
Comparative studies within the literature corroborate these findings.For instance, research by the OECD (2020) demonstrates that investments in renewable energy and pollution control significantly enhance environmental sustainability.Similarly, empirical evidence from the World Bank (2021) highlights the benefits of targeted government spending in improving water and sanitation infrastructure, leading to better public health outcomes.
The practical implications of these findings are manifold.Policymakers in the selected countries should prioritize environmental protection in their budget allocations to ensure sustainable development.This involves not only increasing the overall expenditure but also enhancing the efficiency and effectiveness of the spending through transparent and accountable governance practices.Additionally, businesses can leverage these insights to align their corporate strategies with national sustainability goals, thereby enhancing their market competitiveness and operational resilience.
Policy implications include the need for integrated and coherent policy frameworks that align environmental protection goals with broader economic and social objectives.This requires cross-sectoral collaboration and the involvement of various stakeholders, including government agencies, private sector entities, and civil society organizations.The successful implementation of such policies can create a multiplier effect, driving progress across multiple SDGs and contributing to a greener and more sustainable future for the region.
, are critical issues

Table 1 .
Data and Information Collection

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1   +  2 −  5   ℎ  +   SDG6 it = Clean Water and Sanitation Score for  in year  SDG11 it = Sustainable Cities and Communities Score for  in year  SDG12 it == Responsible Consumption and Production Score for country i in year t SDG13 it = Climate Action Score for country  in year  SDG14 it = Life Below Water Score for country  in year  SDG15 it = Life on Land Score for country  in year  Exep it = Environmental Protection Expenditure for country  in year  Country Macro Characters include; ℎ it = Economic Growth for country  in year   it = Foreign Direct Investment for country  in year   it = Gini Ratio for country  in year

SDG 12: Responsible Consumption and Production Table 3.
The constant term (_cons) has a coefficient of 196.2824 with a p-value of 0.003, indicating a significant baseline level of SDG 11 .The model summary shows an R-squared value of 0.3856 within countries over time, 0.2156 between different countries, and an overall R-squared value of 0.2049, suggesting that the model explains a moderate portion of the variance within countries. performance

Table 5 .
value of 0.0534 within countries over time, 0.3875 between different countries, and an overall R-squared value of 0.3838, suggesting that the model explains a moderate portion of the variance. squared . Malaysia's commitment to sustainable . Thailand's EPE-supported initiatives have improved waste management and resource efficiency but need stronger enforcement (Santiboon & Praneetpolgrang, 2019; UNICEF & WHO, 2017).SDG 13: Climate Action China's significant investments in renewable energy and climate resilience have supported positive climate action outcomes (Z.Wang, 2020) Lin & Xu, 2018).Indonesia faces challenges in climate action due to governance issues and resource misallocation, despite increased EPE (Astuti et al., 2019; Tacconi et al., 2019).Israel's climate action strategy, supported by substantial EPE, has advanced renewable energy projects and climate resilience