Report on AI Data Center Expansion and Child Labor Risks: Emphasizing Sustainable Development Goals

Introduction

Artificial intelligence (AI) companies in the United States are investing billions of dollars to expand data center infrastructure, promising significant economic benefits such as job creation, tax revenue, and infrastructure development. However, this rapid expansion raises critical concerns related to child labor exploitation and abuse, issues that align closely with the United Nations Sustainable Development Goals (SDGs), particularly SDG 8 (Decent Work and Economic Growth), SDG 16 (Peace, Justice and Strong Institutions), and SDG 4 (Quality Education).

Investment and Impacts on Children

Major US technology platforms have committed tens of billions of dollars to build AI-ready data centers across multiple states including Georgia, Virginia, Ohio, Arizona, Oregon, and Washington. The $500 billion Stargate initiative and other AI companies have pledged investments exceeding $1.4 trillion in infrastructure projects nationwide.

While companies focus on how AI products affect children digitally, less attention is given to the foundational risks of child labor within domestic operations such as data center construction. The rapid expansion creates conditions that may increase risks for children, including:

• Heightened demand for low-cost labor
• Extensive construction and hazardous work environments
• Overnight and third-shift work schedules
• Heavy reliance on subcontractors and labor brokers

These factors contribute to a 31% increase in child labor violations reported by the U.S. Department of Labor between 2019 and 2024. Child labor in hazardous conditions risks physical injury, psychological trauma, and exploitation, undermining children’s access to education and health care, thus perpetuating poverty — directly contravening SDG 1 (No Poverty) and SDG 3 (Good Health and Well-being).

Regulatory Environment and Enforcement Challenges

The surge in child labor risks coincides with reduced enforcement of corporate sustainability and human rights obligations by federal and some state regulators. This weakened oversight environment may discourage companies from prioritizing compliance with human rights standards, increasing the likelihood of undetected violations.

When violations surface, often through whistleblowers or media investigations, companies face severe consequences including lawsuits, monetary penalties, and reputational damage, which can erode trust and business value. For example, investigations in 2023 revealed illegal child labor in food processing sectors involving hazardous overnight shifts and dangerous tasks, highlighting the risks of lax enforcement.

This regulatory gap undermines SDG 16 by weakening institutions responsible for protecting human rights and ensuring justice.

Compliance Standards and Due Diligence Framework

Effective mitigation of child labor risks requires robust compliance frameworks, such as UNICEF USA’s Child Labor Compliance Framework, which aligns with international standards including the United Nations Guiding Principles on Business and Human Rights and U.S. Department of Labor guidance.

1. Risk-based assessments tailored to company operations and business relationships
2. Enforceable controls over subcontractors and labor brokers
3. Ongoing monitoring and auditing mechanisms
4. Remediation processes centered on the best interests of the child

For data center construction, due diligence should address:

• Labor sourcing across subcontracting tiers
• Use of staffing agencies and labor brokers
• Hazardous or overnight work conditions
• Age verification practices
• Local labor market conditions

These measures support SDG 8 by promoting decent work conditions and SDG 10 (Reduced Inequalities) by protecting vulnerable children from exploitation.

Key Takeaways and Recommendations

• The focus on AI’s digital impact on children must be expanded to include the physical labor conditions underpinning AI infrastructure development.
• Companies must proactively identify and mitigate child labor risks to uphold children’s rights and comply with legal obligations.
• Implementing child-centered policies and strong due diligence enhances corporate reputation and long-term business sustainability.
• Strengthening regulatory enforcement and corporate governance is essential to prevent child labor violations and align with SDG 16.
• Protecting children’s rights during AI infrastructure expansion contributes to achieving multiple SDGs, including SDG 4, SDG 8, SDG 10, and SDG 16.

Author Information

Jonathan Drimmer is a partner at Steptoe in Washington, DC, co-leading the firm’s business and human rights practice.

Jessica Leinwand serves as general counsel of UNICEF USA and is an adjunct professor on child rights and business at American University’s Washington College of Law.

1. Sustainable Development Goals (SDGs) Addressed or Connected to the Issues Highlighted in the Article

1. SDG 8: Decent Work and Economic Growth
   • The article discusses child labor exploitation risks in data center construction and related industries, highlighting the need for decent work conditions and the elimination of child labor.
2. SDG 16: Peace, Justice and Strong Institutions
   • Issues of regulatory enforcement, legal compliance, and corporate governance are raised, emphasizing the importance of strong institutions and rule of law to protect children’s rights.
3. SDG 4: Quality Education
   • The article notes that child labor prevents access to education, perpetuating cycles of poverty.
4. SDG 3: Good Health and Well-being
   • Child labor risks include bodily injury and psychological trauma, linking to the goal of ensuring healthy lives and promoting well-being.
5. SDG 10: Reduced Inequalities
   • The article highlights vulnerabilities of children from marginalized communities, indicating the need to reduce inequalities.

2. Specific Targets Under Those SDGs Identified Based on the Article’s Content

1. SDG 8: Decent Work and Economic Growth
   • Target 8.7: Take immediate and effective measures to eradicate forced labor, end modern slavery and human trafficking, and secure the prohibition and elimination of the worst forms of child labor.
   • Target 8.8: Protect labor rights and promote safe and secure working environments for all workers.
2. SDG 16: Peace, Justice and Strong Institutions
   • Target 16.6: Develop effective, accountable, and transparent institutions at all levels.
   • Target 16.3: Promote the rule of law at the national and international levels and ensure equal access to justice for all.
3. SDG 4: Quality Education
   • Target 4.1: Ensure that all girls and boys complete free, equitable, and quality primary and secondary education.
4. SDG 3: Good Health and Well-being
   • Target 3.9: Reduce the number of deaths and illnesses from hazardous chemicals and air, water and soil pollution and contamination.
5. SDG 10: Reduced Inequalities
   • Target 10.2: Empower and promote the social, economic and political inclusion of all, irrespective of age, sex, disability, race, ethnicity, origin, religion or economic or other status.

3. Indicators Mentioned or Implied in the Article to Measure Progress Towards the Identified Targets

1. Indicator for Target 8.7:
   • Prevalence of child labor, as reported by the US Department of Labor showing a 31% increase in child labor violations between 2019 and 2024.
2. Indicator for Target 8.8:
   • Number of enforcement actions and regulatory penalties related to labor violations, including child labor in hazardous work environments.
   • Implementation of child labor compliance frameworks and due diligence processes in companies.
3. Indicator for Target 16.6 and 16.3:
   • Effectiveness of regulatory enforcement and corporate governance mechanisms in preventing child labor violations.
   • Number of legal cases, consent orders, and public scrutiny incidents related to child labor violations.
4. Indicator for Target 4.1:
   • Access to education rates among children in communities affected by labor exploitation.
5. Indicator for Target 3.9:
   • Incidence of injuries and health issues among child laborers in hazardous work environments.
6. Indicator for Target 10.2:
   • Measures of social and economic inclusion of vulnerable children, including those at risk of labor exploitation.

4. Table of SDGs, Targets, and Indicators

Source: news.bloomberglaw.com

Report on Active Labour Market Policies and Sustainable Development Goals

Introduction: Context and Importance of ALMPs

As economies undergo rapid technological changes, face population ageing, and accelerate the green transition, governments are investing significantly in Active Labour Market Policies (ALMPs) to support employment. These policies, which include training programmes, job-search assistance, wage subsidies, and entrepreneurship support, are fundamental to employment strategies across OECD countries. In 2022, OECD members invested on average 0.43% of GDP in ALMPs.

Given the substantial public investment, the focus has shifted from merely assessing whether these programmes work to understanding how and why they succeed or fail in practice. This report is based on a new OECD working paper by Sofia Dromundo and Olga Rastrigina, developed with support from the European Union and collaboration with public employment services, policymakers, and social partners.

Emphasizing Sustainable Development Goals (SDGs)

Active Labour Market Policies contribute directly to several SDGs, including:

1. SDG 8: Decent Work and Economic Growth – by promoting employment and inclusive economic participation.
2. SDG 4: Quality Education – through training and skills development programmes.
3. SDG 10: Reduced Inequalities – by targeting vulnerable groups and ensuring equal access to employment opportunities.
4. SDG 3: Good Health and Well-being – by integrating health support in employment services.
5. SDG 17: Partnerships for the Goals – through collaboration among governments, employers, and social partners.

Beyond the Numbers: Limitations of Traditional Evaluation Methods

Traditional evaluations of ALMPs have primarily relied on quantitative methods such as counterfactual impact studies. These methods assess whether participants are more likely to find jobs or earn higher wages compared to non-participants. While these evaluations have provided valuable insights—such as the medium-term benefits of training and the short-term effects of job-search assistance—they fall short in explaining the practical implementation and contextual factors influencing success.

Quantitative data alone do not reveal how programmes are designed, how frontline staff engage with jobseekers, or why outcomes vary across regions. To address these gaps, a qualitative assessment approach is necessary.

A Practical Framework for Qualitative Assessment

The OECD proposes a structured qualitative framework that complements quantitative evaluations by focusing on real-world implementation. Key features include:

• Self-assessment by programme designers and delivery staff describing operational details.
• External assessment by independent experts applying consistent benchmarks.
• Use of scores as learning tools rather than for ranking or competition.
• Facilitation of reflection on strengths, weaknesses, and areas for improvement.

This approach fosters continuous learning and adaptation, aligning with the SDG commitment to inclusive and effective institutions (SDG 16).

Eight Building Blocks of Effective Labour Market Programmes

The framework identifies eight essential criteria for successful ALMPs, which align with multiple SDGs by promoting inclusive and sustainable employment:

1. Evidence-Based Design: Programmes grounded in data and research to ensure effectiveness.
2. Smart Engagement of Service Providers: Efficient collaboration among stakeholders.
3. Proactive Outreach to Vulnerable Groups: Ensuring access for marginalized populations, supporting SDG 10.
4. Careful Assessment and Referral: Tailoring support to individual needs.
5. Integrated Support Services: Combining employment, social, health, and education assistance to address multiple barriers (SDG 3 and SDG 4).
6. Strong Case Management and Follow-Up: Sustaining employment outcomes and preventing relapse into unemployment.
7. Partnerships with Employers: Aligning training with labour market demands, fostering SDG 17.
8. Continuous Monitoring and Evaluation: Creating feedback loops for programme adaptation and improvement.

Significance of the Approach in Current Context

The OECD paper advocates for the routine integration of qualitative assessment in labour market policymaking. This approach:

• Bridges the gap between policy design and delivery.
• Enables governments to learn from practical experiences and adapt programmes to diverse contexts.
• Facilitates sharing of best practices across regions and countries.
• Supports efficient use of public funds amid fast-changing labour markets and budget constraints.
• Ensures ALMPs deliver sustainable benefits for workers, employers, and society, advancing the achievement of SDGs.

Conclusion

Active Labour Market Policies are critical tools in achieving sustainable development by promoting inclusive employment, reducing inequalities, and fostering economic growth. The OECD’s qualitative assessment framework enhances understanding of these policies’ practical implementation, supporting continuous improvement and alignment with the Sustainable Development Goals. Governments and stakeholders are encouraged to adopt this approach to maximize the impact of ALMPs in the evolving global labour market.

1. Sustainable Development Goals (SDGs) Addressed or Connected

1. SDG 8: Decent Work and Economic Growth
   • The article focuses on active labour market policies (ALMPs) aimed at helping people find and keep jobs, which aligns directly with SDG 8’s goal to promote sustained, inclusive, and sustainable economic growth, full and productive employment, and decent work for all.
2. SDG 4: Quality Education
   • Training programmes and skill development mentioned in the article relate to SDG 4, which aims to ensure inclusive and equitable quality education and promote lifelong learning opportunities for all.
3. SDG 10: Reduced Inequalities
   • The article highlights proactive outreach to vulnerable groups and integrated support addressing multiple barriers, which connects to SDG 10’s target to reduce inequality within and among countries.
4. SDG 17: Partnerships for the Goals
   • Partnerships with employers and collaboration among policymakers, social partners, and public employment services relate to SDG 17, which emphasizes strengthening the means of implementation and revitalizing global partnerships.

2. Specific Targets Under Those SDGs Identified

1. SDG 8 Targets
   • Target 8.5: Achieve full and productive employment and decent work for all women and men, including young people and persons with disabilities, and equal pay for work of equal value.
   • Target 8.6: Reduce the proportion of youth not in employment, education, or training.
   • Target 8.3: Promote development-oriented policies that support productive activities, decent job creation, entrepreneurship, creativity, and innovation.
2. SDG 4 Targets
   • Target 4.4: Increase the number of youth and adults who have relevant skills, including technical and vocational skills, for employment, decent jobs, and entrepreneurship.
3. SDG 10 Targets
   • Target 10.2: Empower and promote the social, economic, and political inclusion of all, irrespective of age, sex, disability, race, ethnicity, origin, religion, or economic or other status.
4. SDG 17 Targets
   • Target 17.16: Enhance the global partnership for sustainable development, complemented by multi-stakeholder partnerships that mobilize and share knowledge, expertise, technology, and financial resources.

3. Indicators Mentioned or Implied to Measure Progress

1. Employment and Earnings Outcomes
   • Indicators measuring whether participants find jobs or earn higher wages compared to non-participants (implied in quantitative evaluations).
2. Participation Rates in Training and Job-Search Assistance
   • Indicators related to the number and proportion of people participating in training programmes and job-search assistance.
3. Outreach to Vulnerable Groups
   • Indicators assessing the extent and effectiveness of proactive outreach to vulnerable populations facing barriers such as low skills or health issues.
4. Programme Implementation Quality
   • Qualitative indicators from self-assessment and external assessment frameworks measuring evidence-based design, case management, integrated support, partnerships, and continuous monitoring.
5. Follow-up Support and Sustained Employment
   • Indicators tracking follow-up support after employment and the sustainability of job retention.

4. Table: SDGs, Targets and Indicators

Source: devdiscourse.com

Southeast Asia Agricultural Outlook Series Inception Workshop Highlights Sustainable Development Goals

Workshop Overview

The Southeast Asian Regional Center for Graduate Study and Research in Agriculture (Searca) conducted the Inception Workshop for the Southeast Asia Agricultural Outlook Series (SEA Agri Outlook Series) on January 26–27. The event gathered experts from 11 Southeast Asian countries to discuss and align on the focus, analytical methods, data sources, and report contents for the country studies.

Objectives and Framework

• SEA Agri Outlook Series: A flagship publication designed to provide policy-relevant insights through a mixed-methods analytical framework integrating quantitative data, stakeholder engagement, and modeling tools.
• Focus on Sustainable Development Goals (SDGs): The series emphasizes systemic agricultural transformation to strengthen food security (SDG 2), reduce poverty (SDG 1), and promote sustainable development (SDG 12, SDG 13).
• Outputs: Country and regional reports, and an open-access database to support evidence-based policymaking.

Country Presentations and Collaborative Discussions

Experts from the 11 countries presented overviews of their agricultural sectors, covering:

1. Sector performance and transformation
2. Food and nutrition security status (SDG 2)
3. Major policies and programs supporting agricultural development aligned with SDGs

They also proposed study methodologies, data requirements, and report structures to ensure coherence with the series’ objectives.

Analytical Tools and Data Integration

• Computable General Equilibrium (CGE) Model and Agricultural Transformation Index (ATI): Presented by Angga Pradesha from the International Food Policy Research Institute (IFPRI), these tools support scenario analysis and policy evaluation to guide sustainable agricultural transformation.
• FAO Regional Foresight Report: Meeta Punjabi Mehta from the Food and Agriculture Organization Regional Office for Asia and the Pacific (FAO-RAP) offered to share critical data and scenario-based analyses to anticipate emerging food system challenges over the next 4–5 years, supporting SDG 2 and SDG 13.
• Southeast Asian Agricultural Statistics Database (SAASD): Introduced by Rochella Lapitan of Searca, SAASD is an open-access, interactive dashboard providing comprehensive agricultural data and visualizations to facilitate monitoring of agricultural transformation and sustainability.

Group Discussions on Agricultural Transformation

Participants engaged in focused group discussions addressing:

• Current status and key drivers of agricultural transformation
• Challenges and ongoing interventions
• Review of existing policies, investments, and institutional reforms
• Identification of additional policies required to accelerate and sustain transformation aligned with SDGs

Significance and Future Directions

Searca Center Director Mercedita Sombilla emphasized the workshop’s role in generating vital inputs for regional cross-country analysis under the SEA Agri Outlook Series. She highlighted the collaborative nature of the initiative and its expected high relevance to Searca and participating governments in advancing sustainable agricultural development.

Alignment with Searca’s Development Plan and SDGs

The SEA Agri Outlook Series is firmly anchored in Searca’s 12th Five-Year Development Plan: Sustainable Transformation of Agricultural Systems through Innovation in Southeast Asia (SUSTAIN Southeast Asia). The initiative aims to accelerate sustainable transformation of agriculture and rural communities through:

• Innovation
• Partnerships
• Evidence-based policies

This aligns directly with multiple Sustainable Development Goals, including:

• SDG 1: No Poverty
• SDG 2: Zero Hunger
• SDG 12: Responsible Consumption and Production
• SDG 13: Climate Action
• SDG 17: Partnerships for the Goals

1. Sustainable Development Goals (SDGs) Addressed or Connected to the Issues Highlighted in the Article

1. SDG 2: Zero Hunger
   • The article focuses on agricultural performance, food security, and nutrition in Southeast Asia, directly relating to ending hunger and achieving food security.
2. SDG 1: No Poverty
   • Reducing poverty through agricultural transformation and rural development is emphasized in the article.
3. SDG 12: Responsible Consumption and Production
   • The article discusses sustainable agricultural transformation, which implies sustainable production practices.
4. SDG 13: Climate Action
   • Although not explicitly mentioned, the focus on sustainable agriculture and foresight for future challenges implies relevance to climate resilience and adaptation.
5. SDG 17: Partnerships for the Goals
   • The article highlights collaboration among Southeast Asian countries, international organizations, and experts, reflecting partnerships to achieve sustainable development.

2. Specific Targets Under Those SDGs Identified Based on the Article’s Content

1. SDG 2: Zero Hunger
   • Target 2.3: By 2030, double the agricultural productivity and incomes of small-scale food producers.
   • Target 2.4: Ensure sustainable food production systems and implement resilient agricultural practices.
   • Target 2.1: End hunger and ensure access by all people to safe, nutritious, and sufficient food.
2. SDG 1: No Poverty
   • Target 1.2: Reduce at least by half the proportion of men, women, and children living in poverty in all its dimensions.
3. SDG 12: Responsible Consumption and Production
   • Target 12.2: Achieve the sustainable management and efficient use of natural resources.
4. SDG 13: Climate Action
   • Target 13.1: Strengthen resilience and adaptive capacity to climate-related hazards and natural disasters.
5. SDG 17: Partnerships for the Goals
   • Target 17.16: Enhance the global partnership for sustainable development, complemented by multi-stakeholder partnerships.

3. Indicators Mentioned or Implied in the Article to Measure Progress Towards the Identified Targets

1. Agricultural Transformation Index (ATI)
   • Presented by IFPRI, ATI is a composite indicator measuring agricultural transformation progress, including productivity, diversification, and sustainability.
2. Computable General Equilibrium (CGE) Model Analyses
   • Used to analyze economic impacts and scenarios related to agricultural policies and transformation.
3. Southeast Asian Agricultural Statistics Database (SAASD)
   • An open-access database providing data on agricultural trends, sector performance, food security, and nutrition, supporting measurement of progress.
4. Scenario-based Analyses and Horizon Scanning
   • Used by FAO-RAP to identify emerging challenges and assess future food system directions, indirectly supporting monitoring of resilience and sustainability indicators.

4. Table of SDGs, Targets, and Indicators

Source: manilatimes.net

U.S. Economic Performance in Q4 2025: A Sustainable Development Perspective

Overview of GDP Growth

Real gross domestic product (GDP) in the United States increased at an annual rate of 1.4 percent in the fourth quarter of 2025 (October to December), according to the advance estimate released by the U.S. Bureau of Economic Analysis (BEA). This growth follows a robust 4.4 percent increase in the third quarter of 2025. The release was delayed due to the government shutdown in October–November 2025.

Key Contributors to GDP Growth

The increase in real GDP was primarily driven by:

1. Consumer Spending: Growth in services, especially health care and international travel, contributed significantly.
2. Investment: Increases in intellectual property products, private inventory investment, and equipment, notably in research and development and information processing equipment.

These positive contributions were partly offset by decreases in:

• Government spending, particularly federal government consumption expenditures.
• Exports, influenced by adjustments in the treatment of precious metals used as investment.

Imports decreased, which positively affected GDP calculations.

Price Index and Inflation Measures

• The price index for gross domestic purchases increased by 3.7 percent in Q4 2025, up from 3.4 percent in Q3.
• The personal consumption expenditures (PCE) price index rose by 2.9 percent, slightly higher than the 2.8 percent increase in Q3.
• Excluding food and energy, the PCE price index increased by 2.7 percent, a slight decrease from 2.9 percent in the previous quarter.

Annual GDP Performance for 2025

Real GDP increased by 2.2 percent in 2025 compared to 2024, reflecting sustained growth in consumer spending and investment. The price index for gross domestic purchases rose by 2.6 percent, while the PCE price index also increased by 2.6 percent, consistent with the previous year.

Alignment with Sustainable Development Goals (SDGs)

SDG 8: Decent Work and Economic Growth

• The increase in consumer spending on health care services supports SDG 8 by promoting economic growth and employment in the health sector.
• Investment in intellectual property and research and development fosters innovation, a key driver of sustainable economic growth.
• Despite the government shutdown, efforts to maintain economic stability contribute to sustained growth and decent work opportunities.

SDG 9: Industry, Innovation, and Infrastructure

• Growth in equipment investment, especially in information processing equipment, aligns with SDG 9 by enhancing infrastructure and fostering innovation.
• Increased research and development investment supports technological progress and sustainable industrialization.

SDG 3: Good Health and Well-being

• Increased consumer spending on health care services, including outpatient and hospital care, contributes to improved health outcomes and well-being.

SDG 12: Responsible Consumption and Production

• The decrease in imports and adjustments in export data reflect efforts toward accurate economic accounting and sustainable trade practices.

Technical Notes and Data Considerations

Impact of Federal Government Shutdown

The partial federal government shutdown from October 1 to November 12, 2025, led to furloughs and reduced federal government services, subtracting approximately 1.0 percentage point from real GDP growth in Q4. However, back pay to furloughed employees mitigated impacts on current-dollar federal compensation.

Data Imputation for Missing Price Indexes

Due to the shutdown, the Bureau of Labor Statistics (BLS) was unable to collect October 2025 Consumer Price Index (CPI) data. The BEA imputed missing price indexes by averaging September and November CPI data, ensuring continuity and reliability in inflation measurement.

Sources of GDP Changes

• Consumer Spending: Increased services, particularly health care and international travel.
• Investment: Growth in intellectual property products (R&D), private inventories, and equipment (computers and peripherals).
• Government Spending: Declined due to reduced federal expenditures during the shutdown.
• Exports: Adjusted for investment-related precious metals transactions.

Summary of Key Economic Indicators (Q4 2025)

Upcoming Releases and Data Access

• Next GDP release (Second Estimate for Q4 2025 and Year 2025): March 13, 2026, at 8:30 a.m. EDT.
• BEA has modernized its news release format to include direct links to interactive data tables, enhancing accessibility and transparency.
• Historical and detailed data are available via BEA’s Interactive Data Application and Data Archive.

Conclusion

The U.S. economy demonstrated moderate growth in the fourth quarter of 2025, supported by consumer spending and investment, despite challenges such as the federal government shutdown. These economic activities contribute to multiple Sustainable Development Goals, including promoting sustained economic growth, innovation, health, and responsible consumption. Continued monitoring and data transparency remain essential for informed policy-making aligned with sustainable development.

1. Sustainable Development Goals (SDGs) Addressed or Connected

1. SDG 8: Decent Work and Economic Growth
   • The article discusses real GDP growth, consumer spending, investment, government spending, and employment data, all related to economic growth and labor market conditions.
2. SDG 9: Industry, Innovation, and Infrastructure
   • Increases in investment in intellectual property products, research and development (R&D), equipment, and manufacturing indicate innovation and industrial development.
3. SDG 17: Partnerships for the Goals
   • The article references data sharing and collaboration between government agencies (BEA, BLS, Census Bureau), reflecting partnerships and data transparency.

2. Specific Targets Under Those SDGs Identified

1. SDG 8: Decent Work and Economic Growth
   • Target 8.1: Sustain per capita economic growth in accordance with national circumstances.
   • Target 8.3: Promote development-oriented policies that support productive activities, decent job creation, entrepreneurship, creativity, and innovation.
   • Target 8.5: Achieve full and productive employment and decent work for all women and men.
2. SDG 9: Industry, Innovation, and Infrastructure
   • Target 9.5: Enhance scientific research, upgrade technological capabilities, and encourage innovation.
   • Target 9.2: Promote inclusive and sustainable industrialization and, by 2030, raise industry’s share of employment and GDP.
3. SDG 17: Partnerships for the Goals
   • Target 17.18: Enhance capacity-building support to developing countries to increase significantly the availability of high-quality, timely and reliable data.

3. Indicators Mentioned or Implied to Measure Progress

1. SDG 8 Indicators
   • 8.1.1: Annual growth rate of real GDP per capita.
   • 8.5.2: Unemployment rate, by sex, age, and persons with disabilities.
   • Consumer spending growth rates and investment rates as economic activity measures.
2. SDG 9 Indicators
   • 9.5.1: Research and development expenditure as a proportion of GDP.
   • Investment in intellectual property products and equipment as proxies for innovation and industrial capacity.
3. SDG 17 Indicators
   • 17.18.1: Proportion of countries that have national statistical legislation that complies with the Fundamental Principles of Official Statistics.
   • Availability and accessibility of timely economic data (e.g., GDP estimates, price indexes) as shown by BEA’s data releases and improvements.

4. Table: SDGs, Targets, and Indicators

Source: bea.gov

Audit Report on Roanoke Police Department’s Youth Gun Violence Prevention Grant

Overview

An internal city audit conducted in Roanoke, Virginia, revealed significant issues concerning the management of a youth gun violence prevention grant by the Roanoke Police Department. The audit identified overspending, inadequate background checks for youth mentors, and violations of child labor laws. These findings have implications for the Sustainable Development Goals (SDGs), particularly those related to Quality Education (SDG 4), Decent Work and Economic Growth (SDG 8), and Peace, Justice, and Strong Institutions (SDG 16).

Key Findings

1. Financial Overspending: The Police Department overspent the grant by nearly $100,000.
2. Background Checks: Youth mentors working with children did not undergo full background checks, raising concerns about child safety.
3. Child Labor Violations: Six instances were identified where youth were involved in manual labor and mechanical activities posing safety risks, violating child labor laws.
4. No Fraudulent Billing or Complaints: The audit found no evidence of fraudulent billing and no complaints from clients regarding the services provided.

Responses and Actions Taken

• Elimination of Vendor-Based Mentoring: All mentoring services provided through external vendors have been discontinued to improve oversight.
• New Mentoring Model: The department has developed an internal mentoring program where mentors are hired directly as part-time employees, enhancing accountability and compliance.
• Age Restrictions: Youth under the age of 14 will no longer be engaged in any work activities, aligning with child protection standards.
• Financial Oversight: Establishment of the Police Business Division to oversee financial management and ensure proper use of funds.

Statements from Deputy Chief Mike Crawley

Deputy Chief Mike Crawley acknowledged the concerns raised by the audit, attributing the issues primarily to a lack of oversight rather than malicious intent. He emphasized the department’s commitment to improving internal controls and safeguarding children involved in the program.

“We’re better today than we were before. Obviously, our checks and balances within government—that’s what they’re here for,” Crawley stated. He also highlighted that the funds, although overspent, were used to provide services to children in need, contributing to a reduction in violent crime.

Crawley confirmed that no criminal charges will be filed and no criminal investigation is underway regarding the mentors.

Implications for Sustainable Development Goals

• SDG 4 – Quality Education: Ensuring safe and supportive environments for youth mentors contributes to inclusive and equitable quality education and promotes lifelong learning opportunities.
• SDG 8 – Decent Work and Economic Growth: Compliance with child labor laws and improved labor practices protect young workers and promote decent work conditions.
• SDG 16 – Peace, Justice, and Strong Institutions: Strengthening oversight, transparency, and accountability within the police department supports the development of effective, accountable institutions.

Conclusion

The Roanoke Police Department’s audit findings highlight critical areas for improvement in grant management and youth program oversight. The corrective measures implemented align with the principles of the Sustainable Development Goals by prioritizing child protection, responsible governance, and community safety. Continued monitoring and adherence to these standards will be essential to sustain positive outcomes for youth and the broader community.

1. Sustainable Development Goals (SDGs) Addressed or Connected

1. SDG 16: Peace, Justice and Strong Institutions
   • The article discusses oversight failures, financial mismanagement, and the establishment of a Police Business Division to improve governance and accountability.
2. SDG 8: Decent Work and Economic Growth
   • Issues related to child labor law violations and youth employment practices are highlighted.
3. SDG 3: Good Health and Well-being
   • The article mentions youth gun violence prevention efforts and reduction in violent crime, which relate to promoting health and safety.
4. SDG 4: Quality Education
   • Youth mentoring programs and the development of an internal mentoring model relate to education and youth development.

2. Specific Targets Under Those SDGs Identified

1. SDG 16
   • Target 16.6: Develop effective, accountable and transparent institutions at all levels (addressed by establishing Police Business Division and improving oversight).
   • Target 16.3: Promote the rule of law at the national and international levels and ensure equal access to justice for all (related to compliance with child labor laws and audit findings).
2. SDG 8
   • Target 8.7: Take immediate and effective measures to eradicate forced labor, end modern slavery and human trafficking and secure the prohibition and elimination of the worst forms of child labor (addressed by eliminating child labor law violations and restricting youth work under age 14).
3. SDG 3
   • Target 3.4: By 2030, reduce by one third premature mortality from non-communicable diseases through prevention and treatment and promote mental health and well-being (related to reducing youth gun violence and violent crime).
4. SDG 4
   • Target 4.5: Eliminate gender disparities in education and ensure equal access to all levels of education and vocational training for the vulnerable (implied through mentoring and youth development programs).

3. Indicators Mentioned or Implied to Measure Progress

1. Financial Overspending and Accountability
   • Amount of grant overspending (nearly $100,000) as a measure of financial management effectiveness.
   • Establishment and functioning of the Police Business Division as an institutional accountability indicator.
2. Child Labor Compliance
   • Number of child labor law violations identified (six instances) as an indicator of compliance with labor standards.
   • Implementation of policies prohibiting youth under age 14 from work activities.
3. Youth Safety and Crime Reduction
   • Reduction in violent crime rates among youth as an implied indicator of program effectiveness.
   • No complaints from clients about the mentoring services as a qualitative measure of service quality.
4. Mentoring Program Quality
   • Background checks completion rate for youth mentors (not fully completed previously) as an indicator of program safety and quality.
   • Shift from vendor-based to internal mentoring model as a process indicator for improved oversight.

4. Table of SDGs, Targets and Indicators

Source: wsls.com

This declaration takes into consideration that several concurrent crises have turned the clock backwards in development gains in many countries through such converging crises as climate change, economic instability, conflict, and lingering pandemic effects. Leaders asserted that without renewed political commitment and stronger international cooperation, backed by increased financial investment, the SDGs will be unmet promises instead of attained outcomes.

From this declaration, one major outcry is the reform of global financial systems to allow developing countries access to affordable financing, which is vital to pursue sustainable development. Besides that, science, technology, and innovation, as well as inclusive decision-making that empowers and encompasses youth, women, and marginalized voices, remain very important.

What are the Sustainable Development Goals?

In 2015, the United Nations put in place 17 goals to address global challenges, including poverty, inequality, climate change, environmental degradation, conflict and injustice. The vision was to end obstacles like discrimination, exclusion and inequality that frequently leave the most vulnerable people behind. The SDGs replaced the 2000-2015 Millenium Development Goals which made some progress in areas such as poverty reduction, education and health. However, much of this progress was uneven with deepening inequality both between and within countries.

Will the SDGs be achieved by 2030?

At the moment, no – with five years left to achieve the SDGs, they are widely off track.

Years of underinvestment by all states means that over 80 per cent of the Sustainable Development Goals (SDGs)’ targets are off track. At the mid-way point of the SDGs, in July 2023, the UN reported that progress on more than half of the SDGs was “weak and insufficient”, while for another 30 per cent it had “stalled or gone into reverse”. These include key targets on poverty, hunger and climate action.

What does that mean for our world?

Existing inequalities between and within countries, which have widened due to a series of global crises, including the COVID-19 pandemic, climate change and economic downturns, could spiral further out of control.

The climate crisis together with weaknesses in the current financial system are sending lower- and middle-income countries further into debt. This is because often, their only option to cover the loss and damage caused by climate change is to seek additional loans. Countries in or at risk of spiralling debt spend more on debt repayments than on public services that are essential to people’s rights such as to health and education – fuelling the cycle of vulnerability.

How are human rights being impacted?

In the absence of real progress on the SDGs, the outlook for human rights is worrying.

The UN estimates that by 2030, 585 million people will be chronically undernourished, 1.66 billion people will still be living in extreme poverty, 84 million children will be out of school, 300 million attending school will leave unable to read and write and 660 million people will remain without electricity.

What’s finance got to do with fulfilling these goals?

Everything!

The global financial architecture is rooted in historical inequalities and the continuing legacy of colonialism, which leaves many low-income countries with unsustainable debt, depriving them of the resources they need to finance the SDGs. Tax evasion and avoidance by multinational companies and wealthy individuals cost countries an estimated US$492 billion annually. This is lost revenue, which could be spent on improving everyone’s access to economic, social and cultural rights.

How have the cuts to international aid affected the SDGs?

Food rations have been cut in refugee camps. HIV/AIDS clinics have closed overnight, people are not receiving antiretroviral treatments. Almost half of women-led and women’s organizations surveyed by UN Women expect to shut down within six months if current funding levels persist – with gender-based violence initiatives most at risk. The list goes on.

There’s been a lot of talk about tariffs in the USA. What are they and how are they affecting human rights?

Tariffs are taxes imposed by governments for imported services and goods. 

Tariffs are both an instrument in international trade policy and an industrial policy, where they can be employed to protect domestic industries. The Trump administration has imposed broad and arbitrary tariffs as a political tool to pressure dozens of countries, including Canada, China and Mexico but also many smaller economies, into a range of concessions. The policy, which does not take into account the impact on people’s rights, is hitting some of the poorest and already most vulnerable countries.

Tariffs can have a cascading effect on living conditions, employment, access to essential goods, and economic sovereignty, all of which can undermine human rights. Tariffs on essential imports like medicine, food, or fuel can make these and other basic necessities unaffordable in smaller or lower-income countries.

What are high-income states doing to ensure these goals are achieved?

Not enough.In fact, rather than increasing their funding to support the SDGs, many major Western donors have slashed international assistance, creating a huge crisis.

Nevertheless, there are other ways high-income countries can help. They should commit to structural reforms that could provide sustainable sources of financing for the longer term – from advancing international tax cooperation and addressing the debt crisis, to reforming international financial institutions and promoting more inclusive systems of financing and development.

So, what can be done to achieve these goals?

A series of robust measures must be put in place if we are to rescue the SDGs.

The US and other governments must reverse cuts to aid budgets. States must provide debt relief for countries in or at risk of debt distress. Fossil fuels subsidies must be redirected towards investment in clean energy and leaders must commit to a full, fast, fair, and funded fossil fuel phase out across all sectors and invest adequately in a just and equitable transition.

Adopting these measures will go a long way to rescuing the SDGs and ensure social, economic and climate justice for millions across the world. 

What is Amnesty’s take on financing for development?

Amnesty International is calling for broad transformation of development finance, taxation, debt, and public and private investment to ensure the Sustainable Development Goals are achieved. This will ensure finance is more available and affordable for low-income countries to achieve their human rights obligations.

These changes must take place quickly to meet states’ international obligations to provide international cooperation and assistance to ensure human rights through the progressive realization of economic, social and cultural rights.

The 4th International Conference for Financing for Development will take place from 30 June to 3 July in Seville, Spain. It provides a unique opportunity to reform development financing at all levels and address financing challenges preventing the urgently needed investment push to achieve the Sustainable Development Goals (SDGs) by 2030. The SDGs were put in place 10 years ago to guarantee peace and prosperity for people and the planet, now and in the future.

“Years of underinvestment by all states mean the majority of the Sustainable Development Goals are way off track from their 2030 target. This conference must confront the immediate crisis linked to the cutting of international assistance by major donors whilst committing to structural reforms that could provide sustainable sources of financing for the longer term – from advancing international tax cooperation and addressing the debt crisis, to reforming international financial institutions and promoting more inclusive systems of financing and development,” said Riva Jalipa, Amnesty International’s Financing for Rights Lead Adviser.

A series of robust measures must be put in place if the Sustainable Development Goals are to become a reality.

Riva Jalipa, Amnesty International’s Financing for Rights Lead Adviser

“A series of robust measures must be put in place if the SDGs are to become a reality. The US and other governments must reverse cuts to aid budgets. Wealthy states must support the UN tax treaty process whilst providing debt relief for countries in or at risk of debt distress including cancellation where appropriate. Fossil fuels subsidies must be redirected towards investment in clean energy and leaders must commit to a full, fast, fair and funded fossil fuel phase out across all sectors and invest adequately in a just and equitable transition. Adopting these measures will go a long way to rescuing the SDGs and ensure social, economic and climate justice for millions across the world.”

Amnesty International will also be co-hosting a Virtual Side Event at the Financing for Development Conference, Seville: Reparative Justice in Financing for Development. The session will focus on development financing and reparative justice as a means through which a human rights-based economy which redresses both existing and historical injustices can not only be conceptualized but also practically actioned. Register to attend via Zoom. 

Background

The Sustainable Development Goals (SDGs) were put in place 10 years ago to guarantee peace and prosperity for people and the planet, now and in the future. The 17 goals aimed to address global challenges, including poverty, inequality, climate change, environmental degradation, peace, and justice – to ensure no one was left behind. However,years of underinvestment by all states mean over 80% of the Sustainable Development Goals (SDGs)’ targets are off track due to underinvestment by all states.

            MSMEs account for more than 90% of businesses worldwide and employ the majority of the global workforce. Despite their importance, many face consistent challenges such as limited access to financing, outdated technologies, and the growing impacts of climate change. The UNDP initiative aimed to address these issues by promoting strategies that help small businesses transition toward greener, more resilient models. Through collaboration among governments, financial institutions, and the private sector, the event underscored the need for an economic system that supports both human development and environmental responsibility.

            This global effort directly touches several SDGs, including SDG 8 (Decent Work and Economic Growth), SDG 9 (Industry, Innovation, and Infrastructure), SDG 12 (Responsible Consumption and Production), SDG 13 (Climate Action), and SDG 17 (Partnership for the Goals). Together, these goals reflect a vision for an economy that is inclusive, innovative, and environmentally conscious. Supporting small enterprises is not just about boosting productivity, but also provides social equity, promotes cleaner industries, and partnerships that can make sustainability achievable for everyone.

            The lessons from the MSME Day 2025 are also being seen as being implemented in cities like Miami, where many small businesses are beginning to adopt environmentally friendly practices such as reducing waste, switching to renewable energy, and sourcing materials locally. While these changes may appear as something small, they represent a step forward by all the small businesses towards a more sustainable future. Local action, no matter how small, when it is multiplied across thousands of communities across the country, has the power to create a significant impact at the global scale.

            The message that this initiative is trying to transmit is clear: sustainable development depends on collaboration. Governments must create accessible funding opportunities for small enterprises, so that they can start to become more sustainable and help the environment.  Educational institutions should incorporate sustainability into business training, so all future entrepreneurs have the idea of sustainable business that they can create, generating jobs and a positive impact environment. Also, individuals can make a difference by supporting environmentally responsible companies, so not only do they get more money for their sustainable equipment, but they also create awareness in other businesses to begin implementing those same sustainable ideas.

            As 2030 approaches, the world faces a growing urgency to meet the SDGs. Events like the MSME

Day 2025 function as a reminder that achieving these goals is not something that depends on the government, but

rather on us. Empowering small, sustainable businesses is essential to building a resilient, fair, and sustainable

world where economic success and environmental stewardship go hand in hand. 

Japan is a prime example of the transformational effects free trade can have on the economic prosperity for a developing nation. After the second world war, Japan had a very weak economy and an underutilized labor force. Japan’s factories exported low value-added goods that were inexpensive for the US consumer and other developed nations which took advantage of their low-cost labor. In the following decades, Japan began improving the quality of its products, exporting higher-value goods to the US with improved profit margins. Eventually, Japanese companies started becoming more profitable and rose to prominence as world leaders in various sectors, gaining market share from developed nations. Immense profits generated by Japanese companies resulted in higher wages for workers that increased tax revenue for the government, leading to more infrastructure and domestic investments that improved the nation’s overall social welfare. 

This evolution did not solely benefit Japan, it was beneficial for American and European consumers as well. In addition to lowering consumer good prices, multinational competition forced corporate entities in developed nations to innovate in order to maintain market share. For instance, the “Big Three” automotive companies Ford, Chrysler, and GM, allowed their quality to decrease, turning their back on innovation and fuel efficiency. Competition from Japan drove technical advancements in many core industries strengthening the US economy overall. The auto sector began producing vehicles with lower carbon emissions that resulted in a reduction in greenhouse gases. This evolution clearly demonstrated the positive impacts of international trade for not only global growth and wealth but also for the environment in developed nations. While the prosperity generated from Japan’s export success lifted the nation’s economy, in the end, it also worked against them. The progression that improved the quality of Japanese products also led to an increase in prices and wages for their workers. As an unintended consequence, Japan lost the competitive advantage of low labor costs resulting in a manufacturing shift to other low-cost regions such as Taiwan and China. 

Following Japan’s trajectory, Taiwan started off exporting low value-added goods to developed economies with weak profit margins. Once again this trade disproportionately benefited rich nations who incorporated Taiwan’s inexpensive goods into their profitable finished products. Over time their economy advanced moving from low tech to high tech manufacturing with expanding margins. Today Taiwan is well regarded as a global leader in semiconductor manufacturing. However, just as before this economic success increased the nation’s labor costs harming their comparative advantage for low value-added goods. The cyclical pattern continued as the developing world’s interest shifted towards other low-cost regions such as China and Vietnam. During the last decade, the succession continued even further pushing manufacturing to poorest regions such as Myanmar and Cambodia propelling them into the wheel of global economic development exploiting their population’s modest wage base.

Analyzing historical data on the macro trends in Japan, Taiwan and China there is clear evidence of improvements in GDP per capita, protein consumption, literacy rates, and life expectancy. While the initial cost of entry to the global market may be inequitable, the enhanced social welfare for developing nations demonstrates that the benefits of trade can be both positive and inclusive in the long term. The argument that global trade has had a negative impact oversimplifies the complex dynamics of interconnected world trade. Looking at a single aspect, it is easy to misinterpret the overall benefits of modern trade for the world’s population.

1. Introduction

In order to accomplish the ambitious goal of sustainable economic development, the Chinese authorities enacted several environmental regulations and policies to foster economic growth while disrupting the rising ratio of carbon emissions (Balsalobre-Lorente et al., 2023; Zhang et al., 2021).

To obtain sustainable development along with environmental sustainability, the Chinese authorities remained proactive and have practiced several environmental regulation policies over the years (Zhang et al., 2022). China's first comprehensive environmental law was launched in 1989. It established the State Environmental Protection Administration (SEPA) to enforce environmental laws. Likewise, the Environmental Impact Assessment (EIA) law was proposed in 1990 to assess all significant development projects before proceeding to identify environmental issues and ensure mitigation. Also, China's Agenda 21 (1994) aimed for global sustainable development. China's sustainable development strategy prioritized economic growth, social improvement, and environmental conservation. The Clean Production Promotion Law (2002) encouraged firms to decrease waste, save resources, and reduce pollution. Similarly, The Circular Economy Promotion Law (2008) promoted a resource-efficient, waste-free circular economy. It encourages garbage recycling. Another law, “China's Air Pollution Prevention and Control Law” (2015), assisted in reducing city air pollution while imposing tight criteria for factory and vehicle emissions. China's Soil Pollution Prevention and Control Law (2018) prevented soil contamination. It required firms to clean up polluted locations and hold them accountable (Zhang et al., 2022).

One such policy, launched in 2021, is nationwide carbon markets, comprising around 2200 power sector enterprises, in order to price carbon emissions (Zhang et al., 2021). Further, China has built a green finance system, including green bonds and green loans, to encourage low-carbon growth. In addition, China leads the world in wind and solar energy generation. By the end of 2030, China, as pledged by the Chinese government, will have the capacity to produce 35% of its electricity from green sources. Likewise, through manufacturer incentives and consumer subsidies, China is actively promoting the development and adoption of electric cars; thus, it became the leading electric vehicle market, delivering almost 1.3 million cars in 2020. Besides, China has taken several serious steps, including building and appliance requirements for energy efficiency, to enhance energy efficiency (China Country Climate and Development Report, 2022). All these environmental policies attracted the academic community to assess their contribution to sustainable development in China. Hence, it is rational to analyze how environmental regulation policies contribute to accelerating the sustainable development process.

Simultaneously, China has taken several remarkable steps to enhance human capital. To do so, Chinese authorities targeted education and technology, which significantly contributed to the trigger of human capital in China (Fan et al., 2023; Chen et al., 2023; & Liang et al., 2022). For instance, the Chinese government has undertaken several education reforms since 2005. In 2010, the “New Curriculum” was introduced to promote technical and innovative education across China (Opoku et al., 2022). Also, Chinese authorities invest a large chunk of their budget on rural education in order to enhance the overall education level at the nation-level, as 32 billion dollars were invested in rural education in 2018 (Chen et al., 2023). Since the rise in education level and technological progress tend to increase the number of efficient workers (Solow, 1956), this process leads to enhance numbers of efficient human capital. Also, the ability to make better decisions on account of education and experience increases the efficiency of human capital. Since human capital works as an essential pillar to escalate economic growth (Solow, 1956), it is important to investigate its impact on sustainable development.

Due to the significance of environmental regulation policies and human capital, numerous scholars have made efforts to investigate their impact on sustainable development. In this regard, the academic community has utilized various economic indicators as measures of sustainable development efficiency, including ecological footprints and green growth (Razzaq et al., 2023; Ofori et al., 2023; De Haas and Popov, 2023), carbon emissions (Li et al., 2023), and green energy (Wu et al., 2023; Dogan et al., 2023). However, there remains a considerable gap in this field, highlighting the following aspects: previous literature has not employed a comprehensive indicator to assess the efficiency of sustainable development and analyze its response to environmental regulation policies. Similarly, the effects of human capital on a comprehensive measure of sustainable development have not been explored yet. Furthermore, prior studies have primarily focused on examining average and symmetric effects, whereas the majority of economic trends exhibit asymmetric characteristics (Chishti et al., 2023a; Chishti and Patel, 2023). Therefore, in order to address the aforementioned gaps, this study aims to pose the following research question:

Research question: How are the impacts of environmental regulation policies and human capital on sustainable development efficiency time-varying and asymmetric?

The goal of this study is to investigate the dynamic factors that impact the effectiveness of sustainable development, with the aim of proposing policies for achieving SDG 7 and 8 goals. This study contributes to the scientific literature in several ways. Firstly, it is the first study to utilize the variable of sustainable development efficiency as a more accurate measure of sustainable development. Secondly, this is the first study that targets to divulge how environmental regulation policies shape sustainable development efficiency. To do so, the study splits environmental regulation policies, following Chishti et al. (2021), into positive and negative shocks to explore the detailed and informative findings from a policy-making perspective. Thirdly, another significant contribution of the study is to investigate the effects of positive and negative shocks on human capital on sustainable development efficiency, unlike the previous studies, which considered the linearity of human capital. Fourthly, the study analyzes the effects of industrialization, urbanization, and economic growth on sustainable development efficiency.

Fifthly, for the SDG 7 and 8 goals to be made into a policy framework, the right methodological techniques are needed. The study uses province-level panel data for China from 1998 to 2017, and the chosen economic series seem to be asymmetrical, which shows that their trends change over time and suggests a plausible time-varying link. All such characteristics of the opted series should be taken into account properly. Therefore, to capture the time-varying nexus, the study deploys a non-parametric panel data model by Churchill et al. (2019), wavelet quantile correlation by Kumar and Padakandla (2022), and a non-parametric panel Granger causality test by Dogan et al. (2023). These techniques enable the study to explore robust and reliable results in order to design a comprehensive policy framework to achieve SDGs 7 and 8.

The remainder of the study is organized in the following order: Section 2 covers a pertinent literature review to highlight the literature gap. Section 3 explains a theory-based framework to formulate the econometric model. Section 4 highlights the econometric tools, and Section 5 covers the results along with a discussion. Section 6 concludes the results for developing a policy framework.

As the literature has identified that urbanization (Fan et al., 2023; Chen et al., 2023; Liang et al., 2022), industrialization (Naeem et al., 2023; Azam et al., 2021) and GDP (Zhao et al., 2022; Zheng et al., 2023, & Zou and Zhang, 2022) play a significant role in determining the sustainable development through resources depletion, fossil fuels combustion, and financial support, respectively. 

As the recent literature (Sun et al., 2023; Zheng et al., 2023) has witnessed that environmental regulations policies (ERP) can play crucial in defining the sustainable development. For instance, ERP encourage the sustainable development through promoting the new and clean technologies. This process tends to expand the labor market by creating the new jobs. It leads to trigger the economic growth along with improving the environmental quality by reducing the greenhouse gases, specifically, carbon emissions (Jin et al., 2023a, Jin et al., 2023b; and Wang et al., 2023a, Wang et al., 2023b, Wang et al., 2023c). Also, the ENP encourages the sustainable development through decreasing the waste and natural resources depletion. Also, ERP boosts the sustainable development through promoting the international collaboration in order to address the global environmental issues. 

Recently, many scholars (Chishti et al., 2021; Weimin et al., 2021; Weimin and Zubair Chishti, 2021) have argued that most of the economic series were nonlinear in nature. Simply put, the variations in the economic variables necessitates to treat them as an asymmetric series. Thus, the application of linear methods in order to perform the analysis may tends to inconsistent and biased results due to hindering the likely asymmetric information in the economic series (Chishti et al., 2023). Hence, it rational to split the economic series into positive and negative series to obtain the asymmetric information. In the line with the above discussion, the recent study tends to split the central variables, viz., ERP and HC into positive and negative shocks.

The positive shocks of ERP refer to significant improvements or advancements in policies and regulations related to environmental protection while the negative shocks refer to the decline in the advancements in the environmental regulation policies. Economically, the positive shocks in ERP are expected to trigger the sustainable development through promoting the new and clean technologies. This process tends to expand the labor market by creating the new jobs. It leads to trigger the economic growth along with improving the environmental quality by reducing the greenhouse gases, specifically, carbon emissions (Jin et al., 2023a, Jin et al., 2023b; and Wang et al., 2023a, Wang et al., 2023b, Wang et al., 2023c). Also, the positive trends in ENP encourage the sustainable development through decreasing the waste and natural resources depletion. Also, such positive changes in ERP boost the sustainable development through promoting the international collaboration in order to address the global environmental issues. On the other hand, it rational to argue that the negative shocks in ERP hurt the sustainable development through disrupting the new and clean technologies process. This process tends to contract the labor market by hindering the jobs. It results in dwindling the economic growth along with deteriorating the environmental quality by increasing the greenhouse gases, specifically, carbon emissions. To recapitulate, the upward trends in the ERP encourage the sustainable development while the downward trends in the ERP discourage the sustainable development.

Likewise, the positive shocks in human capital (HC) means the significant improvements in the level of education, skills, and knowledge of a labor force to utilize the capital efficiently. Contrarily, the negative trends in HC indicate the downfall in the level of education, skills, and knowledge of a labor force. Economically, it can be argued that the upward trends in the human capital market tends to enhance the productivity level in an economy on account of higher level of education, skills and experience. It leads to trigger the economic growth (Hondroyiannis et al., 2022; Opoku et al., 2022; and Shahbaz et al., 2022). Contemporality, the higher level of education, skills and experience foster the process of innovation which consequently, improve the environment along with thriving the economic growth through boosting the green technologies. Also, the ability for better decision making on account of education and experience increases the efficiency; it, in response, boosts the growth along with improving the environmental quality. Conversely, it can be inferred that the downfall in the human capital causes the depletion of natural resources inefficiently due to heavily dependence on fossil fuels and low ratio of green technologies. This process tends to hurts the environmental quality along-with increasing the economic growth. To capitulate, the upward trends in human capital (PHC) significantly encourage the sustainable development, while the downward trends in human capital (NHC) discourage the sustainable development process.

Based on the above arguments, it is rational to extend the model by integrating the positive shocks in ERP and human capital and negative shocks in ERP and human capital. ${\mathit{}}_{}$

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Fig. 2. Shocks in environmental regulation policies.

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Fig. 3. Shocks in human capital.

Based on the aforementioned theoretical discussion, the study expects that the positive shocks in environmental regulation policies and human capital supports the sustainable development efficiency (SDE). In a similar vein, economic growth (GDP) is expected to foster the SDE. However, it is highly likely that urbanization (URB) and industrialization (INDS) can deteriorate the SDE process.

5. Results and discussion

5.1. Parametric methods' results

To identify whether the first-generation or the second-generation techniques are suitable to estimate the parametric results (Chishti et al., 2023), the recent study starts by applying the cross-section dependence (CD) test by Baltagi et al. (2012). The outcome presented in Table 2 accepts the alternative hypothesis of cross-sectional dependence, implying that the modeled panel series are cross-sectionally dependent. Hence, it is, econometrically, important to deploy the second-generation tests (such as CADF, and Westerlund cointegration test) and methods (such as Difference GMM, and CS-ARDL) to produce the robust and consistent results. The second-generation unit root test's results, reported in (Panel A) Table 3, all the opted series fulfill the stationarity condition after taking the level or first difference. Simply put, not a single panel series takes the second difference to be a stationary; hence, the study confidently proceeds towards the parametric results. Subsequent to this, the second-generation Westerlund cointegration, as reported in Panel B in Table 3, assures the long-run association by rejecting the null hypothesis of no-cointegration among the panel series.

Table 2. CD test.

Empty Cell	CD test	P-value
SDE	3.80	0.000
PERP	87.31	0.000
NERP	82.13	0.000
PHC	83.11	0.000
NHC	80.65	0.000
URB	32.93	0.000
INS	38.31	0.000
GDP	92.13	0.000

Table 3. Unit root & cointegration tests.

Panel A: CADF test
Variable	At level	At 1st difference
SDE	−1.175	−3.361***
PERP	−2.391**	–
NERP	−1.964	−3.005***
PHC	−2.891***	–
NHC	−1.884	−3.588***
URB	−1.731	−3.363***
INDS	−2.071**	–
GDP	−1.819	−2.192**

Panel B: Westerlund cointegration test
Variance ratio	−2.4054**	0.0081

Table 4 documents the outcome of Difference GMM and CS-ARDL techniques. The results determine that most of the regressor significantly explain the variation in the SDE with the exception of NERP (in Diff. GMM & CS-ARDL results), URB and GDP (in Diff. GMM results). Furthermore, the results show that PERP and URB have the significant positive link with SDE; however, magnitude of the both variables' coefficients is too low to influence the SDE. It implies that the any change in the positive shocks in environmental regulation policies and urbanization process significantly support the sustainable development efficiency; however, the effects is too minor to be considered. The positive and negative shocks in HC significantly encourage the SDE, indicating that SDE gains the significant benefits on account of rise and fall rise in human capital. Ironically, the Diff. GMM coefficient suggests the adverse effects (Karim, 2021, Karim, 2021, Karim et al., 2021), while CS-ARDL coefficient suggest the positive effects of industrialization on SDE. Likewise, only CS-ARDL determines the significant but negative effects of GDP on SDE.

Table 4. Outcome of the parametric methods.

Variables	Coefficients (Diff. GMM)	Coefficients (CS-ARDL)
PERP	1.08E-06***	1.04e-07**
NERP	−2.60E-07	5.23e-08
PHC	1.000000***	0.9999998***
NHC	1.000001***	1.00000***
URB	8.88E-09	5.58e-08**
INDS	−1.21E-06*	3.74e-07**
GDP	−3.44E-07	−3.09e-078***

Note: ***, **, and * indicate the significance level at 1%, 5%, and 10%, respectively.

Note: In the above table, only long-run outcome of CS-ARDL method is reported. The short-run results can be seen in supplementary material.

The results above highlight several inconsistencies. For instance, there are contradictory findings concerning the impact of industrialization, and unexpected positive effects have been identified despite negative shocks to human capital. Additionally, the coefficients of PERP, INDS, and GDP are significant, yet their magnitudes are relatively low. These observations suggest that point estimates obtained through parametric methods may be imprecise. There may be two reasons for these inconsistencies in the results. Firstly, misspecification in the model tends to cause the inconsistent results. Secondly, the parametric methods compute only the on average effects of regressors on the dependent series while reporting a single point estimate. Thus, these methods cannot depict how PERP, NERP, PHC, and NHC influence the SDE over-time. Such loopholes in the outcome of parametric methods inspire to deploy nonparametric panel technique. Therefore, the next section reports the findings of non-parametric panel method.

5.2. Nonparametric panel technique results

This segment elaborates the outcome of the time-varying coefficients, and the common trend of SDE along with the province specific-trend functions.

5.2.1. Time-varying coefficients functions

Fig. 4 visualizes the LLDVE estimate-based time varying coefficient function of PERP, NERP, PHC, NHC, URB, INDS, and GDP to analyze their time-varying effects on SDE in China. The LLDVE results plainly suggest that the nexus between PERP-SDE is significantly time-varying. Specifically, the PERP coefficient exhibits a negative but insignificant influence on SDE till 2003. After that, it demonstrates a sharp rising trend that peaks in 2008 and before plummeting, with insignificant effects observed during 2013–2016. Subsequently, an upward and significant trend is observed. The reason being, the rapid industrialization process in 1990 in China tended to cause the severe environmental issues along with boosting economic growth. To handle the devastative environmental degradation, the Chinese government established “State Environmental Protection Administration” in 1998 through enforcing the environmental laws. Also, in 2006, Chinese authorities launched “Circular Economy Promotion Law” in order to promote sustainable development. Therefore, in Fig. 4, it can be seen an upward trend in ERP which demonstrates the favorable effects, specifically, after 2004. Economically, the such positive shocks in ERP trigger the sustainable development through promoting the new and clean technologies. This process tends to expand the labor market by creating the new jobs. It leads to trigger the SDE along with improving the environmental quality by reducing the greenhouse gases, specifically, carbon emissions (Jin et al., 2023a, Jin et al., 2023b; and Wang et al., 2023a, Wang et al., 2023b, Wang et al., 2023c). Also, the positive trends in ENP encourage the sustainable development efficiency through decreasing the waste and natural resources depletion. Similarly, such positive changes in ERP boost the sustainable development through promoting the international collaboration in order to address the global environmental issues in China. Furthermore, another notable aspect in the graph is a sudden fall in NERP coefficient function after 2008. The likely reason is global financial crises which was started in 2007 and ended in 2008. In response, the global economy has to endure a significant fall in each sector of economy including the Chinese economy (Zou and Zhang, 2022). Therefore, ERP exhibits a downward trend while affecting the sustainable development efficiency.

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Fig. 4. Nonparametric local linear estimates of common trend and coefficient functions. Note: The confidence interval for each estimate is 95% for significance level.

Conversely, NERP has significant and time-varying effects on SDE such that during the all-time period, the NERP show an adverse effect on SDE except for time (i.e., 1998–2000) which exhibits the insignificant negative effects. Logically, the negative shocks in ERP hurt the sustainable development through disrupting the new and clean technologies process. This process tends to contract the labor market by hindering the jobs. It results in dwindling the economic growth along with deteriorating the environmental quality by increasing the greenhouse gases, specifically, carbon emissions. Summing up, the results plainly indicate that upward trend in ERP significantly supports and the downward trend in ERP deteriorates the sustainable development efficiency in China. The aforementioned findings are distinct, as prior studies (Zhao et al., 2022; Zhang et al., 2021; Zhou et al., 2022a, Zhou et al., 2022b; Ahmed et al., 2022) have overlooked the asymmetric effects of ERP on sustainable development.

As for the effects of PHC, the results determine that PHC coefficient's function visualizes the time-varying nexus with SDE such that the upward trend in human capital significantly encourages the SDE specifically after 2009. It implies that PHC plays a supportive role in triggering the SDE after 2009. While before 2009, the effects remain positive but insignificant. There may be several reasons for these results. For instance, Chinese government has taken several education reforms since 2005. In 2010, the “New Curriculum” was introduced to promote the technical and innovative education across the China (Opoku et al., 2022). Also, Chinese authorities invest a large chunk of budget on rural education in order to enhance the overall education level at nation-level as 32 billion dollars were invested on rural education in 2018 (Chen et al., 2023). Since the rise in education level and technological progress tend to increase the number of efficient workers (Solow, 1956), this process leads to enhance the number of efficient human capital. Thus, economically, it can be argued that the upward trends in the human capital market tends to enhance the productivity level in an economy on account of higher level of education, skills and experience. It leads to trigger the economic growth (Hondroyiannis et al., 2022; Opoku et al., 2022; and Shahbaz et al., 2022). Contemporality, the higher level of education, skills and experience foster the process of innovation which consequently, improve the environment along with thriving the economic growth through boosting the green technologies. Also, the ability for better decision making on account of education and experience increases the efficiency; it, in response, boosts the growth along with improving the environmental quality. Fan et al. (2023), Chen et al. (2023), and Liang et al. (2022) support the above findings and argue that human capital is an essential source to boost the sustainable development process.

Focusing on the negative shocks in the human capital (NHC), it can be witnessed that the downward trend in HC significantly discourages the SDE process over the most of the time. It clearly suggests that any external shock that disrupt the human capital progress results in decreasing the SDE. Logically, it can be inferred that the downfall in the human capital causes the depletion of natural resources inefficiently due to heavily dependence on fossil fuels and low ratio of green technologies. This process tends to hurts the environmental quality along-with increasing the economic growth, implying the downfall in SDE. Again, this is another unique aspect of the study which confirms the adverse effects of NHC on SDE.

Whereas the effects of GDP on SDE are concerned, the findings suggest that GDP has a significant and positive impact on SDE, particularly after 2003. Moreover, these favorable effects vary over time, with the strongest impact observed until 2007, followed by a decline that likely reflects the adverse effects of the global financial crisis in 2007–08. However, a gradual recovery is evident thereafter, which accelerates significantly after 2014. The results imply that overall GDP significantly contributes in fostering the SDE over-time, specifically, after 2014. Plausibly, the rising budget allocation by Chinese authorities to trigger the sustainable development plays a key role in this regard. For example, $366 billion dollars were allocation by China's National Development and Reform Commission for renewable energy sector development in 2008. In 2012, a package of $1.9 billion were allocated to encourage the use of environmentally friendly products. Further, China released $382 billion under the program of “13th Five-Year Plan for Energy Development” in 2015, $290 billion under program of “Guiding Opinions on Accelerating the Development of Green Finance” in 2016, and $5 billion in 2019 in order to promote green energy development through green finance (Naeem et al., 2022a, Naeem et al., 2022b, Siddique et al., 2023). All such measures significantly contribute in thriving the economic growth by fulfilling the energy demand. This process leads to enhance the economic growth along with improving the environmental quality through increasing the SDE.

Regarding the effects of industrialization (INDS), the results indicate that SDE process has to face significant loss on account of INDS as the negative association is observed. Further, these linkages are dynamic over time, with the magnitude of adverse effects appearing to increase and become more intense during 2016–17 (Karim et al., 2022d, Naeem et al., 2023c). Economically, the Chinese economy heavily relies on the industrial sector as its contribution to GDP was recorded by 39.4% in 2021 (Investopedia, 2022) with the growth rate of 8.1% (World Bank, 2022). The rapid growth in industrial sector requires a large amount of energy which is mainly stemmed from fossil fuels. For instance, coal accounted for 63.6% of total electricity generation in 2021 (Statista, 2023). This process, ultimately, leads to degrade the environment which results in a downward trend in SDE. These results are in the line with Naeem et al. (2023), Liao et al. (2023), Naeem et al., 2022, Naeem et al., 2023a, Naeem and Karim, 2021 and Voumik and Ridwan (2023).

In the case of urbanization, the same findings are witnessed as of INDS. However, the magnitude of adverse effects tends to fall over time such that it becomes insignificantly positive after 2014. Also, Naqvi et al. (2023), Chen et al. (2023), Huo et al. (2023), and Lee et al. (2023) support the above results while arguing that urbanization impedes sustainable development growth process through producing the greenhouse gases.

5.2.2. Common and province-specific trend function

This segment of the paper visualizes the LLDVE-based estimates of common trend for SDE, as given in Fig. 4, along with the province specific trend functions for each province, as depicted in Fig. 5A, and B. The notable aspect of the LLDVE method is that it allows the trend function to evolve with unknown functional forms over the time to capture the likely trending phenomenon, unlike the parametric methods which assume the linear trend in the panel models. Also, province-specific trends are documented in order to confirm whether the heterogeneous trends across the provinces exist or not.

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Fig 5. A Nonparametric local linear estimates of province-specific trend functions. Note: The confidence interval for each estimate is 95% for significance level.

B. Nonparametric local linear estimates of province-specific trend functions. Note: The confidence interval for each estimate is 95% for significance level.

Regarding the common trend function for SDE, it can be observed that the common trend has, overall, an upward and significant trend, implying that SDE is consistently escalating over time. Particularly, a sharp upward has been witnessed since 1998, followed by a slight downfall after 2001 till 2004. Possibly, the downfall from 2001 to 2004 reflects the deteriorating impact of the 9/11 event (Karim et al., 2023b, Mbarki et al., 2023, Naeem et al., 2023b). The same downward trend is also observed after 2007, implying the adverse effects of the financial crisis in 2007–08. Another decline can be seen after 2014, indicating the possible negative effects of the financial crisis in 2014 (Karim et al., 2022b, Karim et al., 2023a, Karim and Naeem, 2022, Pham et al., 2022, Siddique et al., 2022). Summing up, SDE's common trend has the predominant upward trend while also depicting the adverse effects of various economic shocks over time (Benlagha et al., 2022, Billah et al., 2022, Farid et al., 2023, Karim et al., 2022a, Karim et al., 2022c, Karim et al., 2023a).

This segment also visualizes the province-specific trend patterns in order to affirm that whether these trends follow the pattern of common trend function or not as depicted in Fig. 5A and B. It can be observed that, out of 30 provinces, 18 provinces' individual trends closely follow the pattern of common trend, implying that these provinces have gaining the same benefits regarding enhancing the SDE. The remaining 12 provinces' individual trends demonstrate the significant differences from the common trend function, implying heterogeneity across these provinces from the main trend function. Further, most of these 12 provinces' individual trend pattern remain above the common trend pattern, indicating that SDE rate is high in these provinces as compared to the national level SDE rate.

5.3. Robustness check

To assess the robustness of the main results based on LLDVE estimates, the study relies on two novel methods: Wavelet Quantile Correlation (WQC) method and non-parametric panel granger causality (NPPGC) test.

5.3.1. Wavelet quantile correlation

To do so, the study converts the provincial level annual data into quarterly data, following Chishti et al. (2023), Qingquan et al. (2020), and Shahbaz et al. (2018), in order to capture the detailed information. Next, all series are summed to make them representative of all provinces. Before diving into discussion of the WQC outcome, it is worth noting that the results of WQC are visualized in heatmaps and the color-bar given in right-side of each heatmap exhibits the significance and intensity of the effects. Further, it is assumed that quantiles 1–3 indicate the short-run, quantiles 4–6 indicate medium-run, and quantiles 7–9 indicate the long-run. The vertical axis of each heatmap shows the sample time. All the results are reported in Fig. 6. (See Fig. 7.)

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Fig. 6. Wavelet correlation method's results.

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Fig. 7. Non-parametric panel granger causality test outcome.

Regarding the effects of PERP, the results plainly support the outcome of LLDVE. The findings reveal that PERP has approximately insignificant impact on SDE during short to long run over 1998Q1 to 2007Q4 with the exception of 3rd to 6th quantiles in 2002Q4 that show significantly positive effects. After 2008Q1, SDE gains the considerable benefits on account of PERP. On the other hand, the NERP demonstrates the significant adverse effects on SDE level during the all (short-long) runs over the all-time, implying that the negative shocks in ERP disrupt the process of SDE in China, supporting the LLDVE estimate (Alawi et al., 2023, Appiah et al., 2022, Arfaoui et al., 2023).

In the case of PHC and NHC, the results exhibit that PHC predominantly supports and NHC discourages the SDE level over the time across the various time horizons. Similarly, INDS significantly deteriorates the SDE process over most of the time across different time horizons except for a few quantiles in the short and medium run which demonstrate the favorable effects. The same results are observed in the case of URB. In the case of GDP, it is visualized that GDP plays an essential role in fostering the SDE as GDP possesses clearly positively effects on SDE across all runs over most of the time period. Summing up, WQC estimates validate the main results by supporting the estimates of LLDVE.

5.3.2. Non-parametric panel granger causality

As a second robustness check, the study deploys the novel non-parametric panel granger causality (NPPGC) test which is capable of capturing the causal nexus between the selected series across various quantiles and the outcome is reported in Fig. 7. It is worth noting that the quantiles from 0.05 to 0.35 imply short-run, the quantiles from 0.4 to 0.65 imply the medium-run, and the quantiles from 0.7 to 0.95 imply the long-run. Further, the threshold significance level is 2, indicating the significance level at 5% if the estimated t-values remains above the threshold significance level. The results are reported in.

Regarding the PERP, it can be witnessed that estimated values remain above the threshold values during the quantiles of 0.4 to 0.95 with the exception of 0.65. It confirms the significant granger causality that runs from PERP to SDE in the medium and long-run. The same causality is witnessed from NERP to SDE across the quantiles of 0.5 to 0.95. It reveals that any policy shocks to PERP and NERP may results in affecting SDE in China in the medium and long-run. Also, it implies that PERP and NERP can significantly predict SDE process which may have an enormous importance in the context of suitable policy-making. Likewise, PHC and NHC also significantly granger cause the SDE across the various quantiles. Further, GDP is the significant predictor of SDE across the all quantiles. In addition, INDS and URB granger cause the SDE during the most of the quantiles. Summing up, the modeled series significantly granger cause the SDE in the short, medium, and long run, implying that any policy shock to these series can influence the SDE in China and can guide in inferring the important policy implications for different time horizons.

First, the UN policy brief stresses the need for a concise, widely accepted, comparable, and universally applicable (p. 10) framework to complement GDP. The expanded wealth framework IISD applies in our work is just that. Based on the global comprehensive/inclusive wealth frameworks developed by the World Bank and the UN Environment Programme, this robust framework complements GDP by measuring the assets that underpin well-being in all its forms: economic, environmental, and social. Our country partners understand the utility of the framework and are working with us to implement it using country data and expertise. We have modified the global methods used by the World Bank in ways that will ensure comparability and universal applicability—for example, by simplifying the approach to measuring human capital and produced capital.

The three coutries are using a simplified method of estimating the value of produced assets. This method builds on guidance for measuring capital stocks from the Organisation for Economic Co-operation and Development (OECD) and uses basic data on fixed capital formation available in essentially all countries. As such, it effectively leverages what already exists. Data for fixed capital formation in major economic sectors were readily available in all three countries for at least a 20-year time horizon. Using OECD methodological guidance, these data were readily converted to the time series of stock values required to measure wealth.

Second, the Secretary-General emphasizes that any framework to measure beyond GDP must be country owned (p. 10). Our wealth framework is being applied in three countries with very different development priorities, challenges, and data availability. Nevertheless, robust estimates have been produced for all three countries by national experts using national data. The results reveal useful insights in each. To help build country ownership, IISD provides guidance and quality control while leaving the estimation work to country experts. These experts are responsible for liaising with national statistical offices, central banks, and other data providers to collect data, calculate indices, prepare reports, and consult on policy recommendations. The IISD team provides support and arranges peer-support meetings between the country experts. The approach has been strongly collaborative from the start, with the goal of ensuring country ownership of the methods and results in the end.

Third, the Secretary-General suggests that measuring beyond GDP should be “iterative and dynamic, based on what exists, while allowing for the addition of new indicators” (p. 10). By building upon the World Bank’s and UN Environment Programme’s efforts to measure expanded wealth indicators, IISD is already applying this guidance in its efforts to go beyond GDP. 

Finally, the Secretary-General also stresses that any framework intended to complement GDP should convey strong and clear messages that are actionable and intuitive (p. 10). IISD’s collaborative approach to building expanded wealth measures provides useful insights for the countries involved. It helps them build the capacity that will inevitably be needed if countries are to move beyond GDP. Our experience shows that data collection, estimation, and interpretation will consist of a multi-year effort.

While it is important to understand the concepts and rationale for this work, many of the specific challenges in national application only become evident through “doing.” IISD’s engagement with country partners has, so far, lasted 4 years and involved more than 14,000 hours of technical support. Our experience shows that with support, countries can produce expanded wealth measures. Over time, countries will be able to produce this data on their own—just as they do for GDP. But reaching that goal will require targeted long-term support and guidance so countries can gain the experience they need.

Belmont University’s Innovation Labs Partners with TBN

This funding allows the Innovation Labs, established in 2022, to work alongside the Transformational Business Network (TBN), creating the Transformational Business Network Alliance. This strategic partnership will enable both organizations to expand their support for social entrepreneurs and innovators in developing regions around the world. By leveraging their combined resources and expertise, the Transformational Business Network Alliance aims to foster sustainable economic growth and social impact through the promotion of innovative, ethical business models.

Encouraging Development and Reducing Poverty

The objective of this collaboration is to encourage human development and reduce poverty in economically disadvantaged and underserved areas through business-focused solutions. By engaging in these partnerships, organizations aim to foster sustainable economic growth and create meaningful employment opportunities for local communities. Not only do these business-driven approaches empower individuals, but they also contribute to the overall advancement of the regions involved, ultimately leading to a higher quality of life and greater social equity.

Ambitious Goals for the Next Five Years

In the coming five years, the TBN Alliance aspires to initiate approximately 1,800 ventures, generating nearly 11,850 new employment opportunities in frontier and burgeoning markets around the globe. To achieve this ambitious goal, the TBN Alliance will focus on partnering with local entities, fostering innovation, and providing resources to assist in the development and growth of these ventures. Their emphasis on sustainability and social impact will in turn contribute to the overall improvement of the communities involved, resulting in long-term benefits and economic growth.

Startups Addressing Poverty and Fostering Local Entrepreneurship

These startups will strive to tackle poverty by generating jobs, providing essential goods and services, developing affordable innovations, and testing solutions in smaller communities. A crucial aspect of these startups’ initiatives includes addressing the specific needs and challenges faced by impoverished communities while simultaneously fostering local entrepreneurship and self-reliance. By emphasizing sustainability and long-term development, these innovative companies aim to create a meaningful impact on the lives of millions of individuals and contribute to breaking the cycle of poverty.

TBN’s Track Record of Success

Since its inception in 2003, TBN has assisted over 800 entrepreneurs and set up 429 ventures in Asia, Africa, Indonesia, and the Americas, enabling them to positively impact their local communities and contribute to the global economy. These ventures have helped create sustainable job opportunities, enhance skill development, and provide access to essential services for millions of people in these regions.

Innovation and Empowerment in Current Projects

Successful projects like Kopernik, Agape, and Bawa Hope are already making a notable difference. These innovative initiatives have not only brought forth sustainable solutions to some of the most pressing global problems, but they have also empowered grassroots communities to actively participate in their own development and growth. Through continued collaboration and perseverance, the success of these projects has the potential to inspire and pave the way for even more impactful and transformative efforts in the future.

Facilitating Economies of Scale and Accelerated Innovation

This partnership between Belmont Innovation Labs and TBN will facilitate economies of scale through the combined expertise and resources of both organizations. As a result, businesses and startups can anticipate accelerated innovation, reduced operational costs, and increased competitiveness within their respective industries.

Supporting Businesses Addressing Social Issues Globally

Through this initiative, businesses tackling social challenges, such as education, healthcare, and poverty alleviation, will receive crucial funding and resources to expand their impact. By facilitating partnerships between these businesses and key stakeholders, the aim is to foster sustainable development and empower underprivileged communities worldwide.

Frequently Asked Questions

What is the purpose of the Belmont University’s Innovation Labs and TBN partnership?

The purpose of this collaboration is to create the Transformational Business Network Alliance, which aims to encourage human development, reduce poverty, and foster sustainable economic growth in economically disadvantaged and underserved areas through business-focused solutions.

What are the goals of the TBN Alliance for the next five years?

In the coming five years, the TBN Alliance aims to initiate approximately 1,800 ventures, generating nearly 11,850 new employment opportunities in frontier and burgeoning markets around the globe.

How do startups contribute to poverty reduction and local entrepreneurship?

Startups help tackle poverty by generating jobs, providing essential goods and services, developing affordable innovations, and testing solutions in smaller communities. They address the specific needs and challenges faced by impoverished communities while fostering local entrepreneurship and self-reliance.

What is TBN’s track record of success?

Since 2003, TBN has assisted over 800 entrepreneurs and established 429 ventures in Asia, Africa, Indonesia, and the Americas. These ventures have created sustainable job opportunities, enhanced skill development, and provided access to essential services for millions of people in these regions.

What are some examples of successful projects?

Successful projects like Kopernik, Agape, and Bawa Hope have brought forth sustainable solutions to global problems and empowered grassroots communities to participate in their own development and growth.

How does this partnership facilitate economies of scale and accelerated innovation?

This partnership combines the expertise and resources of both Belmont Innovation Labs and TBN, enabling businesses and startups to anticipate accelerated innovation, reduced operational costs, and increased competitiveness within their industries.

How are businesses addressing social issues globally supported by this initiative?

Through this initiative, businesses tackling social challenges, such as education, healthcare, and poverty alleviation, will receive crucial funding and resources to expand their impact. By facilitating partnerships between these businesses and key stakeholders, the aim is to foster sustainable development and empower underprivileged communities worldwide.

First Reported on: pridepublishinggroup.com

The post Innovation Lab Sets Up Global Entrepreneurs for Social Impact appeared first on Under30CEO.

My name is Michael Wanjuzi Makongo. I am a farmer and climate change activist who is deeply passionate about the environment. I am also a Laudato si’ Animator in Uganda. Laudato si’ Animators are part of a global movement dedicated to caring for God’s creation by following the Encyclical teachings of the Pope and LSA chaplet. Based on prayer and advocacy, Animators lead their global communities to sustainable action.

In my position, I go to churches and encourage Christians to be environmental stewards through practice and dialogue. Nangalwe Catholic Church in the Manafwa district of Uganda’s Eastern Region is very active in restoration and tree planting in the community. By planting these trees, we hope to restore balance to the ecological imbalances brought about by climate change.

I also make sure schools and other community members are not left behind. For Sikusi Primary School, we made a community nursery bed where all members can participate in environmental protection and also recite the Encyclical teachings of Pope Francis. The community bed specialized in Hass Avocado trees with a variety of other species. We have some challenges as we go through our daily activities, like pests and diseases and climate change, but we keep moving forward with the job at hand. It is a learning process for the children in schools, church members, and the locals who visit the nursery bed from time to time. 

In 2020, Manafwa District and I registered our tree planting goals on the UN Partnership Platform. This is a global registry of multi-stakeholder partnerships committed to promoting the SDGs in their communities. The goals we set on the platform focused on environment restoration by growing trees to help with climate change mitigation and community improvements. We accomplished a lot and also planted trees whose fruit will be sold to improve household income.

Laudato si’ is a moral charter for sustainable development. It is a mindset change towards the Environment on which we can take collective action that will bring foundational change to society and the entire Environment. Thanks to the message and resources I received in the course, I am equipped to speak up when things are not going well and take action. I can mobilize the community to protect Mother Nature in accordance with the Laudato si’ Movement. To learn more about Manafwa District’s goals, check out our partnership platform.

Thank you.  

https://climateactionproject.org/profile/MichaelWanjuzimakongo28681 

If you find yourself using the terms ESG and impact investing interchangeably, you’re not alone. Some of the smartest and most sophisticated educators and investors in the world have trouble distinguishing between the two. And these are people overseeing billions, if not trillions of dollars, collectively. 

Coined in 2004, ESG emerged as a joint effort by the UN, the International Finance Corporation (IFC), and the Swiss Government to support the financial industry’s consideration of ESG issues in mainstream investment decision-making (although its roots exist in the socially responsible movement or SRI). This is not surprising given that much of the underlying progress in socially- or environmentally-focused investing over the last 15 years has been driven by governments, particularly those in the EU and the UK. (Sorry, but the US didn’t catch on until 2011.)

Impact investing, on the other hand, wasn’t coined until 2007 when the Rockefeller Foundation, along with other philanthropists, investors, and entrepreneurs, put a name to investments made with the intention of generating measurable social impact alongside a financial return. This group would go on to found the Global Impact Investing Network (GIIN), the leading network of practitioners promoting the infrastructure, research, and education around impact investing. 

Thus, while ESG was ushered in by the public sector, impact investing evolved through efforts by the private sector. As a result, ESG attempts to serve as a guideline for public understanding of environmental, social, and governance factors, while the for-profit nature of impact serves as an incentive to act in favor of and drive capital toward these interests.

Three principles define impact investing: first, there must be an expectation of financial return alongside social and/or environmental impact (or at least a return on capital); second, the change sought—typically social or environmental—must be intentional; and third, there must be an attempt to measure the change.

With that context, let’s consider six additional ways ESG and impact investing are different:

1. ESG is a framework. Impact investing is a strategy.

ESG is a construct for helping stakeholders understand how an organization manages risks and opportunities around sustainability issues. However, it tends to be based on backward-looking measures resulting from the normal course of business. That’s not to say that the measures can’t be used to inform future business decisions, but they are generally more of an assessment or scorecard of past activity.

Impact, on the other hand, is forward-looking. It is a strategy used to define the types of investments an investor is targeting. In fact, one of the core principles of impact investing is intentionality, or an explicit aim to generate measurable social or environmental benefit. Generally, this translates to an alignment with one or more of the UN Sustainable Development Goals as a cornerstone of the investment strategy. The results are targeted performance metrics that are measured against stated objectives, which ultimately hold investors accountable. Indeed, intentionality is a first line of defense against impact-washing or false claims about an investment’s impact.

2. ESG faces fiduciary scrutiny. Impact does not.

As a lens for addressing social and environmental issues, ESG requires discretion by asset managers in its application. For example, an existing multi-billion dollar pension fund feels pressure to invest with an ESG lens. However, there is no single interpretation of ESG factors or end result of that application. This becomes a problem because fiduciary law requires that a trustee act solely in the interests of the beneficiary. As a result, as Max Schanzenbach and Robert Sitkoff wrote for Stanford Law Review, the duty of loyalty is violated if the application of ESG factors was based on the manager’s “own sense of ethics or to obtain collateral benefits for third parties” rather than in the best interest of beneficiaries.

 As an investment strategy, impact does not face the same scrutiny because funds employing this approach stand alone. In other words, investors opt into these funds knowing the investment manager’s intentions before investing.

3. ESG can be risk-mitigating or an opportunity. Impact is both.

As a systematic approach to assessing an organization’s level of effectiveness in environmental, social, and governance performance, ESG can be used to mitigate risk by helping investors exclude or screen investments in companies that don’t adhere to pre-existing standards. This includes particular countries, sectors, companies, or even performance or impact metrics. For example, a company or country with low or nonexistent labor standards would likely preclude investment by an ESG-focused fund. Alternatively, a company with exceptionally high labor standards within a country of typically low labor conditions would be an opportunity to support environmental and social progress in that country. In this instance, that company would make an excellent ESG investment based on standards already in place that had already been reported upon.

 An impact investor, meanwhile, would look to the future—at the opportunity that lies ahead. This might be a private company looking to establish better labor conditions within a country where labor standards are quite low. In this instance, an impact investor has few, if any, data points from which to work. As a result, they must rely on existing or emerging research to help guide their social and environmental considerations. Further, research suggests that investment decisions made incorporating social and environmental factors translate to higher company valuation and performance, both through systematic risks that affect the market as a whole and idiosyncratic risks endemic to a particular asset. Thus, companies failing to manage these risks may have higher costs of capital, more volatility, and accounting irregularities.

4. ESG is generally a financial-first framework. Impact investing generally equally weights financial, social, and environmental impact.

Due to the ex post nature of ESG measures, the primary source of value for ESG-focused investors is financial return (and arguably should be, based on fiduciary duty). This is because environmental and social benefits are evaluated after an investment is made although, again, these measures can be used to inform future investments.

Impact investments, on the other hand, take all three financial, social, and environmental benefits into consideration, and may even prioritize social and environmental benefits early on in an investment as long as financial returns are positive. Further, impact investors recognize that financial and social/environmental performance are often interconnected and mutually reinforcing—a principle known as collinearity. Through this lens, impact investing is not concessionary; rather, it is a driver of financial performance.

5. ESG-focused investments are primarily public market entities. Impact investments are primarily private market entities. But could that change?

Because ESG measures rely on publicly reported data, ESG-focused investments tend to exist within the public markets. Any company can receive an ESG rating—even a negative one—as long as data is available to examine the company.

Impact investments have historically taken place in the private markets, where innovative approaches to some of the world’s greatest problems often require sophisticated and patient capital as well as active engagement in promoting responsible business and sustainable value. However, the natural progression of the startup financing cycle has resulted in more impact investments going public (for example, Oak Street Health, Acciona Energia, and PowerSchool). And while research notes the difficulty of achieving additionality—an outcome that would not have occurred without that capital—in the public equity markets due to market efficiencies, Impact Management Project suggests that the prospect of systems change could accelerate growth in the number of investors strategically “signaling that impact matters.”

6. All impact funds are ESG-compliant, but not all ESG funds are impact.

It’s impossible to incorporate the future into the past but it is essential to use the past to inform the future. Because impact investing is inherently forward-looking, it is possible if not best practice to incorporate ESG-focused findings into future investments. The same cannot be said of ESG funds, which focus on activity that has already occurred. 

For example, an ESG framework might generally prevent investment in companies that produce significant greenhouse gas emissions. An impact fund, however, may only invest in companies actively helping to reduce them. As a result, all impact investors integrate ESG factors into their investment process.

Despite continued efforts by impact market participants to define impact investing’s purpose and goals, many definitions of impact continue to exist. For example, are diverse-led non-impact companies defined by impact? Supporting diverse founders seems to be a goal of impact investing, but where does one draw the line, and more importantly, how does one measure the impact goals of investors relative to the impact of underlying businesses? Before we can delve deeper into what impact investing is, it’s important to understand what impact investing is not.

Too often, ESG is confused with impact investing, which obscures the enormous efforts of the impact investing space. Understanding the difference not only facilitates better-informed conversations but helps channel funds appropriately and further amplifies the progress of the sector toward achieving the audacious Sustainable Development Goals (SDGs) by 2030.

There is little doubt that the future of both business and finance incorporates social and environmental considerations. At the same time, the symbiotic relationship between these benefits and financial performance ensures the sustainability of purpose-driven organizations. Having the knowledge to differentiate between what lies in the past and what is part of our future is essential in ensuring the success of our people and planet.