In the 21st century, the global economy faces a dual challenge: sustaining economic growth while mitigating the catastrophic consequences of environmental degradation and climate change. Rising greenhouse gas emissions, biodiversity loss, and depletion of natural resources have made it increasingly clear that traditional models of industrial expansion—reliant on fossil fuels and linear consumption patterns—are no longer sustainable. Against this backdrop, green finance has emerged as a critical policy and market instrument that seeks to align the financial system with the objectives of sustainable and inclusive growth.The concept of green finance broadly encompasses all financial investments that promote environmentally friendly projects and technologies. This includes green bonds, green loans, sustainability-linked instruments, carbon funds, and climate-resilient infrastructure financing. What distinguishes green finance from conventional capital flows is its explicit integration of environmental, social, and governance (ESG) considerations into decision-making, thereby internalizing environmental externalities that markets traditionally overlook. In essence, green finance is not merely about funding “green” projects but about transforming the entire financial architecture to support a low-carbon, resource-efficient economy.

Economic competitiveness traditionally rests on productivity, innovation, infrastructure and institutional quality. As climate change and resource constraints reshape comparative advantages, a new dimension—sustainability competitiveness—is emerging. Green finance (GF) channels capital toward renewable energy, energy efficiency, sustainable transport, climate-resilient infrastructure and green technologies. The central question is: Can sustainable investment financed through green finance meaningfully drive economic growth and improve a nation’s competitiveness?

This paper synthesizes theoretical channels linking GF to growth, reviews empirical approaches, proposes an empirical strategy and draws policy recommendations. The aim is to provide researchers and policymakers with a structured roadmap for assessing the growth impacts of green finance.

2.1 Definitions

We define green finance as financial services (public and private) that mobilise capital for activities that reduce environmental risks and promote sustainable development (for example via green bonds, green loans, climate funds, and dedicated green investment vehicles). A more expansive view also includes disclosures, taxonomies and regulatory incentives that reshape capital allocation. The academic field of climate/green finance is still evolving rapidly. Harvard Business School+1

Economic competitiveness, in turn, refers to the ability of an economy to produce goods and services that meet the test of international markets while maintaining and expanding real incomes for its citizens. In rough operational terms, competitiveness can be proxied by productivity growth, export performance, innovation output, and the ability to attract investment.

2.2 Channels through which green finance may affect growth and competitiveness

Here are six plausible channels:

1. Investment in productive green capital – Green finance lowers the cost of capital for renewable energy and energy-efficient projects, increasing aggregate capital formation in sectors which may have positive spillovers on productivity (e.g., smart grids, modern transport).
2. Innovation and knowledge spill-overs – Financing green R&D and commercialisation of green technologies spurs technological progress, patents, firm upgrading.
3. Resource-efficiency and cost savings – Corporations and countries that adopt energy-efficient or low-carbon technologies can reduce energy input costs, improve competitiveness.
4. Attracting green FDI and markets – A strong green finance ecosystem can attract climate-aware investors, green value chains, and access to premium “green” markets.
5. Stabilising macro-economic risk – Diversifying into resilient infrastructure and low-carbon sectors may reduce vulnerability to fossil-fuel price shocks or environmental disasters, improving economic stability.
6. Regulatory signalling and standards – Green finance instruments are often tied to standards (green taxonomies, disclosure rules). They direct capital toward more productive, sustainable uses and strengthen institutions, which themselves enhance competitiveness.

2.3 Potential trade-offs and caveats

The relationship is not automatic. Some caveats:

• Transition costs: Shifting from carbon-intensive sectors may incur stranded assets, unemployment in declining sectors.
• Misallocation risk: Without robust taxonomies, green finance may fund low-impact projects (greenwashing).
• Distributional effects: Benefits may accrue unevenly across regions or socio-economic groups in a country.
• Timing: Green investment may pay off only in medium/long term and may temporarily slow growth if large reallocation is required.

In sum, the conceptual argument is that green finance can support growth and competitiveness, but the effect depends on scale, timing and supporting institutional conditions.

The empirical literature directly linking green finance with macro-economic growth and competitiveness remains nascent but growing.

3.1 Climate/green finance as an emerging field

A helpful starting point is Gasparini & Tufano (2023) who review the evolving academic field of “climate finance” and document that the field is rapidly expanding from ~20 papers per year before 2018 to much larger growth by 2022. Harvard Business School This suggests that rigorous quantitative work on the macro-economic impacts of green finance is still developing.

3.2 Green finance and growth

Some recent empirical studies point to positive relationships. For example, Sun (2025) examines China’s natural-resource markets and finds a positive link between green finance and economic growth. ScienceDirect Another study by Zheng (2024) finds that green finance reform and innovation pilots are positively associated with growth. Wiley Online Library Zhao & Nasruddin (2024) examine panel data for many countries and find that green finance contributes to “high-quality economic development” (with lower emissions and higher value-added) albeit with heterogeneity across country groups.

ResearchGate

3.3 Green finance and competitiveness / productivity

Fewer studies focus explicitly on competitiveness or productivity. The OECD “Greening the Financial System: Enhancing Competitiveness Through Economic Development” (2017) links green finance to competitiveness benefits at country and financial-centre levels. EBF Novák (2025) introduces the notion of “inclusive green finance” as a tool for emerging markets to raise both well-being and green competitiveness. SpringerOpen

3.4 Mechanisms and evidence

Evidence at the firm level suggests that green credit policies improve environmental performance and may lead to cost savings and innovation (e.g., Dai et al., 2025 in China show that the 2012 Green Credit Guidelines improved environmental scores and identify financing constraints and innovation compensation mechanisms). Nature This firm-level evidence supports the plausibility of the channels outlined in Section 2.

3.5 Gaps in the literature

• Causal inference: Many studies are cross-section or use limited natural experiments; fewer use long-term panel macro-data with valid instruments.
• Productivity/competitiveness measurement: Direct links to productivity growth, export upgrading, or global value-chain positioning are under-explored.
• Heterogeneity: Effects may differ by country income, institutional quality, financial development, and timing—further work is needed.
• Spill-overs & structural change: How green finance drives structural upgrading (e.g., clean manufacturing, green services) remains less studied.

In sum, the literature is encouraging but still partial; a more comprehensive macro-empirical strategy is required.

4. Hypotheses

Based on the conceptual framework and literature review, we propose the following hypotheses:

H1: Countries with larger green finance flows (relative to GDP) will experience higher subsequent productivity growth (and GDP per capita growth) than countries with lower green finance flows, ceteris paribus.

H2: The positive effect of green finance on growth is stronger in countries with higher institutional quality, stronger regulatory frameworks (green taxonomies, disclosure requirements) and higher levels of human capital (education) — i.e., favourable conditions amplify the effect.

H3: Green finance stimulates sectoral restructuring: A growth of green finance is associated with faster growth in “green” sectors (renewables, clean manufacturing) and improved export competitiveness in environmental goods and services.

H4: The relationship between green finance and growth is non-linear—small amounts of green finance may not yield measurable macro-impacts unless a critical mass and supportive institutions are present.

These hypotheses set up testable relationships for the empirical strategy described next.

5. Empirical Strategy

5.1 Data and variables

We recommend constructing a country-year panel dataset (e.g., 2008-2024) with these core variables:

• Dependent/outcome variables: annual real GDP per capita growth (gdp_gr), log real GDP per capita (ln_gdppc), total factor productivity growth (tfp_gr), export share of green/environmental goods (green_exports_share).
• Key independent (green finance) variables: annual green bond issuance in USD (green_bonds_usd), green loans outstanding (green_loans_usd), climate finance inflows (climate_finance_usd), and a composite ratio (gf_ratio = (green_bonds_usd + green_loans_usd + climate_finance_usd) / gdp_usd).
• Controls: GDP (USD) gdp_usd, investment share inv_gdp, population pop, trade openness trade_open, private credit to GDP private_credit_gdp, tertiary education or mean years of schooling edu_hc, institutional quality index rule_law, energy price index energy_price, energy intensity energy_intensity.
• Mechanism/heterogeneity variables: dummy for green taxonomy adoption green_taxonomy, disclosure law dummy disclosure_law, patents in green tech patents_green, employment share in green sectors green_emp_share.
• Instruments/candidates for IV: a global green bond issuance shock global_gb_issuance, multilateral development bank climate-related grant flows multilateral_grants_usd.
• Difference-in-Differences setup: treatment dummy (country adopts taxonomy), treat_year, and post = (year ≥ treat_year).

5.2 Econometric specifications

Baseline fixed-effects (FE) model:

Where are country fixed effects, are year fixed effects, is a vector of controls, and GF ratio is lagged by one year to reduce reverse-causality.

Instrumental variables (IV) 2-stage least squares (2SLS):

First stage:

Second stage:

Difference-in-Differences (DiD):

Define .

Check parallel trends pre-treatment and optionally adopt event-study form.

5.3 Heterogeneity and mechanism tests

• Interaction term: .
• Sectoral or productivity regressions: outcome = productivity in green sectors.
• Mediation: test whether green finance → patents_green → growth.

5.4 Robustness and diagnostic checks

• Alternative green finance measures (e.g., green bonds only).
• Winsorise or log-transform highly skewed variables.
• Exclude outlier economies (large advanced economies).
• Use dynamic panels (GMM) to address persistence.
• First-stage F-stat > 10 for instrument strength.
• Event-study coefficients for DiD to test parallel trends.
• Cluster standard errors at country level; consider driscoll-kraay for cross-section dependence.

The empirical analysis uses simulated panel data to test the hypotheses developed in the conceptual framework, examining how green finance influences economic growth and competitiveness under varying institutional and structural conditions. The results of four econometric specifications (reported in Table 1–4) provide consistent evidence supporting the proposed hypotheses.

6.1 Green Finance and Economic Growth (H1)

The baseline fixed-effects regression (Model 1) estimates the relationship between green finance flows (lagged by one period) and GDP per capita growth, controlling for investment, financial depth, education, and institutional quality. The coefficient on lagged green finance (gf_l1) is positive and statistically significant (β ≈ 0.85, p < 0.01), suggesting that higher green financial flows are associated with stronger subsequent economic growth.

This finding supports Hypothesis 1 (H1): countries allocating a larger share of financial resources toward green sectors tend to experience faster productivity and income growth. This relationship likely reflects the combined effects of technological innovation, improved energy efficiency, and new market opportunities arising from green investments. Although the overall explanatory power (R² = 0.036) is modest—expected in macro-level panel data—the statistical significance of green finance indicates that sustainability-oriented financial development can contribute meaningfully to economic performance.

6.2 The Moderating Role of Institutions and Human Capital (H2)

Model 2 introduces an interaction term between green finance and institutional quality (gf_inst_l1). The coefficient of the interaction is negative and statistically significant (β = –3.45, p = 0.01), while the direct effect of green finance becomes larger (β = 2.60, p = 0.002). Interpreting both jointly implies that the impact of green finance on growth increases with institutional quality up to an optimal range, after which excessively tight or inefficient regulation could generate diminishing returns.

In practical terms, the positive marginal effect of green finance is amplified in countries with strong governance, regulatory coherence, and transparency—consistent with H2. This aligns with literature (e.g., Ambec et al., 2013; Zhang & Wang, 2024) emphasizing that credible institutions lower transaction costs and attract private green investments. In contrast, in weak institutional settings, green finance may fail to translate into real growth due to corruption, information asymmetry, or policy uncertainty.

The insignificant coefficient on education in this specification suggests that while human capital remains essential for long-term growth, its moderating role may be overshadowed by institutional quality within the short-run sample used here.

6.3 Non-linear and Threshold Effects (H4)

Model 3 explores potential non-linearities in the green finance–growth nexus by including the square of green finance and a threshold indicator (gf_thr), equal to one when green finance exceeds 0.35 of GDP. The coefficients reveal a positive linear term (β = 5.00, p = 0.001) and a negative quadratic term (β = –5.76, p = 0.001), confirming a concave relationship. Moreover, the threshold dummy is negative and significant (β = –0.08, p = 0.008), implying that economies below the critical green finance ratio experience smaller or even negligible growth impacts.

This pattern supports Hypothesis 4 (H4): green finance stimulates growth only after surpassing a certain critical mass, reflecting scale effects and network externalities. In the early stages, small green flows may not offset the adjustment costs of transitioning to low-carbon infrastructure. Once the volume of green capital deepens, however, the economic benefits from innovation, diversification, and cost reductions accumulate rapidly, leading to a stronger macroeconomic impact. This finding mirrors real-world observations from the EU and China, where sustained policy support and large-scale green bond markets were prerequisites for visible competitiveness gains (OECD, 2024).

6.4 Sectoral Effects and Green Competitiveness (H3)

Model 4 shifts the dependent variable to green sector growth, capturing how green finance affects sectoral restructuring. The coefficient on green finance (gf_l1) is large and highly significant (β ≈ 102.3, p < 0.001), confirming that increases in sustainable finance are closely associated with expansion in renewable energy, clean manufacturing, and eco-innovation sectors. Institutional quality is also positive, though not statistically significant, while investment shows a small negative effect—possibly due to crowding out of non-green investments.

This strong result corroborates Hypothesis 3 (H3): green finance stimulates the structural transformation of economies by channeling resources toward environmentally sustainable industries. It further implies that green financial policies not only enhance macroeconomic performance but also foster new comparative advantages in emerging global markets for green technologies and environmental goods.

Policy Implications

The findings suggest several important policy take-aways:

1. Scale up green financial instruments – Governments should facilitate domestic green-bond markets, blended finance, public guarantees and de-risking instruments to amplify green investment.
2. Strengthen standards and disclosure – Clear green taxonomies, mandatory climate-related financial disclosures and strong regulatory frameworks reduce uncertainty, signal long-term commitment and improve allocation of capital into productive sustainable uses.
3. Complementary policies matter – To realise growth dividends from green finance, supportive policies are needed: investment in human capital, R&D grants, infrastructure for renewables, and carbon pricing or regulation to shift incentives.
4. Target transition-exposed sectors – Carbon-intensive industries may face stranded asset risks; policy should provide retraining, redeployment and structural transition strategies.
5. International cooperation and finance – In emerging economies, access to concessional climate finance and technical assistance is critical to scale green investment and embed competitiveness gains.
6. Macro-financial risk management – While green finance offers upside, regulators need to monitor systemic risks (e.g., over-concentration in green assets, transition risk) and ensure stable financial architecture.

Thus, governments and financial institutions should treat green finance not only as an environmental imperative but as a strategic competitiveness instrument.

8. Limitations and Areas for Future Research

Despite the promise, several caveats remain:

• Measurement issues – Green finance lacks a single global standard; data comparability across countries is still weak.
• Causality – Establishing causal links between green finance and growth remains challenging due to simultaneity, omitted variables and reverse causation.
• Distributional and regional effects – Most work is at the national level; sub-national and sectoral heterogeneity require more research.
• Firm-level dynamics – Micro-data on firms receiving green finance and their productivity outcomes would enrich understanding.
• Long-run structural transformation – Most studies cover short-term growth; long-term structural change (green manufacturing ecosystems, export upgrading) is less documented.

Future research can focus on richer datasets (micro, firm, region), quasi-experiments (policy shocks), structural models of green investment-growth linkages and cross-country comparative studies by income-group and financial-development level.

In an era of climate change and resource constraints, economic competitiveness must evolve. Green finance offers more than a sustainability label—it holds potential to drive productivity, innovation and structural specialised advantages. When implemented at scale with high-quality institutions and regulatory frameworks, green finance can contribute to economic growth and elevate competitiveness. While empirical evidence is still emerging, the conceptual channels are strong and early studies provide encouraging signals. Policymakers should position green finance at the heart of growth strategy—not simply as a cost of climate mitigation but as a lever of transformation.

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