Does intellectual property rights protection help reduce carbon emissions?

In the face of increasingly severe environmental challenges today, particularly issues related to global warming and glacier melting, scholars have extensively explored methods to reduce carbon emissions (CE) to promote sustainable development. A substantial body of research suggests that improving energy structure (ES) and technological progress (TP) are crucial pathways to achieving carbon reduction. As a key factor influencing innovation and social development, intellectual property rights protection (IPRP) is also an indispensable part of the global economy. However, over the past few decades, many countries have faced varying degrees of intellectual property infringement issues. With the international community’s collective efforts to reduce CE continuously strengthening, gaining a deeper understanding of the impact and mechanisms of IPRP on CE is of paramount importance for achieving global decarbonization goals. Existing research largely emphasizes the innovation and growth effects of IPRP, with mixed views on whether stronger IPRP helps or hinders innovation in developing economies where imitation can be a growth engine. Environmental impacts of IPRP, particularly on CE, remain underexplored, with mixed evidence from country- or region-specific studies. This study fills these gaps by adopting a global perspective using unbalanced panel data for 116 countries (2008–2020) to assess how IPRP affects CE, uncover the mechanisms (via ES, TP, and economic growth, EG), and examine moderating effects of political stability (PS) and potential nonlinearities. We find that increases in IPRP are associated with increased CE, challenging the notion that IPRP unconditionally promotes environmental sustainability. Mechanistically, IPRP indirectly promotes CE growth by inhibiting ES improvement and by steering TP toward profitability rather than environmental sustainability; IPRP also indirectly increases CE via EG. Political stability mitigates the positive impact of IPRP on CE. Lastly, we uncover an inverted U-shaped relationship between IPRP and CE, with a turning point beyond which stronger IPRP suppresses CE.

The literature articulates several channels through which IPRP may influence carbon emissions. On one hand, IPRP can incentivize eco-innovation and the development of clean technologies by enabling innovators to appropriate returns (e.g., Popp 2010; Hall and Helmers 2013), potentially reducing CE over time as clean technologies diffuse and costs decline. On the other hand, market incentives may bias innovation towards profitable high-carbon technologies; patent thickets and higher licensing costs can restrict diffusion of green technologies, particularly in developing countries, leading to higher CE. The Environmental Kuznets Curve (EKC) framework suggests that the environmental impact of economic drivers, including IPRP, may be nonlinear: initial phases may see rising emissions, followed by reductions after a threshold as preferences and technologies shift. The study develops and tests the following hypotheses: - H1a: IPRP promotes an increase in CE. - H1b: With the expansion of IPRP, its impact on CE shifts from positive to negative (inverted U-shaped relationship). - Mediating effects: Energy structure (ES), technological progress (TP), and economic growth (EG) may mediate the IPRP–CE relationship. - H2a: IPRP indirectly reduces CE by improving ES. - H2b: IPRP indirectly increases CE by inhibiting ES improvement. - H3a: IPRP reduces CE by fostering TP that lowers emissions. - H3b: IPRP increases CE by fostering TP that raises emissions (e.g., efficiency gains in high-carbon sectors, diffusion constraints). - H4a: IPRP indirectly reduces CE by promoting EG that supports cleaner production. - H4b: IPRP indirectly increases CE by promoting EG in high-carbon sectors. - Moderation: Political stability (PS) may strengthen environmental governance and clean technology diffusion. - H5: PS reduces the promotive effect of IPRP on CE. The review highlights institutional disparities between developed and developing countries: stronger IPRP and governance in high-income contexts can support green innovation and diffusion, whereas weaker institutions and greater reliance on fossil-intensive growth in lower-income contexts may cause stronger IPRP to amplify CE. These insights motivate a global, mechanism-rich, and nonlinear empirical assessment.

Data and sample: Unbalanced panel of 116 countries from 2008 to 2020. Variables (mostly log-transformed except ratio-type variables); robust standard errors clustered at the country level; country and period fixed effects. Models: - Baseline fixed-effects model: CE_it = β0 + β1 IPRP_it + Σ β2 Controls_it + μ_i + γ_t + ε_it, where CE is carbon emissions, IPRP is intellectual property rights protection, Controls include trade openness, industrial structure, urbanization, and economic growth; μ_i and γ_t denote country and time effects. - Mediation models (Baron & Kenny causal steps) for mediators M ∈ {ES, TP, EG}: (1) CE_it = α0 + α1 IPRP_it + α2 Controls_it + μ_i + γ_t + ε_it (2) M_it = b0 + b1 IPRP_it + b2 Controls_it + μ_i + γ_t + ε_it (3) CE_it = c0 + c1 IPRP_it + c2 M_it + c3 Controls_it + μ_i + γ_t + ε_it - Moderation model for political stability (PS): CE_it = β0 + β1 IPRP_it + β2 PS_it + β3 (IPRP_it × PS_it) + Σ β4 Controls_it + μ_i + γ_t + ε_it. Variable construction and sources: - Dependent variables (CE): Total carbon emissions (TCE, log) and carbon emissions per capita (CEP, log), World Bank. - Core explanatory variable (IPRP): Intellectual Property Rights Protection index from the International Property Rights Index (IPRI) by the International Property Rights Alliance. - Mediators: - ES: Share of renewable energy consumption in total energy consumption, World Bank. - TP: R&D activity index from UNCTAD’s Frontier Technology Readiness Index (publications and patenting in 11 frontier technologies). - EG: GDP per capita (constant 2015 US$, log), World Bank. - Moderator: PS measured by the World Bank’s Political Stability and Absence of Violence index (higher is more stable). - Controls: Trade openness (trade/GDP), industrial structure (share of secondary industry in GDP), urbanization (urban population share), and economic growth (GDP per capita), all primarily from the World Bank. Estimation details and diagnostics: - Fixed-effects chosen per Hausman tests; variance inflation factor (VIF) test indicates no severe multicollinearity (max VIF = 5.72). - Robustness checks: (i) Alternative IPRP measure (World Economic Forum); (ii) Alternative dependent variable: CO2 emissions per 2015 US$ of GDP; (iii) Excluding post-2018 observations to mitigate COVID-19 impacts; (iv) Endogeneity addressed via 2SLS using instruments: Rule of Law (World Bank) and lagged IPRP (L.IPRP). Under-identification, weak identification, and Sargan tests support instrument validity. - Nonlinearity: Quadratic term of IPRP (IPRP^2) included to test for inverted U-shape; turning point calculated and marginal effects plotted.

• Baseline effects: IPRP is positively and significantly associated with CE. In fixed-effects models with full controls, IPRP coefficients are 0.273 (TCE) and 0.261 (CEP), both significant at the 5% level, supporting H1a. Urbanization and EG are also positively associated with CE. Hausman tests favor fixed effects; VIF indicates no severe multicollinearity (5.72). - Robustness: Results hold when using alternative IPRP measures, alternative CE measures (CO2 per GDP), excluding post-2018 data, and when addressing endogeneity with 2SLS (instruments: Rule of Law and lagged IPRP). Instrument relevance and validity tests (under-identification, weak identification, Sargan) indicate credible identification. - Heterogeneity (by income groups): Interaction results show that higher IPRP is associated with lower CE in high-income countries (HIC) and (for TCE) upper-middle-income countries (UMIC), but higher CE in lower-middle-income countries (LMIC). For example, interaction coefficients: IPRP×HIC −0.492** (TCE), −0.427** (CEP); IPRP×UMIC −0.498** (TCE); IPRP×LMIC +0.498** (TCE). - Mediation (mechanisms): • IPRP → ES: −0.411** (significant negative); ES → CE: −0.244*** (TCE, CEP), indicating that stronger IPRP suppresses ES improvement, which in turn increases CE (supports H2b). • IPRP → TP: +0.060**; TP → CE: +0.529** (TCE), +0.261* (CEP), indicating that IPRP fosters TP that, on balance, raises CE (supports H3b). • IPRP → EG: +0.229***; EG → CE: +0.492** (TCE), +0.591*** (CEP), indicating IPRP increases CE indirectly via EG (supports H4b). - Moderation by political stability (PS): The interaction IPRP×PS is negative and significant: −0.267** (TCE), −0.214** (CEP), indicating PS mitigates the positive effect of IPRP on CE (supports H5). - Nonlinear relationship: Adding a quadratic term yields IPRP coefficient 1.745** and IPRP^2 coefficient −0.497**, evidencing an inverted U-shaped relationship between IPRP and CE (supports H1b). The turning point is approximately IPRP ≈ 1.8 (within the observed range), implying IPRP initially increases CE, but beyond the threshold, further strengthening of IPRP reduces CE. - Overall: Globally, current IPRP levels tend to elevate CE through delayed ES transition and by channeling TP and EG toward carbon-intensive paths. However, with stronger IPRP and supportive institutions (e.g., higher PS), the relationship can turn favorable to emission reductions.

The study addresses the central question of whether stronger IPRP reduces carbon emissions by revealing a nuanced, context-dependent relationship. Empirically, IPRP is associated with higher CE at prevailing global levels, primarily via three mechanisms: (1) it slows improvements in energy structure by raising costs and barriers to green technology access and diffusion; (2) it fosters technological progress that is often directed toward profitable, high-carbon applications; and (3) it promotes economic growth that, in many countries, remains carbon intensive. These results reconcile conflicting accounts in the literature by demonstrating that IPRP’s environmental impact depends on development stage, institutional capacity, and the direction of innovation. Political stability weakens the positive IPRP–CE linkage, consistent with the view that stable institutions can enforce environmental regulations, support long-term green R&D, and facilitate international cooperation and technology transfer. The inverted U-shaped relationship adds a dynamic perspective: early strengthening of IPRP coincides with higher CE as firms scale and optimize incumbent high-carbon technologies; beyond a threshold, further IPRP can enhance green innovation, diffusion, and policy coherence sufficiently to reduce CE. Heterogeneity across income groups underscores the role of institutional quality and industrial structures: high- and upper-middle-income countries are better positioned to translate IPRP into cleaner outcomes, whereas lower-middle-income countries may experience heightened emissions without complementary policies.

Using panel data from 116 countries (2008–2020), the study finds that intellectual property rights protection generally increases carbon emissions at prevailing global levels. Mechanism analyses show that IPRP indirectly raises emissions by suppressing improvements in energy structure and by fostering technological progress and economic growth that are, on balance, carbon-increasing. Political stability mitigates these adverse effects. A nonlinear, inverted U-shaped relationship emerges: IPRP initially raises CE, but after a turning point, stronger IPRP can reduce CE. Policy recommendations include: (1) incorporate explicit incentives for environmental technologies in IP frameworks (e.g., expedited examination, fee reductions for low-carbon innovations); (2) expand funding, subsidies, and tax incentives to accelerate renewable energy R&D, commercialization, and market penetration; (3) align environmental regulations with IP policy (e.g., stricter scrutiny for environmentally harmful technologies); and (4) strengthen international cooperation and technology transfer, especially for developing countries, including simplifying IP/technology transfer and providing technical and financial support. These steps can help reconcile innovation incentives with global decarbonization objectives.

The study’s measures of core constructs such as IPRP and CE are constrained by data availability and quality, potentially affecting precision. The moderating variables (e.g., political stability) embody complex, multifaceted dynamics that are difficult to fully capture and may vary across countries and over time. The global sample is unbalanced, and some country-year observations are missing. While multiple robustness checks and instrumental-variable strategies were employed, residual endogeneity cannot be fully ruled out. Future research should refine measurement, consider additional institutional moderators, and focus on rapidly changing economies (e.g., emerging markets) to further elucidate context-specific dynamics.