Renewable energy (RE) innovation as a trade driver: a causal analysis of developed and developing countries Open Access

In this era of rapid technological advancement and interconnected economies, technological innovation plays a crucial role in the renewable energy (hereinafter, RE) transition, providing a viable pathway to reduce greenhouse gas (GHG) emissions and achieve net-zero targets. In response to the COP21 Paris Agreement and increasing climate challenges, industries worldwide are undergoing a sustainable transformation (Cao et al., 2024a; Kang and Park, 2023). Environmental policies such as Emissions Trading Systems (ETS), the EU Carbon Border Adjustment Mechanism (CBAM), and carbon taxation mechanisms are not only driving sustainability efforts but also reshaping global trade patterns as firms and governments adapt to stricter regulations and seek competitiveness in the rapidly growing RE market (Ambroziak et al., 2022; Dhayal et al., 2024).

The global push for RE adoption has accelerated both RE innovation and RE trade growth. According to the International Energy Agency (IEA) (2023), global clean energy investment surpassed fossil fuel investment for the first time in 2023, reaching a record $1.74tn, compared to $1.05tn in fossil fuels. Moreover, RE is projected to overtake coal as the leading source of electricity generation by 2025, underscoring its central role in the global energy transition. Despite this rapid growth, a key policy question remains: Does RE innovation drive RE trade by enhancing technological competitiveness and market access, or does RE trade stimulate innovation through technology spillovers, market expansion and competitive pressures? This question is particularly relevant given that substantial investments from governments and stakeholders were necessary to kickstart the RE industry due to high uncertainty and low returns (Agrawal et al., 2024a; International Renewable Energy Agency (IRENA), 2017).

Understanding whether RE innovation or RE trade acts as the primary driver is essential for designing effective policy strategies, whether through innovation-driven or trade-driven approaches (OECD, 2019). However, the causality between innovation and trade remains a subject of debate, as competing theoretical perspectives suggest that both factors contribute to competitiveness and productivity. The nature of this relationship may vary across industries, as different sectors exhibit distinct innovation-adoption patterns (Guei, 2022; Dhayal et al., 2024). This highlights the need for a sector-specific examination of the RE industry, rather than relying on broader industrial classifications.

Despite its policy significance, empirical research on the trade-innovation nexus in the RE sector remains limited, particularly concerning differences between developed and developing countries (Arshad et al., 2023; Filipescu et al., 2013; Guei, 2022). Existing studies primarily analyze aggregate trade and innovation across multiple industries (Gur, 2020; Johnson and Van Wagoner, 2021; Onodera, 2008; Palangkaraya, 2012), without isolating the RE industry. Furthermore, many studies use RE electricity generation as a proxy for innovation (Kolosok et al., 2022; Pfeiffer and Mulder, 2013), while patent data provides a more precise measure of technological innovation (Feng and Zheng, 2022; Scarpellini et al., 2019; Streb, 2016). To address these gaps, this study constructs and processes raw data from the US Patent and Trademark Office (USPTO) and UN Comtrade databases, offering a comprehensive and accurate representation of RE innovation and trade activities across countries.

This study empirically investigates the causal relationship between RE innovation and RE trade using a panel data set of 96 countries (54 developed and 42 developing countries) from 1991 to 2022. Using panel vector error correction models (VECMs) and Granger causality tests, the findings reveal a long-run equilibrium relationship between RE innovation and RE trade in both developed and developing countries. However, in the short run, RE innovation significantly drives trade in developed countries, whereas no significant causal relationship is observed in developing countries. These findings raise concerns about structural and financial barriers impeding RE trade participation in developing countries despite growing international investments (Li et al., 2024; Mukherjee et al., 2023).

This study contributes to the literature by offering empirical insights into the trade-innovation nexus within the RE sector, addressing a gap in prior research that primarily focused on broader industrial classifications. Second, it highlights key differences between developed and developing countries, emphasizing the need for differentiated policy approaches tailored to their respective economic contexts. Finally, this study aligns with broader discussions on sustainable development, emphasizing how RE innovation and trade can advance environmental sustainability while maintaining economic growth (Liu et al., 2023).

The remainder of this paper is structured as follows. Section 2 reviews the literature on trade, innovation and their roles in the RE transition. Section 3 presents the data collection process, stationarity and cointegration tests, and empirical model specification. Section 4 presents the empirical results, followed by discussion in Section 5. Finally, Section 6 concludes with policy implications and recommendations.

The urgency of global climate action and energy transition has intensified interest in the role of RE innovation and trade in addressing climate change. For instance, Liu et al. (2023) find that green energy production, green technological innovation and green international trade significantly reduce ecological footprints in South Asia. International Trade Centre (ITC) (2024) presents that trade policies facilitate RE adoption in developing countries, thereby promoting energy transition and creating value addition opportunities. Gielen et al. (2019) further emphasize that RE innovation reduces the costs of RE technologies, making sustainable energy more competitive in global markets.

Beyond environmental benefits, RE innovation and trade also shape economic and industrial transformations (Fang et al., 2022; Shabbir et al., 2024). Sustainability transitions across industries are influenced by institutional structures and evolving consumption trends (Cao et al., 2024a). Agrawal et al. (2024a) highlight that green innovation serves as a catalyst for circular economy practices, driving new business opportunities and climate solutions. Meanwhile, Agrawal et al. (2024b) argue that global supply chains are increasingly disrupted by climate change, geopolitical conflicts, and pandemics, reinforcing the need for Industry 5.0 technologies to mitigate risks. Dhayal et al. (2023) further stress that the transition to Industry 5.0, supported by RE technologies and green finance, is essential for achieving sustainable development and maintaining competitive advantages.

Despite the growing importance of RE innovation and RE trade, their causal relationship remains an open question. While technological progress has accelerated, financial and regulatory barriers continue to hinder RE adoption, particularly in developing countries (Shabbir and Cheong, 2024). Political instability, investment uncertainty, and low returns further complicate RE innovation and implementation (Agrawal et al., 2024a; IRENA, 2017). This raises a critical policy question: does RE innovation drive trade, or does trade expansion foster further innovation? Understanding this dynamic is essential for designing policies that balance sustainability goals with economic competitiveness.

The theoretical relationship between trade and innovation has been widely discussed in both classical and modern trade theories. Traditional perspectives argue that international trade fosters innovation by expanding market size, increasing competition and facilitating knowledge diffusion (Ricardo, 1817; Vernon, 1966). The World Bank (2020) suggests that trade integration, particularly through global value chains, accelerates technological upgrading in developing countries. Conversely, modern trade theories propose that innovation itself is a key driver of trade by enhancing competitiveness, supporting specialization and fostering long-term economic growth through knowledge spillovers (Krugman, 1979; Posner, 1961; Romer, 1990; Schumpeter, 1942). These perspectives lead to different policy implications: if innovation drives trade, strengthening R&D incentives, intellectual property protections and financial mechanisms such as green tax incentives should be prioritized (Ahmad et al., 2024; Liu et al., 2023). Conversely, if trade fosters innovation, reducing trade barriers, strengthening RE supply chains and promoting international technology transfer agreements would be more effective strategies.

Empirical research has produced mixed findings on the causality between trade and innovation (Arshad et al., 2023; Filipescu et al., 2013; Guei, 2022; Gur, 2020; Johnson and Van Wagoner, 2021; Palangkaraya, 2012). Onodera (2008) finds that firms engaged in international trade and investment exhibit higher productivity and innovation levels than domestic firms, largely due to knowledge spillovers and competition effects. Guei (2022) suggests that this relationship varies across sectors, implying that the RE industry may not follow the same patterns observed in traditional manufacturing or technology sectors. Some studies indicate bidirectional causality, where innovation and exports reinforce each other (Palangkaraya, 2012; Gur, 2020), while others find unidirectional causality – such as imports driving innovation in the U.S. (Johnson and Van Wagoner, 2021) or exports driving innovation in Spain (Filipescu et al., 2013). These inconsistencies suggest that further research is needed to clarify the trade-innovation nexus, particularly in the RE sector.

Despite the extensive literature on trade and innovation, sector-specific research on the RE industry remains limited (Kolosok et al., 2022). Moreover, the role of institutional quality, regulatory frameworks and financial accessibility varies significantly between developed and developing countries, influencing the relationship between trade and innovation (Cao et al., 2024b; Li et al., 2024; Shabbir and Cheong, 2024). This study addresses these gaps by empirically examining the causal link between RE innovation and trade, differentiating between developed and developing countries.

This study uses a panel data set covering 96 countries, including 54 developed and 42 developing countries, over the period from 1991 and 2022. Country classification follows the World Bank’s income-based threshold, where countries with a Gross National Income (GNI) per capita above $13,205 are categorized as developed.^[1] The study integrates data on RE innovation and RE trade, both of which are defined using the World Intellectual Property Organization (WIPO) International Patent Classification (IPC) Green Inventory classification, specifically under the “Alternative Energy Production” category (WIPO, 2018).

The WIPO IPC Green Inventory consists of seven broad categories, which encompass a wide range of environmentally friendly technologies (Scarpellini et al., 2019; Kang and Park, 2023). This study focuses specifically on the “Alternative Energy Production” category, covering biofuels, fuel cells, wind, solar, hydro, geothermal and other RE technologies. The complete list of relevant technologies is presented in Table 1. This standardized classification ensures comparability of patent-related innovation and trade data across countries and years.

RE technological innovation (⁠$TIit$⁠) is measured by the number of patents in the RE industry, as recorded by the USPTO, which is one of the triadic patent families. The focus on USPTO patent data allows for a more accurate assessment of innovation outputs that align with international technological advancements in RE (Streb, 2016). Patent data are classified using the IPC codes of the WIPO classification, and only granted patents are considered, excluding pending and abandoned applications to ensure data accuracy.

RE industry trade (⁠$TRit$⁠) is measured as the aggregate sum of total exports (⁠$EXit$⁠) and imports (⁠$IMit$⁠) of RE-related products, sourced from the UN Comtrade Database. RE trade products are classified using Harmonized System (HS) six-digit codes, mapped to IPC categories based on the methodology of Lybbert and Zolas (2014). To ensure consistency across the study period, HS2002 six-digit codes were converted to HS1992 codes using the United Nations Statistics Division (UNSD) concordance tables. A concordance mapping aligns WIPO IPC patent classifications with relevant HS product trade codes.

Figures 1 and 2 illustrate the trends in RE innovation, trade, exports and imports for developed and developing countries over the study period. Figure 1 presents the trends in RE innovation (left) and RE trade (right). The left panel shows a general upward trend in RE innovation for both groups, with developed countries consistently producing significantly more RE patents. However, while RE innovation in developed countries has slowed since 2017, developing countries have experienced rapid growth since 2019, with patent counts rising from 510 to 738 in 2022. The sharp decline in 2005 likely reflects a temporary drop in overall USPTO patent approvals.

The right panel of Figure 1 illustrates a steady increase in RE trade volume for developed and developing countries. Between 1991 and 2022, RE trade expanded from $93.72bn to $604.91bn in developed countries and from $1.46bn to $238.43bn in developing countries. However, recent years saw stagnation or declines, with developed countries showing signs of recovery in 2022, while trade in developing countries continued to decline. The 2009 drop corresponds to the Great Recession.

Figure 2 further categorizes RE trade into RE exports (left panel) and RE imports (right panel). The left panel shows a widening gap in RE exports between developed and developing countries. Between 1991 and 2022, RE exports increased from $48.12bn to $305.68bn in developed countries, while it increased from $0.88bn to $134.62bn in developing countries. This indicates that developed countries have maintained a dominant position in RE exports, with a significantly larger volume compared to developing countries.

The right panel of Figure 2 presents the RE imports exhibit a narrower gap between developed and developing countries compared to exports. Imports increased from $45.60bn to $299.23bn in developed countries and from $0.58bn to $107.94bn in developing countries. While both regions faced declines in recent years, developed countries showed a mild recovery from 2021 to 2022, while developing countries remained stagnant.

The key variables and their descriptive statistics are presented in Table 2. A concordance mapping ensures that IPC-classified patents correspond with relevant HS-classified trade products. Since patent counts and trade volumes differ in scale and distribution, all variables were log-transformed to normalize distributions and mitigate heteroskedasticity.

The study uses a panel VECM (Pesaran et al., 1999) to perform Granger causality test and analyze the short-term dynamics and the long-run equilibrium relationship between RE innovation and RE trade. Before conducting the Granger causality test, panel unit-root tests and cointegration tests are conducted to determine the appropriate estimation model.

First, the stationarity of the variables is assessed using five panel unit-root tests: Levin-Liu-Chu (LLC), Breitung, Im-Pesaran-Shin (IPS), ADF-Fisher and PP-Fisher (Breitung, 2000; Dickey and Fuller, 1979; Im et al., 2003; Levin et al., 2002; Phillips and Perron, 1988). The null hypothesis of these tests assumes the presence of unit roots, indicating that the series is nonstationary. Tables 3 and 4 present the results for developed and developing countries, respectively.

Table 3 reports the panel unit-root test results for developed countries with a constant and both constant and time trend specifications. Most level variables reject the null hypothesis at the 5% significance level, indicating stationarity. However, the Breitung t-statistics show weaker evidence of stationarity when a time trend is included for RE trade, exports and imports. Differenced variables for all indicators exhibit stationarity across all test statistics.

Similar results are found for developing countries in Table 4. Most level variables are stationary, rejecting the null hypothesis of a unit root, except for the LLC test on RE trade, exports and imports, where p-values exceed 0.1, suggesting the presence of unit roots. However, all differenced variables exhibit stationarity, confirming that they follow an I(1) process.

Given these findings, Pedroni’s (1999, 2001) cointegration test is conducted to evaluate the presence of a long-run relationship among the variables. The null hypothesis of no cointegration is tested against the alternative hypothesis that the variables share a common long-run relationship. The test is performed across within-dimension and between-dimension statistics for RE trade, exports and imports, with the lag length selected using the Akaike Information Criterion (AIC).

Table 5 presents the panel cointegration test results for developed countries. The majority of tests strongly reject the null hypothesis of no cointegration at the 1% significance level, except for the Panel v-statistic, which is significant only at the 10% level for RE innovation and trade and at the 5% level for RE innovation and exports. Nonetheless, the Panel rho, Panel PP, and Panel ADF statistics consistently provide robust evidence of a long-run equilibrium relationship between RE innovation and trade, exports and imports.

Similarly, Table 6 presents Pedroni’s panel cointegration test results for developing countries. The results confirm strong evidence of cointegration across all variables, with the exception of the Panel v-statistic. The Panel rho, Panel PP and Panel ADF statistics consistently reject the null hypothesis of no cointegration at the 1% significance level, suggesting a stable long-run relationship between RE innovation and trade variables. Overall, the results confirm a long-run equilibrium relationship between RE innovation and trade in both developed and developing countries. Although the strength of the evidence varies slightly across tests, the robust significance of the Panel rho, Panel PP and Panel ADF statistics supports the presence of cointegration.

Given the stationarity and cointegration results, the panel VECM (Pesaran et al., 1999) is used to examine the short-run dynamics and long-run equilibrium adjustments between RE innovation and trade. The panel VECM can be written as follows:

where $TIit$ represents RE technological innovation in country i at time t, $TRit$ represents RE trade, Δ denotes the first difference operator, $εi,t-1$ is the lagged error correction term (ECT) derived from the long-run cointegrating equation, $θi$ are coefficients for the ECT, $αip$ and $βip$ are coefficients to be estimated and $uit$ represents the error terms. RE trade (⁠$TRit$⁠) is further decomposed into exports (⁠$EXit$⁠) and imports (⁠$IMit$⁠), therefore, following four equations are included:

Referring from Engle and Granger (1987), a two-step procedure is conducted to perform Granger causality tests. In the first step, the ECT (⁠$εi,t-1$⁠), is obtained from the residuals of the estimated fixed-effects panel regression, capturing deviations from the long-run equilibrium. In the second step, the VECM is estimated to assess short-run causality. To determine the optimal lag length for the VECM, the lag length that minimizes the information criteria (Akaike Information Criterion [AIC], Bayesian Information Criterion [BIC], Hannan-Quinn Information Criterion [HQIC]) are calculated (Akaike, 1969, 1977; Schwarz, 1978; Hannan and Quinn, 1979; Andrew and Lu, 2001). Based on selection order criteria, optimal lag lengths are selected for the VECM estimation.

This section presents the results of the panel VECM estimation and Granger causality tests, analyzing the relationship between RE innovation and RE trade in developed and developing countries. The VECM estimation results are provided in Tables 7 and 8, while Tables 9 and 10 present the Granger causality test results.

Table 7 presents the panel VECM estimation results where RE innovation is the dependent variable. Models (1) to (3) show the results for developed countries, while models (4) to (6) present results for developing countries, incorporating lagged RE trade, exports and imports as independent variables, respectively.

In developed countries, the coefficient for the lagged dependent variable is negative and highly significant across all models, indicating a mean-reverting process in RE innovation. The ECT is also positive and significant, suggesting a strong adjustment toward the long-run equilibrium, with approximately 32.1% of the disequilibrium corrected each period. However, the coefficients of RE trade, exports and imports are positive but statistically insignificant, implying that RE trade does not significantly impact RE innovation in the short run.

For developing countries, the lagged dependent variable exhibits a slightly larger negative coefficient, indicating a stronger mean-reverting effect in RE innovation. The ECT is also significant, confirming long-run adjustments, with approximately 30.3% to 31.2% of the disequilibrium corrected each period. However, similar to developed countries, RE trade, exports and imports do not have significant short-run effects on RE innovation.

Overall, these findings indicate that RE innovation exhibits a mean-reverting behavior in both developed and developing countries, but trade-related variables do not significantly influence innovation in the short run. Furthermore, the ECT is significant and positive in all models, demonstrating a strong adjustment mechanism toward long-run equilibrium in both developed and developing countries, although the adjustment speed is slightly faster in developed countries.

Table 8 presents the panel VECM estimation results where RE trade, exports and imports are the dependent variables. Models (7) to (9) show results for developed countries, while models (10) to (12) focus on developing countries.

In developed countries, the coefficient for lagged RE innovation is positive and statistically significant, suggesting that an increase in RE innovation positively affects RE trade, exports, and imports. The coefficients range from 0.450 to 0.467, reinforcing the role of RE innovation as a driver of trade activities. The coefficients for lagged RE trade, exports and imports are negative and highly significant, highlighting a stabilizing trade pattern over time. The ECT is positive and highly significant, confirming strong long-run adjustments toward equilibrium.

For developing countries, the coefficient for lagged RE innovation is positive but not statistically significant, indicating that RE innovation does not significantly affect RE trade, exports, or imports in the short run. Similar to developed countries, the coefficients for lagged RE trade, exports and imports are negative and highly significant, confirming a mean-reverting process in RE trade patterns. The ECT is also highly significant, suggesting strong long-run adjustments toward equilibrium.

Overall, these findings suggest that in developed countries, RE innovation plays a significant role in shaping trade dynamics, whereas in developing countries, other factors such as institutional frameworks and financial constraints may be more influential in driving trade activities in the short run. However, both developed and developing countries exhibit strong long-run adjustments towards equilibrium, reinforcing the importance of RE innovation-trade integration over time.

Based on the estimation results of the panel VECM, Granger causality Wald test is conducted to examine the short-run causal relationship between the RE innovation and RE trade. Table 9 presents results for developed countries, indicating a unidirectional Granger causality from RE innovation to RE trade, exports and imports at the 5% significance level, whereas the reverse causality is not statistically significant. This suggests that in developed countries, RE innovation is a key driver of trade activities related to RE.

Table 10 presents the Granger causality Wald test results for developing countries. The test results do not indicate significant Granger causality between RE innovation and RE trade, exports, or imports. None of the test statistics reach common significance thresholds, suggesting that changes in RE innovation do not predict changes in RE trade, and vice versa. This contrasts with the findings for developed countries, suggesting that structural and financial barriers may prevent RE innovation from translating into trade expansion in developing countries.

The empirical findings reveal distinct dynamics between developed and developing countries in the relationship between RE innovation and RE trade. Both country groups exhibit strong long-run adjustments toward equilibrium, highlighting the potential for RE innovation to influence trade over time. However, in developed countries, RE innovation significantly drives trade, exports and imports in the short-run, whereas developing countries show no short-run Granger causality between RE innovation and trade. This suggests that structural barriers such as weak financial systems, governance inefficiencies and competing socio-economic priorities in developing countries could limit the integration of RE technologies into trade markets (Li et al., 2024; World Bank, 2020; Yan et al., 2024). These disparities raise concerns about the ability of developing countries to effectively participate in the expanding global RE trade sector. Mukherjee et al. (2023) argue that developing countries should focus on internal capability-building, while developed countries should address technology-related barriers when adopting Industry 5.0 technologies.

One of the key constraints to RE innovation in developing countries is limited financial accessibility (Agrawal et al., 2024a; Dhayal et al., 2023). RE technologies require substantial upfront investments, and high uncertainty regarding returns discourages private-sector participation (Sarkar and Singh, 2010; Sovacool, 2013). While green finance mechanisms aim to mitigate investment risks by providing long-term capital, their accessibility remains restricted in many developing countries due to underdeveloped financial markets and limited investor confidence. These financial constraints slow down technology adoption and prevent RE innovation from translating into trade expansion. Comin and Mestieri (2017) highlight that the technology diffusion gap between developed and developing countries is widening, as firms in developing countries continue to rely on both new and outdated technologies. Additionally, Ahmad et al. (2022) emphasize that effective financial risk management is essential for fostering RE innovation and sustainability. Yan et al. (2024) further argue that disparities in financial accessibility, coupled with regulatory inefficiencies, exacerbate barriers to RE trade participation in developing countries.

Institutional quality would be another critical determinant of RE trade and innovation integration (Liu et al., 2023). Developed countries benefit from stable regulatory frameworks, strong enforcement mechanisms and well-established policy support, enabling large-scale deployment of RE technologies (North, 1990; OECD, 2013). In contrast, fragmented governance structures, policy inconsistencies and weak regulatory enforcement in developing countries hinder market development. The Diffusion of Innovations Theory (DOI) suggests that early adopters play a crucial role in technology dissemination (Agrawal et al., 2024a). However, without institutional stability and policy incentives, RE technologies struggle to gain traction in developing countries (Cao et al., 2024a). Similarly, Innovation System Theory (IST) emphasizes that innovation requires interconnected collaboration between policymakers, industries and research institutions (Dhayal et al., 2024). While developed countries have well-coordinated innovation ecosystems, developing countries often face fragmented systems that impede knowledge diffusion, technology commercialization and RE trade expansion.

Beyond institutional and financial limitations, environmental and trade policies would also shape RE trade outcomes. International agreements such as the Kyoto Protocol, the Montreal Protocol and the Paris Agreement have played a central role in accelerating RE adoption in developed countries (Kang et al., 2021; Mehmood et al., 2024). These agreements create binding emissions reduction targets, promote RE innovation and foster market specialization (Aldy and Pizer, 2015). Additionally, technological advancements in RE have significantly reduced costs and improved efficiency, strengthening the global competitiveness of sustainable energy (OECD, 2019; Xue et al., 2024). However, while these agreements have successfully encouraged innovation-driven trade in developed countries, their impact on developing countries remains constrained by financial and institutional limitations. Coelho (2005) and ITC (2024) highlight that restrictive trade policies, weak regulatory frameworks and limited institutional capacity in developing countries present significant barriers to RE transition.

Environmental taxation policies would add another layer of complexity. Nchofoung et al. (2023) argue that environmental taxes encourage RE adoption in developed countries by internalizing the cost of pollution. However, in developing countries, where financial constraints and governance inefficiencies are prevalent, such policies can increase energy costs without providing viable alternatives, thereby discouraging adoption. UNCTAD (2024) reports that developing countries face higher trade costs for RE products, with average tariffs ranging from 2.5% in Asia and Oceania to 7.1% in Africa. Ahmad et al. (2024) suggest that targeted green tax incentives, coupled with subsidies and foreign investment, could help mitigate these negative effects. Without appropriate financial and regulatory support, environmental taxes could disproportionately hinder RE trade participation in developing countries.

This study examines the causal relationship between RE innovation and RE trade across developed and developing countries. The findings confirm a long-run equilibrium relationship between RE innovation and RE trade in both groups of countries. However, in the short run, RE innovation significantly drives trade in developed countries, whereas no significant causal relationship is observed in developing countries. These results suggest that structural differences, including financial constraints, policy support and institutional quality, would influence the extent to which RE innovation translates into trade integration, particularly in developing countries.

These findings underscore the need for differentiated policy approaches tailored to the economic context, ensuring that both developed and developing countries can maximize the benefits of RE innovation and trade integration. In developed countries, where RE innovation drives trade, policymakers should reinforce innovation-driven strategies by continuing to support R&D investments, strengthening intellectual property protections and facilitating technology transfer to sustain trade growth. In contrast, developing countries require institutional reforms, enhanced financial accessibility and knowledge-sharing initiatives to ensure that RE innovation translates into trade integration. Expanding green finance mechanisms, implementing targeted subsidies and tax incentives and fostering international collaboration will be critical in bridging the innovation-trade gap and enabling developing countries to integrate into global RE trade markets. Moreover, environmental taxation policies in developing countries should be complemented with financial incentives to mitigate economic burdens and promote clean energy adoption.

This study makes several contributions to the literature. First, it advances the trade-innovation nexus literature by providing empirical evidence specific to the RE sector and highlighting key differences between developed and developing countries, filling a gap in prior research that has largely focused on broader industry classifications. Second, it emphasizes the need for differentiated policy approaches tailored to distinct economic and institutional contexts. Finally, it contributes to sustainability discussions by emphasizing how RE innovation and trade can promote sustainable development, reinforcing the importance of balanced policies that ensure both innovation diffusion and equitable market participation.

Future research should explore the mechanisms that facilitate faster and more inclusive RE technology diffusion. Further empirical investigations into financial, political and institutional factors shaping the trade-innovation relationship could offer deeper insights into policy design. Additionally, comparative analyses across other high-technology industries, such as artificial intelligence (AI) and robotics, could provide a broader understanding of whether similar innovation-adoption patterns exist, informing strategies for technology diffusion and trade integration. Ultimately, closing the innovation-trade gap in the RE sector will require coordinated global efforts, ensuring equitable participation in the green economy.