Impact Mechanism of Renewable Energy Technology Innovation on Carbon Productivity Based on Spatial Durbin Model
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5.2. Results of Descriptive Statistics
The estimation of each variable in the model further yields the double-fixed space Durbin estimation of the model, as shown in Table 7.
In Table 7, the coefficients of the core explanatory variables and the spatial lag term of CP are both significant at the 1% level and take positive values, which shows that CP has spatial auto-correlation and there will be an effect between CPs between places. REIT has a favorable promotion of CP and spatial SEs, as evidenced by the significant results of its spatial lag term and core explanatory variables at the 1% and 5% levels, respectively. Since the spatial lag term of REIT is 0.161, the CP of this province will be boosted by 0.161% with each 1% increase in REIT in other provinces. Possible reasons are that CP is driven by technological progress, enhances economic output, achieves a sustainable economy, and exhibits regional differences. Within the research interval, there is a large-scale international capacity transfer and technological upgrading, coupled with the advantage of renewable energy technology utilization in economically developed areas, which allows REIT to generate SE through economic relations and geographical linkages, causing spatial spillover effects on CP in neighboring provinces.
The direct decomposition effect and indirect decomposition effect of REIT on CP are demonstrated in Table 8. Table 8 displays significant results for the direct, indirect, and total decomposition effects of REIT at the 1%, 5%, and 1% levels, respectively. The direct decomposition coefficient of REIT is 0.146, which thus indicates that a 1% increase in REIT in a specific province increases local CP by 0.146%. The indirect decomposition coefficient of REIT is 0.189, which thus indicates that a 1% increase in REIT in a specific province increases local CP by 0.189%, which includes 0.161% of the surrounding provinces, i.e., there is a feedback effect of 0.028. In summary, REIT not only directly promotes the growth of CP in specific provinces but also indirectly promotes further growth of CP through the increase in REIT in neighboring provinces. The possible reason is that, within the research interval, technological innovation in one area can spread to other areas through mechanisms such as ID, DOOW, and IER. The interrelated economic activities among provinces and the competitive attractiveness among regions can lead to the spatial flow of technology and capital, accelerating the promotion and application of RE technology. This, in turn, raises the level of RE in neighboring provinces and further promotes the increase in CP within the region through spatial SEs.
5.4. Heterogeneity Analysis Results
This study uses double-fixed SDM to estimate the mechanism of the impact of REIT on CP for each of the eight economic areas in order to analyze the mechanism of the influence of various economic regions on CP. The results of the heterogeneity analysis obtained are displayed in Table 11.
In Table 11, REIT in the eight regions can have different impacts on CP, of which REIT in the five regions of Northeast, Southwest, North Coast, East Coast, and Middle Reaches of the Yangtze River can show different levels of significance on CP, while in the three regions of Northwest, South Coast, and Middle Reaches of the Yellow River, it is not significant. This shows that REIT in the five regions of the Northeast, Southwest, North Coast, East Coast, and Middle Reaches of the Yangtze River can promote CP. Among them, the REIT in the North Coast and East Coast regions has a stronger spatial SE on CP. In contrast, the three regions of the Northwest, South Coast, and Middle Yellow River have a weak level of REIT; thus, the spatial SE of REIT on CP is not obvious enough.
Possible reasons include that the five regions of the Northeast, Southwest, North Coast, East Coast, and Middle Reaches of the Yangtze River have higher levels of economic development, more advanced infrastructure, a stronger industrial base, more robust policy support, and more financial investment. These factors collectively promote the implementation of renewable energy projects and the application of new technologies. They boost the development and application of REIT, effectively enhancing CP. The North Coast and East Coast regions, with higher levels of high-tech industry development, have greater openness and connections to international markets, making it easier to attract domestic and foreign investments, technology, and high-end talent. Enterprises and research institutions in these areas have more R&D investments and achievements in renewable energy technology, energy efficiency improvement, and low-carbon technologies. This accelerates the innovation and application of renewable energy technology, resulting in a stronger spatial spillover effect of REIT on CP.
In addition, there are differences in the impact of UL, GDPPC, GS, EC, LFI, and other factors on CP across regions, which is due to the inconsistency of the actual situation in each region. UL has a positive impact on CP in the Northeast, North Coast, East Coast, and South Coast regions; GDPPC has a positive impact on CP in six regions: Northeast, Northwest, Southwest, North Coast, South Coast, and the Middle Yellow River; GS has a positive impact on CP in the North Coast and East Coast regions; EC has a positive impact on CP in five regions: Northwest, North Coast, East Coast, South Coast, and the Middle Yellow River; and LFI has a positive impact on CP in five regions: Northwest, Southwest, South Coast, Middle Yellow River, and the Middle Reaches of the Yangtze River. These differences are due to the unique conditions of each region.
The possible reasons are as follows: (1) The higher level of UL in the Northeast, North Coast, East Coast, and South Coast regions includes improved infrastructure, public services, energy efficiency, and waste management systems. This often leads to a shift in the industrial structure towards higher value-added and lower carbon emissions, creating a favorable environment for industrial upgrading. This agglomeration effect can enhance production efficiency and innovation capacity in these four regions, thereby increasing CP. (2) The Northeast, Northwest, Southwest, North Coast, South Coast, and Middle Yellow River regions have higher GDPPC, indicating a higher level of economic development and living standards. This means that additional resources can be allocated for research and development and the adoption of clean energy technologies in these six regions, leading to an improvement in CP. (3) The North Coast and East Coast regions have strong GS, with financial subsidies, tax incentives, policy guidance, and increased investment in renewable energy, all aimed at promoting the use of low-carbon technologies and practices and enhancing CP. (4) The Northwest, North Coast, East Coast, South Coast, and Middle Yellow River regions are shifting their EC towards cleaner sources, such as solar and wind energy. This transition helps to reduce dependence on fossil fuels, lower CE, and increase CP. (5) The regions of the Northwest, Southwest, South Coast, Middle Yellow River, and the Middle Reaches of the Yangtze River have higher LFI. This attracts advanced technology and management experience, promoting technology transfer and knowledge spillover. As a result, the energy efficiency and innovation capacity of local enterprises are enhanced, thereby improving CP.
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