In recent years, the global push for sustainable development has placed a spotlight on the importance of green technology innovation (GTI) and its impact on energy efficiency and environmental sustainability. Understanding the relationship between GTI, energy efficiency, and environmental regulation (ER) is crucial for policymakers and researchers alike. In this article, we delve into a comprehensive analysis that combines spatial autocorrelation techniques and estimated results to shed light on this complex relationship.<\/p>\n
To begin our analysis, we conducted a spatial autocorrelation analysis to examine the spatial correlations between various variables, including energy efficiency (EEE), GTI, ER, and two components of GTI – SubGI and SymGI. The results, presented in Table 2, revealed significant positive spatial clustering and correlation among provinces for EEE, GTI, SubGI, and SymGI. Additionally, there was a strong positive spatial correlation between primary technological efficiency (PTE) and secondary technological efficiency (SE), except for a few years. These findings highlight the pronounced spatial dependence and correlation among these variables, emphasizing the need to consider spatial effects in our study.<\/p>\n
Using the Dynamic Spatial Durbin Model (DSDM), we estimated the impact of GTI on EEE, both with and without considering the influence of ER. The results, presented in Table 3, showed that the coefficients for the variables were generally significant under all three spatial weight matrices. The lagged term coefficient of EEE and the spatial spillover term coefficient of EEE under weight \\({W}_{b}\\) were both significantly positive, indicating a clear pattern of continuity and high interdependence among EEE in different provinces of China.<\/p>\n
Furthermore, the coefficient for the quadratic term of GTI was significantly positive, suggesting a U-shaped relationship between GTI and EEE. The study proposes that this pattern may be attributed to the time and initial investments required for the transformation of GTI, leading to stable energy consumption and CO2 emissions, and subsequently a decline in EEE. However, once GTI is widely adopted, energy consumption and CO2 emissions decrease, resulting in improved EEE.<\/p>\n
The study also found that the direct effect coefficients of ER on EEE and the spatial spillover effect coefficients were opposite in sign. The direct interaction effect coefficients between ER and GTI, as well as the spatial interaction effect coefficients between ER and GTI, were also opposite in sign. This complexity makes it challenging to assess the impact of ER on EEE and the role of ER in this impact. Therefore, the study decomposed the model results and focused on analyzing short-term effects.<\/p>\n
Table 4 presents the results of the direct, indirect, and total effects of GTI on EEE considering the impact of ER. The coefficients of the total effect of GTI were significantly negative under the weighting matrices \\({W}_{a}\\) and \\({W}_{b}\\). This suggests that the inhibitory effect of GTI on neighboring regions is greater than its promoting effect on the local region. Additionally, the study found a critical point in the impact of GTI on EEE, where the positive direct effect outweighs the negative spatial spillover effect, thereby improving EEE.<\/p>\n
Under all three weight matrices, the total effect coefficient of ER on EEE was significantly positive, indicating that the implementation of ER enhances EEE. The coefficient for the interaction term between ER and GTI was significantly positive, suggesting that ER mitigates the negative impact of GTI on EEE. This is particularly true in the early stages of GTI implementation when businesses face high sunk costs. The implementation of environmental policies encourages investment in green technology, leading to a decrease in EEE. However, as GTI reaches its critical point, ER strengthens the promoting effect of GTI on EEE, stimulating long-term investment and collaboration.<\/p>\n
To unravel the specific source of GTI’s influence on EEE, the study decomposed GTI into SubGI and SymGI and conducted a new empirical analysis, as shown in Table 5. The results indicated that the effect of GTI on EEE is primarily driven by SubGI, which refers to the development and expansion of new clean energy technologies. This finding highlights the importance of clean energy technologies in reducing resource wastage and greenhouse gas emissions.<\/p>\n
To further understand which component of EEE is influenced by GTI, the study decomposed EEE into PTE and SE and conducted a new empirical analysis, as shown in Table 6. The results revealed that the impact of GTI on EEE is primarily manifested in PTE, with SE showing non-significant coefficients for the explanatory variables. This suggests that the development of GTI primarily affects the primary technological efficiency of energy consumption.<\/p>\n
To ensure the reliability of the methodology and conclusions, a robustness test was conducted by replacing control variables and using lagged one-period explanatory variables. The results, presented in Tables 8 and 9, demonstrated the robustness of the findings, as the coefficients maintained the same positive or negative signs and levels of significance.<\/p>\n
In conclusion, this comprehensive analysis provides valuable insights into the impact of GTI on EEE and the role of ER in this effect. The study highlights the spatial dependence and correlation among these variables, emphasizing the need to consider spatial effects. The findings suggest a U-shaped relationship between GTI and EEE, with ER playing a significant role in mitigating the negative impact of GTI. Furthermore, the development of new clean energy technologies is a key driver of GTI’s impact on EEE. These insights can inform policymakers and researchers in their efforts to promote sustainable development and energy efficiency.<\/p>\n","protected":false},"excerpt":{"rendered":"
Analyzing the Spatial Autocorrelation and Estimated Results In recent years, the global push for sustainable development has placed a spotlight on the importance of green technology innovation (GTI) and its impact on energy efficiency and environmental sustainability. Understanding the relationship between GTI, energy efficiency, and environmental regulation (ER) is crucial for policymakers and researchers alike. […]<\/p>\n","protected":false},"author":2,"featured_media":6202,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[96],"tags":[],"class_list":["post-6201","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-green-technology"],"_links":{"self":[{"href":"https:\/\/buzz360news.com\/index.php\/wp-json\/wp\/v2\/posts\/6201","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/buzz360news.com\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/buzz360news.com\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/buzz360news.com\/index.php\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/buzz360news.com\/index.php\/wp-json\/wp\/v2\/comments?post=6201"}],"version-history":[{"count":0,"href":"https:\/\/buzz360news.com\/index.php\/wp-json\/wp\/v2\/posts\/6201\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/buzz360news.com\/index.php\/wp-json\/wp\/v2\/media\/6202"}],"wp:attachment":[{"href":"https:\/\/buzz360news.com\/index.php\/wp-json\/wp\/v2\/media?parent=6201"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/buzz360news.com\/index.php\/wp-json\/wp\/v2\/categories?post=6201"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/buzz360news.com\/index.php\/wp-json\/wp\/v2\/tags?post=6201"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}