## 4 Empirical Analysis
### Formation of Analysis Modeling with the SEM-VALTM Model
This indicates that a 1% change in the economic sector results in a 71% change in the environmental sector in the opposite direction. The social sector has a direct effect on the environmental sector of 46% in the opposite direction at the 1% significance level. This shows that a 1% change in the social sector leads to a 46% change in the environmental sector in the opposite direction. In this research, various findings have emerged from the analysis using the SEM-VALTM model. The research has uncovered insights into the error correction mechanism \((ECM_{t-1})\), particularly in the economic sector. The parameter value is \(-0.49\), significant \begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**Dependent Variables**} & \multirow{2}{*}{**Type of Effect**} & \multicolumn{4}{c}{**Independent Variables**} \\ \cline{3-6}  & & & **Economic** & **Social** & **Environmental** & **Error Correction Mechanism (\(ECM_{t-1}\))** \\ \hline \multirow{3}{*}{Economic} & DE & - & - & - & \(-0.49\)*** \\  & IE & - & - & - & - \\ \cline{1-1}  & DE & 0.39 *** & - & - & \(-0.26\)*** \\ \cline{1-1}  & IE & - & - & - & - \\ \cline{1-1} Environmental & DE & 0.71 *** & 0.46 *** & - & \(-0.06\)*** \\ \cline{1-1} \cline{2-6}  & IE & 0.10 *** & - & - & - \\ \hline \hline \end{tabular} Note: In the above, *** denotes significance, \(\alpha\) = 0.01, DE is a direct effect, and IE is an indirect effect.  
\end{table} 
Table 3: The results of the relationship size analysis of the SEM-VALTM model. at the 1% level, indicating that adjustments in the economic sector have a 49% capacity to revert to equilibrium. This signifies the highest adjustment speed towards equilibrium. Furthermore, the social sector and environmental sector exhibit lower adjustment capacities towards equilibrium (\(ECM_{t-1}\)), at 26% and 6%, respectively, indicating their relative slower rates of adjustment compared to the economic sector. From this research, it was discovered that the SEM-VALTM model demonstrates that the industrial structure rate in the economic sector has the most significant negative influence on the environmental sector, resulting in the greatest ecological damage. Furthermore, it was found that the environmental sector has the most difficulty in recovering to its normal state. Therefore, as a proactive strategic approach, the researcher has formulated a new scenario policy emphasizing the use of clean technology and renewable capabilities. In this research, the researcher employed sensitivity analysis on all factors to examine their suitability for use in formulating the new scenario policy. The results indicated that the factors with statistical significance at a 99% confidence level, ranking highest in both short-term and long-term tests, were clean technology and renewable energy. In the social sector, it was found that only the employment rate passed the sensitivity analysis in the short term. However, in the long term, it did not meet the 99% confidence level requirement. Therefore, the researcher prioritized developing the new scenario policy based on these variables to urgently devise strategies for managing Thailand, particularly to reduce greenhouse gas emissions. If economic and environmental measures are effectively implemented, it is expected that strategies addressing social dimensions can be formulated in subsequent phases. When considering the magnitude of influence between sectors, the economic sector was found to have the greatest impact on the environmental sector, followed by the social sector. This underscores that changes in the economic sector will most significantly affect the environmental sector. The results suggest that the researcher concludes that the SEM-VALTM model can be used to measure performance for forecasting purposes, ensuring its reliability for future forecasting applications. Additionally, the researcher utilized the data from this study to apply it to various previously established models for comparison of their performance.