Ious years will likely be adjusted by 68 annually. four.five. Robustness Verify Evaluation As described early, the FMOLS, DOLS, and CCR have been applied to verify the robustness of your empirical findings. Consequently, these estimates are presented in Table five.Table five. Robustness check. FMOLS Variable LMVA LT LDC LM LEC C Coefficient p-Value 0.009 0.009 0.000 0.261 0.000 0.000 DOLS Coefficient 0.167 -0.529 0.159 -0.212 0.881 7.035 p-Value 0.030 0.000 0.000 0.003 0.000 0.000 CCR Coefficient p-Value 0.039 0.068 0.002 0.516 0.000 0.-0.256 -0.224 0.152 -0.107 0.913 six.-0.252 -0.274 0.140 -0.074 0.906 six.Supply: Authors’ estimate.As seen in Table five, the estimated coefficients in the DOLS would be the same because the ARDL long-run estimated coefficients. Industrialization, financial improvement when measured by domestic credit for the private sector, and energy consumption showed a good influence on financial development at five , 1 , and 1 significance levels, respectively. On the other hand, financial development when measured by income supply and trade openness displayed a statistically considerable negative impact on financial Thiophanate-Methyl Autophagy growth at a 1 significance level. In contrast to this, the estimated coefficient of industrialization determined by the FMOLS and CCR estimators was located to become negatively connected with economic growth that is not in line with the ARDL long-run coefficients. In addition to that, income supply as an indicator for economic development was found to be insignificant. Moreover, domestic credit towards the private sector and energy consumption positively influenced financial growth at a 1 significance level depending on the FMOLS and CCR estimators. Additionally, openness demonstrated a unfavorable effect on financial development. These findings offer a strong empirical testimony that industrialization and financial development are important keys to attaining sustained financial development within the long run in Indonesia. four.6. Diagnostic Test and Parameter Stability The diagnostic tests of heteroscedasticity, serial correlation, normality, and Ramsey RESET were applied, and also the results are reported in Table six. Table 6 shows that the estimated model is homoscedastic, not affected by serial correlation, and typically distributed and that the functional form is correctly formulated. Furthermore, the cumulative sum (CUSUM) of recursive residuals and cumulative sum square (CUSUMSQ) of recursive residuals methods were performed to detect the stability and reliability of estimated coefficients within the long run and short run. The results are presented in Figures 1 and two, respectively.Table 6. Diagnostic tests. Table six. Diagnostic tests.Economies 2021, 9, 174 HeteroscedasticityTest Test Test: Breusch-Pagan-Godfrey Heteroscedasticity Test: Breusch-Pagan-Godfrey Breusch-Godfrey Serial Correlation LM Test Breusch-Godfrey Serial Correlation LM Test Normality Jaraue-Bera Normality Jaraue-Bera Ramsey RESETTable six. Diagnostic tests. Ramsey RESETTest TestSource: Authors’ estimate. Source: Authors’ estimate.Test Heteroscedasticity Test:F-Statistic F-Statistic 1.22 1.22 four.497 4.497 0.297 0.297 0.001 0.F-StatisticProbability Probability 0.38 0.38 0.05 0.05 0.86 0.86 0.97 0.Probability10 of1.22 0.38 Table 66shows that Paganestimatedmodel is homoscedastic, not affected by serial Table shows thatthe estimated model is homoscedastic, not suffering from serial Breusch- the -Godfrey correlation, and generally distributed and that the functional form is correctly formulated. correlation, andBreusch-Godfrey Serial and that the f.