ISSN: 2226-6348
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This study investigates the impact of various economic indicators on the sustainability index using robust regression analysis. The dataset comprises 73 observations, and the model evaluates the effects of four independent variables: democracy index (dem_index), inflation, GDP, and economic growth (ec_growth). The results reveal significant insights into the relationship between these indicators and the sustainability index. The regression model demonstrates a significant overall fit, with an F-statistic of 9.31 and a p-value of 0.0000, indicating that the model is statistically significant. The R-squared value of 0.3051 suggests that approximately 30.51% of the variance in the sustainability index can be explained by the independent variables included in the model. The root mean squared error (Root MSE) is 8.9467, reflecting the average error in the model's predictions. The analysis shows that the democracy index (dem_index) has a positive but statistically insignificant coefficient (0.2749245, p=0.951), implying no substantial impact on the sustainability index. In contrast, inflation exhibits a negative and statistically significant coefficient (-1.594545, p=0.000), indicating that higher inflation significantly reduces the sustainability index. GDP has a negative coefficient (-0.0046032, p=0.080), which is near statistical significance, suggesting a potential but weak negative influence on the sustainability index. Economic growth (ec_growth) has a positive but statistically insignificant coefficient (0.3109447, p=0.269), indicating no clear impact on the sustainability index. The constant term (_cons) is statistically significant (82.65478, p=0.003), reflecting the baseline value of the sustainability index when all predictors are zero. The study highlights the significant negative effect of inflation on the sustainability index, while other variables like democracy index, GDP, and economic growth show no significant impact. These findings underscore the importance of managing inflation to enhance sustainability outcomes. Further research is recommended to explore additional factors influencing sustainability and to refine the model's predictive accuracy.
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