In the Indian context, this study looks at a number of aspects of revenue mobilisation, taxpayer behaviour, and tax administration. The study finds important patterns and connections in the dynamics of tax collecting by applying quantitative analytical techniques such a regression analysis, ratio analysis, CAGR (compound annual growth rate) analysis, and correlation analysis. The results of regression analysis highlight the impact of the economy on tax collection, showing a robust positive connection between GDP and direct tax revenue. Throughout a 22-year period, ratio analysis shows rising efficiency patterns in tax collecting processes, while CAGR analysis shows a steady increase in the taxpayer base, especially among small- and medium-sized firms and individual taxpayers. Moreover, an examination of the Tax Effort Ratio suggests that direct taxes are making a larger contribution to overall tax revenue, which is indicative of changes in the composition of income. Positive correlations between various direct tax types and overall tax revenue are revealed by correlation analysis, highlighting the interdependence of tax collecting dynamics. The study admits its limitations, which could affect the finding’s generalisation and interpret. These limitations include data limits, methodological difficulties, and contextual issues. However, the knowledge gained has significant implications for additional study areas, decision-making by managers, and policy formation with regards to improving the efficiency of tax administration, encouraging compliance with taxes, and supporting sustainable financial governance in India. In order to tackle these issues and develop proven methods for enhancing the results of tax administration and fostering equitable economic growth, interdisciplinary cooperation, involvement of stakeholders, and continuous surveillance and evaluation are advised. Keywords: Tax, Regression, CAGR, Tax Effort Ratio, Correlation, Ratio, Revenue, Income.
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