Theories of Economic Growth: An Analysis of Classical and Modern Approaches

Abstract

This study provides a comprehensive theoretical analysis of classical and modern economic growth theories by examining their conceptual foundations, principal determinants, and significance in understanding long-term economic development. It traces the evolution of economic growth thought from early classical views—centered on labor and capital—to contemporary perspectives that emphasize the roles of innovation, human capital, and technology. Employing a comparative and descriptive theoretical approach, the research draws upon seminal works of classical economists such as Adam Smith and David Ricardo, alongside modern frameworks including the Solow-Swan neoclassical model and endogenous growth theories proposed by Paul Romer and others. Through an extensive literature review and conceptual comparison, the study identifies the major theoretical transitions and their underlying assumptions over time. The findings suggest that while classical models laid the groundwork for growth theory through the lens of capital accumulation and labor productivity, modern approaches offer more nuanced and internally driven mechanisms of sustained growth, particularly through the inclusion of technological progress and knowledge creation. This paper contributes to the broader discourse on economic theory by mapping the intellectual progression of growth models and emphasizing the interconnections between traditional and modern approaches. It further illustrates the importance of integrated theoretical models in interpreting contemporary economic dynamics. For policymakers, the insights from this analysis offer a deeper understanding of how growth theories can inform long-term development strategies, especially in the context of knowledge-based and digital economies. However, as a theory-oriented study, it does not engage in empirical data analysis; future research may expand upon this framework through the application of statistical methods and case-based modeling to validate and operationalize theoretical conclusions.