WAVELET-BASED COMPUTATIONAL FRAMEWORK FOR THE SOLOW-SWAN ECONOMIC MODEL

In this paper, we introduce an innovative numerical technique for addressing the classical Solow-Swan economic growth model through the application of the Haar wavelet approach. The Solow-Swan model, a cornerstone of neoclassical economics, elucidates long-run economic growth influenced by capital accumulation, labor, and technological advancements. Although various computational methods have been utilized to study its behavior, the use of wavelet-based techniques, specifically Haar wavelets, has been largely overlooked. The Haar wavelet method provides distinct benefits, such as computational simplicity and adaptability to piecewise continuous functions. By transforming the Solow-Swan model into a set of algebraic equations using Haar wavelet expansion, we showcase the method’s ability to accurately capture growth dynamics. We present numerical results to substantiate the efficacy of this approach and compare it with conventional numerical techniques, underscoring the advantages of wavelet-based solutions. This study offers a fresh perspective on economic modeling, emphasizing the potential of wavelet theory in the numerical analysis of growth equations.