Vol 20 No 2 (2026): BAREKENG: Journal of Mathematics and Its Application
Articles

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

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  • Jay Kishore Sahani,
  • Pankaj Sharma,
  • Nikhil Khanna,
  • Ajay Kumar
Jay Kishore Sahani
Department of Mathematics, D.A.V. PG College, India
Pankaj Sharma
Department of Mathematics, Pondicherry University, India
Nikhil Khanna
Department of Mathematics, College of Science, Sultan Qaboos University, Oman
Ajay Kumar
Department of Science and Computation, Shri Vishwakarma Skill University, India
DOI: https://doi.org/10.30598/barekengvol20iss2pp1557-1568
Published January 26, 2026
Keywords
  • Approximate solutions,
  • Economic growth,
  • Haar Wavelets,
  • Numerical Methods,
  • Solow-Swan Model
How to Cite
[1]
J. K. Sahani, P. Sharma, N. Khanna, and A. Kumar, “WAVELET-BASED COMPUTATIONAL FRAMEWORK FOR THE SOLOW-SWAN ECONOMIC MODEL”, BAREKENG: J. Math. & App., vol. 20, no. 2, pp. 1557-1568, Jan. 2026.

Copyright (c) 2026 Jay Kishore Sahani, Pankaj Sharma, Nikhil Khanna, Ajay Kumar

Creative Commons License

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Abstract

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.

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