NUMERICAL METHODS FOR MODELING INFLATION: A COMPARATIVE ANALYSIS OF MATHEMATICAL MODELS
Authors/Creators
- 1. Institute of Mechanics and Seismic Stability of Structures named after. M.T. Urazbaeva Academy of Sciences of the Republic of Uzbekistan , Tashkent, Uzbekistan
Description
Inflation modeling is a critical area of research in economic analysis, enabling policymakers and analysts to predict and control inflationary trends effectively. This paper provides a comparative overview of advanced differential equation-based mathematical models used in inflation estimation, including the Poisson equation, the heat equation, Navier-Stokes equations, Hamilton-Jacobi-Bellman (HJB) equation, Kalman filtering, and stochastic differential equations (SDEs). The paper also introduces numerical methods, such as finite difference and iterative algorithms, for solving these models. A concrete example problem related to regional inflation variations is explored, showcasing numerical solutions for better understanding and implementation.
Files
31-41 Javlonbek T.pdf
Additional details
References
- 1. Evans, L. C. Partial Differential Equations. American Mathematical Society. A comprehensive resource covering the theory of partial differential equations, essential for understanding models such as the Poisson and heat equations in economic contexts.
- 2. Sargent, T. J., Ljungqvist, L. Recursive Macroeconomic Theory (3rd ed.). MIT Press. This book discusses modern macroeconomic modeling, including the application of the Hamilton-Jacobi-Bellman equation for policy analysis (2012).