Abstract

The prices of goods often exhibit cyclical patterns, reflecting the business cycle of the economy. This paper develops a model to analyse and forecast these cyclical patterns, using data for the price of stable crops in Nigeria. The Baxter-King Filter isolates the cyclical components and smooths the data, on which the Discrete Fourier Transform (DFT) is used to determine the frequencies of the cycles. The Fourier series is used to reconstruct the price trends using periodic signals, eliminating short-term shocks and variations. Results indicate critical cycles of 13, 14, 19, 47, 52, and 53 months, which are often missed in other methods of analysis. These findings demonstrate the value of combining the Discrete Fourier Transform and Fourier series as a powerful tool for uncovering price inflation dynamics and improving forecasting models for policy analysis.

Keywords: Fourier Transform, Economic Forecasting, Fourier Series, Discrete Fourier Transform, Macroeconomic Modelling

How to Cite:

Raizada, A., (2025) “The Use of the Discrete Fourier Transform and Fourier Series Analysis in Macroeconomic Modelling and Forecasting”, UCL Journal of Economics 4(1). doi: https://doi.org/10.14324/111.444.2755-0877.2027