Fourier Transformation on Model Fitting for Pakistan Inflation Rate

Anam Iqbal (), Basheer Ahmad (), Kanwal Iqbal () and Asad Ali ()

Business and Economic Research, 2018, vol. 8, issue 1, 84-94

Abstract: Inflation is one of the serious economic indicators in Pakistan. Inflation can be crawling, walking, running, hyper and stagflation according to nature. To model monthly inflation rate in Pakistan periodogram analysis and frequency domain analysis which is also known as Fourier analysis or spectral analysis is used. After analyzing the data, inflation cycle length is observed and appropriate Fourier series models are fitted to the data. Monthly inflation rate is also analyzed by Auto Regressive Integrated Moving average (ARIMA). Further, models are compared and it is found that Fourier series models are more suitable to forecast inflation rate of Pakistan.

Keywords: Inflation; Periodogram; Fourier Series Models; ARIMA Models; Stationarity; Root Mean Square Error; Mean Absolute Error (search for similar items in EconPapers)
Date: 2018
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