Spectral Analysis: Time Series Analysis in Frequency Domain
ICFAI Business School, Hyderabad
Kaushik Roy Chowdhury
M.Phil/Ph.D, Indira Gandhi Institute of Devevlopment Research
August 9, 2009
ICFAI University Journal of Applied Economics, Vol. 8, No. 5 & 6, pp. 83-101, September-November 2009
This paper describes how the frequency domain analysis provides an alternative approach to time domain analysis for a given time series. Spectral and periodogram analysis for a given time series are performed to detect trends and seasonalities in the data. A cross-spectral analysis is used to find causality and co-movements in two different time series. Univariate frequency domain analysis is done using time series of varying nature including simulated white noise process, random walk process, AR (1) process, Wolfer’s Sunspot Data and Box-Jenkins Airlines Data; while bivariate (cross spectral) analysis is done for macroeconomic variables such as Money in Circulation and Inflation.
Keywords: spectral analysis, periodogram, cross-spectral analysis, time-series analysis
JEL Classification: C1, C22, C32, E4Accepted Paper Series
Date posted: August 11, 2009 ; Last revised: February 10, 2010
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