Estimating Time-Varying ARMA Models Using Fourier Coefficients

Walter Enders and Jorge Ludlow

ISU General Staff Papers from Iowa State University, Department of Economics

Abstract: There is a large and growing literature indicating that traditional time-series models cannot properly capture the behavior of many important economic variables. The problem is that standard time-series models are linear so that they imply a symmetric adjustment process. Consider the simple linear^(1) model: *r = ctx,.i + e, (1) where: is a stationary random variable, and e,is a white-noise disturbance such that = for every time period t.

Date: 1998-10-01
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