Forecasting Spanish GDPs with Spectral Analysis

The paper emphasizes the recent use of spectral analysis for forecasting financial and economic time series which deserves consideration from econometricians. Time series of Spanish nominal and real GDPs are decomposed in simpler signals called approximations and details in the framework of the one-dimensional discrete wavelet analysis. The simplified signals are recomposed after Burg extension. 2017-2026 forecasts with spectral analysis are less optimistic than the ones of government agencies. Benchmarking spectral analysis to an ARIMA model show the pertinence of adding spectral analysis to the battery of tools used by econometricians and quantitative analysts for the forecast of economic time series.