Title: Does time-frequency scale analysis predict inflation? Evidence from Tunisia

Authors: Bilel Ammouri; Fakhri Issaoui; Habib Zitouna

Addresses: University of Tunis (UR-DEFI and ESSEC Tunis), 4, Abou Zakaria El Hafsi Street, Montfleury, Tunis, 1089, Tunisia; Axefinance, Street Lac Huron, La Couverture Building, 1053 Les Berges du Lac, Tunisia ' University of Tunis (UR-PS2D and ESSEC Tunis), 4, Abou Zakaria El Hafsi Street, Montfleury, Tunis 1089, Tunisia; University of Tunis (ESSEC Tunis), 4, Abou Zakaria El Hafsi Street, Montfleury, Tunis, 1089, Tunisia ' UR-MASE and Faculty of Economic Sciences and Management of Nabeul, University of Carthage, Campus Universitaire Mrezga, Nabeul, 8000, Tunisia

Abstract: Forecasting macroeconomic indicators has always been an issue for economic policymakers. Different models are available in the literature; for example univariate and/or multivariate models, linear and/or nonlinear models. This diversity requires a multiplicity of the used techniques. They can be classified as pre and post-time series. However, this multiplicity allows the improvement of a better forecast of the macroeconomic indicators during unrest (be it political, economic, and/or social). In this paper, we deal with the problem of the performance of the macroeconomic models for predicting Tunisia's inflation during instability following the 2011 revolution. To achieve this goal, the time-frequency-scale analysis (Fourier transform, wavelet transform, and Stockwell transform) is used. In fact, we are interested in the ability of these techniques to improve predictor performances. We suggest the performance of the adopted approach (time-frequency-scale analysis). This performance is not quite absolute because their performance is less than the multivariate model (dynamic factor model) during economic instability.

Keywords: inflation forecast; univariate model; multivariate model; time-frequency-scale analysis; Fourier transform; wavelet transform; Stockwell transform; Tunisia.

DOI: 10.1504/IJCEE.2021.10036614

International Journal of Computational Economics and Econometrics, 2021 Vol.11 No.2, pp.161 - 188

Received: 11 Feb 2019
Accepted: 19 Aug 2019

Published online: 27 Apr 2021 *

Full-text access for editors Access for subscribers Purchase this article Comment on this article