Abstract
The major goal of this paper is a better understanding of the price dynamics of the eight West African Economic and Monetary Union (WAEMU) member states. More specifically, the study intends to find the best models with suitable forecasting power for the monthly Harmonized Consumer Price Indices (HCPI) of each of the WAEMU countries. Descriptive statistics and time series modeling approaches were applied to the HCPI base 100=2008 series covering the period from January 1998 to December 2019. The analysis revealed that Guinea-Bissau had the highest average HCPI of 99.88 and Senegal the lowest of 93.73. Togo attained the highest HCPI of 119.60 and Benin the lowest of 71.54 over the period studied. The indices of Togo and Guinea-Bissau have the highest and the smallest variance of 225.56 and 79.60, respectively. All the indices have an upward trend and contain cyclical and seasonal components. Using the Box-Jenkins methodology and Expert Modeler of SPSS five types of outliers, i.e. additive, additive patch, transient, innovational and level change, have been detected and different SARIMA models were proposed. Bartlett's B-test detects significant periodic effects in the residuals of the models for Burkina-Faso and Cote d’Ivoire. The residuals of all the models have been declared Gaussian by Shapiro-Wilks and Jarque-Bera normality tests while those of Cote d’Ivoire fail the latest test for normality due to the discrepancy of their skewness with that of a normal distribution. Adequacy of the claimed models has been corroborated by adequate values of key fitting and predicting statistics and the non-significance of the paired t-test on the mean difference between the observed and the adjusted values. Thus SARIMA (0,1,0) (0,1,1)12 model was found to best fit the HCPI for Burkina Faso, Cote d'Ivoire, Niger, Senegal and Togo; and the data for Benin, Guinea Bissau and Mali are found to be SARIMA (3,1,0) (1,0,1)12, SARIMA (0,1,0) (1,0,1)12 and SARIMA (1,1,1) (0,1,1)12 process, respectively. The differences between the retained models raise doubts on the claimed objective of convergence of the economies of the WAEMU countries. Engle's Lagrange Multiplier test for autoregressive conditional heteroscedasticity (ARCH) reveals the homoscedasticity of the residuals of all the models but the one of Cote d'Ivoire. Thus, for better modeling of the index of Cote d’Ivoire, a GARCH model may be envisioned.
Highlights
Price indices constitute through their history and their forecasts essential elements in decision making, planning, and policy evaluation
Time series are often supposed to have four components: a trend, that represents the long-term evolution; a cyclical component which is a smooth, almost periodic movement around the trend with phases of growth and recession; a seasonal component representing the sub-annual fluctuations that are repeated more or less regularly from year to year; and an irregular component, regrouping all the more or less erratic fluctuations not taken into account in previous components
Parsimonious seasonal autoregressive integrated moving average (SARIMA) models having white noise residuals, good fitting and forecasting abilities have been proposed as processes for generating the harmonized consumer price index (HCPI) of each of the eight West African Economic and Monetary Union member countries
Summary
Price indices constitute through their history and their forecasts essential elements in decision making, planning, and policy evaluation. The harmonized consumer price index (HCPI) adopted in 1996 by the West African. Joseph Koula et al.: On the Analysis and Modelling of the Harmonized Consumer Price Indices of West African. Economic and Monetary Union (WAEMU) member states is no exception to this regard. The HCPI has three main domains of possible uses; namely economic, accounting, and social domains. It can serve for instance as a measuring instrument of the inflation and indexation of income or as a deflator of macroeconomic aggregates such as the Gross Domestic Product. The convergence of inflation rates constituting a requirement in the WAEMU, this index is a convenient multilateral surveillance instrument
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