Analysis and Forecasting of Consumer Price Index (CPI) in Kenya and South Africa using Holt Winter Model

Jackson K. Njenga
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Abstract

In this paper, Holt-Winters exponential smoothing approach is applied to model and forecast monthly CPI in Kenya and South Africa. Monthly data from January 2000 to December 2023 was obtained from Central Bank of Kenya and South Africa department of statistics. Time series decomposition showed that the trend component is the most dominant component in both countries. Kenya Holt-Winters estimated model has parameters 0.6756, 0.0077 and 1 for level smoothing, trend smoothing and seasonal smoothing respectively. On the other hand, South Africa estimated model has parameters 0.8917, 0.1057 and 1 for level smoothing, trend smoothing and seasonal smoothing respectively. The estimated models are efficient and effective as on average the fitted values are less than one percent off the observed values. The initial values for level smoothing, trend smoothing and seasonal smoothing are approximately equal in both countries. The estimated models are then used to predict CPI next twelve months. Over the forecast period, South Africa will experience a lower index as compared to Kenya. In both countries, it’s expected that monthly CPI will rise.
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利用霍尔特冬季模型分析和预测肯尼亚和南非的消费价格指数 (CPI)
本文采用霍尔特-温特斯指数平滑法对肯尼亚和南非的月度消费物价指数进行建模和预测。从肯尼亚中央银行和南非统计部门获得了 2000 年 1 月至 2023 年 12 月的月度数据。时间序列分解显示,趋势成分是两国最主要的成分。肯尼亚霍尔特-温特斯估计模型的水平平滑、趋势平滑和季节平滑参数分别为 0.6756、0.0077 和 1。另一方面,南非估计模型的水平平滑、趋势平滑和季节平滑参数分别为 0.8917、0.1057 和 1。由于拟合值与观测值的平均偏差小于 1%,因此估计模型是高效和有效的。两国的水平平滑、趋势平滑和季节平滑初始值大致相同。然后使用估计模型预测未来 12 个月的 CPI。在预测期内,南非的指数将低于肯尼亚。预计两国的月度 CPI 都将上升。
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