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Arima Forecasting Model for Uganda's Consumer Price Index

机译:乌干达消费者价格指数的Arima预测模型

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In Uganda, the Central Bank watches closely inflation which happens to be one of the key macroeconomic indicators for which the central bank rate is anchored on. Uganda Bureau of Statistics disseminates monthly Consumer Price Indices (CPIs) to the various stakeholders. Currently, the CPI is computed for eight urban centres spread across the country. The monthly CPIs serve mostly those users who require past and current inflation rates. The main objective of this study is to identify and estimate an ARIMA model for the CPI and use it to make short term forecasts. We relied upon monthly Consumer Price Indices from January 2010 to July 2020 obtained from Uganda Bureau of Statistics. The time series was transformed so as to make it stationary, before identification and estimation of ARIMA (p, d, q) (P, D, Q)_(12) models. An ARIMA (1, 1, 1) (0, 1, 1)_(12) with no constant was selected as the best model, because it had the least AIC and BIC. Additionally, all the coefficients of the ARs and MAs were significant at 1% level. Using the selected model, inflation forecasts were generated for 12 months (August 2020 to July 2021) and found to fluctuate between 4.7 and 6 percent. We recommend this model to Uganda Bureau of Statistics and Central Bank to use it to make forecasts and disseminate them to users. In conclusion, generally good forecasts are vital for better resource allocation, planning and decision making.
机译:在乌干达,中央银行密切关注势头,这恰好是中央银行率锚定的关键宏观经济指标之一。乌干达统计局将每月消费者价格指数(CPI)传播给各利益攸关方。目前,CPI计算在全国各地的八个城市中心。每月CPI主要服务于需要过去和当前通胀率的那些用户。本研究的主要目标是识别和估算CPI的ARIMA模型,并使用它来进行短期预测。我们依赖于2010年1月至7月20日从乌干达统计局获得的每月消费者价格指数。在识别和估计Arima(P,D,Q)(P,D,Q)_(12)模型之前,改变了时间序列以使其静止。选择没有常数的Arima(1,1,1)(0,1,1)(0,1,1)作为最佳模型,因为它具有最低的AIC和BIC。另外,ARS和MA的所有系数在1%水平下显着。使用所选模型,将膨胀预测产生12个月(2020年8月至7月2021),发现在4.7%和6%之间波动。我们向乌干达统计局和央行局局建议这一模型将其用来使预测并将其传播给用户。总之,对于更好的资源分配,规划和决策,通常良好的预测至关重要。

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