A Model Approach to Understanding Monetary Aggregates Growth in Sierra Leone and Implications for Policy Formulation

Emerson Abraham Jackson, Patricia Sarah Vandy
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Abstract

This study has adopted a model approach to developing an understanding of monetary aggregates (MA) growth in Sierra Leone, which certainly has implications for effective policy formulation by the central bank authority. In pursuance of this, we utilized the Autoregressive Moving Average (ARIMA) model with data spanning 2002M1 to 2021M12 to investigate the out-of-sample projection performance of the disaggregated components that makes up the MA for Sierra Leone – typically in this case Reserve Money (RMA), Currency-in-Circulation (CiC) and Reserve Money (RM). In our evidence from the empirical projection (covering the period 2022M1-2022M12), we observed that RM is projected to grow more than CiC over the observed period. Given RM being the operational target of the Bank of Sierra Leone, we believe that such an outcome is a promising indication particularly in ensuring the bank addresses its core mandates of monitoring price and financial stability. The increased scope of RM in the BSL system is a laudable outcome when it comes to meeting reserve requirements and also managing risks about price and financial stability. The study recommends that the BSL adopt innovation strategies concerned with FinTech and the emergence of the National Switch to effectively manage the MA portfolio in the entire banking system, which will also support the overall growth ambition of the central government.  
理解塞拉利昂货币总量增长的模型方法及其对政策制定的影响
本研究采用了一种模型方法来理解塞拉利昂的货币总量(MA)增长,这当然对中央银行当局有效的政策制定有影响。为此,我们利用自回归移动平均(ARIMA)模型,其数据跨越2002年至2012年,研究构成塞拉利昂MA的分解成分的样本外预测性能——在这种情况下,通常是储备货币(RMA)、流通货币(CiC)和储备货币(RM)。在我们的实证预测(涵盖2022M1-2022M12期间)的证据中,我们观察到,在观测期间,预计RM的增长将超过CiC。鉴于RM是塞拉利昂银行的业务目标,我们认为这样的结果是一个有希望的迹象,特别是在确保银行履行其监测价格和金融稳定的核心任务方面。当涉及到满足准备金要求以及管理价格和金融稳定风险时,BSL系统中RM范围的扩大是一个值得称赞的结果。该研究建议BSL采用与金融科技相关的创新战略和国家转换的出现,以有效管理整个银行系统的MA投资组合,这也将支持中央政府的整体增长目标。
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