Disaggregated Short-Term Inflation Forecast (STIF) for Monetary Policy Decision in Sierra Leone

Abstract

In this paper, the researchers have developed a short term inflation forecasting (STIF) model using Box-Jenkins time series approach (ARIMA) for analysing inflation and associated risks in Sierra Leone. The model is aided with fan charts for all thirteen components, including the Headline CPI as communication tools to inform the general public about uncertainties that surround price dynamics in Sierra Leone – this then make it possible for policy makers to utilise expert judgments in a bid to stabilize the economy. The uniqueness of this paper is its interpretation of risks to each of the disaggregated components, while also improving credibility of decisions taken by policy makers at the Bank of Sierra Leone [BSL]. Empirically, Food and Non-Alcoholic Beverages, Housing and Health components indicate that shock arising from within or outside of Sierra Leone can significantly impact headline CPI, with immediate pass-through effect of high prices on consumers’ spending, at least in the short-run. The outcome of this empirical research shows uniqueness of the disaggregated model in tailoring policy makers’ attention towards targeting sector-specific policy interventions. Fan Charts produced have also highlighted degree of risks, which is based on confidence bands, which shows deviation from the baseline forecast. The ultimate goal is to improve sectoral productive capacity, while at the same time, monitoring price volatility spill-over through empirical disaggregation of the CPI basket – in association with this, outcome from the study also shows that the use of multivariate models like VAR would be welcome to monitor events on price dynamics in the national economy.