Analyzing Determinants of Inflation When There are Data Limitation: The Case of Sierra Leone

Abstract

This paper examines the determinants of inflation in Sierra Leone using a structural vector autoregression (VAR) approach to help forecast inflation for operational purposes. Despite data limitations, the paper accurately models inflation in Sierra Leone. As economic theory predicts, domestic inflation is found to increase with higher oil prices, higher money supply, and nominal exchange rate depreciation. The paper then employs a historical decomposition approach to pinpoint the sources of a marked decline in inflation in 2006 and assesses its forecasting properties. Overall, the model serves as a useful addition to the toolkit for analyzing and forecasting inflation in countries with limited data availability.