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

_IMF Working Papers, December 1, 2008_

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## Bibliographic details
- Authors: Kadima D. Kalonji, Jan Gottschalk, Ken Miyajima
- Published: December 1, 2008
- Series: IMF Working Papers
- DOI: https://doi.org/10.5089/9781451871296.001

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### Summary and Main Findings
- The 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.
- Domestic inflation is found to increase with:
  - higher oil prices,
  - higher money supply, and
  - nominal exchange rate depreciation.
- The paper employs a historical decomposition approach to pinpoint the sources of a marked decline in inflation in 2006 and assesses the model’s forecasting properties.
- Overall conclusion: the model serves as a useful addition to the toolkit for analyzing and forecasting inflation in countries with limited data availability.

### Methodology
- Structural vector autoregression (VAR) methodology is used to analyze determinants of inflation and to produce forecasts for operational purposes.
- Historical decomposition is applied to identify the drivers of the marked decline in inflation in 2006.

### Policy-Relevant Implications
- Modeling inflation with a structural VAR can be effective even when data availability is limited.
- Key policy-relevant relationships identified:
  - Oil price increases are associated with higher domestic inflation.
  - Increases in money supply are associated with higher domestic inflation.
  - Nominal exchange rate depreciation is associated with higher domestic inflation.
- The model can inform operational forecasting and policy analysis in low-data environments.

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_Source: https://www.imf.org/en/publications/wp/issues/2016/12/31/analyzing-determinants-of-inflation-when-there-are-data-limitation-the-case-of-sierra-leone-22520_