Jackson, Emerson Abraham and Tamuke, Edmund (2021): The Science and Art of Communicating Fan Chart Uncertainty: The case of Inflation Outcome in Sierra Leone.
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Abstract
The use of macro-econometric modelling technique has become a norm for policy decisions in central banks and in particular, the Bank of Sierra Leone. This study has leveraged on the technicalities of scientific and artistic approaches of assessing risks around point / baseline forecast; this in general makes it more convincing for probability confidence bands to be used in explaining uncertainty that surround point forecast in particular. In the case of this study, the use of the Box-Jenkins ARIMAX model has made it possible to highlight the relevance of Composite Leading Indicator (CLI) like Exchange Rate in alerting signals about early turning point of inflation outcome, both in terms of the uncertainty and risks surrounding its projections. With the derived (scientific) probability distribution of risks (30%, 60% and 90%), it was possible for the study outcome to unearth vast amount of information from the Inflation Fan Chart, particularly with respect to the art of providing balanced assessment of policy framework needed to communicate the BSL’s price stability objective. While the use of Fan Chart is hailed as a very relevant tool, the paper also recommend the use of other model approaches like Scenario and Sensitivity analysis, also considered relevant in providing leading evidence of balancing risks surrounding macroeconomic outlook.
Item Type: | MPRA Paper |
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Original Title: | The Science and Art of Communicating Fan Chart Uncertainty: The case of Inflation Outcome in Sierra Leone |
English Title: | The Science and Art of Communicating Fan Chart Uncertainty: The case of Inflation Outcome in Sierra Leone |
Language: | English |
Keywords: | Fan Chart; Normal Distribution; Forecast uncertainty; Balanced Risks |
Subjects: | C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C15 - Statistical Simulation Methods: General C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C52 - Model Evaluation, Validation, and Selection C - Mathematical and Quantitative Methods > C8 - Data Collection and Data Estimation Methodology ; Computer Programs > C81 - Methodology for Collecting, Estimating, and Organizing Microeconomic Data ; Data Access E - Macroeconomics and Monetary Economics > E3 - Prices, Business Fluctuations, and Cycles > E37 - Forecasting and Simulation: Models and Applications E - Macroeconomics and Monetary Economics > E5 - Monetary Policy, Central Banking, and the Supply of Money and Credit > E59 - Other |
Item ID: | 105892 |
Depositing User: | Mr Emerson Abraham Jackson |
Date Deposited: | 10 Feb 2021 05:30 |
Last Modified: | 10 Feb 2021 05:30 |
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URI: | https://mpra.ub.uni-muenchen.de/id/eprint/105892 |