The Science and Art of Communicating Fan Chart Uncertainty: The Case of Inflation Outcome in Sierra Leone

  • Emerson Abraham JACKSON Bank of Sierra Leone, Freetown, Sierra Leone
  • Edmund TAMUKE Bank of Sierra Leone, Freetown, Sierra Leone

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 recommends the use of other model approaches like Scenario and Sensitivity analysis, also considered relevant in providing leading evidence of balancing risks surrounding macroeconomic outlook.

References

[1] Aikman D., Barett P., Kapadia S., King M., Proudman J., Taylor T., Weymarn I. and Yates T. 2010. Uncertainty in macroeconomic policy making: art or science? Paper delivered to Royal Society Conference on “Handling Uncertainty in Science”, March 2010, London. Available at: http://www.bankofengland.co.uk/publications/ Pages/news/2010/034.aspx
[2] Blix M., and Sellin P. 1998. Uncertainty bands for inflation forecasts, Severiges Riskbank Working Paper Series. Available at: https://www.econstor.eu/bitstream/10419/83036/1/76864125X.pdf
[3] Ehrmann, M., and Fratzscher, M. 2002. Interdependence between the Euro Area and the US: What role for EMU? European Central Bank Working Paper No. 02-200.
[4] Elder, R. 2005. Assessing the MPC’s. Quarterly Bulletin. Available at: https://ssrn.com/abstract=813845
[5] Franta, M., Baruník, J., Horváth, R. and Šmídková, K. 2014. Are Bayesian fan charts useful? The effect of zero lower bound and evaluation of financial stability tests, International Journal of Central Banking, 10(1): 159-187.
[6] Gibbons, J.F., and Mylroie, S. 1973. Estimation of impurity profiles in ion-implanted amorphous targets using joined half-Gaussian distributions. Applied Physics Letters, 22(11): 568-569. DOI: 10.1063/1.1654511
[7] Hamilton J.D., and Perez-Quiros, G. 1996. What do the leading indicators lead? The Journal of Business, 69: 27 – 49.
[8] Jackson, E.A. and Jabbie, M. 2020. Twin deficit hypothesis as an indication of government failure in Sierra Leone: An empirical investigation (1980 to 2018). İktisat Politikası Araştırmaları Dergisi, Journal of Economic Policy Researches, 7(1): 43-68. DOI: https://doi.org/10.26650/JEPR658440
[9] Jackson, E.A. and Tamuke, E. 2018. Probability forecast using fan chart analysis: A case of the Sierra Leone economy. Journal of Advanced Studies in Finance, 9(1): 34-44. DOI: https://doi.org/10.14505/jasf.v9.1(17).04
[10] Jackson, E.A., Jabbie, M., Tamuke, E., and Ngombu, A. 2020. Adoption of inflation targeting in Sierra Leone: An empirical discourse. İktisat Politikası Araştırmaları Dergisi, Journal of Economic Policy Researches, 7(2): 1-32. DOI: https://doi.org/10.26650/JEPR735604
[11] Jackson, E.A., Tamuke E., and Jabbie M. 2019. Disaggregated Short-Term Inflation Forecast (STIF) for monetary policy decision in Sierra Leone. Financial Markets, Institutions and Risks (FMIR), 3(4): 32-48. DOI: https://doi.org/10.21272/fmir.3(4).32-48.2019
[12] John, S. 1982. The three-parameter two-piece normal family of distributions and its fitting. Communications in Statistics – Theory and Methods, 11(8): 879-885. DOI: https://doi.org/10.1080/03610928208828279
[13] Johnson, N.L., Kotz, S., and Balakrishnan, N. 1994. Continuous univariate distributions, Volume 1, John Wiley and Sons. ISBN: 978-0-471-58495-7
[14] Kongcharoen, C, Kruangpradit, T. 2013. Autoregressive Integrated Moving Average with Explanatory Variable (ARIMAX) model for Thailand export. The 33rd International Symposium on Forecasting.
[15] Mordi, C.N.O., Adebiyi, M.A., and Adamgbe, E.T. 2012. Short term inflation forecasting for monetary policy in Nigeria. Central Bank of Nigeria (CBN). Available at: https://www.academia.edu/10165507/SHORT_ TERM_INFLATION_FORECASTING_FOR_MONETARY_POLICY_IN_NIGERIA
[16] Razi, A., and Loke, P.L. 2017. Fan chart: The art and science of communicating uncertainty. IFC Bulletin Chapters, in: Bank for International Settlements (Ed.), Statistical implications of the new financial landscape, Volume 43, Bank for International Settlements.
[17] Stock, J.H., and Watson, M.W. 2003. Introduction to Econometrics. Addison Wesley. Available at: https:// scholar.harvard.edu/stock/publications/introduction-econometrics
[18] Wallis, K.F. 2014. The two-piece normal, binormal, or double Gaussian distribution: Its origin and rediscoveries. Statistical Science, 29(1): 106-112. Available at: https://arxiv.org/pdf/1405.4995.pdf
[19] Warburton, C.E.S., Jackson, E.A. 2020. Monetary policy responses to exogenous perturbations: The case of a small open economy (2007-2018). PSL Quarterly Review, 73(293): 181-201. DOI: https://doi.org/10.13133/2037643_73.293_5
Published
2021-06-30
How to Cite
JACKSON, Emerson Abraham; TAMUKE, Edmund. The Science and Art of Communicating Fan Chart Uncertainty: The Case of Inflation Outcome in Sierra Leone. Journal of Advanced Studies in Finance, [S.l.], v. 12, n. 1, p. 28-39, june 2021. ISSN 2068-8393. Available at: <https://journals.aserspublishing.eu/jasf/article/view/6380>. Date accessed: 19 oct. 2021. doi: https://doi.org/10.14505//jasf.v12.1(23).03.
Section
Journal of Advanced Studies in Finance