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Probability Forecast Using Fan Chart Analysis: A case of the Sierra Leone Economy

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  • Jackson, Emerson Abraham
  • Tamuke, Edmund

Abstract

This article made use of ARIMAX methodology in producing probability forecast from Fan Chart analysis for the Sierra Leone economy. In view of the estimation technique used to determine best model choice for outputting the Fan Chart, the outcomes have shown the importance of Exchange Rate variable as an exogenous component in influencing Inflation dynamics in Sierra Leone. The use of Brier Score probability was also used to ascertain the accuracy of the forecast methodology. Despite inflation outcome is showing an upward trend for the forecasted periods, the probability bands (upper and lower) have also revealed the peculiarity of the Sierra Leone economy when it comes to addressing policy measures for controlling spiralling inflation dynamics.

Suggested Citation

  • Jackson, Emerson Abraham & Tamuke, Edmund, 2018. "Probability Forecast Using Fan Chart Analysis: A case of the Sierra Leone Economy," MPRA Paper 88853, University Library of Munich, Germany, revised 04 Sep 2018.
    • Handle: RePEc:pra:mprapa:88853
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    References listed on IDEAS

    as
    1. Emerson Abraham Jackson & Edmond Tamuke & Abdulai Sillah, 2018. "Modelling Monthly Headline Consumer Price Index (HCPI) through Seasonal Box-Jenkins Methodology," International Journal of Sciences, Office ijSciences, vol. 7(01), pages 51-56, January.
    2. Nicolas Perez-Mora & Miquel L. Alomar & Victor Martinez-Moll, 2018. "Spanish Energy Market: Overview Towards Price Forecast," International Journal of Energy Economics and Policy, Econjournals, vol. 8(3), pages 1-7.
    3. Kallon, Kelfala M, 1994. "An Econometric Analysis of Inflation in Sierra Leone," Journal of African Economies, Centre for the Study of African Economies, vol. 3(2), pages 199-230, October.
    4. Casillas-Olvera, Gabriel & Bessler, David A., 2006. "Probability forecasting and central bank accountability," Journal of Policy Modeling, Elsevier, vol. 28(2), pages 223-234, February.
    5. Tilmann Gneiting & Roopesh Ranjan, 2011. "Comparing Density Forecasts Using Threshold- and Quantile-Weighted Scoring Rules," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 29(3), pages 411-422, July.
    6. EMERSON Abraham Jackson, 2018. "Comparison Between Static And Dynamic Forecast In Autoregressive Integrated Moving Average For Seasonally Adjusted Headline Consumer Price Index," Revista Economica, Lucian Blaga University of Sibiu, Faculty of Economic Sciences, vol. 70(1), pages 53-65, August.
    7. Michael P. Clements, 2004. "Evaluating the Bank of England Density Forecasts of Inflation," Economic Journal, Royal Economic Society, vol. 114(498), pages 844-866, October.
    8. Kenneth F. Wallis, 2004. "An Assessment of Bank of England and National Institute Inflation Forecast Uncertainties," National Institute Economic Review, National Institute of Economic and Social Research, vol. 189(1), pages 64-71, July.
    9. Gneiting, Tilmann & Ranjan, Roopesh, 2011. "Comparing Density Forecasts Using Threshold- and Quantile-Weighted Scoring Rules," Journal of Business & Economic Statistics, American Statistical Association, vol. 29(3), pages 411-422.
    10. Edmund TAMUKE & Emerson JACKSON & Abdulai SILLAH, 2018. "Forecasting Inflation In Sierra Leone Using Arima And Arimax: A Comparative Evaluation. Model Building And Analysis Team," Theoretical and Practical Research in the Economic Fields, ASERS Publishing, vol. 9(1), pages 63-74.
    11. James W. Taylor, 2008. "A Comparison of Univariate Time Series Methods for Forecasting Intraday Arrivals at a Call Center," Management Science, INFORMS, vol. 54(2), pages 253-265, February.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Jackson Emerson Abraham, 2017. "Theoretical and Methodological Context of (Post)-Modern Econometrics and Competing Philosophical Discourses for Policy Prescription," Journal of Heterodox Economics, Sciendo, vol. 4(2), pages 119-129, December.
    2. Jackson, Emerson Abraham & Tamuke, Edmund, 2019. "Predicting disaggregated tourist arrivals in Sierra Leone using ARIMA model," MPRA Paper 96845, University Library of Munich, Germany, revised 23 Dec 2019.
    3. Emerson Abraham JACKSON & Mohamed JABBİE & Edmund TAMUKE & Augustine NGOMBU, 2020. "Adoption of Inflation Targeting in Sierra Leone: An Empirical Discourse," Journal of Economic Policy Researches, Istanbul University, Faculty of Economics, vol. 7(2), pages 21-50, July.
    4. Jackson, Emerson Abraham & Kamara, Purity & Kamara, Abdulsalam, 2022. "Determinants of Inflation in Sierra Leone," MPRA Paper 117278, University Library of Munich, Germany, revised Apr 2023.
    5. Jackson, Emerson Abraham, 2020. "Understanding SLL / US$ exchange rate dynamics in Sierra Leone using Box-Jenkins ARIMA approach," MPRA Paper 97965, University Library of Munich, Germany, revised 03 Jan 2020.
    6. JACKSON Emerson Abraham & TAMUKE Edmund & JABBIE Mohamed, 2019. "Disaggregated Short-Term Inflation Forecast (Stif) For Monetary Policy Decision In Sierra Leone," Revista Economica, Lucian Blaga University of Sibiu, Faculty of Economic Sciences, vol. 71(3), pages 31-53, November.
    7. Jackson, Emerson Abraham & Tamuke, Edmund, 2021. "The Science and Art of Communicating Fan Chart Uncertainty: The case of Inflation Outcome in Sierra Leone," MPRA Paper 105892, University Library of Munich, Germany, revised 05 Jan 2021.

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    More about this item

    Keywords

    Inflation Forecast; ARIMAX; Fan Chart; Brier Score; Sierra Leone;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • E27 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation: Models and Applications
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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