IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/96845.html
   My bibliography  Save this paper

Predicting disaggregated tourist arrivals in Sierra Leone using ARIMA model

Author

Listed:
  • Jackson, Emerson Abraham
  • Tamuke, Edmund

Abstract

This study have uniquely mad use of Box-Jenkins ARIMA models to address the core of the threes objectives set out in view of the focus to add meaningful value to knowledge exploration. The outcome of the research have testify the achievements of this through successful nine months outof-sample forecasts produced from the program codes, with indicating best model choices from the empirical estimation. In addition, the results also provide description of risks produced from the uncertainty Fan Chart, which clearly outlined possible downside and upside risks to tourist visitations in the country. In the conclusion, it was suggested that downside risks to the low level tourist arrival can be managed through collaboration between authorities concerned with the management of tourist arrivals in the country.

Suggested Citation

  • 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.
  • Handle: RePEc:pra:mprapa:96845
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/96845/1/MPRA_paper_96845.pdf
    File Function: original version
    Download Restriction: no
    ---><---

    Other versions of this item:

    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. 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.
    3. 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.
    4. repec:srs:journl:jasf:v:9:y:2018:i:1:p:34-44 is not listed on IDEAS
    5. J W Taylor, 2003. "Short-term electricity demand forecasting using double seasonal exponential smoothing," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 54(8), pages 799-805, August.
    6. Ikechukwu Kelikume & Adedoyin Salami, 2014. "Time Series Modeling and Forecasting Information: Evidence from Nigeria," The International Journal of Business and Finance Research, The Institute for Business and Finance Research, vol. 8(2), pages 41-51.
    7. 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.
    8. Nicholas Apergis & Andrea Mervar & James E. Payne, 2017. "Forecasting disaggregated tourist arrivals in Croatia," Tourism Economics, , vol. 23(1), pages 78-98, February.
    9. Emerson JACKSON & Edmund TAMUKE, 2018. "Probability Forecast Using Fan Chart Analysis A Case of the Sierra Leone Economy," Journal of Advanced Studies in Finance, ASERS Publishing, vol. 9(1), pages 34-44.
    10. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    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 & Jabbie, Mohamed, 2019. "Disaggregated Short-Term Inflation Forecast (STIF) for Monetary Policy Decision in Sierra Leone," MPRA Paper 96735, University Library of Munich, Germany, revised 26 Nov 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 & 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.
    5. 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.
    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. 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.
    8. Jackson, Emerson Abraham, 2020. "Importance of the Public Service in Achieving the UN SDGs," MPRA Paper 101806, University Library of Munich, Germany, revised 02 Jun 2020.
    9. Barrow, Devon K., 2016. "Forecasting intraday call arrivals using the seasonal moving average method," Journal of Business Research, Elsevier, vol. 69(12), pages 6088-6096.
    10. 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.
    11. Theresa Maria Rausch & Tobias Albrecht & Daniel Baier, 2022. "Beyond the beaten paths of forecasting call center arrivals: on the use of dynamic harmonic regression with predictor variables," Journal of Business Economics, Springer, vol. 92(4), pages 675-706, May.
    12. Mauro Bernardi & Lea Petrella, 2015. "Multiple seasonal cycles forecasting model: the Italian electricity demand," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 24(4), pages 671-695, November.
    13. Kim, Myung Suk, 2013. "Modeling special-day effects for forecasting intraday electricity demand," European Journal of Operational Research, Elsevier, vol. 230(1), pages 170-180.
    14. 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.
    15. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    16. Barrow, Devon & Kourentzes, Nikolaos, 2018. "The impact of special days in call arrivals forecasting: A neural network approach to modelling special days," European Journal of Operational Research, Elsevier, vol. 264(3), pages 967-977.
    17. James W. Taylor, 2012. "Density Forecasting of Intraday Call Center Arrivals Using Models Based on Exponential Smoothing," Management Science, INFORMS, vol. 58(3), pages 534-549, March.
    18. Taylor, James W., 2010. "Triple seasonal methods for short-term electricity demand forecasting," European Journal of Operational Research, Elsevier, vol. 204(1), pages 139-152, July.
    19. Taylor, James W. & Snyder, Ralph D., 2012. "Forecasting intraday time series with multiple seasonal cycles using parsimonious seasonal exponential smoothing," Omega, Elsevier, vol. 40(6), pages 748-757.
    20. Ibrahim, Rouba & Ye, Han & L’Ecuyer, Pierre & Shen, Haipeng, 2016. "Modeling and forecasting call center arrivals: A literature survey and a case study," International Journal of Forecasting, Elsevier, vol. 32(3), pages 865-874.

    More about this item

    Keywords

    ARIMA Methodology; Out-of-Sample Forecast; Tourist Arrivals; 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
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • L83 - Industrial Organization - - Industry Studies: Services - - - Sports; Gambling; Restaurants; Recreation; Tourism

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pra:mprapa:96845. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Joachim Winter (email available below). General contact details of provider: https://edirc.repec.org/data/vfmunde.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.