PREDICTING DISAGGREGATED TOURIST ARRIVALS IN SIERRA LEONE USING ARIMA MODEL
Abstract
This study has uniquely made use of Box-Jenkins ARIMA models to address the core of the three objectives set out in view of the focus to add meaningful value to knowledge exploration. The outcome of the research has testified the achievements of this through successful nine months out-of-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 provide 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 tourism in the country.
References
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[12] Kelikume, I, and Salami, A. 2014. Time series modeling and forecasting inflation: Evidence from Nigeria. The International Journal of Business and Finance Research, 8(2), 41-51.
[13] Kravchuk, K. 2017. Forecasting: ARIMAX Model Exercises (Part-5). Available at: https://www.google.co.uk/amp/s/www.r-bloggers.com/forecasting-arimax-modelexercises-part-5/amp/.
[14] Mason, P. 2015. Tourism impacts, planning and management. London: Routledge; 3th Edition. ISBN: 978-1138016293, 272 p.
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[16] Pankratz, A. 1983. Forecasting with Univariate Box - Jenkins Models: Concepts and cases. USA: John Wiley & Sons, Inc. ISBN: 9780471090236.
[17] Pereda, M.H. 2002. Repeat visitors of a tourist destination. Journal of Travel Research, 36(1): 35-43.
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[21] Tamuke, E., Jackson, E.A., and Sillah, A. 2018. Forecasting inflation in Sierra Leone using ARIMIA and ARIMAX: A comparative evaluation. Theoretical and Practical Research in the Economic Fields, Volume IX, Issue 1(17): 63-74.
[22] Taylor, J.W. 2003. Short-term electricity demand forecasting using double seasonal exponential smoothing. Journal of Operational Research Society, 54: 799-805.
[23] Taylor, J.W. 2008. A Comparison of univariate time series methods for forecasting intraday arrivals at a call center. Management Science, 54: 253-265.
[24] Wold, H. 1938. A study in the analysis of stationary time series. Doctoral Thesis, Uppsala: Almqvist & Wiksell.
[25] Yuksel, A., and Yuksel, F. 2007. Shopping risk perceptions: Effects on tourists’ emotions, satisfaction and expressed loyalty intentions. Tourism management, 28(3): 703-713. DOI: 10.1016/j.tourman.2006.04.025.
*** Statistics Sierra Leone. 2018. Report on the 2016 and 2017 Real Gross Domestic Product (RGDP) Figures at 2006 Price Index. Available at: www.statistics.sl/images/StatisticsSL/Documents/gdp/2017_gdp_analysis.pdf.
*** Statistics Sierra Leone. 2012. Tourism statistics bulletin 2011. Available at: https://www.statistics.sl/images/StatisticsSL/Documents/Publications/2011/tourism_bulletin_2011.pdf.
*** Trading Economics (n/d). Sierra Leone tourist arrivals. Available at: https://tradingeconomics.com/sierra-leone/tourist-arrivals.(accessed: 13th August, 2019).
*** World Travel & Economic Council. 2019. Travel and tourism impact 2019. Available at: https://www.wttc.org/-/media/files/reports/economic-impact-research/regions-2019/world2019.pdf.
[2] Betts, BSH. 2016. The role of tourism in the development of Sierra Leone. American Scientific Research Journal for Engineering, Technology, and Sciences, 26(4): 205-224.
[3] Bokhari, H., and Feridun, M. 2006. Forecasting inflation through Econometric Models: An empirical study on Pakistani. Data Dogus Universitesi Dergisi, 7(1): 37-47.
[4] Green, S. 2011. Time series analysis of stock prices using the Box-Jenkins Approach. Master’s Thesis submitted to College of Graduate Studies, Georgia Southern University.
[5] Hamjah, M.A. 2014. Climatic effects on major pulse crops production in Bangladesh: An application of Box-Jenkins ARIMAX Model. Journal of Economics and Sustainable Development, 5(15): 169-180.
[6] Jackson, E.A. 2015a. Deforestation on the Freetown Peninsula – A case of Livelihood and Biodiversity Loss in the Goderich community. International Journal of Research in Agriculture and Forestry, 2(7): 21-34.
[7] Jackson, E.A. 2015b. Ethnographic narrative of forest decline in the Goderich community: The people’s perspectives. Forest Research, 4(4): 1-7. DOI:https://doi.org/10.4172/2168-9776.1000157.
[8] Jackson, E.A. 2018. Comparison between static and dynamic forecast in autoregressive integrated moving average for seasonally adjusted headline consumer price index. Revista Economica, 70(1): 53 – 65.
[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.
[10] Jackson, E.A., Sillah, A., and Tamuke, E. 2018. Modelling monthly Headline Consumer Price Index (HCPI) through Seasonal Box-Jenkins methodology. International Journal of Sciences, 7(1): 51-56. DOI:https://doi.org/10.18483/ijSci.1507.
[11] Jackson, E.A., Tamuke, E., and Jabbie, M. 2019. Disaggregated Short-Term Inflation Forecast (STIF) for monetary policy decision in Sierra Leone. Lucian Blaga University of Sibiu, Faculty of Economic Sciences, Revista Economica, 71(3): 31-53, November.
[12] Kelikume, I, and Salami, A. 2014. Time series modeling and forecasting inflation: Evidence from Nigeria. The International Journal of Business and Finance Research, 8(2), 41-51.
[13] Kravchuk, K. 2017. Forecasting: ARIMAX Model Exercises (Part-5). Available at: https://www.google.co.uk/amp/s/www.r-bloggers.com/forecasting-arimax-modelexercises-part-5/amp/.
[14] Mason, P. 2015. Tourism impacts, planning and management. London: Routledge; 3th Edition. ISBN: 978-1138016293, 272 p.
[15] Nyomi, T. 2019. Understanding Inflation trends in Israel: A Univariate approach. MPRA_Paper_92427.
[16] Pankratz, A. 1983. Forecasting with Univariate Box - Jenkins Models: Concepts and cases. USA: John Wiley & Sons, Inc. ISBN: 9780471090236.
[17] Pereda, M.H. 2002. Repeat visitors of a tourist destination. Journal of Travel Research, 36(1): 35-43.
[18] Petrevska, B. 2017. Predicting tourism demand by A.R.I.M.A. Models. Economic Research, 30(1): 939-950. DOI:https://doi.org/10.1080/1331677X.1314822.
[19] Slutsky E.E. 1927. Slozhenie sluchainykh prichin, kak istochnik tsiklicheskikh protsessov. Voprosy Kon Yunktury, 3: 34–64.
[20] Stock, J.H., and Watson, M.W. 2003. Introduction to econometrics. Amsterdam: Addison Wesley. ISBN: 9780201715958. Available at: https://www.sas.upenn.edu/~fdiebold/Teaching104/Ch1-7_slides.pdf
[21] Tamuke, E., Jackson, E.A., and Sillah, A. 2018. Forecasting inflation in Sierra Leone using ARIMIA and ARIMAX: A comparative evaluation. Theoretical and Practical Research in the Economic Fields, Volume IX, Issue 1(17): 63-74.
[22] Taylor, J.W. 2003. Short-term electricity demand forecasting using double seasonal exponential smoothing. Journal of Operational Research Society, 54: 799-805.
[23] Taylor, J.W. 2008. A Comparison of univariate time series methods for forecasting intraday arrivals at a call center. Management Science, 54: 253-265.
[24] Wold, H. 1938. A study in the analysis of stationary time series. Doctoral Thesis, Uppsala: Almqvist & Wiksell.
[25] Yuksel, A., and Yuksel, F. 2007. Shopping risk perceptions: Effects on tourists’ emotions, satisfaction and expressed loyalty intentions. Tourism management, 28(3): 703-713. DOI: 10.1016/j.tourman.2006.04.025.
*** Statistics Sierra Leone. 2018. Report on the 2016 and 2017 Real Gross Domestic Product (RGDP) Figures at 2006 Price Index. Available at: www.statistics.sl/images/StatisticsSL/Documents/gdp/2017_gdp_analysis.pdf.
*** Statistics Sierra Leone. 2012. Tourism statistics bulletin 2011. Available at: https://www.statistics.sl/images/StatisticsSL/Documents/Publications/2011/tourism_bulletin_2011.pdf.
*** Trading Economics (n/d). Sierra Leone tourist arrivals. Available at: https://tradingeconomics.com/sierra-leone/tourist-arrivals.(accessed: 13th August, 2019).
*** World Travel & Economic Council. 2019. Travel and tourism impact 2019. Available at: https://www.wttc.org/-/media/files/reports/economic-impact-research/regions-2019/world2019.pdf.
Published
2019-12-31
How to Cite
JACKSON, Emerson Abraham; TAMUKE, Edmund.
PREDICTING DISAGGREGATED TOURIST ARRIVALS IN SIERRA LEONE USING ARIMA MODEL.
Theoretical and Practical Research in Economic Fields, [S.l.], v. 10, n. 2, p. 132-142, dec. 2019.
ISSN 2068-7710.
Available at: <https://journals.aserspublishing.eu/tpref/article/view/4259>. Date accessed: 21 dec. 2024.
doi: https://doi.org/10.14505/tpref.v10.2(20).06.
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