Predicting disaggregated tourist arrivals in Sierra Leone using ARIMA model

Jackson, Emerson Abraham and Tamuke, Edmund (2019): Predicting disaggregated tourist arrivals in Sierra Leone using ARIMA model. Forthcoming in: Theoretical and Practical Research in Economic Fields , Vol. 10, No. 2(20) (31 December 2019)

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.

• Item Type: MPRA Paper
• Language: English
• Keywords: ARIMA Methodology; Out-of-Sample Forecast; Tourist Arrivals; Sierra Leone
• Subjects: C - Mathematical and Quantitative Methods > C3 - Multiple or Simultaneous Equation Models ; Multiple Variables > C32 - Time-Series Models ; Dynamic Quantile Regressions ; Dynamic Treatment Effect Models ; Diffusion Processes ; State Space Models; C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C52 - Model Evaluation, Validation, and Selection; C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C53 - Forecasting and Prediction Methods ; Simulation Methods; L - Industrial Organization > L8 - Industry Studies: Services > L83 - Sports ; Gambling ; Restaurants ; Recreation ; Tourism

References

Apergis, N., Mervar, A., and Payne, J. (2017). Forecasting Disaggregated tourist arrivals in Croatia: Evidence from seasonal univariate time series models. Tourism EconomicsVol. 23(1): pp. 78-98.

Betts, BSH. (2016). The Role of Tourism in the Development of Sierra Leone. American Scientific Research Journal for Engineering, Technology, and Sciences, Vol. 26(4): pp. 205-224.

Bokhari, H. and Feridun, M. (2006).Forecasting Inflation through Econometric Models: An Empirical Study on Pakistani Data.Dogus Universitesi Dergisi, 7(1), 37-47.

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.

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.

Jackson, E.A. (2018): Comparison between Static and Dynamic Forecast in Autoregressive Integrated Moving Average for Seasonally Adjusted Headline Consumer Price Index. Revista Economica, Vol. 70(1): pp. 53 – 65.

Jackson, E.A. (2015a). Deforestation on the Freetown Peninsula – A Case of Livelihood and Biodiversity Loss in the Goderich Community. International Journal of Research n Agriculture and Forestry, Vol. 2(7): pp. 21-34.

Jackson, E.A. (2015b). Ethnographic Narrative of Forest Decline in the Goderich Community: The People’s Perspectives. Forest Research, Vol. 4(4): pp. 1-7. DOI: 10.4172/2168-9776.1000157.

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, Vol. 9(1): p. 34-44.

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: 10.18483/ijSci.1507.

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.

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-part5/amp/. (Accessed: 17th February, 2018).

Mason, P. (2015). Tourism impacts, planning and management. London: Routledge.

Nyomi, T. (2019). Understanding Inflation trends in Israel: A Univariate approach. MPRA_Paper_92427.

Petrevska, B. (2017). Predicting tourism demand by A.R.I.M.A. models. Economic Research, Vol. 30(1): 939-950. DOI: 10.1080/1331677X.1314822.

Pankratz, A. (1983). Forecasting with Univariate Box - Jenkins Models: Concepts and Cases. USA: John Wiley & Sons, Inc.

Pereda, M.H. (2002). Repeat visitors of a tourist destination. Journal of Travel Research, Vol. 36(1): pp. 35-43.

Slutsky E. E. (1927) Slozhenie sluchainykh prichin, kak istochnik tsiklicheskikh protsessov. Voprosy kon yunktury, 3(1927), 34–64.

Statistics Sierra Leone. (2018). Report on the 2016 and 2017 Real Gross Domestic Product (RGDP) Figures at 2006 Price Index. Available at: https:// www.statistics.sl/images/StatisticsSL/Documents/gdp/2017_gdp_analysis.pdf. (Accessed: 13th August, 2019).

Statistics Sierra Leone. (2012). Tourism Statistics Bulletin 2011. Available at: https://www.statistics.sl/images/StatisticsSL/Documents/Publications/2011/tourism_bulletin_201 1.pdf. (Accessed: 14th August, 2019).

Stock, J.H. and Watson, M.W. (2003). Introduction to Econometrics. Amsterdam: Addison Wesley.

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, Vol. 9(1(17)): pp. 63-74.

Taylor, J.W. 2003. Short-term electricity demand forecasting using double seasonal exponential smoothing. Journal of Operational Research Society, 54(2003), 799-805.

Taylor, J.W. (2008). A Comparison of Univariate Time Series Methods for Forecasting Intraday Arrivals at a Call Center. Management Science, 54(2008), 253-265.

Trading Economics (n/d). Sierra Leone Tourist Arrivals. https://tradingeconomics.com/sierraleone/tourist-arrivals. (Accessed: 13th August, 2019).

Wold, H. (1938). A study in the analysis of stationary time series. Doctoral Thesis, Uppsala: Almqvist & Wiksell. World Travel & Economic Council (2019). Travel and Tourism Impact 2019. Available at: https://www.wttc.org/-/media/files/reports/economic-impact-research/regions2019/world2019.pdf. (Accessed: 14th August, 2019).

Yuksel, A., and Yuksel, F. (2007). Shopping risk perceptions: Effects on tourists’ emotions, satisfaction and expressed loyalty intentions. Tourism management, Vol. 28(3): pp. 703-713. DOI: 10.1016/j.tourman.2006.04.025.