Preprint Article Version 1 This version is not peer-reviewed

Predicting Disaggregated Tourist Arrivals in Sierra Leone using ARIMA Model

Version 1 : Received: 6 September 2019 / Approved: 9 September 2019 / Online: 9 September 2019 (12:11:03 CEST)

How to cite: Jackson, E.A..; Tamuke, E. Predicting Disaggregated Tourist Arrivals in Sierra Leone using ARIMA Model. Preprints 2019, 2019090102 (doi: 10.20944/preprints201909.0102.v1). Jackson, E.A..; Tamuke, E. Predicting Disaggregated Tourist Arrivals in Sierra Leone using ARIMA Model. Preprints 2019, 2019090102 (doi: 10.20944/preprints201909.0102.v1).

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 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 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.

Subject Areas

ARIMA Methodology; Out-of-Sample Forecast; Tourist Arrivals; Sierra Leone

Comments (0)

We encourage comments and feedback from a broad range of readers. See criteria for comments and our diversity statement.

Leave a public comment
Send a private comment to the author(s)
Views 0
Downloads 0
Comments 0
Metrics 0


×
Alerts
Notify me about updates to this article or when a peer-reviewed version is published.