Modelling and Forecasting Zimbabwe’s Tourist Arrivals Using Time Series Method: A Case Study of Victoria Falls Rainforest

Tendai Makoni, Delson Chikobvu


Modelling and forecasting of tourist arrivals at one of the Seven Natural Wonders of the World, the Victoria Falls Rainforest, is critical to the tourism industry and economy of Zimbabwe. The aim of this paper is to provide quantitative techniques that will help with accurate tourist arrivals forecasting, shedding light on seasonality and other patterns of tourist arrivals. A time series plot of the monthly tourist arrivals statistics from January 2006 to December 2017 availed by the Zimbabwe Tourism Authority and Zimbabwe Parks and Wildlife Management Authority shows an upward trend in tourist arrivals with large fluctuations. To tame the variance which is increasing with time, a logarithm transformation is done on the data. A SARIMA (2, 1, 0)(2, 0, 0)12 model fits well to the data and outperformed other SARIMA models and the naïve, seasonal naïve and Holt-Winters exponential smoothing models. A two-year future out-of-sample forecast is done using this model and gives reasonable forecasts that indicate a general rise in tourist arrivals. Investors, tourism managers and the government can make use of such results in order to find effective and efficient solutions to the investment, foreign currency, accommodation, transport and infrastructure development problems and other tourist-related challenges faced by Zimbabweans.


tourist arrivals; seasonality; time series; SARIMA models; Zimbabwe tourism figures

Full Text:



Copyright (c) 2018 Tendai Makoni, Delson Chikobvu

Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.