Hierarchical Forecasting of the Zimbabwe International Tourist Arrivals

The objectives of the paper is to: (1) adopt the hierarchical forecasting methods in modelling and forecasting international tourist arrivals in Zimbabwe;and (2) coming up with Zimbabwe international tourist arrivals Prediction Intervals (PIs) in Quantile Regression Averaging (QRA) to hierarchical tourism forecasts The unavailability of statistical models for Zimbabwe international tourist arrivals that cater for disaggregated tourism data and account for uncertainty due to parameter estimation methods, has resulted in poor marketing strategies, infrastructure and policies targeting wrong tourism groups Furthermore, the country is failing to attract significant Foreign Direct Investment for particular tourist arrivals Zimbabwe’s monthly international tourist arrivals data from January 2002 to December 2018 was used The data set was disaggregated according to the purpose of the visit Three hierarchical forecasting approaches, namely top-down, bottom-up and optimal combination approaches were applied to the data The results showed the superiority of the bottom-up approach over both the top-down and optimal combination approaches Forecasts indicate a general increase in aggregate series The combined methods provide a new insight into modelling tourist arrivals The approach is useful to the government, tourism stakeholders, and investors among others, for decision-making, resource mobilisation and allocation The Zimbabwe Tourism Authority (ZTA) could adopt the forecasting techniques to produce informative and precise tourism forecasts The data set used is before the COVID-19 pandemic and the models indicate what could happen outside the pandemic During the pandemic the country was under lockdown with no tourist arrivals to report on The models are useful for planning purposes beyond the COVID-19 pandemic Copyright © 2021 International Academic Press