Abstract
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. Zimbabwe’s monthly international tourist arrivals data from January 2002 to December 2018 was used. The dataset used was before the COVID-19 period and were disaggregated according to the purpose of the visit (POV). 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.
Highlights
The tourism sector is an important economic sector of every economy
Statistical methods in the form of the hierarchical forecasting approach, Quantile Regression Averaging (QRA) and Prediction Intervals (PIs) and other methods used in this paper will be discussed
According to [52], a grouped time series is a collection of time series that can be grouped together in a number of non-hierarchical ways, while a hierarchical time series is a collection of several time series are linked together in a hierarchical structure
Summary
The tourism sector is an important economic sector of every economy. It helps alleviate poverty and promotes economic growth ([1]). Accurate tourism demand forecasts lead to proper tourism management as they help in decision-making and planning. The government and investors are interested in tourism purpose of visit as well as forecasts at the national level, provincial level and each tourist attraction centre. Accurate international tourism demand forecasts are beneficial to investors in particular, in determining how much to invest and in which tourism sector. The government needs accurate forecasts for resource allocation and policy implementation. The tourism managers need accurate forecasts in policy formulation and amendment. Accurate tourism forecasts can be generated through the use of statistical methods and other techniques.
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