Forecasting tourism recovery amid COVID-19

Area of Science:

• Tourism Economics
• Econometrics
• Pandemic Impact Analysis

Background:

• The COVID-19 pandemic severely disrupted global tourism, necessitating new forecasting methods.
• Existing tourism demand forecasts became obsolete due to the pandemic's unprecedented impact.

Purpose of the Study:

• To develop and apply a hybrid forecasting model for tourism recovery in Hong Kong.
• To evaluate the economic consequences of the COVID-19 pandemic on Hong Kong's tourism sector.

Main Methods:

• Utilized an autoregressive distributed lag-error correction model for baseline tourism demand forecasts.
• Incorporated Delphi adjustments with diverse recovery scenarios to refine predictions.
• Combined econometric modeling with expert judgment for robust forecasting.

Main Results:

• Generated multiple forecast scenarios for Hong Kong's tourism recovery trajectory.
• Quantified the potential economic effects of the pandemic on the local tourism industry.
• Demonstrated the utility of hybrid forecasting approaches in crisis situations.

Conclusions:

• The hybrid econometric and Delphi approach provides a viable method for forecasting tourism recovery post-pandemic.
• Understanding varied recovery paths is essential for policy-making and industry support.
• Accurate forecasting aids in mitigating the economic damage to the tourism sector.