arXiv (Cornell University) · 2020 · 12 citations · 6 references
ManagementEconomicsTourism ManagementEconometricsForecastingTourismRegional ForecastingTourism EconomicsTourism ImpactsTourism Impacts ManagementEconomic Impact Of TourismMean Squared ErrorMean Squared Error EstimationMoving Average ModelsPandemic Impacts On TourismRoot Mean Squared Error AnalysisRoot Mean Squared Forecast ErrorTourism Forecasting
The study aimed to forecast the total earnings lost of the tourism industry of the Philippines during the COVID-19 pandemic using seasonal autoregressive integrated moving average. Several models were considered based on the autocorrelation and partial autocorrelation graphs. Based on the Akaike's Information Criterion (AIC) and Root Mean Squared Error, ARIMA(1,1,1)$\times$(1,0,1)$_{12}$ was identified to be the better model among the others with an AIC value of $-414.51$ and RMSE of $47884.85$. Moreover, it is expected that the industry will have an estimated earning loss of around 170.5 billion pesos if the COVID-19 crisis will continue up to July. Possible recommendations to mitigate the problem includes stopping foreign tourism but allowing regions for domestic travels if the regions are confirmed to have no cases of COVID-19, assuming that every regions will follow the stringent guidelines to eliminate or prevent transmissions; or extending this to countries with no COVID-19 cases.
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