FORECAST OF THE NUMBER OF WORKERS IN THE ACCOMMODATION AND FOOD SERVICES INDUSTRY CONTRIBUTING TO EBPM OF COVID-19

Abstract

This paper constructs a multiple regression model for forecasting the number of workers in the accommodation and food service industry as a model that satisfies four requirements that contribute to EBPM: high forecasting accuracy, rapidity, persuasiveness, and the ability to support policy making. In addition to a normal model that forecasts the number of workers every quarter for the next two quarters, we construct an emergency model that can incorporate the impact of unforeseen events such as the recent declaration of a state of emergency by using impulse response analysis of the VAR model for the prediction of explanatory variables in the regression model. The emergency model predicts that the number of workers will fall to the lowest level since the global financial crisis, indicating that it is an urgent issue to take supportive measures for the industry.