Forecasting the Unemployment in the US Under COVID-19 Based on the ARIMA Model

Abstract

This paper discusses the unemployment rate of the United States before and during COVID-19. The unemployment rate is always the most important index used to measure the current state of a country’s economy. The labor market since COVID-19 hit in March 2020 displays some changes due to the government’s policies and economists’ advice. This paper uses the autoregressive integrated moving average (ARIMA) model to forecast the future tendency of unemployment in several aspects, such as the layoffs and discharges rate, job openings rate, and hire rate. The research is mainly about how to use different variables to examine the changes in unemployment in the United States after the outburst of the COVID-19 pandemic in March 2020, and comparing the labor market before and after COVID-19. The assumption that the COVID-19 pandemic does not bring a negative influence on the unemployment rate was overturned after collecting the data and using the model to test, and this paper has drawn a new conclusion.