Abstract

In recent years, as a result of the Covid-19 pandemic, the health and personal care stores have been remarkably affected in a wide range of aspects. This became one of the reasons why medical staff felt pressure, leading to quite a number of staffs resigning, and meanwhile the management pattern of medical employees changes and seems to be more strict. Furthermore, the prevalence of Covid-19 pandemic also causes some mental diseases such as sleeping disturbance, anxiety as well as skin problems whether for adults or younger people. As a consequence, the health and personal care industry has been brought to light. This industry has become high in demand like never before. Therefore, complemented by daily and monthly U.S. coronavirus cases, retail sales of health and personal care stores in the USA is a time series worth analyzing. Best-fit ARIMA model for the retail sales is determined to be ARIMA (2, 2, 3) to forecast future health and personal care retail sales in hope of supporting the industry prepare for the ongoing pandemic and in case of another crisis. Regression models are built to find correlations between health and personal care retail sales and coronavirus cases. Additionally, this paper extended ARIMA by employing dynamic regression model which generates a more accurate forecast from regression with ARIMA (0, 1, 1) errors.

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