Modeling the Cointegration Dynamics between COVID-19 Infection Rates, Death Rates, and the Population in the US

This chapter is an attempt to examine the short and long-run relationships between the total population, the cumulative number of new COVID-19-infected cases, and the cumulative number of deaths due to COVID-19 in different states in the US. The bounds testing approach to cointegration and error correction models, developed within an autoregressive distributed lag (ARDL) framework is applied to the cumulative number of COVID-19 infections and deaths as of October 25, 2023, starting on February 15, 2020. The ARDL (1,4,3) model is found suitable for investigating the short-run relationships between the study variables. The model is highly significant, and the value of the coefficient of determination is R2 = 96%. The result of the bounds test indicates that there is a stable long-run relationship between these variables. In addition, the CUSUM and CUSUMSQ tests confirm the stability of the model parameters.