An investigation of the impact of COVID-19 on health-related cryptocurrencies using time-varying parameters and impulse responses

Abstract

This study examines the impact of COVID-19 on health-related cryptocurrencies. More precisely, we use the variable-Lag time-series (VLT) causality to test whether the pandemic caused the price performance and the volume of transactions of these cryptocurrencies. We then employ time-varying parameter (TVP) models to capture the sign of this effect (for the evidenced cases) and the impulse responses among the cryptocurrencies since they may affect one another. The results show there is no certain pattern, which means that for the years of the pandemic, COVID-19, has impacted cryptocurrencies differently, except for one case. Moreover, the results are very unstable during 2021, indicating time-varying characteristics for all cases, while during 2022, the impact of the pandemic on these cryptocurrencies was mostly negative. Similarly, during 2020 the price was negatively affected, but the transaction volume was mainly positively impacted. Spillovers are evidenced only for 2022, for certain cases both in the prices and volume of transactions. The results indicate that the pandemic affected cryptocurrencies heterogeneously, evidencing a different pattern among the three years examined. This finding should be taken into consideration in the adoption of relevant technological advancements in healthcare.