Impact of Covid-19 Prevalence in Seoul on Subway Usage

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Sang-Uk Jung

Abstract

This article shows that there is a negative impact of government’s social distancing policy, daily COVID-19 confirmed cases, daily volume of new articles related to COVID-19, and a weekend dummy on subway ridership in Seoul, Korea. Multiple regression with OLS is applied to 289 daily data mostly collected from the Open Government Data Portal during the early stages of COVID-19 pandemic, from January 1 to October 30, 2020. The model is run separately for four subway station categories: commercial, office, residential, and other area. Different impacts of explanatory variables across different area have some policy and managerial implications. This study concludes with future research.

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