International tourist arrivals as a determinant of the severity of Covid-19: international cross-sectional evidence

ABSTRACT

The imposition of international travel restrictions to prevent the spread of the Coronavirus has been a controversial issue. In this paper we examine the effect of international tourist arrivals on the population fatality rate and the case fatality, where fatality is caused by Covid-19, using a cross-sectional sample covering 146 countries. In addition to international tourist arrivals, 12 other explanatory variables are examined. Data on the dependent and explanatory variables were obtained from various sources, including the European Centre for Disease Prevention and Control, the World Bank, BBC and other sources. The role of internal population mobility is not considered explicitly, but it is captured by measures of lockdown that restrict movement. The results of the empirical analysis show that international tourist arrivals have a greater effect on the severity of Covid-19 than any of the other factors. This means that the imposition of international travel bans is justifiable by the objective of containing the virus.

KEYWORDS:

• Covid-19
• tourism
• population fatality rate
• case fatality rate
• extreme bounds analysis
• variable addition tests

JEL:

• I10
• I19

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 These claims will be discussed in detail later on.

2 For an overview, see https://www.who.int/global_health_histories/background/en/.

3 A detailed description of the data, as well as variable definition and measurement can be found in the data section.

4 Non-refoulement encompasses obligations not to return a person to a place where they may face torture or cruel, inhuman or degrading treatment or punishment, and not to expel a refugee to a place where their life or freedom would be threatened.

5 https://www.ecdc.europa.eu/en/publications-data/download-todays-data-geographic-distribution-covid-19-cases-worldwide

6 An alternative dependent variable is excess deaths, which can be used on the grounds that the reported deaths may underestimate the Covid-19 fatality rate. For example, as of 15 October, 216,025 deaths from COVID-19 have been reported in the US compared to excess deaths of 299,028 excess deaths. The problem is that no uniform set of data on excess death is available for all countries in the sample. Using a unified set of data from the same source is better for the purpose of comparison.

7 https://www.ghsindex.org/report-model/.

8 https://data.worldbank.org/indicator/EN.POP.DNST.

9 The results are not reported here but they will be made available by the corresponding author upon request.

10 Further empirical analysis has been conducted by using non-nested model selection tests. The results confirm what is reported in this paper. Additional results can be obtained from the corresponding author upon request.