International remittance flows and the economic and social consequences of COVID-19

Pandemic COVID-19 has laid bare the multiple vulnerabilities which migrants face. The health of international migrant workers has largely been ‘neglected’ (Daniels, 2020), while both living and working conditions in some settings have meant they are especially vulnerable to infection (Han, 2020). The economic prospects of (labour) migrants become even more fragile under conditions of restricted travel and economic slowdown; while in some sectors the ‘dirty, dangerous and demanding’ work often performed by migrants is needed more than ever.

According to the World Economic Forum (WEF), ‘everyone from a migrant agricultural worker relying on a paycheck in Portugal to a foreign healthcare worker living in Sweden is potentially impacted by a dramatic tightening of borders’ (WEF, 2020). The consequences of this potential ‘throttling’ of international migration is usually measured in abstract, macroeconomic terms – for example, migrants contribute nearly 10% of global GDP (MGI, 2016; WEF, 2020).

Here, we introduce a chord diagram to visualize the latest inter- (and intra-) regional global data on international remittances using the circlize package (Gu et al., 2014) in R (Figure 1). While chord diagrams have been applied elsewhere to show migratory flows (for example, Qi et al., 2017), we believe this is the first time they have been applied to remittance data. We use the latest publicly available bilateral remittance (2018) from the World Bank (2020) and plot the international flow between (and within) UN geographic regions (UNSD, 2020). These data reflect first-generation remittances, and not the actions of second-generation diaspora, retirees moving back to their country of origin or ‘tax exiles’.

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Figure 1.

Circular visualization of bilateral remittance estimates for 2018 using migrant stocks, host/origin country incomes (millions, US$).

There are several important caveats to note for these data. They are not actual officially reported data; rather ‘analytical estimates based on logical assumptions’ (for further details, see the methodology in World Bank (2020)). Data from transit migrants and refugees are also likely to be significant undercounts. Finally, in our application, intra-national remittances from internal migrants are absent.

The graphic really emphasizes the interconnectedness of the ‘global economy of work’. The estimated total amount of remittances moving between countries in 2018 was US$68.3bn (up from US$46.4bn in 2010) (World Bank, 2020). Crucially, though, we must consider the main mechanisms by which remittances occur, namely within families. The ‘neglect’ of a migrant in one setting – New York, Singapore, Dubai – will therefore have profound economic and social consequences not just on the local economy, but on countries, communities and families around the world.