Macro Analysis /

Covid-19: Download our Emerging Markets vulnerability data model

  • Data illuminates the debate about which countries will be most affected by Covid-19 and the global lockdown

  • We provide a customisable dataset to assess vulnerability to the virus and ability to withstand economic hibernation

  • Download the model and tailor the indices to your views about how best to assess exposure

Covid-19: Download our Emerging Markets vulnerability data model
Paul Domjan
Paul Domjan

Senior Contributing Analyst

Tellimer Research
29 April 2020
Published byTellimer Research

I’ve previously argued that there are two main axes of risk for emerging markets from Covid-19: domestic exposure to the virus and the ability to withstand the withdrawal of external demand during global hibernation.

Global vulnerability to Covid-19 (interactive chart; hover over countries for more detail)

Source: Tellimer Research, Paul Domjan

Both of these are complex issues, and we have had robust debates within Tellimer about which factors matter most. Exposure to developed market hibernation may be harder to assess than domestic exposure to the virus itself given the complexity global interconnections that become channels of contagion, and there has certainly been less research to develop a framework with which at assess it. I provided one approach, using 18 factors, to measure both axes of risk. However, you may disagree with the relevance and weighting of some of these factors. This downloadable workbook allows you to tailor the data according to your preferences.


Tailor the model

The workbook allows you to tailor the index to your preference by adjusting the weights in row 1. The scores for the two axes of vulnerability will be recomputed with your weights. The weights do not need to total to any particular number, and the score for each country will be a weighted average based on your chosen weights for the factors for which there is data available for that country. If you want to remove a factor either because you do not think it is relevant, or because you are concerned that there is not data available for enough countries, please set the weight for that factor to zero.

Filtering and displaying your index

You can choose which countries appear on the scatterplot by filtering on index membership, which is based on the MSCI classifications for developed, emerging and frontier markets. You can also show a bespoke group of countries by adding Xs in column B and then filtering on that column. Please note that filtering the data will also affect which countries appear on the maps of domestic and international exposure and that the maps may only appear or update correctly with a recent version of Office365.

Index factor methodology

Those factors that are provided by the original data source as a score (eg quality of health administration at ports of entry) have been rescaled to match the 0-1 scale used here, with 1 being stronger and 0 being weakest. All other factors have been scored using percentile ranks. I have chosen percentile ranks rather than percentiles to manage outliers. I appreciate that this removes clustering in the data and enforces a linear distribution, but for this exercise, I judged that managing outliers consistently and without judgment was more important.