Introduction

In response to Covid19 governments all over the world scrambled to enact policies to protect the health of their citizens. These policies were primarily directed towards mitigating the health crisis, but they used a rapid rise in unemployment almost everywhere in the world. Governments that did not pre-empt this crisis in employment were forced to enact additional policies to mitigate the employment crisis.

In this project_ by Omdena, we used publicly available data to look at countries around the world and analyze their vulnerability to the employment crisis caused by the COVID-19 pandemic._

Figure 1. Context of the problem: The COVID-19 pandemic caused governments to enact policies to mitigate the health crisis, which led to (in many countries) an economic crisis as well; In many cases, governments were forced to enact additional policies.

Context: Lockdown and economic policies

In order to analyze the situation in a particular country, and be able to compare policies between them, the University of Oxford released a dataset comprising the government responses by country, updated on a daily basis, and showing the changes in three main groups of policies: Containment and closure, economic response or fiscal measures, and health-related policies. [1]

Among the Confinement policies, there are three specific ones that, according to the ILO [2], have had the most impact on the world of work. These three policies are:

● C2 (Workplace closedown)

● C5 (Closedown of public transportation)

● C7 (Restriction in the internal movement of citizens)

Each of these have different stringency values, ranging from 0 (no enactment of restriction) to 2 (or 3 in the case of C2) being the highest level a mandatory closedown with few exceptions. With these levels in mind, countries are categorized according to the level of lockdown they have.

The categories are:

Full lockdown: All three policies are in mandatory closing.

**Partial lockdown: **At least one of the policies is mandatory (the rest are working either just on a recommend closing level or are not enacted).

Weak lockdown: None of the policies is mandatory.

The Stringency of the policies applied by a country determines a stringency index, which is calculated by the creators of the policy dataset [1].This index goes from 0, which is no policies being taken, to 100, meaning the country is at its maximum stringency and lockdown level. This index is updated on a daily basis, creating what we refer to as the Stringency curve.

Variables to quantify vulnerability

Since this article focuses on those populations that have a higher vulnerability regarding unemployment during the COVID-19 crisis, some indicators need to be introduced that help represent the vulnerability of the population within a country. The indicators considered here are the following.

● **High Impacted Sector Exposure. **The 14 economic sectors considered by the ILO, have been aggregated into 5 categories according to the level of impact that the current economic crisis has brought to them in particular (measured from real-time and financial data for each sector from the ILO). (Source: ILO Monitor. COVID-19 and the world of work. Second Edition [3]). From this, high-impact sectors are those that lie on the most negatively impacted side of this scale (these are Accommodation and food services, Real estate, Manufacturing, and Wholesale and retail trade). It is worth mentioning that other sectors, like Education and Agriculture, are also impacted by the crisis, but in general to a lower extent than those mentioned above.

● **Inequality-adjusted Human Development Index (IHDI). **The IHDI is an indicator available currently for 150 countries, that takes into account the country’s average achievements in health, education, and income. Furthermore, it weights these three dimensions with their distribution across the population (their level of inequality). It can, therefore, be considered as a general measure of the resiliency of each country to adverse effects on health, education, and income. (Definition is taken from the United Nations Development Program [4]).

● **Informality Rate. **The informality rate is the percent of people participating in the informal economy, out of the total labor force of that country. There are several criteria defined by the ILO to consider an employee as being an informal worker, such as; No contributions to social security and not an entitlement of a worker to paid annual leave and or sick leave. (Source: ILO. Women and Men in the informal economy: A statistical picture [5]).

● **Stringency Index. **This index measures the severity of implementation of the affecting policies, as mentioned before.

In order to be able to jointly use these variables to compare across countries, we define two indicators:

**Impact Weighted Informality Rate: **% share of high impact sectors * Informality rate

This indicator aims to define vulnerability in terms of the exposure of a country to the most adversely affected economic sectors and the share of workers in the informal economy that are likely affected by those adverse effects. The higher the value of this indicator, the higher the vulnerability.

**Impact Weighted IHDI: **% share of high impact sectors *(1-IHDI)

This indicator aims to define vulnerability in terms of the exposure of a country to the most adversely affected economic sectors and the resilience of that country to those adverse effects. The higher the value of this indicator, the higher the vulnerability.

A global perspective

Considering the indicators of the vulnerability described above, we dive into how these look on a global and then on a regional basis.

In Figure 2, countries that appear colored are those that, as of May 1, 2020, are reported to be under full lockdown measures by the Oxford policy database, based on the definition provided above. Furthermore, these countries have little or no income support from their governments (meaning less than 50% or no loss of wage is being compensated by government financial support). As of May 1, 2020, most governments globally have attained a plateau in their stringency curve, which means most of the strict lockdown measurements are already enacted and have been for at least a month in most countries. In figure 2, the color of the country represents its IHDI index, and the intensity of it represents the share of the population working in highly impacted sectors. The more intense (darker) the color, the higher the people that work in sectors like Accommodation, Manufacturing, Real Estate, or Retail, which are those most severely affected by the crisis.

Figure 2. Countries under full lockdown measures (as of May) with little or no income support colored by IHDI index. The intensity of color represents the share of its population working in highly impacted sectors.

The scatterplot in Figure 3 shows the same countries shown on the map, describing on the x-axis the share of the population in highly impacted sectors, and their stringency index on the y-axis. The sizes of the circles in the scatterplot represent the joint indicator **Impact Weighted Informality Rate **defined above. The following table represents the top 15 countries ranked by both this indicator and the Impact Weighted IHDI, in descending order of value (vulnerability).

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