In the scatter plot below we see a clear relationship between GDP and extreme poverty. Countries with a high GDP per capita have very low extreme poverty rates, while countries with a low GDP per capita have a higher extreme poverty rate. This is not too surprising, since extreme poverty is bound to a monetary value. The GDP per capita as the country’s gross domestic product (GDP) divided by its population, gives us the mean GDP for the nation’s population. In general, even if the inequality is large within a country with a high GDP, the likelihood to live with less than 1.90$ per day is very unlikely. Additionally, most of these rich industrial countries can afford social insurances to prevent its population from falling into extreme poverty. We have seen in the dashboard that there is national poverty in these countries. These two types of poverty cannot be compared but are meant to show that each country must also address poverty in its own country. Regarding the achievement of the first SDG, a specific focus should be put on the sub-Saharan countries. On the animation of extreme poverty timeseries from 1990 to 2019, we observed very few changes in this region.
Only in an ideal world, we would assume that each citizen shares the same standard of living. Often, there is a small population stratum, who owns a large part of the wealth. For this reason, we wanted to look at the relationship between the change in extreme poverty and the GINI index. We subtracted the extreme poverty rate from 1990 with the rate in 2019 and saw, if there was an increase or a decrease in extreme poverty. We cannot see a correlation between the GINI index and the change in extreme poverty at all. It is also rather unlikely that growing inequality is responsible for more extreme poverty. In most of the countries where extreme poverty increased, civil wars were the decisive reason and not inequality. Regarding the SDG eight and ten, economic growth is certainly beneficiary to reduce poverty, but it should be clear, that all people benefit equally from it.
Since March 2020, when the WHO declared the coronavirus as a global pandemic, economies have been partially shut down and lockdowns were imposed on the population. As our global time series ends in 2019, we cannot see any effects yet, however assumptions on the development can be made based on historic data and some preliminary data from countries that already have data available. First studies show that the pandemic negatively impacts the GDP of countries by causing a decline in economic activity either by government-imposed measures or voluntary social distancing (Choi et al. 2022; König and Winkler, 2021; Salisu et al. 2022). As soon as global data becomes more comprehensive, it would be interesting to analyze the effects Covid-19 has on the poverty rates and if the inequalities between the poor and the rich were also affected. Furthermore, differences between countries and possible links between the intensity of the impact and the extent of measures taken to fight the pandemic could be worth investigating. Another interesting factor might be how long it will take different countries and their economies to recover as this presumably affects the poverty rate in the long run. The report by World Relief (2022) predicts that in countries with relatively more people living in poverty, the effects are far more extensive and will persist far longer into the future. This is due to the prevalence of other crises that already contributed to the poverty issues before. Countries already overwhelmed by other issues do not have the capacity to take planned measures and have low resilience against the pandemic. The World Inequality Report by Chancel et al. (2022) states that the COVID crisis increased inequality between the rich and the poor of populations. However, rich countries have the means to prevent massive increases in poverty, which shows the importance of social states to fight poverty.