Statistics on Poverty

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There’s a descriptive post here on the link between poverty and human rights.

Content:

1. GDP and poverty correlation
2. Poverty and education
3. Number of people living on less than $1 a day
4. Number of people suffering from hunger
5. Homelessness
6. Income inequality

1. GDP and poverty correlation

As an empirical matter, economic growth (annual growth in GDP per capita) and poverty reduction go hand in hand.

(source)

(source)

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2. Poverty and education

Here’s a graph showing the correlation between poverty and lack of education in the 50 states of the US:

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3. Number of people living on less than $1 a day

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4. Number of people suffering from hunger

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5. Homelessness

On any given night in the U.S., anywhere from 700,000 to 2 million people are homeless, according to estimates of the National Law Center on Homelessness and Poverty. That’s approx. 0.7 % of the total population. The majority are single men and/or African-American. One fourth of homeless have been homeless for at least five years.

Take a look at this graph from the NSHAPC, National Survey of Homeless Assistance Providers and Clients.

In Russia, an estimated 4 million on a total population of 140 million are homeless, which is almost 3 % (source). Given the local climate it is no surprise that hundreds of people die in the streets during winter.

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6. Income inequality

The inequality of wealth or income in a particular country is traditionally measured by the Gini coefficient (named after Corrado Gini). This coefficient is the result of a comparison of the percentage of the population and the percentage of the total income of the population. E.g. 80% of the population earns 50% of the total income, and the remaining 20% earns the other half.

You can see this on the graph below. The diagonal 45° line represents the fictional state of equal income: 5% of the population earns 5% of the income, 10 earns 10, 20 earns 20 etc. In reality, income distribution is of course unequal and is somewhere along the curved line, the Lorenz curve, with the majority of the population earning the minority share of the national income, and a minority earning the majority.

The more curved this line, the more unequal the income. The Gini coefficient is the surface between the diagonal and the curved line, divided by the whole surface under the diagonal.

This is then expressed as a value between 0 and 1 (following a complicated mathematical formula which I will not inflict on you). 0 corresponds to perfect equality: everyone having exactly the same income, = diagonal. And 1 corresponds to perfect inequality where one person has all the income, while everyone else has zero income. There will be no curve in this case as the curve comprises the horizontal axis and the right-hand vertical axis. Both extremes obviously being impossible. In real life, the lowest is 0.249 in Japan; the highest is 0.707 in Namibia (most recent data).

A complete list of countries’ performances is here.

There seems to be a negative trend:

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