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inequality

Remember to call your grandparents: Multigenerational mobility in the developing world

Daniel Mahler's picture

A large body of literature has shown that the outcomes of children are tied to the outcomes of their parents or, in other words, that children face different life prospects based on their family background. But there is no reason to believe that such “persistence” of outcomes is limited to two generations. Social mobility (or lack thereof) depends not just on how parents influence the outcomes of their children, but also on how outcomes persist across multiple generations, from grandparents to grandchildren.

Are men the new weaker sex? The rise of the reverse gender gap in education

Francisco Ferreira's picture
It is probably fair to say that the World Bank’s latest report on intergenerational mobility - Fair Progress? Economic Mobility across Generations around the World – is the first-ever attempt to paint a truly global picture of how achievement – or the lack thereof – is transmitted across generations. Though there are results for income mobility for a subset of countries, most of the analysis focuses on educational attainment across 148 economies, representing over 95% of the world’s population.

#InheritPossibility: How is your life different from your parents’ when they were your age?

Venkat Gopalakrishnan's picture

How has your life changed for you compared to your parents or grandparents when they were your age? How do you see your children’s lives and possibilities compared to your own? To find out we’ve kicked off a social media campaign to highlight the issue of intergenerational mobility. And we invite you to take part in the #InheritPossibility campaign and share your stories.  

How is your life different from that of your parents?

Venkat Gopalakrishnan's picture
© You Ji/World Bank
© You Ji/World Bank


Yunus owns a fabric store in Blantyre, Malawi. The store was founded by his grandfather, who immigrated to Malawi in 1927, and has now been in his family for three generations. Business is good, Yunus said, but that the cost of essential services like electricity and water has gone up since his grandfather and father owned the store. Even so, he remains optimistic.
 
Marija Bosheva is a student at an agriculture and forestry vocational high school in Kavadarci, Macedonia. Like many high school students around the world, she takes daily lessons in history, math, biology, and chemistry. However, unlike many of her peers, she is also studying oenology — the art of making wine.
 
Are you carrying on a family tradition, like Yunus? Do you work or study in an entirely new field that didn’t exist when your parents were your age? How has life changed for you compared to your parents or grandparents when they were your age, and how do you see your children’s lives and possibilities compared to your own? Are you in the same position vis a vis your peers as your parents were vis a vis theirs?
 
Share your story, using the hashtag #InheritPossibility.

The South African economy is growing faster—but how fast?

Marek Hanusch's picture
Construction workers. South Africa. Photo: Trevor Samson/World Bank

The South African economy has been off to a good start in 2018. Statistics SA, the country’s national statistical service, released national accounts figures with revisions that pointed to more positive momentum in the economy than previously thought. South Africa grew by 1.3% in 2017, beating the consensus estimate of economists, and the revised numbers no longer record a technical recession early in the year.

No, 70% of the world’s poor aren’t women, but that doesn’t mean poverty isn’t sexist

Carolina Sanchez's picture
“Seventy percent of the world’s extreme poor are women”. If you’ve encountered this statistic before, please raise your hand. That is a lot of hands. And yet, this is what we call a ‘zombie statistic’: often quoted but rarely, if ever, presented with a source from which the number can be replicated.

Machine learning and the measurement of injustice

Daniel Mahler's picture

Machine learning methods are increasingly applied in the development policy arena. Among many recent policy applications, machine learning has been used to predict poverty, soil properties, and conflicts.

In a recent Policy Research Working Paper by Paolo Brunori, Paul Hufe and Daniel Mahler (BHM hereafter), machine learning methods are utilized to measure a popular understanding of distributional injustice – the amount of unequal opportunities individuals face. Equality of opportunity is an influential political ideal since it combines two powerful principles: individual responsibility and equality. In a world with equal opportunities, all individuals have the same chances to attain social positions and valuable outcomes. They are free to choose how to behave and they are held responsible for the consequences of their choices.

Game-changers and whistle-blowers: taxing wealth

Jim Brumby's picture
Also available in: Français 

High and rising income inequality is a serious concern in many countries, as highlighted in the IMF’s recent Fiscal Monitor. Wealth, however, is distributed even more unequally than income, as in the picture below.

Poor places. Rich places. Can geography explain it all?

Nga Thi Viet Nguyen's picture



“Tell me where you live, and I can predict how well you’ll do in life.”
 
Does welfare vary largely across space?
 
Although I don’t have a crystal ball, I do know for a fact that location is an excellent predictor of one’s welfare. Indeed, a child born in Togo today is expected to live nearly 20 years less than a child born in the United States. Moreover, this child will earn a tiny fraction—less than 3%—of what his or her American counterpart will earn.

The 2017 global poverty update from the World Bank

Francisco Ferreira's picture
This year’s global poverty update from the World Bank is a minor one. Until reference year 2008, the World Bank published new poverty estimates every three years, and between 2010 and 2013 we released new numbers every year (see here).

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