Thailand has transitioned from a low-income to an upper middle-income country in a single generation. Poverty has declined to 7.1 percent in 2015 – as measured by the international upper-middle income class poverty line – and access to basic education and health has become nearly universal. Despite all these historic achievements, inequality remains a key concern for Thai people.
Graduating from college remains one of the best routes out of poverty. Recent research shows that returns to higher education are now larger than the returns to any other education sector, and they are particularly large for low-income countries. In low- and middle-income countries, the private (wage) returns to accessing higher education are 26.8 percent and 20.2 percent, respectively, relative to obtaining a high school degree. Women tend to have higher rates of return than men, and there is even some evidence (from the United States) that children from poor families benefit the most from higher education.
This is the twelfth in this year's series of posts by PhD students on the job market.
Social commentators and researchers struggle to explain why, despite growing inequality in many countries around the world, there is often relatively limited support among poorer people for policies where they are set to benefit (such as increases in cash transfers or in the minimum wage). Recent research drawing on surveys from the United States and Europe has identified a potential reason for why poorer people are not more supportive of redistribution: they don’t realise they are poor. These studies illustrate the majority of people tend to think they are positioned around the middle of the national income distribution regardless of whether they are actually rich or poor.
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.
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.
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? Are you in the same position vis a vis your peers as your parents were vis a vis theirs?
- Fair Progress
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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.
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.