SO478 - week 2

« Back to SO478

These are my notes from October 03 for SO478 at the London School of Economics for the 2017-2018 school year. I took this module as part of the one-year Inequalities and Social Science MSc program.

The usual disclaimer: all notes are my personal impressions and do not necessarily reflect the view of the lecturer.

Global inequalities


Income inequality in the developing world by Martin Ravallion

Summary: income inequality in developing world less than 30 years ago, but this is mostly due to falling inequality between countries (as those on the bottom, esp China, catch up) whereas inequality within countries is slowly rising (though flat since 2000).

Who are the Global Top 1% by Sudhir Anand and Paul Segal

Global Income Distribution by Christoph Lakner and Branko Milanovic

Published in the The World Bank Economic Review. I have my own feelings on the World Bank but I’ll try to leave them aside when writing this review.


Given by Dr Sudhir Anand, Professor of Economics at Oxford University, who co-authored one of the papers above. The lecture he delivered is primarily a summary of that paper.

Different methodological approaches

The reason we care about national income on its own (not just per capita) is because it has some influence on a country’s authority and power when negotiating trade agreements and the like.

On PPP adjustments: obviously problematic in the sense of reducing a multidimensional vector to a scalar. Takes a typical “basket of goods” but of course the definition of that is subjective and, in the end, politically motivated (whether consciously or not). The same problem that arises when thinking about inflation.

On scaling household size: tricky topic with lots of different approaches and factors to consider (economies of scale, varying consumption patterns, cultural norms, etc). No real way to equalise across households so most research just makes assumptions about what a “household” means and isn’t too worried about how that aligns with reality.

China is an equalising force for concepts 1-3, but disequalising for concept 0 (because its national income is so high, and growing; but of course its national income per capita is still quite low).

For the paper, they looked at three different indices: Gini, MLD (also known as Theil L) and Theil T. The latter two are additively decomposable (not just into two components, but into any number, with weights). Incidentally, you can use variance as a measure of inequality; it’s just going to be an absolute measure, not a relative one.

Global Gini right now is 0.70,, which is much higher than in any individual country (speaks to how high inter-country inequality is right now).


This was the first official seminar with our permanent seminar groups (last week was fairly ad-hoc). Focused on introductions (who we are, where we’re from, and some thoughts on inequality within our own countries). I talked about China (since Canada was taken) and its very unique position within the global inequality hierarchy: on one level, it’s been responsible for reducing worldwide income inequality via the lifting of such a large number of people out of poverty, but on another level income inequality is still staggeringly high. The rural-urban gap (which is responsible for, by some estimates, 10% of economic inequality within the country) is especially worrying, and I could see its consequences when I was living in Beijing—I, along with most of my international school friends, had various housekeepers during my time there, and they tended to be young women from rural areas (mostly Sichuan in my case) who gave up pretty much all their free time to live in someone else’s house and take care of the household while being paid a pittance. Which says something about their economic and social prospects where they came from. Among mainland citizens, 1% of the population controls 1/3 of all the wealth, which is quite scary.

Another thing to consider with China is its tumultuous recent history. During the Great Leap Forward, economic inequality was presumably lower, but a lot of people (especially my parents’ generation) were incredibly poor … It’s kind of obvious, but still deserves to be said: we can’t focus just on inequality measures when trying to understand the health of an economy. Any discussion of inequality ought to be accompanied by its proper geopolitical context, not to mention the level of economic development.

Some interesting statistics on inequality brought up by the other students: