The first of a series of posts on researching wealth and poverty in Ethiopia.

This month my colleagues and I published a new article on measuring poverty and wealth in Ethiopia. Here I tell the story of how I came to work on this, and some of the lessons I learned along the way. It’s been a long journey, and the questions behind this work are ones I’ve been musing on all my life. Having grown up mainly in England in the afterlife of the British Empire, I was drawn to Africa by the prospect of understanding the roots and persistence of global inequalities. [1] Why was it, I wondered, that in one part of the world people should live in such poverty and in another part of the world in such comfort?

When I went to Ethiopia as a graduate student, my thinking on this question was challenged by interacting with people whose ways of life (and senses of the world) were very different from my own. Whether among rural folk or city-dwellers, few seemed to share my preconceived idea that wealth and poverty were straightforward concepts. I remember a conversation over lunch with some seasoned Ethiopian social scientists, in which I pressed them: “Couldn’t we all agree that a farmer eking out a living on a small patch of land was unambiguously poorer than a university lecturer?”

We could not. Why? Partly because poverty is highly relative — there are rich farmers, and poor lecturers. Yes, absolute definitions of poverty exist (e.g. income less than one dollar per day) but a lot gets hidden when you use such crude definitions as these.

Many more sophisticated approaches to poverty measurement exist, and our new article takes as its point of departure one called Poverty Flows (or Stages of Progress). I first encountered it through Anirudh Krishna’s (2010) book, One Illness Away: Why People Become Poor and How they Escape Poverty. The book made a big impression on me when I came across it as a graduate student. By this time I’d spent more than a decade working on-and-off in Ethiopia, but I was still perplexed. Krishna proposed – and seemed to demonstrate – a way of understanding poverty that took local ideas and experiences seriously, while also allowing comparison across the globe.

The key idea was simple: While the things that mattered for being well-off (a car, cattle, a tine roofed house as opposed to a grass hut) might differ from place to place, the idea of a ladder of social status was universal. Figure out what mattered to people as markers of wealth and poverty, and you could then design a survey to establish where everyone sat in relation to each other.

None of this was truly original: Participatory Rural Appraisal practitioners in the 1970s had developed manuals for wealth ranking, and ladders were commonplace in household surveys used by development agencies in the late 20^th century. [2] Where Krishna broke new ground was in assembling multi-country teams to carry out such studies in parallel and adding a time dimension to the surveys: asking people not only how they were doing now, but where they were on the ladder 10, 20 or 30 years ago.

A moving image

Adding a time dimension makes the difference between a snapshot and moving images. Once you start thinking in terms of direction, tempo and pattern of change, a great deal more complexity presents itself. [3] New questions can be asked: First, what kinds of changes have taken place? Who’s getting richer, who poorer? Trends in the global economy looked different, Krishna noted, when you took higher-resolution pictures of change. If growth wasn’t evenly shared, the numbers of people falling into poverty might rise even while national economic growth was occurring. [4] A rising tide didn’t necessarily lift all boats.

Second what kinds of events – personal, collective, global – precipitate improvement or deterioration in people’s fortunes? Here is where illness comes in. And a host of other things: safety-nets and trap-doors; access to opportunities; intergenerational privilege and discrimination; displacement and environmental change … and much more besides.

In the next post I’ll describe how my colleagues and I applied this approach to measuring changes in wealth and poverty over the past decade in Ethiopia’s Omo Valley.

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Notes

[1] I take the phrase ‘afterlife of empire’ from Gamlin, J., Gibbon, S., and Calestania, M. (2021). The biopolitics of COVID-19 in the UK: Racism, nationalism, and the afterlife of colonialism. Chapter 6 in: Manderson, Burke, and Wahlberg, eds. Viral Loads: Anthropologies of urgency in the time of COVID-19. London: UCL Press (pp. 108-127).

[2] Crystal Biruk (2018). Cooking data. Duke University Press (p. 54).

[3] My impression is that in quantitatively inclined social sciences, longitudinal analysis was long set apart as a kind of optional extra, or as the preserve of particularly advanced students. When I was attending the University of Michigan’s summer school in quantitative methods in 2010, I recall time series analysis being spoken about by some as too sophisticated for most doctoral students in the social sciences.

[4] In One Illness Away, Krishna shows the pace of descents into poverty can increase in conditions of a growing economy – as it did in Uganda (1980-2005), Peru (1979-2004), and North Carolina, USA (1995-2005) (p. 64).