Measuring Hope: A Quantitative Approach – Forthcoming in JDS

I am pleased to report that my paper – written with co-authors Duncan Boughton, Kyan Htoo, Aung Hein, and Ellen Payongayong – “Measuring Hope: A Quantitative Approach with Validation in Rural Myanmar” (working paper version here) is now officially forthcoming in the Journal of Development Studies. Here is the abstract:

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The Cardinal Treatment of Ordinal Variables

Last weekend, I came across a paper published in the European Economic Review by Carsten Schroder and Shlomo Yitzhaki entitled “Revising the Evidence for Cardinal Treatment of Ordinal Variables” (2017). I found the paper to be well-written, intuitive, and important. Although there are no direct policy implications of this paper, papers like these need to be publicized, for the sake of all research that does aim to provide meaningful implications for the world.

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“Are you poor?”

I do a bit of consulting work on the side from time to time. It is usually fun and always interesting. Last week when sitting in a meeting developing an organizational toolbox for global monitoring and evaluation the question was raised, “Why don’t we just ask ‘Are you poor?’ isn’t that the most important thing to measure?”

The logic was right. When I graduated college I was, technically speaking, poor. But if you’d have asked me then ‘Are you poor?’ I would surely have said “no”. I had just graduated college and was navigating the job market for the first time. It was a stressful time with not a whole lot of income but I had opportunities on my horizon, so I did not consider myself poor.

The question picks at a more general question: Why use objective measurements (like income or assets or calorie intake) when subjective attitudes (probably) matter more?

My answer in the meeting sited the recent research on happiness. A lot of researchers are attempting to unwrap the complexity of human happiness as an angle to measure well-being. The inherent difficultly in asking somebody, ‘Are you happy?’ is happiness is multidimensional and relative on an extensive laundry list of (probably) unknown factors. For example: You could ask somebody whose relative has just died ‘Are you happy?’ and get different answers simply based on how they interpret the question rather than actual changes in well-being. Almost certainly in the strict context of the funeral of a close relative they will not admit to be happy, but in a more broad context of the direction their life is going they could no doubt admit to being happy.

It turns out, in many ways, poverty is a lot like happiness. It is inherently multidimensional and relative on an extensive list of (probably) unknown factors.

After the meeting I did some searching for anybody who had actually gone out somewhere and asked a significant number of people ‘Are you poor?’ I didn’t find much, and for good reason. I turned to Angus Deaton, currently one of the world’s leading experts in poverty measurements, and his book Measuring Poverty for some guidance.

Everyone has some idea of what poverty is, and most people have little difficulty answering the question, “Do you consider yourself poor?” although some people need a moment or two to think about it. Nor do people find it hard to answer the same question about their neighbors or other people that they know. Yet these simple ideas turn out to be hard to extend to countries, and harder still to the world as a whole.

Why is it hard to extend these ideas to nations or the world in general? It is tricky to ask somebody if they are poor because the actual measurement may pick up on warped incentives rather than a subjective measurement of poverty identification. 

A Participatory Rural Assessment, usually known by its acronym PRA, is a procedure often used by researchers and by non-governmental organizations (NGOs) working in villages in poor countries. These researchers sit with the villagers at the local gathering place and find out about the village, mapping its houses, the school, the water supply, its agricultural activities, and who lives where. It is common to ask the villagers to say who is well-off, who is not so well-off, and who is poor and, in most cases, villagers have no difficulty in making the identification. No doubt there are some mistakes, and some people conceal some assets from their neighbors, but the results usually make sense. The poor are often people who cannot work because they are ill or suffer from a long term disability, or are elderly. They are also poor and vulnerable groups in specific locations, such as those Indian widows who are unfortunate enough not to have sons to support them. Such information can sometimes be used as part of poverty relief efforts. In India, one scheme, the Antyodaya (last man first) food program, relies on local councils to identify the very poorest few percent of rural households, who receive subsidized food rations. There is a similar scheme in Indonesia. But it is possible to push this local poverty identification too far. If the sums to be distributed are large enough, they become worth misappropriating, and their is an incentive for people to identify their friends and relatives (or themselves) as poor. Similarly, some NGOs have discovered that, if they use the poverty identification to enroll people into employment or training schemes, then after a few visits everyone is reported to be poor.

The key lesson is clear. Measuring poverty is an approximation and always wrong in one way or another. Poverty identification almost certainly is a measurement we care most about, but it is extremely difficult – if not impossible – to measure with any sort of precision or accuracy. The next best thing is to measure a bunch of objective indicators that tend to be associated with people who most likely identify as being poor. Which is, basically, what we already try to do.