Via Mashable: How Mobile Technology is a Game Changer for Developing Africa.
There are a lot of initiatives out there that engage with mobile phones for development. The most impressive I have seen is Lifelines India, in part coordinated by some friends and colleagues at Development Alternatives. Volunteers bring the phones to villages, and for a small fee they can call a number and record their questions. Each farmer receives a reference number for the query and can call back in a day and use that reference number to access the reply. The project promised and delivered rapid replies to queries (less than twenty-four hours) and provided information of great value to farmers. Today it reaches around 150,000 farmers in four Indian states.
This is but one of many initiatives. The Global Adaptation Information Network project I have been part of for the past four years is heavily predicated on using mobile phones to connect communities throughout the Global South. And Mickey Glantz has toyed with the idea of expanding Sparetime University to mobile platforms to expand access,
What this article failed to recognize, though, is the interesting boom in cell phone app development in Africa right now – app developers in Kenya are recognized as some of the best in the world at designing lightweight apps for low bandwidth networks. For those who are fed up with lazy, bloated coding of software here in the US (why your programs run so slowly, even on new computers and fast internet connections), it may be that Africa is the future . . .
Category: development
Availability isn't validity . . .
So, to clarify one one my points from my previous post, let me use an example to show why building an index of development (or an index of anything, really) on data based on its availability can lead to tremendous problems – and result in a situation where the index is actually so misleading as to be worse than having no index at all.
A few years ago, Nate Kettle, Andrew Hoskins and I wrote a piece examining poverty-environment indicators (link here, or check out chapter 9 of Delivering Development when it comes out in January) where we pointed out that the data used by one study to evaluate the relationship between poverty and the environment in Nigeria did not bear much relationship to the meaningful patterns of environment and livelihood in Nigeria. For example, one indicator of this relationship was ‘percentage of irrigated area in the total agricultural area’, an index whose interpretation rested on the assumption that a greater percentage of irrigated area will maximize the environment’s agricultural potential and lead to greater income and opportunity for those living in the area. While this seems like a reasonable interpretation, we argued that there were other, equally plausible interpretations:
“While this may be a relatively safe assumption in places where the irrigated area is a very large percentage of total agricultural area, it may not be as applicable in places where the irrigated area is relatively small and where the benefits of irrigation are not likely to reach the entire population. Indeed, in such settings those with access to irrigation might not only experience greater opportunities in an average year, but also have incomes that are much more resistant to environmental shocks that might drive other farmers to adopt severe measures to preserve their livelihoods, such as selling off household stocks or land to those whose incomes are secured by irrigation. In such situations, a small but rising percentage of area under irrigation is as likely to reflect a consolidation of wealth (and therefore declining incomes and opportunities for many) in a particular area as it does greater income and opportunity for the whole population.” (p.90)
The report we were critiquing made no effort to control for these alternative interpretations, at least in part because it had gathered data at the national scale for Nigeria. The problem here is that Nigeria contains seven broad agroecological zones (and really many more subzones) in which different crops and combinations of crops will be favored – averaging this across the country just homogenizes important differences in particular places into a general, but meaningless indicator. When we combined this environmental variability with broad patterns of land tenure (people’s access to land), we found that the country really had to be divided up into at least 13 different zones – in each zone, the interpretation of this poverty-environment indicator was likely to be consistent, but there was no guarantee that it would be consistent from zone to zone. In some zones, a rising area under irrigation would reflect a positive shift in poverty and environmental quality, while in others it might reflect declining human well-being.
To add to this complexity, we then mapped these zones against the smallest administrative units (states) of Nigeria at which meaningful data on poverty and the environment are most likely to be available. What resulted was this:
As you can see, there are several states with multiple zones inside their borders – which means a single indicator cannot be assumed to have the same interpretion across the state (let alone the entire country). So, while there might be data on poverty and environmental quality available at the state level such that we can identify indicators and build indexes with it, the likelihood is that the interpretation of that data will be, in many cases, incorrect, leading to problematic policies (like promoting irrigation in areas where it leads to land consolidation and the marginalization of the poor) – in other words, making things much worse than if there was no index or indicator at all.
Just because the data is available doesn’t mean that it is useful, or that it should be used.
Polishing a turd? Another day, another index
UNDP and the Oxford Environment and Human Development Initiative recently announced the launch of the Multidimensional Poverty Index (MPI), the newest rapid poverty assessment tool. This is the latest effort to expand the measurement of poverty beyond indicators of economic productivity, and is being hailed (at least by UNDP and OEHDI) as a significant advance in our efforts to understand the nature of poverty. I’m not so sure . . .
We have tried to come up with quick measures (often referred to as indicators) of things like development, poverty and food insecurity for decades. We chase after such indicators because, if they provide us with quick, cheap understandings of the human condition in particular places, they can guide policy and program design, thus maximizing the benefit of the aid money we spend around the world. Since the mid-twentieth century, development thought has attached to various indicators of poverty and development. For example, one of the earliest (and still prevalent) indicators of development is the Gross Domestic Product (GDP), which measures the value of all goods and services produced in a country in a given year. GNP per capita is the number you get when you divide this value by the population of the country at hand, thus getting a measure of average per-person economic productivity. The presumption here is that this average economic productivity reflects wages, and thus the ability of individuals to meet their material needs. It certainly means something that the per capita GDP of the United States was $46350 in 2008 (the last year for which the World Bank has data), while Malawi’s per capita GDP was $288 in that same year (no, that is not a typo). But what that means in terms of people’s real quality of life, their opportunities, etc. is not at all clear. Clearly, Malawians are far less economically productive than Americans – but to address this issue, we have to understand why this is so. Once we start to explore the different levels of economic productivity, we find that the causes of these differences are many, leading to other questions, such as why are so many Malawians engaged in subsistence farming, while Americans are engaged in the wage economy? In short, per capita GDP is an interesting starting point for analysis, but it does not really capture the dynamics of poverty and human well-being in a manner that allows us to do anything about these situations.
To address this issue, other indicators and indexes (indices) that aggregate various indicators into a single value have emerged. Perhaps the most famous is the Human Development Index, pioneered by UNDP’s Human Development Reports. The HDI blends four indicators (life expectancy at birth, the adult literacy rate, the combined enrollment rate for primary, secondary, and tertiary schools, and a purchasing power parity adjusted measure of per capita GDP) to capture three different issues (health, education and income) which are then aggregated into a single score that runs from 0 (no human development) to 1 (presumably some sort of ideal human development). This measure of well-being certainly moves beyond the purely economic, and probably does a better job of capturing the dynamics of poverty and well-being than any single measure, economic or otherwise, might. But still, this is a limited index – there is no way to capture things like gender disparities that greatly impact people’s well-being and opportunities.
And now comes the MPI, the latest effort to get a development index right. The MPI has quite a few more variables, and it has moved away from any reference to the economy in its measurement of poverty:
1. Health (each indicator weighted equally at 1/6)
- Child Mortality: If any child has died in the family
- Nutrition: If any adult or child in the family is malnourished
2. Education (each indicator weighted equally at 1/6 )
- Years of Schooling If no household member has completed 5 years of schooling
- Child Enrolment If any school-aged child is out of school in years 1 to 8
3. Standard of Living (each of the six indicators weighted equally at 1/18)
- Electricity If household does not have electricity
- Drinking water If does not meet MDG definitions, or is more than 30 mins walk
- Sanitation If does not meet MDG definitions, or the toilet is shared
- Flooring If the floor is dirt, sand, or dung
- Cooking Fuel If they cook with wood, charcoal, or dung
- Assets If do not own more than one of: radio, tv, telephone, bike, motorbike
There is a lot to like here – moving toward standard of living, and away from income, does a lot to make different situations comparable across countries and continents. And shifting measures of health from life expectancy, which can be compromised by any number of issues in the life cycle, to child mortality and nutrition, which are highly correlated to health outcomes, is also a good idea. But in the end, what will the MPI really add to our understanding of the dynamics of poverty and well-being that we could not have gleaned through the HDI – or through GDP, for that matter? Put another way, I am worried that a lot of time and effort has gone into polishing a turd.
In my forthcoming book, I make an extended argument for doing away with these indicators altogether. They are top-down efforts to organize and classify human experience in a manner that gives the illusion of actionable information, but none of the analytic purchase we actually need to do something in the world. A close look at the MPI and its constituent indicators illustrates my point*. Let’s examine Standard of Living – recall that I really like this category, and this reframing of this component of human well-being. But what, exactly, do the indicators have to do with standard of living? For example, why are radios, tvs, telephones, bikes, and motorbikes such critical assets in this index? First, this presumes that these commodities are proxies for people’s standard of living, which is questionable at best. Second, even if we accept that commodity ownership is an important part of the standard of living, why are we focused on these commodities? For example, surely cattle ownership is far more important than any of these when evaluating people’s assets in East Africa. And why does flooring matter so much? Yes, it is possible that worms or other insects and animals could find their way into an earth-floored house, why not focus on roofing or wall materials (which are much more important in keeping out insects, and therefore dealing with issues like malaria)?
Why did the designers of this index choose these variables? The answer, in part, lies in their explanation for their selection of variables “The ten indicators are almost the only set of indicators that could have been used to compare around 100 countries.” (p.13) While you have to work with the data you have, availability is not a valid criteria for evaluating the usefulness of a particular measure. In other words, if you are using an indicator variable as a proxy for a much larger process or issue, you have a responsibility to make sure that indicator actually says something meaningful about that process. It is not at all clear to me that these variables have a meaningful link to the standard of living in many parts of the world.
To the credit of those who designed the MPI, they note that “one of the main lessons of this first exercise of estimating multidimensional poverty for developing countries is the urgent need to start collecting information on key internationally comparable indicators at the individual level” (p.13). I’ve been part of an effort to rethink just how we identify and access this information, by building an information network that allows communities in the Global South to communicate with one another and with “experts” in the Global North – a bottom-up collection of data on the global state of human well-being. Our estimates suggest that this approach would, in the relatively short term, become much more accurate and cost-effective for identifying and addressing the challenges that limit human well-being around the world than current top-down efforts, as embodied in large indices like the MPI.
If indices like the HDI, and now the MPI, tell us very little about the causes, and therefore the solutions, for the problems and challenges that the global poor deal with on a daily basis, they are not useful analytical tools – at best, they are a first step in a process of inquiry that identifies an interesting trend for future analysis. So why are they still around? At least in part because they are great PR vehicles – they make for interesting maps that ostensibly show how bad things are for so many people, and which justify continued development efforts to donors. That is simply not good enough to justify the continued time and effort required to refine these indices.
*I’m not going to even get into the issue of weighting – basically, every individual variable listed above is weighted equally in this index. So, infant child mortality rates have the same impact on the MPI score as using wood fuel, having a dirt floor, and television ownership. Stop and think about that for a second.
Equality in the oddest places – or why purchasing power parity matters
My family and I are in the midst of a relocation to Washington, DC, a city with a cost of living at least 35% higher than my current home here in Columbia, SC. The rent for our (nice but hardly lavish) new place approaches double that of my current mortgage, and childcare is going to run us 50% above what we are used to here. And I am moving to take up a fellowship that grants me a 13% increase over my current salary to make up these costs . . . yes, I am going backward to take up this position, but I think this opportunity is too important to pass up. Luckily, my wife agrees.
The net outcome of this is a situation where my family will be living hand-to-mouth for a year or two, despite having two pretty good salaries under one roof. This situation reminds me of a story I use to explain the importance of purchasing power parity when comparing incomes and/or material standards of living in different places. Purchasing power parity is a measure of what your money will buy you, based on a “market basket” of goods that you might buy in each place. Since things like food are much more expensive here in the United States than they are in farming communities in sub-Saharan Africa, it makes no sense to compare incomes between these two places without normalizing for what those incomes can purchase. Which leads to my story . . .
My first year doing fieldwork in Ghana, I spent a lot of time simply hanging around, talking to people, getting my bearings and building relationships. Once the folks in Dominase and Ponkrum realized that I was 1) actually listening to them when they spoke and 2) willing to answer any questions they might have of me, I never lacked for evening conversation. This was especially true when I was buying the akpeteshi (distilled palm wine – it’s pretty serious stuff).
One night, while I was talking about money, incomes and making a living with a group of people in Dominase, the issue of my income and net worth came up. Now, at the time I was a graduate student in Anthropology, just about to start a Ph.D. program in Geography. I was fortunate enough to have a National Science Foundation Graduate Research Fellowship, which is (by grad school standards) a very generous award . . . but it was still not much to live on. In the interest of honesty, I told them exactly what my annual stipend amounted to: $14,000*. Once someone managed to convert that into Cedis (the local currency, then trading at about 2300 to the dollar), this news resulted in shouting and amazement.
I then asked if I could explain what things cost me in America. I began to lay things out – my rent of $350/month (this provoked a near-riot, as $350 is as much as some households earn in a year in these villages). Then the cost of food – and another near riot, as the farmers began to realize that crops like the oranges they sold me for the equivalent of 5 cents were worth at least twenty times that amount in the US. I then explained about my car, gasoline, insurance, clothing, etc. Never let anyone suggest that a lack of education leads to deficiencies in mathematics – despite incomplete elementary educations, nearly every person in these villages engages in trade in markets in nearby towns. As a result, they can add and subtract large and complex sums in their heads very, very rapidly. Several of the villagers talking to me were converting the amounts I was listing into Cedis, and then adding this total up as we went along. As I came to the end, one of them looked at me and said (in Fante, via my field assistant’s interpretation) “then you have nothing!” “Yes!” I replied (in English – I did not yet speak Fante – but yes is pretty well understood in Anglophone Africa). There was a pause, and then a general cheer of “nothing!” broke out among the assembled group – and with that, most residents of the village stopped seeing me as particularly rich, and therefore much more able to understand what it meant to live from hand to mouth as they did**. At the end of each month, we all had nothing!
Here I am, some 13 years later – with tenure, and paid reasonably well. And moving into a situation where, once again, at the end of each month I will have nothing! I’m not sure if the folks in Dominase and Ponkrum will be horrified or amused. But they will understand . . .
* I should note that I was completely screwed by NSF with regard to the size of my stipend – there was no cost of living adjustment across the four years I held the fellowship. As soon as it ran out for me, though, they instituted a 50% (!!!) increase – the next year. Yes, I am still a little bitter about that.
** This is not to say that I did, in the end, completely understand what it meant to be a resident of these villages. While I tried as hard as I could to live under the same strictures as the villagers when I was in the villages, I also spent time in more comfortable settings in Cape Coast. Further, when things went wrong (such as in 1998, when the monsoon failed and a lot of the farms around these villages failed), I experienced short-term discomfort and frustration, but always knew that I had resources to meet my needs, if only I chose to walk a few miles to the nearest road and catch a cab. Thus, while I spent a few days without food in 1998, like everyone else in these villages, I always knew that if things got really bad, I could get to a road and to a store where I could buy food with money from my bank account in the US. Thus, I cannot say that I understand what it is like to live on the edge like the people I work with do each and every day – honestly, none of us really can.
Finally, a hopeful note on malaria?
Ah, malaria – I’m all too acquainted with this particular issue, having had it several times in the course of my fieldwork. The first time is pretty miserable . . . but by about the fourth case, it is just a day feeling like you have the flu. Of course, this presumes that you are relatively young and healthy – if not, malaria can be quite dangerous.
I am one of the “lucky” few who could not go near Mefloquine (brand name Larium to those of you who have taken anti-malarials) back when it was the “best choice” for preventing malaria. I didn’t get malaria . . . but it did drive me toward a temporary bipolar situation and left me with residual vertigo that even now, 13 years later, I still feel at times. So, after that experience, I simply stopped taking antimalarials entirely, and tried to deal with bugsprays and long pants as much as possible. The relatively recent arrival of Malarone has made it possible for me to take effective antimalarials again, and when I am on short trips I do. For the long term, though, you really shouldn’t be taking anti-malarials . . . they are really not good for you, and at some point they do become more problematic than malaria itself.
Given this situation, I have taken a rather acute interest in the efforts to battle malaria. I’ve watched vaccines come and go. I’ve seen the rage for bed nets as panacea consume everyone, even though they are quite compromised in their effectiveness by the fact that the anopheles mosquito likes to fly in the evening, when people are not yet in bed, and tends to fly very low to the ground, and thus below the level of many beds. Hell, some crazy people have come up with a laser that can shoot mosquitos out of the air, thus preventing bites – the coolest, and most totally impractical solution for malaria I’ve ever seen (click here for a movie – really). How, precisely, are people meant to power and maintain a LASER WHEN THEY HAVE NO ELECTRICITY? And as I have watched all of these efforts, I have wished and hoped that someone could figure out a way to deal with this damn disease for the purely selfish reason that I am tired of getting it.
So, I was pretty excited to hear about a new development in this fight – an effort to genetically engineer mosquitos so that they cannot carry the parasite in the first place (LA Times, BBC, Tonic). Malaria is obscenely difficult to kill, because it goes through a large number of stages in its life cycle, and each stage is vulnerable to treatment in different ways – thus, a treatment that works early in the infection cycle may not work on later stage infections – and worse, if there are parasites going through different stages at the same time (some have been gestating for longer than others), a treatment might only work on a fraction of the parasites in the bloodstream and liver at any given time. But malaria has one weakness – it must have people to live in. Without us, eventually there would be no malaria – we are the host, and mosquitos must collect it from our blood, before passing it to other people. So, if the mosquito cannot act as the carrier, the parasite cannot move between hosts – and eventually the parasite dies out (the only real way to contract malaria is through mosquito bite*). In other words, this just might work . . .
But there are serious caveats here. First, we have to genetically modify mosquitos to do this. Then we have to get the genetically modified versions to mate with unmodified versions, and for the genes that restrict malaria to be the ones that emerge in the offspring. Since these genes would not convey any adaptive advantage to the mosquitos (the genetic modification actually causes them to die young, which strikes me as a significant genetic disadvantage), there is really no guarantee that this would happen – it could be that the modified mosquitos’ impact on the overall genetic pool is tiny – or huge. I shudder a little at the proposed solution for this (From LA Times):
“connecting the gene to a piece of DNA that helps it spread by, for example, producing something that kills any mosquitoes that don’t contain the desired gene. Other research groups are working to develop such clever genetic tricks, but they are still years away from implementation.”
Once we start playing with a wider set of genes, I get worried. As the article goes on to note, the effects of such modification are hard to predict in a single species, and since that species participates in a wider ecosystem, the impact on other species is equally hard to predict. The last thing anyone wants are supermosquitos (a la superweeds and other superbugs that have resulted from previous genetic modification efforts). So this is not a magic bullet, just a hopeful volley in what has been, and promises to be, a long battle.
*Funny side story: in 1999, I arrived back in Syracuse, NY just as a pretty bad case of malaria flared up. Despite my protestations, several of my grad student colleagues bundled me off to the emergency room. When the admissions person asked me what was wrong, I told her – rather simply – “I have malaria”. The women stared at me for a second, and then said “should I be wearing a mask or something?” I was pretty beaten up at that point, with an accordingly short temper, which explains my response: “Honey, unless you have a jar of anopheles mosquitos back there, I think we’re going to be alright.”
Development is not the same thing as adaptation
One of the most interesting and distressing trends in recent development thought has been the convergence of adaptation to global change (I use global change as a catch-all which includes environmental and economic change) and development. Development agencies increasingly take on the idea of adaptation as a key component of their missions – which they should, if they intend to build projects with enduring value. However, it is one thing to incorporate the idea of adaptation into development programming. It is entirely another to collapse the two into the same mission.
Simply put, development and adaptation have two different goals. In general, development is about improving the conditions of life for the global poor in some form or other. Adaptation implicitly suggests an effort to maintain what exists without letting it get worse . . . which sounds great until you think about the conditions of life in places like rural sub-Saharan Africa, where things are often very bad right now. A colleague of mine at USAID, in the context of a conversation about disaster relief and development, said it best: the mandate of disaster relief is to put things back to the way they were before the disaster. In a place like Haiti, that isn’t much of a mandate.
All of this becomes pretty self-evident after a moment of thought. Why, then, do we see the collapse of these two efforts into a single program in the world of development practice? For example, what does it mean when food security projects and programs start to define themselves in terms of adaptation? It seems to me that the goal shifts for these programs – from improvement to the maintenance of existing situations. If a development agency was there in the first place, the existing situation is likely unacceptable. To me, this means that this subtle shift in mission is also unacceptable.
Why am I going on about this? I am about to take up a job as the Climate Change Adaptation Coordinator for USAID’s Bureau of Democracy, Conflict and Humanitarian Assistance. In this job, I will have to negotiate this very convergence at the program level. How we work out this convergence over the next few years will have tremendous implications for development efforts for decades to come – and therefore huge implications for billions of people around the world. And I don’t pretend to have all the answers . . . but I will think out loud in this space as we go.
Why the world needs geographers . . .
Thank you, xkcd. Thank you.
The food bubble?
Frederick Kaufman has a very interesting piece (subscription required) on an underreported phenomena in the 2008 spike in food prices – what he calls a “food bubble” caused by commodities investment vehicles structured around wheat futures.
While I think this article is worth reading and considering carefully, it is important to recall that Kaufman is trying to make a particular point about the pervasiveness of problematic investment vehicles in our economy, and the ways in which these vehicles seem to hurt everyone but the people who invent them. This point is well-made. However, in making this point Kaufman underplays a couple of really important points:
1) Wheat is but one of the staples that saw a price spike in 2008. And while price stress on one staple (wheat) can lead people to start shifting into another (corn), driving the prices of the second commodity up, it would take some serious research to substantiate the (implicit) idea that a price spike in wheat could have a dramatic impact on corn prices in Africa (where wheat is the 8th most important crop, at 3.2% of total agricultural production) (via FAOSTAT). Wheat is important, but maize is the crop that links the world together . . . which leads to my second point:
2) There was a convergence of factors that created the price spike in 2008. In one sentence, Kaufman acknowledges several important factors:
“By the time the normal buying season began, drought had hit Australia, floods had inundated northern Europe, and a vogue for biofuels had enticed U.S. farmers to grow less wheat and more corn.”
But this is only one sentence in the whole article. In an effort to point out the impact of investment vehicles on global food security, Kaufman’s narrative underplays just how important these other factors were in driving up the price of other staples like corn (the extra corn was largely rerouted to biofuels, and the drought in Australia removed a great deal of expected production from the world supply).
The point here: food insecurity is enormously complex, and caused by the intersection of processes and events operating at multiple scales. Even as we tease out some of these processes and events, we must also highlight how each specific process or event intersects with other causes to produce particular outcomes in particular places.
Promises, promises
The BBC has a nice piece capturing the lack of follow-through on the G-8 promises of more aid to the developing world here. It is pathetic, but sadly unsurprising, that we have seen only 44% of the G-8 commitment come to fruition.
The whole thing makes Noel Gallagher (the former – and probably impending – talent in Oasis) look like a cross between a policy genius and a fortune teller:
From Guardian.co.uk:
“Correct me if I’m wrong, but are they hoping that one of these guys from the G8 is on a quick 15 minute break at Gleneagles (in Scotland) and sees Annie Lennox singing Sweet Dreams and thinks, ‘F**k me, she might have a point there, you know?’
“Keane doing Somewhere Only We Know and some Japanese businessman going, ‘Aw, look at him… we should really f**king drop that debt, you know.’
“It’s not going to happen, is it?”