Delivering Development

While development – thought broadly as social/economic/political change that somehow brings about a change in peoples’ quality of life – generally entails changes in behavior, conversations about “behavior change” in development obscure important political and ethical issues around this subject, putting development programs and projects, and worse the people those programs and projects are meant to help, at risk.

We need to return to a long standing conversation about who gets to decide what behaviors need changing.  Most contemporary conversations about behavior change invoke simple public health examples that obscure the politics of behavior change (such as this recent New York Times Opinionator Piece). This piece appears to address the community and household politics of change (via peer pressure), but completely ignores the fact that every intervention mentioned was introduced by someone outside these communities. This is easy to ignore because handwashing or the use of chlorine in drinking water clearly reduces morbidity, nobody benefits from such morbidity, and addressing the causes of that morbidity requires interventions that engage knowledge and technology that, while well-established, were created someplace else.

But if we open up this conversation to other sorts of examples, the picture gets much more complicated. Take, for example, agricultural behaviors. An awful lot of food security/agricultural development programming these days discusses behavior change, ranging from what crops are grown to how farmers engage with markets. Here, the benefits of this behavior change are less clear, and less evenly-distributed through the population. Who decides what should be grown, and on what basis? Is improved yield or increased incomes enough justification to “change behaviors”? Such arguments presume shockingly simple rationales for observed behaviors, such as yield maximization, and often implicitly assume that peasant farmers in the Global South lack information and understandings that would produce such yields, thus requiring “education” to make better decisions. As I’ve argued time and again, and demonstrated empirically several times, most livelihoods decisions are a complex mix of politics, local environment, economy, and social issues that these farmers weigh in the context of surprisingly detailed information (see this post or my book for a discussion of farm allocation in Ghanaian households that illustrates this point). In short, when we start to talk about changing peoples’ behaviors, we often have no idea what it is that we are changing.

The fact we have little to no understanding of the basis on which observed decisions are made is a big, totally undiscussed problem for anyone interested in behavior change. In development, we design programs and projects based on presumptions about people’s motivations, but those presumptions are usually anchored in our own experiences and perceptions – which are quite often different from those with whom we work in the Global South (see the discussion of WEIRD data in psychology, for example here). When we don’t know why people are doing the things we do, we cannot understand the opportunities and challenges that come with those activities/behaviors. This allows an unexamined bias against the intelligence and experience of the global poor to enter and lurk behind this conversation.

Such bias isn’t just politically/ethically problematic – it risks real programmatic disasters. For example, when we perceive “inefficiency” on many African farms, we are often misinterpreting hedging behaviors necessary to manage worst-case scenarios in a setting where there are no safety nets. Erasing such behaviors in the name of efficiency (which will increase yields or incomes) can produce better outcomes…until the situation against which the farmers were hedged arises. Then, without the hedge, all hell can break loose. Among the rural agricultural communities in which I have been working for more than 15 years, such hedges typically address climate and/or market variability, which produce extremes at frequent, if irregular, intervals. Stripping the hedges from these systems presumes that the good years will at least compensate for the bad…a dangerous assumption based far more on hope or optimism than evidence in most places where these projects are designed and implemented. James Scott’s book The Art of Not Being Governed provides examples of agrarian populations that fled the state in the face of “modernization” efforts not because they were foolish or backward, but because they saw such programs as introducing unacceptable risks into their lives (see also this post for a similar discussion in the context of food security).

This is why my lab uses an approach (on a number of projects ranging from climate services evaluation and design to disaster risk reduction) that starts from the other direction – we begin by identifying and explaining particular behaviors relevant to the challenge, issue, or intervention at hand, and then start thinking about what kinds of behavioral change are possible and acceptable to the people with whom we work. We believe that this is both more effective (as we actually identify the rationales for observed behaviors before intervening) and safer (as we are less likely to design/condone interventions that increase vulnerability) than development programming based on presumption.

This is not to say that we should simply valorize all existing behaviors in the Global South. There are inefficiencies out there that could be reduced. There are things like handwashing that are simple and important. Sometimes farmers can change their practices in small ways that do not entail big shifts in risk or vulnerability. Our approach to project design and assessment helps to identify just such situations. But on the whole, we need to think much more critically about what we are assuming when we insist on a particular behavior change, and then replace those assumptions with information. Until we do, behavior change discussions will run the risk of uncritically imposing external values and assumptions on otherwise coherent systems, producing greater risk and vulnerability than existed before. Nobody could call that development.

Andy Sumner was kind enough to invite me to provide a blog entry/chapter for his forthcoming e-book The Donors’ Dilemma: Emergence, Convergence and the Future of Aid. I decided to use the platform as an opportunity to expand on some of my thoughts on the future of food aid and food security in the context of a changing climate.

My central point:

By failing to understand existing agricultural practices as time-tested parts of complex structures of risk management that include concerns for climate variability, we overestimate the current vulnerability of many agricultural systems to the impacts of climate change, and underestimate the risks we create when we wipe these systems away in favor of “more efficient”, more productive systems meant to address this looming global food crisis.

Why does this matter?

In ignoring existing systems and their logic in the name of addressing a crisis that has not yet arrived, development aid runs a significant risk of undermining the nascent turn toward addressing vulnerability, and building resilience, in the policy and implementation world by unnecessarily increasing the vulnerability of the poorest populations.

The whole post is here, along with a number of other really interesting posts on the future of aid here. Head over and offer your thoughts…

I’m a big fan of accountability when it comes to aid and development. We should be asking if our interventions have impact, and identifying interventions that are effective means of addressing particular development challenges. Of course, this is a bit like arguing for clean air and clean water. Seriously, who’s going to argue for dirtier water or air. Who really argues for ineffective aid and development spending?


More often than not, discussions of accountability and impact serve only to inflate narrow differences in approach, emphasis, or opinion into full on “good guys”/ “bad guys” arguments, where the “bad guys” are somehow against evaluation, hostile to the effective use of aid dollars, and indeed actively out to hurt the global poor. This serves nothing but particular cults of personality and, in my opinion, serves to squash out really important problems with the accountability/impact agenda in development. And there are major problems with this agenda as it is currently framed – around the belief that we have proven means of measuring what works and how, if only we would just apply those tools.

When we start from this as a foundation, the accountability discussion is narrowed to a rather tepid debate about the application of the right tools to select the right programs. If all we are really talking about are tools, any skepticism toward efforts to account for the impact of aid projects and dollars is easily labeled an exercise in obfuscation, a refusal to “learn what works,” or an example of organizations and individuals captured by their own intellectual inertia. In narrowing the debate to an argument about the willingness of individuals and organizations to apply these tools to their projects, we are closing off discussion of a critical problem in development: we don’t actually know exactly what we are trying to measure.

Look, you can (fairly easily) measure the intended impact of a given project or program if you set things up for monitoring and evaluation at the outset.  Hell, with enough time and money, we can often piece enough data together to do a decent post-hoc evaluation. But both cases assume two things:

1)   The project correctly identified the challenge at hand, and the intervention was actually foundational/central to the needs of the people at hand.

This is a pretty weak assumption. I filled up a book arguing that a lot of the things that we assume about life for the global poor are incorrect, and therefore that many of our fundamental assumptions about how to address the needs of the global poor are incorrect. And when much of what we do in development is based on assumptions about people we’ve never met and places we’ve never visited, it is likely that many projects which achieve their intended outcomes are actually doing relatively little for their target populations.

Bad news: this is pretty consistent with the findings of a really large academic literature on development. This is why HURDL focuses so heavily on the implementation of a research approach that defines the challenges of the population as part of its initial fieldwork, and continually revisits and revises those challenges as it sorts out the distinct and differentiated vulnerabilities (for explanation of those terms, see page one of here or here) experienced by various segments of the population.

Simply evaluating a portfolio of projects in terms of their stated goals serves to close off the project cycle into an ever more hermetically-sealed, self-referential world in which the needs of the target population recede ever further from design, monitoring, and evaluation. Sure, by introducing that drought-tolerant strain of millet to the region, you helped create a stable source of household food that guards against the impact of climate variability. This project could record high levels of variety uptake, large numbers of farmers trained on the growth of that variety, and even improved annual yields during slight downturns in rain. By all normal project metrics, it would be a success. But if the biggest problem in the area was finding adequate water for household livestock, that millet crop isn’t much good, and may well fail in the first truly dry season because men cannot tend their fields when they have to migrate with their animals in search of water.  Thus, the project achieved its goal of making agriculture more “climate smart,” but failed to actually address the main problem in the area. Project indicators will likely capture the first half of the previous scenario, and totally miss the second half (especially if that really dry year comes after the project cycle is over).

2)   The intended impact was the only impact of the intervention.

If all that we are evaluating is the achievement of the expected goals of a project, we fail to capture the wider set of impacts that any intervention into a complex system will produce. So, for example, an organization might install a borehole in a village in an effort to introduce safe drinking water and therefore lower rates of morbidity associated with water-borne illness. Because this is the goal of the project, monitoring and evaluation will center on identifying who uses the borehole, and their water-borne illness outcomes. And if this intervention fails to lower rates of water-borne illness among borehole users, perhaps because post-pump sanitation issues remain unresolved by this intervention, monitoring and evaluation efforts will likely grade the intervention a failure.

Sure, that new borehole might not have resulted in lowered morbidity from water-borne illness. But what if it radically reduced the amount of time women spent gathering water, time they now spend on their own economic activities and education…efforts that, in the long term, produced improved household sanitation practices that ended up achieving the original goal of the borehole in an indirect manner? In this case, is the borehole a failure? Well, in one sense, yes – it did not produce the intended outcome in the intended timeframe. But in another sense, it had a constructive impact on the community that, in the much longer term, produced the desired outcome in a manner that is no longer dependent on infrastructure. Calling that a failure is nonsensical.

Nearly every conversation I see about aid accountability and impact suffers from one or both of these problems. These are easy mistakes to make if we assume that we have 1) correctly identified the challenges that we should address and 2) we know how best to address those challenges. When these assumptions don’t hold up under scrutiny (which is often), we need to rethink what it means to be accountable with aid dollars, and how we identify the impact we do (or do not) have.

What am I getting at? I think we are at a point where we must reframe development interventions away from known technical or social “fixes” for known problems to catalysts for change that populations can build upon in locally appropriate, but often unpredictable, ways. The former framing of development is the technocrats’ dream, beautifully embodied in the (failing) Millennium Village Project, just the latest incarnation of Mitchell’s Rule of Experts or Easterly’s White Man’s Burden. The latter requires a radical embrace of complexity and uncertainty that I suspect Ben Ramalingan might support (I’m not sure how Owen Barder would feel about this). I think the real conversation in aid/development accountability and impact is about how to think about these concepts in the context of chaotic, complex systems.

Ok, so that title was meant to goad my fellow anthropologists, but before everyone freaks out, let me explain what I mean. The best anthropology, to quote Marshall Sahlins, “consists of making the apparently wild thought of others logically compelling in their own cultural settings and intellectually revealing of the human condition.” This is, of course, not bound by time. Understanding the thought of others, wherever and whenever it occurs, helps to illuminate the human condition. In that sense, ethnographies are forever.

However, in the context of development and climate change, ethnography has potential value beyond this very broad goal. The understandings of human behavior produced through ethnographic research are critical to the achievement of the most noble and progressive goals of development*. As I have argued time and again, we understand far less about what those in the Global South are doing than we think, and I wrote a book highlighting how our assumptions about life in such places are a) mostly incorrect and b) potentially very dangerous to the long-term well-being of everyone on Earth.  To correct this problem, development research, design, and monitoring and evaluation all need much, much more engagement with qualitative research, including ethnographic work. Such work brings a richness to our understanding of other people, and lives in other places, that is invaluable to the design of progressive programs and projects that meet the actual (as opposed to assumed) needs of the global poor now and in the future.

As I see it, the need for ethnographic work in development presents two significant problems. The first, which I have discussed before, is the dearth of such work in the world. Everyone seems to think the world is crawling with anthropologists and human geographers who do this sort of work, but how many books and dissertations are completed each year? A thousand? Less?  Compare that to the two billion (or more) poor people living in low-income countries (and that leaves aside the billion or so very poor that Andy Sumner has identified as living in middle-income countries).  A thousand books for at least two billion people? No problem, it just means that each book or dissertation has to cover the detailed experiences, motivations, and emotions of two million people. I mean, sure, the typical ethnography addresses an N that ranges from a half dozen to communities of a few hundred, but surely we can just adjust the scale…



OK, so there is a huge shortage of this work, and we need much, much more of it. Well, the good new is that people have been doing this sort of work for a long time. Granted, the underlying assumptions about other people have shifted over time (“scientific racism” was pretty much the norm back in the first half of the 20th Century), but surely the observations of human behavior and thought might serve to fill the gaps from which we currently suffer, right. After all, if a thousand people a year knocked out a book or dissertation over the past hundred years, surely our coverage will improve.  Right?

Well, maybe not. Ethnographies describe a place and a time, and most of the Global South is changing very, very rapidly. Indeed, it has been changing for a while, but of late the pace of change seems to be accelerating (again, see Sumner’s work on the New Bottom Billion). Things change so quickly, and can change so pervasively, that I wonder how long it takes for many of the fundamental observations about life and thought that populate ethnographies to become historical relics that tell us a great deal about a bygone era, but do not reflect present realities.  For example, in my work in Ghana, I drew upon some of the very few ethnographies of the Akan, written during the colonial era. These were useful for the archaeological component of my work, as they helped me to contextualize artifacts I was recovering from the time of those ethnographies. But their descriptions of economic practice, local politics, social roles, and livelihoods really had very little to do with life in Ghana’s Central Region in the late 1990s.  In terms of their utility for interpreting contemporary life among the Akan, they had, for all intents and purposes, expired.

So, the questions I pose here:

1)    How do we know when an ethnography has expired?  Is it expired when any aspect of the ethnography is no longer true, or when a majority of its observations no longer hold?

2)    Whatever standard we might hold them to, how long does it take to reach that standard? Five years? Ten years? Thus far, my work from 2001 in Ghana seems to be holding, but things are wobbling a bit.  It is possible that a permanent shift in livelihoods took place in 2006 (I need to examine this), which would invalidate the utility of my earlier work for project design in this area.

These are questions worth debating. If we are to bring more qualitative, ethnographic work to the table in development, we have to find ways to improve our coverage of the world and our ability to assess the resources from which we might draw.



*I know some people think that “noble” and “progressive” are terms that cannot be applied to development. I’m not going to take up that debate here.

I’ve just spent nearly three weeks in Senegal, working on the design, monitoring, and evaluation of a CCAFS/ANACIM climate services project in the Kaffrine Region. It was a fantastic time – I spent a good bit of time out in three villages in Kaffrine implementing my livelihoods as governmentality approach (for now called the LAG approach) to gather data that can inform our understanding of what information will impact which behaviors for different members of these communities.

This work also included a week-long team effort to build an approach to monitoring and evaluation for this project that might also yield broader recommendations for M&E of climate services projects in other contexts.  The conversations ranged from fascinating to frustrating, but in the process I learned an enormous amount and, I think, gained some clarity on my own thinking about project design, monitoring, and evaluation. For the purposes of this blog, I want to elaborate on one of my long-standing issues in development – the use of panel surveys, or even broad baseline surveys, to design policies and programs.

At best, people seem to assume that the big survey instrument helps us to identify the interesting things that should be explained through detailed work. At worst, people use these instruments to identify issues to be addressed, without any context through which to interpret the patterns in the data. Neither case is actually all that good. Generally, I often find the data from these surveys to be disaggregated/aggregated in inappropriate manners, aimed at the wrong issues, and rife with assumptions about the meaning of the patterns in the data that have little to do with what is going on in the real world (see, for example, my article on gendered crops, which was inspired by a total misreading of Ghanaian panel survey data in the literature). This should be of little surprise: the vast bulk of these tools are designed in the abstract – without any prior reference to what is happening on the ground.

What I am arguing here is simple: panel surveys, and indeed any sort of baseline survey, are not an objective, inductive data-gathering process. They are informed by assumptions we all carry with us about causes and effects, and the motivations for human behavior. As I have said time and again (and demonstrated in my book Delivering Development), in the world of development these assumptions are more often than not incorrect. As a result, we are designing broad survey instruments that ask the wrong questions of the wrong people. The data from these instruments is then interpreted through often-inappropriate lenses. The outcome is serious misunderstandings and misrepresentations of life on globalization’s shoreline. These misunderstandings, however, carry the hallmarks of (social) scientific rigor even as they produce spectacular misrepresentations of the decisions, events, and processes we must understand if we are to understand, let alone address, the challenges facing the global poor.  And we wonder why so many projects and policies produce “surprise” results contrary to expectations and design? These are only surprising because the assumptions that informed them were spectacularly wrong.

This problem is easily addressed, and we are in the process of demonstrating how to do it in Kaffrine. There are baseline surveys of Kaffrine, as well as ongoing surveys of agricultural production by the Senegalese agricultural staff in the region. But none of these is actually tied to any sort of behavioral model for livelihoods or agricultural decision-making. As a result, we can’t rigorously interpret any patterns we might find in the data.  So what we are doing in Kaffrine (following the approach I used in my previous work in Ghana) is spending a few weeks establishing a basic understanding of the decision-making of the target population for this particular intervention. We will then refine this understanding by the end of August through a full application of the LAG approach, which we will use to build a coherent, complex understanding of livelihoods decision-making that will define potential pathways of project impact. This, in turn, will shape the design of this program in future communities as it scales out, make sense of the patterns in the existing baseline data and the various agricultural services surveys taking places in the region, and enable us to build simple monitoring tools to check on/measure these pathways of impact as the project moves forward. In short, by putting in two months of serious fieldwork up front, we will design a rigorous project based on evidence for behavioral and livelihoods outcomes. While this will not rule out surprise outcomes (African farmers are some pretty innovative people who always seem to find a new way to use information or tools), I believe that five years from now any surprises will be minor ones within the framework of the project, as opposed to shocks that result in project failure.

Incidentally, the agricultural staff in Kaffrine agrees with my reading of the value of their surveys, and is very excited to see what we can add to the interpretation of their data. They are interested enough to provide in-town housing for my graduate student, Tshibangu Kalala, who will be running the LAG approach in Kaffrine until mid-July. Ideally, he’ll break it at its weak points, and by late July or early August we’ll have something implementable, and by the end of September we should have a working understanding of farmer decision-making that will help us make sense of existing data while informing the design of project scale up.

I am in Tromsø, Norway for a workshop on gender and adaptation. The conversation has been very interesting, with a lot of different people bringing different ideas/concerns to the table.  As you might imagine, a lot of it has been fodder for thought. But today a comment by Torjer Andreas Olsen, of the Centre for Sami Studies (SESAM) at the University of Tromsø, really stuck with me. In a conversation about business and innovation, he suggested that we face a challenge in the use of the term “innovation” when we talk about indigenous peoples such as the Sami. Because most business discussions of innovation are focused on technological change, they fail to see the development of new forms of knowledge and information as innovation.  Therefore, while indigenous peoples (and I would extend this argument to most of the global poor) have the capacity to produce important information and knowledge about the world, this often does not come attached to technological change and therefore goes unacknowledged.

I think Torjer is dead right, and I think I can extend his argument a bit here. By failing to acknowledge the production of knowledge and information as itself an innovation, we basically allow ourselves to write off the global poor as lacking innovation. This enables our usual narratives of development – of a helpless global poor waiting for someone to come save them from their routinized ways. This is enhanced by climate change, as this narrative, run to its logical end, suggests that the global poor have pretty much nothing to contribute in their own efforts to adapt, and therefore require massive interventions from the “innovative north”.

This is a major problem for development, especially as major donor start embracing the idea of innovation.  While at USAID, I looked up at the wrong time in a meeting and was tasked with identifying the Agency definition of innovation.  My friend and colleague Mike Hanowski kindly threw himself under the bus and volunteered to help me. What followed was a fairly hilarious afternoon where Mike and I called various people in the Agency to obtain this definition. Every person we called passed us to another person, until we were passed back to the first person we had called.  Really.  So, no formal definition of innovation (maybe this has changed, but I doubt much of the Agency would know if even if it had).

Now, I am a fan of the Development Innovation Ventures (DIV) folks at USAID (a group that was started after the aforementioned story). They do promote interesting, relatively edgy ideas within the Agency. But look at what DIV does – every project amounts to the use of a technology to address a “big challenge” for development.  In and of itself, this is fine…but in this focus, DIV (inadvertently) reinforces the trope of the helpless global poor, waiting for the “innovative north” (or ideally an “innovative southerner”, presented as an outlier who can lead the helpless poor in his/her country or community to a brighter future). Even as we find interesting solutions to development challenges, we are reinforcing the idea that such solutions are the Global North’s to give to those in the Global South. As long as this is the case, we will continue to miss the interesting opportunities to address these and other challenges that exist in the minds and practices of the global poor.

While many paint the combined impact of climate change and global markets as something new, unpredictable, and unmanageable, they fail to grasp that most situations we are projected to see in the next few decades* have been experienced before in the form of previous extremes.  Take, for example, the figure below:


This is a graph of the annual rainfall at one rain gauge in Ghana, near where I conducted the research that made up a big part of my book Delivering Development.  The downward trend in rainfall is clear (and representative of the trend in this part of coastal West Africa that, according to my colleagues at IRI, continues to this day and is confirmed by satellite measurements).  There are complex things happening inside these annual figures, including shifting timing of rainfall, but for the purposes of discussion here, it serves to make a point.  While there is indeed a downward trend that continues to this day, there have already been several years where the total precipitation was much lower than the current average precipitation, or the likely annual precipitation for the next few decades.

This means is that the farmers in Dominase and Ponkrum, like so many around the world, have already seen the future – that is, they have already lived through at least one, if not several, seasons like those we expect to become the norm some decades in the future.  These farmers survived those seasons, and learned from them, adjusting their expectations and strategies to account for the possibility of recurrence. These adjustments are likely over- or under-compensating for the likelihood of recurrence right now, as livelihoods strategies in these villages are largely reactive, reflecting last season’s events more than the average season. Further, the year-to-year hedging of farms against climate variability can be a costly practice – the likely “insurance premium” of lost production in a good year (due to planting in less-than-ideal, but precipitation-hedged situations like the tops and bottoms of hills – see my discussion in Chapter 4 of Delivering Development) probably eats up somewhere between 10% and 20% of total potential production.  So these management strategies are not ideal. But they do reflect local capacities to adjust and account for extreme conditions, the extreme rainfall or drought events out along the tails of historical distributions whose unpredictable recurrences characterize a changing climate regime.  Many of these farmers have little or no access to inputs, limited to no access to seasonal forecasts, and live in states without safety nets, yet they have repeatedly survived very difficult seasons.  Clearly, their capacity for survival in an uncertain environment and economy is worthy of our respect.

This is not a phenomenon specific to Ghana.  For example, the farmers in southern Mali with whom I (and many others) have been working to deliver better and more relevant climate services, such as seasonal and short-term forecasts.  Most, if not all, of these farmers are using local indicators, such as the flowering of a particular tree or the emergence of a particular insect, as indicators that help them time various activities in their agricultural cycle. Many trust their local indicators more than the forecasts, perhaps with some reason – their indicators actually seem to work and the forecasts are not yet as accurate as anyone would like.  But these indicators work under current climate regimes, and these regimes are changing. At some point, the tree will start to flower at a different, perhaps less appropriate time, or simply cease to flower. The insect will emerge at a different time, or perhaps be driven away by the emergence of new predators that can now move into the area. If the climate continues to change, local indicators will eventually fail.

I humbly suggest that instead of reengineering entire agroecological systems and their associated economies in the here and now (a fairly high risk enterprise), we should be building upon the capacities that already exist.  For example, we can plan for the eventual failure of local indicators – we can study the indicators to understand under what conditions their behaviors will change, identify likely timeframes in which such changes are likely to occur, and create of new tools and sources of information that will be there for farmers when their current sources of information no longer work. We should be designing these tools and that information with the farmers, answering the questions they have (as opposed to the questions we want to ask).  We should be building on local capacity, not succumbing to crisis narratives that suggest that these farmers have little capacity, either to manage their current environment or to change with the environment.

Farmers in the Global South have already fed the future. Perhaps they did not do it all that well, and all they managed was to stave off catastrophe. But given the absence of safety nets in most places in the Global South (see Theme 3, points 2 and 3), and the limited access so many farmers have to inputs and irrigation, avoiding catastrophe is an accomplishment that warrants study and serious consideration. We should build on that capacity, not blow it up.

The key principals and points:

1)   A future under climate change is not a great unknown for farmers in the Global South. Most farmers have already managed several seasons as difficult, or more difficult, than what we project to be normal in the next few decades. Presuming these farmers are facing a catastrophe they cannot see coming fails to grasp the ways in which these past seasons inform contemporary planning.

2)   Farmers have already developed strategies for addressing extreme seasons (i.e. drought or excessive precipitation). We should start with an understanding of what they already do, and why, before moving in with our interventions, lest we inadvertently undo otherwise functional safety nets.

3)   Existing indigenous strategies for managing climate variability are not perfect. They tend to overestimate or underestimate actual risks of particular weather and climate states, tend to magnify the importance of the previous season (as opposed to historical averages, or current trends) when planning for the next season, and tend to be very costly in terms of lost potential agricultural productivity.

4)   Current indigenous tools for making agricultural decisions, such as local indicators, are likely more robust than any climate product we can deliver right now. Just because this information comes in the form of a plant or animal behavior does not make it any less valid.

5)   Current indigenous tools for making agricultural decisions will likely start to fail as climate regimes change. This fact presents an opportunity for development organizations to start working with farmers to identify useful information and ways of providing it such that this information is available when local indicators fail.



*Given the propagation of uncertainty in models of the global climate, global water availability, global land cover, the global economy, and global population (all of which, incidentally, impact one another), I don’t pay much attention to model results beyond about 2040, with 2030 being the really outer threshold of information that might usefully inform planning or our understanding of biophysical process.  On the 100-year scale, we may as well be throwing darts at a wall as running models. I have no idea why we bother.

While behavioral economics continues to open old questions in development to new scrutiny, I am still having a lot of problems with the very unreflexive approach BE takes toward its own work (see earlier takes on this here and here).  Take, for example, Esther Duflo’s recent lectures discussing mistakes the poor make.  To discuss the mistakes the poor make, we must first understand what the goals of the poor are.  However, I simply don’t see the behavioral economists doing this.  There is still a lurking, underlying presumption that in making livelihoods decisions people are trying to maximize income and or the material quality of their lives.  This, however, is fundamentally incorrect.  In Delivering Development and a number of related publications (for example, here, here, and here) I have laid out how, in the context of livelihoods, material considerations are always bound up in social considerations.  If you only evaluate these actions as aimed at material goals, you’ve only got a part of the picture – and not the most important part, in most cases.  Instead, what you are left with are a bunch of decisions and outcomes that appear illogical, that can be cast as mistakes.  Only most of the time, they are not mistakes – they are conscious choices.

Let me offer an example from Delivering Development and some of my other work – the constraint of women’s farming by their husbands.  I have really compelling qualitative evidence from two villages in Ghana’s Central Region that demonstrates that men are constraining their wives’ farm production to the detriment of the overall household income.  The chart below shows a plot of the size of a given farm versus its market orientation for the households operating under what I call a “diversified” strategy – where the husband farms for market sale, and the wife for subsistence (a pretty common model in sub-Saharan Africa).  As you move up the Y axis, the farm gets more oriented toward market sale (1 on that scale is “eat everything”, 3 is sell and eat equally, and 5 is sell everything).  Unsurprisingly, since men’s role requires them to produce for market, the size of their farm has little impact on their orientation.  But look at the women’s farms – just a tenth of a hectare produces a marked shift in orientation from subsistence to market production…because women own that surplus beyond subsistence, and sell it.  They take the proceeds of these sales, buy small goods, and engage in petty trading, eventually multiplying that small surplus into significant gains in income, nearly equaling their husbands.  What is not to like?

Well, from the perspective of those in these villages, here is something: among the Akan, being a “good man” means being in control of the household and out-earning your wife.  If you don’t, your fitness as a man gets called into question, which can cost you access to land.  For wives, this is bad because they get their land through their husbands.  So as a result, being in a household where the woman out-earns her husband is not a viable livelihoods outcome (as far as members of these households are concerned).  Even if a man wanted to let his wife earn more money, he would do so at peril of his access to land. So he is not going to do that.  What he is going to do is shrink his wife’s farm the next season to ensure she does not out-earn him (and I have three years of data where this is exactly what happens to wives who earn too much).  There is a “mistake” here – some of these men underestimated their wives’ production, which is pretty easy to do under rain-fed agriculture in a changing climate.  That they are this accurate with regard to land allocation is rather remarkable, really.  But the decision to constrain women’s production is not a mistake, per se: it is a choice.

We can agree or disagree with the premises of these choices, and their outcomes, but labeling them as mistakes creates a false sense of simplicity in addressing problematic outcomes – because people only require “correction” to get to the outcomes we all want and need.  This, in turn, rests on/reproduces a sense of superiority on the part of the researcher – because s/he knows what is best (see a previous post on this point here).  That attitude, applied to the case above, would not result in a productive project design aimed at addressing income or other challenges in these villages.

Yes, people do things against material interest…but there is always a logic behind a decision, and that logic is often deeply entrenched.  We would be better off talking about decisions poor people make (for better or worse), and dedicating our time to understanding why they make these decisions before we start deciding who is mistaken, and what to do about it.

I’ve just burned 15,000 words in Third World Quarterly laying out my argument for how to think about livelihoods as more than material outcomes – and how to make that vision implementable, at least via fieldwork that runs in length from days to months.  I am happy to send a copy of the preprint to anyone who is interested –and I will post a version to my website shortly.

Update: 11/22: So, after seeing Tom Murphy’s Storify of the twitter exchange, it is now clear that Sachs was on fire – the man was engaged in several conversations at once along the lines below…and he seems to have been responding to all of them pretty coherently, and in real time. I admit to being impressed (No, seriously, click on the Storify link there and just scroll. It is boggling). So recognize that what you see below is what I saw in my feed (his other conversations were with people I don’t follow, so I didn’t realize they were ongoing). Still, glad to get geography’s foot back in the door…

So, quite by surprise, I found myself on the end of an extended twitter exchange with Jeff Sachs.  I’ve hassled him via twitter before, and never had a response. So, I was a bit taken aback to see my feed light up about 30 seconds after I tweeted with @JeffDSachs at the front end! To give Sachs credit, he stayed quite engaged and did seem to be taking on some of my points. Granted, 140 characters is hardly enough to really convey the issues at hand, but I did the best I could to represent contemporary human geography. Y’all be the judge – this is the feed, slightly rejiggered to clarify that at times Sachs and I were crossing each other’s messages – he was clearly responding to a previous message sometimes when he tweeted back after one of my tweets. Also, Samuel Danthine was also on the conversation, and I kept him in the timeline as it seems he and I were coming from the same place:

I’ve long hated the term “poverty traps,” development shorthand for conditions in which poverty becomes self-reinforcing and therefore inescapable without some sort of external intervention.  They made no analytic sense (nobody ever defined poverty clearly across this literature, for example), and generally the idea of the poverty trap was hitched to a revival of “big push” development efforts that had failed in the 1950s and 1960s.  Further, it was always clear to me that the very idea of a poverty trap cast those living in difficult circumstances as helpless without the intervention of benevolent outsiders.  This did not align at all with my experiences on the ground in rural sub-Saharan Africa.

This is not to suggest that there is no such thing as structural inequality in the world – the running head start enjoyed by the Global North in terms of economic development has created significant barriers to the economic development of those residing in the Global South.  These barriers, perhaps most critically the absurd and damaging regime of subsidies that massively distorts global agricultural markets, must be addressed, and soon.  Such barriers generally result in perverse outcomes that impact even those in the Global North (anyone who thinks the American food system makes any sense at all really needs to read more.  Start with Fast Food Nation, move to The Omnivore’s Dilemma, and work out from there. And don’t get me going on the potential climate impacts of structural inequality).

But this enduring focus on structural problems in the global economy has had the effect of reducing those in the Global South to a bunch of helpless children in need of salvation by the best and most noble of those in the Global North, who were to bring justice, opportunity, and a better future to all.  If this isn’t the 21st Century version of the White Man’s Burden, then I don’t know what is.  Bill Easterly makes a very similar point very eloquently, and at much greater length, here.

I am a social scientist*, and I believe that the weight of evidence eventually wins arguments.  And today it occurred to me that in this case, this long line of arguing that those who insisted on talking about poverty traps were a) generally misrepresenting the world and b) inappropriately infantilizing those living in the Global South now has that weight of evidence behind it.  Andy Sumner’s work on the New Bottom Billion basically blows up the idea of the poverty trap – he demonstrates that since the 1990s, a lot of people that were thought to be living in poverty traps have improved their incomes such that many have moved out of poverty (at least if one defines poverty on the basis of income).  People who were thought to be trapped by structural inequality have been defying expectations and improving their circumstances without clear correlations to aid or development efforts, let alone the “big push” arguments of Sachs and others.  In short, it looks like we don’t really understand what people are doing at the margins of the Global South, and that the global poor are a lot more capable than development seems to think.  Poor people attached to the anchor of structural inequality are dragging it to improved incomes and well-being in thousands of small, innovative ways that are adding up to a massive aggregate change in the geography and structure of global poverty.

In short, the Global South never needed the most enlightened of the Global North to clear the path and push them up the ladder of development (if you want to get all Rostow about it).  Instead, what is clearly needed is a new, substantial effort to better understand what is happening out on Globalization’s Shoreline, and to work with the global poor to examine these efforts, identify innovative, locally-appropriate, and locally-owned means of transforming their quality of life, and find means of bringing those ideas to (appropriate) scale.  Anything else is just hubris at best, and subtle class/race bigotry at worst.

The data is speaking. Anyone ready to listen?





*Well, I am a qualitative social scientist which means my work is more generative and humanities/arts flavored than is typical in the sciences, which generally value the reporting of observations in the framework of already-established biophysical processes.

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