Entries tagged with “livelihoods”.


So, DfID paid London’s School of Oriental and African Studies (SOAS) more than $1 million to answer a pretty important question: Whether or not Fairtrade certification improves growers’ lives. As has shown up in the media (see here and here) and around the development blogosphere (here), the headline finding of the report was unexpected: wage workers on Fairtrade-certified sites made less than those working on regular farms. Admittedly, this is a pretty shocking finding, as it undermines the basic premise of Fairtrade.

Edit 12 June: As Matt Collin notes in a comment below, this reading of the study is flawed, as it was not set up to capture the wage effects of Fairtrade. There were no baselines, and without baselines it is impossible to tell if there were improvements in Fairtrade sites – in short, the differences seen in the report could just be pre-existing differences, not a failure of Fairtrade. See the CGDev blog post on this here. So the press’ reading of this report is pretty problematic.

At the same time, this whole discussion completely misses the point. Fairtrade doesn’t work as a development tool because, in the end, Fairtrade does absolutely nothing to address the structural inequalities faced by those in the primary sector of the global economy relative to basically everyone else. Paying an African farmer a higher wage/better price means they are now a slightly wealthier farmer. They are still exposed to environmental shocks like drought and flooding, still tied to shocks and trends in global commodities markets over which they have almost no leverage at all, often still producing commodities (like coffee and cocoa) for which demand is very, very elastic, and in the end still living in states without safety nets to help them weather these economic and environmental shocks. Yes, I think African farmers are stunningly resilient, intelligent people (I write about this a lot). But the convergence of the challenges I just listed means that most farmers in the Global South are addressing one or more of them almost all the time, and the cost of managing these challenges is high (both in terms of hedging and coping). Incremental changes in agricultural incomes will be absorbed, by and large, by these costs – this is not a transformative development pathway.

So why is everyone freaking out at the $1 million dollar finding – even if that finding misrepresents the actual findings of the report? Because it brutally rips the Fairtrade band-aid off the global economy, and strips away any feeling of “doing our part” from those who purchase Fairtrade products. But of course, those of us who purchase Fairtrade products were never doing our part. If anything, we were allowing the shiny idea of better incomes and prices to obscure the structural problems that would always limit the impact of Fairtrade in the lives of the poor.

Bill Gates has a Project Syndicate piece up that, in the context of discussing Nina Munk’s book The Idealist, argues in favor of Jeffrey Sachs’ importance and relevance to contemporary development.

I’m going to leave aside the overarching argument of the piece. Instead, I want to focus on a small passage that, while perhaps a secondary point to Gates, strikes me as a very important lesson that he fails to apply to his own foundation (though to be fair, this is true of most people working in development).

Gates begins by noting that Sachs came to the Gates Foundation to ask for MVP funding, and lays out the fundamental MVP pitch for a “big push” of integrated interventions that crossed health, agriculture, and education sectors that Sachs was selling:

[Sachs’] hypothesis was that these interventions would be so synergistic that they would start a virtuous upward cycle and lift the villages out of poverty for good. He felt that if you focus just on fertilizer without also addressing health, or if you just go in and provide vaccinations without doing anything to help improve education, then progress won’t be sustained without an endless supply of aid.

This is nothing more than integrated development, and it makes sense. But, as was predicted, and as some are now demonstrating, it did not work. In reviewing what happened in the Millennium Villages that led them to come up short of expectations, Gates notes

MVP leaders encouraged farmers to switch to a series of new crops that were in demand in richer countries – and experts on the ground did a good job of helping farmers to produce good crop yields by using fertilizer, irrigation, and better seeds. But the MVP didn’t simultaneously invest in developing markets for these crops. According to Munk, “Pineapple couldn’t be exported after all, because the cost of transport was far too high. There was no market for ginger, apparently. And despite some early interest from buyers in Japan, no one wanted banana flour.” The farmers grew the crops, but the buyers didn’t come.

But then Gates seems to glide over a really key question: how could a smart, well-intentioned man miss the mark like this? Worse, how could a leading economist’s project blow market engagement so badly? Gates’ throwaway argument is “Of course, Sachs knows that it’s critical to understand market dynamics; he’s one of the world’s smartest economists. But in the villages Munk profiled, Sachs seems to be wearing blinders.” This is not an explanation for what happened, as telling us Sachs suffered from blinders is simply restating the obvious. The real issue is the source of these blinders.

The answer is, to me, blindingly obvious. The MVP, like most development interventions, really never understood what was going on in the villages targeted for intervention. Sure, they catalogued behaviors, activities, and outcomes…but there was never any serious investigation into the logic of observed behaviors. Instead, the MVP, like most development interventions, was rife with assumptions about the motivations of those living in Millennium Villages that produced these observed activities and outcomes, assumptions that had little to do with the actual logic of behavior. The result was interventions that implicitly infantilized the Millennium villagers by providing interventions that implicitly assumed, for example, that the villagers had not considered the potential markets for new and different crops/products. Such interventions assume ignorance as the driver of observed behaviors, instead of the enormously complex decision-making that underlies everyday lives and livelihoods in even the smallest village.

To give you an idea of what I mean, take a look at the following illustrations of the complexity of livelihoods decision-making (these are from my forthcoming article on applying the Livelihoods as Intimate Government approach in Applied Geography – a preprint is here).

First, we have #1, which illustrates the causes behind observed decisions captured by most livelihoods frameworks. In short, this is what most contemporary development planning gets to, at best.

Figure 1

However, this is a very incomplete version of any individual’s decision-making reality. #2 illustrates the wider range of factors shaping observed decisions that become visible through multiscalar analysis that nests particular places in wider networks of economic, environment, and politics. Relatively few applications of livelihoods frameworks approach this level of complexity, and those that do tend to consider the impacts of markets on particular livelihoods and places.

Figure 2

While this is better than the overly-simplistic framing of decisions in #1, it is still incomplete because motivations are not, themselves, discrete. #3 illustrates the complex web of factors, local and extralocal, and the ways in which these factors play off of one another at multiple scales, different times, and in different situations.

Figure 3

When we seek to understand why people do what they do (and do not do other things), this is the complexity with which we must engage.

This is important, because were Gates to realize that this was the relevant point of both Munk’s book and his own op-ed, he might better understand why his own foundation has

many projects…that have come up short. It’s hard to deliver effective solutions, even when you plan for every potential contingency and unintended consequence. There is a natural tendency in almost any kind of investment – business, philanthropic, or otherwise – to double down in the face of difficulty. I’ve done it, and I think most other people have too.

So, what do you do? Well, we have an answer: The Livelihoods as Intimate Government approach we use at HURDL (publications here and here, with guidance documents coming later in the summer) charts an analytic path through this level of complexity. Before the usual objections start.

1) We can train people to do it (we are doing so in Mali as I write this). You don’t need a Ph.D. in anthropology to use our approach.

2) It does not take too much time. We can implement at least as fast as any survey process, and depending on spatial focus and resources, can move on a timeframe from weeks to two months.

3) It is not too expensive – qualitative researchers are not expensive, and we do not require high-end equipment to do our work.

The proof is in the reactions we are getting from our colleagues. Here in Mali, I now have colleagues from IER and agricultural extension getting fired up about our approach as they watch the data coming in during our pilot phase. They are stunned by how much data we can collect in a short period of time, and how relevant the data is to the questions at hand because we understand what people are already doing, and why they are doing it. By using this approach, and starting from the assumption that we must understand what people are doing and why before we move to interventions, we are going to lay the foundation for more productive interventions that minimize the sorts of “surprise” outcomes that Gates references as an explanation for project failure.

There are no more excuses for program and project design processes that employ the same limited methods and work from the same problematic assumptions – there are ways to do it differently. But until people like Gates and Sachs reframe their understanding of how development should work, development will continue to be plagued by surprises that aren’t all that surprising.

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.

I’m getting a bit better at updating my website…probably because I have more to update. Specifically, I’ve put up some new work on the publications page. There, you will find:

On the preprints page, I have two new pieces up:

Also be sure to check out the HURDL website. We’ve got new pubs up, and the last member of the lab (Bob Greeley) finally has a bio up!

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’ve always been a bit skeptical of development programs that claim to work on issues of environmental governance. Most donor-funded environmental governance work stems from concerns about issues like sustainability and climate change at the national to global scale. These are legitimate challenges that require attention. However, such programs often strike me as instances of thinking globally, but implementing locally (and ideally someplace else). You see, there are things that we in the wealthiest countries should be doing to mitigate climate change and make the world a more sustainable place. But they are inconvenient. They might cost us a bit of money. They might make us do a few things differently. So we complain about them, and they get implemented slowly, if ever.

Yet somehow we fail to see how this works in exactly the same manner when we implement programs that are, for example, aimed at the mitigation of climate change in the Global South. These programs tend to take away particular livelihoods activities and resources (such as cutting trees, burning charcoal, or fishing and hunting particular species), which is inconvenient, tends to reduce household access to food and income, and forces changes upon people – all of which they don’t really like. So it is sort of boggling to me that we are surprised when populations resist these programs and projects.

I’m on this topic because, while conducting preliminary fieldwork in Zambia’s Kazungula District last week, I had yet another experience of this problem. In the course of a broad conversation on livelihoods, vulnerabilities, and opportunities in his community, a senior man raised charcoal production as an alternative livelihood in the area (especially in the dry season, when there is little water for gardening/farming and no nearby source of fishing). Noting that charcoal production was strictly limited for purposes of limiting the impacts of climate change*, a rationale whose legitimacy he did not challenge, he complained that addressing the issue of charcoal production is not well understood or accepted by the local population. He argued that much of the governance associated with this effort consisted of agents of the state telling people “it’s an offense” and demanding they stop cutting trees and burning charcoal without explaining why it is an offense. He then pointed to one of his sons and said “how can you tell him ‘don’t cut this tree’? And his fields are flooding [thus destroying his crops, a key source of food and income].” But the quote that pulled it all together…

“Don’t make people be rude or be criminals. Give them a policy that will open them.”

The text is clear here: if you are going to take away a portion of our livelihoods for the sake of the environment, please give us an alternative so we can comply. This is obvious – and yet to this point I think the identification and implementation of alternative livelihoods in the context of environmental governance programs is, at best, uneven.

But the subtext might be more important: If you don’t give us an alternative, you make us into criminals because we will be forced to keep practicing these now-banned activities. And when that happens, we will never view the regulations or those that enforce them as legitimate. In other words, the way we tend to implement environmental governance programming undermines the legitimacy of the governance structures we are trying to put in place.

Oops.

The sad part is that there have been innumerable cases of just the phenomena I encountered last week at other times and in other places. They’ve been documented in reports and refereed publications. Hell, I’ve heard narratives like this in the course of my work in Ghana and Malawi. But environmental governance efforts continue to inadequately explain their rationales to the populations most affected by their implementation. They continue to take away livelihoods activities from those that need them most in the name of a greater good for which others pay no tangible price. And they continue to be surprised when people ignore the tenets of the program, and begin to question the legitimacy of any governance structure that would bring such rules into effect. Environmental governance is never going to work if it is the implementation of a “think globally, implement locally (ideally someplace else)” mentality. It has to be thought, understood, and legitimized in the place it will be implemented, or it will fail.

 

 

* Yes, he really said that, as did a lot of other people. The uniformity of that answer strikes me as the product of some sort of sensitization campaign that, to be honest, is pretty misplaced. There are good local environmental reasons for controlling deforestation, but the contribution of charcoal production to the global emissions budget is hilariously small.

First up on my week up update posts is a re-introduction to my reworked livelihoods approach. As some of you might remember, the formal academic publication laying out the theoretical basis for this approach came out in early 2013. This approach presented in the article is the conceptual foundation for much of the work we are doing in my lab. This pub is now up on my home page, via the link above or through a link on the publications page.

The premise behind this approach, and why I developed it in the first place, is simple. Most livelihoods approaches implicitly assume that the primary motivation for livelihoods decisions is the maximization of some sort of material return on that activity. Unfortunately, in almost all cases this is a massive oversimplification of livelihoods decision-making processes, and in many cases is fundamentally incorrect. Think about the number of livelihoods studies where there are many decisions or behaviors that seem illogical when held up to the logic of material maximization (which would be any good livelihoods study, really). We spend a lot of time trying to explain these decisions away (idiosyncrasy, incomplete information, etc.). But this makes no sense – if you are living on $1.25 a day, and you are illogical or otherwise making decisions against interest, you are likely dead. So there must be a logic behind these decisions, one that we must engage if we are to understand why people do what they do, and if we are to design and implement development interventions that are relevant to the needs of the global poor. My livelihoods approach provides a means of engaging with and explaining these behaviors built on explicit, testable framings of decision-making, locally-appropriate divisions of the population into relevant groupings (i.e. gender, age, class), and the consideration of factors from the local to the global scale.

The article is a straight-ahead academic piece – to be frank, the first half of the article is not that accessible to those without backgrounds in social theory and livelihoods studies. However, the second half of the article is a case study that lays out what the approach allows the user to see and explain, which should be of interest to most everyone who works with livelihoods approaches.

For those who would like a short primer on the approach and what it means in relatively plain English, I’ve put up a “top-line messages” document on the preprints page of my website.

Coming soon is an implementation piece that guides the user through the actual use of the approach. I field-tested the approach in Kaffrine, Senegal with one of my graduate students from May-July 2013. I am about to put the approach to work in a project with the Red Cross in the Zambezi Basin in Zambia next month. In short, this is not just a theoretical pipe dream – it is a real approach that works. In fact, the reason we are working with Red Cross is because Pablo Suarez of Boston University and the Red Cross Climate Centre read the academic piece and immediately grasped what it could do, and then reached out to me to bring me into one of their projects. The implementation piece is already fully drafted, but I am circulating it to a few people in the field to get feedback before I submit it for review or post it to the preprints page. I am hoping to have this up by the end of January.  Once that is out the door, I will look into building a toolkit for those who might be interested in using the approach.

I’m really excited by this approach, and the things that are emerging from it in different places (Mali, Zambia, and Senegal, at the moment). I would love feedback on the concept or its use – I’m not a defensive or possessive person when it comes to ideas, as I think debate and critique tend to make things stronger. The reason I am developing a new livelihoods approach is because the ones we have simply don’t explain the things we need to know, and the other tools of development research that dominate the field at the moment (i.e. RCTs) cannot address the complex, integrative questions that drive outcomes at the community level. So consider all of this a first draft, one that you can help bring to final polished form!

There is a lot of hue and cry about the issue of loss and damage at the current Conference of the Parties (COP-19). For those unfamiliar with the topic, in a nutshell the loss and damage discussion is one of attributing particular events and their impacts on poorer countries to climate variability and change that has, to this point, been largely driven by activities in the wealthier countries. At a basic level, this question makes sense and is, in the end, inevitable. Those who have contributed the most (and by the most, I mean nearly all) to the anthropogenic component of climate change are not experiencing the same level of impact from that climate change – either because they see fewer extreme events, more attenuated long-term trends, or simply have substantially greater capacity to manage individual events and adapt to longer-term changes. This is fundamentally unfair. But it is also a development challenge.

The more I work in this field, and the more I think about it, the more I am convinced that the future of development lies in creating the strong, stable foundations upon which individuals can innovate in locally-appropriate ways. These foundations are often tenuous in poorer countries, and the impacts of climate change and variability (mostly variability right now) certainly do not help. Most agrarian livelihoods systems I have worked with in sub-Saharan Africa are massively overbuilt to manage climate extremes (i.e. flood or drought) that, while infrequent, can be catastrophic. The result: in “good” or “normal” years, farmers are hedging away very significant portions of their agricultural production, through such decisions as the siting of farms, the choice of crops, or the choice of varieties. I’ve done a back-of-the-envelope calculation of this cost of hedging in the communities I’ve worked with in Ghana, and the range is between 6% and 22% of total agricultural production each year. That is, some of these farmers are losing 22% of their total production because they are unnecessarily siting their fields in places that will perform poorly in all but the most extreme (dry or wet) years. When you are living on the local equivalent of $1.25/day, this is a massive hit to one’s income, and without question a huge barrier to transformative local innovations. Finding ways to help minimize the cost of hedging, or the need for hedging, is critical to development in many parts of the Global South.

Therefore, a stream of finance attached to loss and damage could be a really big deal for those in the Global South, something perhaps as important as debt relief was to the MDRI countries. We need to sort out loss and damage. But NOT NOW.

Why not? Simply put, we don’t have the faintest idea what we are negotiating right now. The attribution of particular events to anthropogenic climate change and variability is inordinately difficult (it is somewhat easier for long-term trends, but this has its own problem – it takes decades to establish the trend). However, for loss and damage to work, we need this attribution, as it assigns responsibility for particular events and their costs to those who caused those events and costs. Also, we need means of measuring the actual costs of such events and trends – and we don’t have that locked down yet, either. This is both a technical and a political question: what can we measure, and how should we measure it is a technical question that remains unanswered. But what should we measure is a political question – just as certain economic stimuli have multiplier effects through an economy, disasters and long-term degradation have radiating “multipliers” through economies. Where do we stop counting the losses from an event or trend? We don’t have an answer to that, in part because we don’t yet have attribution, nor do we have the tools to measure costs even if we had attribution.

So, negotiating loss and damage now is a terrible idea. Rich countries could find themselves facing very large bills without the empirical evidence to justify the size of the bills or their responsibility for paying them – which will make such bills political nonstarters in rich countries. In short, this process has to deliver a bill that everyone agrees should be paid, and that the rich countries agree can be paid. At the same time, poorer countries need to be careful here – because we don’t have strong attribution or measurements of costs, there is a real risk that they could negotiate for too little – not enough to actually invest in the infrastructure and processes needed to ensure a strong foundation for local innovation. Either outcome would be a disaster. And these are the most likely outcomes of any negotiation conducted in blindly.

I’m glad loss and damage is on the table. I hope that more smart people start looking into it in their research and programs, and that we rapidly build an evidence base for attribution and costing. That, however, will take real investment by the richest countries (who can afford it), and that investment has not been forthcoming.  If we should be negotiating for anything right now, it should be for funds to push the frontiers of our knowledge of attribution and costing so that we can get to the table with evidence as soon as humanly possible.

I’ve been off the blog for a while now. OK, about two months, which is too long. The new semester, and a really large number of projects, has landed on me like an avalanche. I have a small lab that I now manage (the Humanitarian Response and Development Lab, HURDL), and while I am fortunate to have a bunch of really good students in that lab, I’ve never run a lab before (nor have I ever worked in someone else’s lab before). So figuring out how best to manage projects and personnel is a new challenge that eats up time. As I told my students, this is not a fully operational, efficient program that they have joined. It’s more like a car that has stalled, and every day I am pushing it along screaming “pop the clutch” at whoever is in the driver’s seat.  To follow the metaphor, there are a lot of fits and starts right now, but things are coming together.  Among them:

  • A report on gender and adaptation in agrarian settings for USAID’s Office of Gender Equality and Women’s Empowerment and the Office of Global Climate Change which, through both literature review and empirical example, is a first step toward thinking about and implementing much more complex ideas about gender in project design and evaluation. This report will spawn several related journal articles. Watch this space for both activities and publications.
  • A long-awaited report offering a detailed, if preliminary, assessment of the Mali Meteorological Service’s Agrometeorological Advisory Program. I started this project before I left USAID, but it is finally coming together. Again, a set of journal articles will come from this – our empirical basis alone is absurd (720 interviews, 144 focus groups, 36 villages covering most of Southern Mali).  There are going to be a lot of interesting lessons for those interested in providing weather and climate information to farmers in this report…
  • A white paper/refereed article laying out how to implement the Livelihoods as Governmentality (LAG) approach that I presented in this article earlier this year. It is one thing to present a reframing of livelihoods decision-making and the livelihoods approach, and another to make it implementable. One of my students and I piloted this approach over the summer in Senegal, and we are pulling it together for publication now.  This will become the core of some trainings that we are likely to be doing in 2014 as we start building capacity in various countries to conduct detailed livelihoods analyses that might inform project design.

Then there is work in Zambia with the Red Cross on anticipatory humanitarian assistance (focused on hydrometeorological hazards), and a new project as part of a rather huge consortium looking at migration as an adaptation strategy in deltas in several parts of the world.

Did I mention that it’s a small lab – me and three other students working on all of this? Yeah, we’re a little short-staffed. I’m supposed to have a postdoc/research associate on board to help as well, but there have been some contract challenges that have prevented me from advertising the position. I hope to have that out some time in the next month or two, ideally to bring someone on for a year, extendable if the funding comes through.  So if you are interested in gender and some combination of development, climate change adaptation, and disaster risk reduction/humanitarian assistance, and want to join a really outstanding group of people wired in to a lot of donors and partners, and working on projects that bring critical scholarship to the ground, let me know…

So that’s where I’ve been hiding. I am crawling out from under the rock, and hope to rejoin the blogosphere in a more active capacity in coming weeks. Thanks for your patience…

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.