Livelihoods


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.

Over the past year, I’ve been working with Mary Thompson (one of my now-former students – well done, Dr. Thompson) on a report for USAID that explores how the Agency, and indeed development more broadly, approaches the issue of gender and adaptation in agrarian settings. The report was an idea that was hatched back when I was still at USAID. Basically, I noticed that most gender assessments seemed to start with a general “there are men, and there are women, and they are different, so we should assess that” approach. This binary approach is really problematic for several reasons.

  • First, not all women (or men) are the same – a wealthy woman is likely have different experiences and opportunities than a poor woman, for example. Lumping all women together obscures these important differences.
  • Second, different aspects of one’s identity matter more or less, depending on the situation. To understand the decisions I make in my daily life, you would have to account for the fact that sometimes my decisions are shaped by the fact I am professor (such as when I am in the classroom), and other times where what I do is influenced by my role as a father. In both cases, I am still a man – but I occupy two different identity spaces, where my gender might not be as important as my profession or my status as a (somewhat) responsible adult in the house.
  • Third, this approach assumes that there are gendered differences in the context of adaptation to climate change and variability in all situations. While there are often important gendered differences in exposure, sensitivity, and adaptive capacity in relation to the impacts of climate change and variability, this is not always the case.

My colleagues in both the Office of Gender Equality and Women’s Empowerment (GENDEV) and the Office of Global Climate Change agreed that these issues were problematic. They enthusiastically supported an effort to assess the current state of knowledge on gender and adaptation, and to illustrate the importance of doing gender differently through case studies.

Mary and I reviewed the existing literature on gender and adaptation in agrarian settings, exploring how the issue has been addressed in the past. We also focused on a small emerging literature in adaptation that takes a more productive approach to gender that acknowledges and wrestles with the fact that gender roles really take much of their meaning, responsibilities, and expectations from the intersection of gender and other social categories (especially age, ethnicity, and livelihood/class). You can find a first version of this review in the annex of the report. However, Mary and I substantially revised and expanded this literature review for an article now in press at Geography Compass. A preprint version is available on the preprints page of my website.

The bulk of the report – and the part probably of greatest interest to most of my readers – are three case studies that empirically illustrate how taking a binary approach to gender makes it very difficult to identify some of the most vulnerable people in a given place or community, and therefore very different to understand their particular challenges and opportunities. These cases are drawn from my research in Ghana and Mali, and Mary’s dissertation work in Malawi. They make a powerful case for doing gender assessments differently.

This report is not the end of the story – my lab and I are still working with GENDEV and the Office of Global Climate Change at USAID, now identifying missions with adaptation projects that will allow us to implement parallel gender assessments taking a more complex approach to the issue. We hope to demonstrate to these missions the amount of important information generated by this more complex approach, show that greater complexity does not have to result in huge delays in project design or implementation, and ideally influence their project design and implementation such that these projects result in better outcomes.

More to come…

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.

CGD has an interesting short essay up, written by Matthew Darling, Saugato Datta, and Sendhil Mullainathan, entitled “The Nature of the BEast: What Behavioral Economics Is Not.” The piece aims to dispel a few myths about behavioral economics, while offering a quick summary of what this field is, and what its goals are. I’ve been looking around for a good short primer on BE, and so I had high hopes for this piece…unfortunately, for two reasons the piece did not live up to expectations.

First, the authors tie themselves in a strange knot as they try to argue that behavioral economics is not about controlling behavior. While they note that BE studies and tools could be used to nudge human behavior in particular directions, they argue that “What distinguishes the behavioral toolset [from those of marketers, for example], however, is that so many of the tools are about helping people to make the choices that they themselves want to make.” This claim sidesteps a very important question: how do we know what choices they want to make? What we see as problematic livelihoods outcomes might not, in fact, be all that problematic to those living those outcomes, and indeed might have local rationales that are quite reasonable. While this might seem an obvious point, most BE work that I have seen seems to rest on a near-total lack of understanding of why those under investigation engage in the behaviors that “require explanation”. Therefore, the claim that BE helps people make the choices they want to make is, in fact, rather patriarchal in that the determination of what choices people want to make does not rest with those people, but with the behavioral economist. Sadly, this is a fairly accurate representation of much work done under the heading of BE. It would have been better if the authors had simply pointed out that BE is no more obsessed with incentives than any other part of economics, and if people are worried about behavioral control, they’d best have a look at the US (or their own national) tax code and focus their anxiety there.

Second, the authors argue “Behavioral economics differs from standard economics in that it uses a more realistic (and more complicated) model for people [and their decisions].” Honestly, I have seen no evidence for a coherent model of humans or their behavior in BE. What I have seen is a lot of rigorous data collection, the results of which are then shoehorned into some sort of implicit explanatory framework laden with unexamined assumptions that generally do not hold in the real world. Rigorously identifying when particular stimuli result in different behaviors is not the same thing as explaining how those stimuli bring about those behaviors. BE is rather good at the former, and not very good at all at the latter. The authors are right – we need more realistic and complicated models of human decision-making, and there are some out there (for example, see here and here – email me if you need a copy of either .pdf). BE would do well to actually read something outside of economics if it is serious about this goal. There are a couple of disciplines out there (for example, anthropology, geography, some aspects of sociology and social history) that have long operated with complex framings of human behavior, and have already derived many of the lessons that BE is just now (re)discovering. In this light, then, this short paper does show us what BE isn’t: it isn’t anthropology, geography, or any other social science that has already engaged the same questions as BE, but with more complex framings of human behavior and more rigorous interpretations of observed outcomes. And if it isn’t that, what exactly is the point of this field of inquiry?

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…

Development and humanitarian assistance have, over their respective histories, attracted rather substantial literatures. The percentage of that literature I might call “accessible” to the general public is quite small, and much of that popular literature does very little to convey the experience of working in these fields (indeed, very little of the literature in general accomplishes this)*. In 2010, after 13 years of studying development and development issues as an academic, I joined USAID in a policy position. It took only a few days for me to realize that I had no idea what was going on, what motivated decisions within the Agency, and what it actually meant to do development and humanitarian assistance. Nothing in my reading (and I am an academic, so it was a lot of reading) had prepared me for this experience.

In retrospect, it is too bad Missionary, Mercenary, Mystic, Misfit had not yet been written before I went to USAID, but I suspect that even if it had been I would not have read it (academic snobbery and all). This would have been a mistake.  MMMM presents a compelling, accurate feel for what it is to be a part of the development and humanitarian assistance industry.  While J’s attention to detail is striking (for those of us in the industry, this accuracy can draw us in but also make us grumpy, as more than once I found myself muttering something about a particular meeting or document described in MMMM), he works in a lot of real material into an interesting, compelling read. In short, this book accomplishes something remarkable: I can recommend it to not only to anyone who thinks that humanitarian assistance or development looks like a good career path, but also to anyone who needs a good beach read this summer. Take that, Jeff Sachs, et. al.…

Set in Bur Amina, Ethiopia, MMMM traces J’s protagonist, Mary-Ann, through the twists and turns of delivering humanitarian assistance to refugees near the Ethiopia/Somalia border.  The plot moves Mary-Ann through different positions in her small NGO, accurately conveying how abruptly one’s life and position can change in this world…and also (perhaps inadvertently) demonstrates one of the most important lessons of any career: competence is in much shorter supply than most people realize, and if you are good at your job people will notice. At the same time, J lays out the jockeying of assistance organizations in the context of a humanitarian crisis, and the challenges of balancing the goal of helping the world’s most vulnerable with the institutional imperatives of budgeting, fundraising, and surviving.  Even the most careerist and craven of the characters in MMMM is understandable and relatable – the reader can understand why they are pushing for a particular project or outcome, even as the reader loathes them for it.  Perhaps this is why Soledad Muñiz Nautiyal, in her review of the book, noted “the book presents ‘the good, the bad and the ugly’ of the aid industry without ever adopting a cynical perspective, and merely acts as an observer of a complex picture”.  This perspective, which permeates MMMM, makes the world of compromise that is humanitarian assistance palatable.  As the book so effectively conveys, too much idealism can render you irrelevant and ineffective.  Some readers may hate this lesson and perspective. If so, you will probably hate the real world of humanitarian assistance.

The reliability of even J’s loathsome characters leads to my next major point about MMMM.  In this book, J addresses my principal critique of his first effort, Disastrous Passion.  In Disastrous Passion, I felt that J created well-rounded, interesting humanitarian assistance characters, but many of the ancillary characters felt like caricatures.  This, perhaps, was a product of J failing to live by the first rule of so many writers: write what you know. In Disastrous Passion, I felt like I knew the characters that worked for the various donors and agencies in Haiti, but the ancillary characters felt a bit like unwanted interlopers.  In MMMM, even the ancillary characters are better-rounded, and I was drawn in by them. I had exactly one moment in the book that I felt was too shallow – when the protagonist has to address a problematic personnel issue (trying to avoid spoilers here), J never explains the motivations of the problematic person. Now, on one had I must say that this reflect reality – sometimes people do things that are inexplicable. It is a frustration the real world hands us. But somehow, in the context of MMMM, this made that character feel a bit shallow – like a plot device that allowed us to see another stressor in Mary-Ann’s life.  And while I did note that the character of Jon is, in many ways, the oracle of J in the narrative, unlike Dave Algoso I did not find this intrusive or slow reading. Instead, I thought these passages tended to crystallize the many plotlines J traces at various points in the book without having to abandon the narrative

I really enjoyed the book. It was a quick read, and one that I found difficult to put down. It was interesting, the plot very believable, the characters relatable, and the lessons (both overt and subtle) worthwhile. Whether or not you want to go into development or humanitarian assistance as a career, if you care about global poverty and want to better understand just how difficult this work really is – and you want to understand the real reasons why it is so difficult – then go get your copy of Missionary, Mercenary, Mystic, Misfit. It is well worth the read.

 

Buy it here:

Find a set of pictures that inspired details from MMMM on the book’s Facebook page here.

 

 

 

 

*I feel compelled here to note that John Perkins’ Confessions of an Economic Hit Man is just awful. I can’t speak to the veracity of his firsthand accounts, but his reading of institutional motivations and processes is beyond poor. Seriously, don’t waste your time…

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.

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