Entries tagged with “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.

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.

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:

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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.

In the world of food security and agricultural development there is a tendency to see market integration as a panacea for problems of hunger (see Theme 2, point 4). There is ample evidence that market integration creates opportunities for farmers by connecting them to the vast sums of money at play in the global food markets. But there is equally ample evidence pointing to the fact that markets are never just a solution – negotiating global markets from the position of a small producer presents significant challenges such as the management of commodity price instability (without meaningful market leverage).  The academic side, and much of the implementation side, of the food security world already recognizes this issue, driven by (repeated) studies/experiences of food insecurity and famine showing that markets are nearly always the most important driver of this stress on the global poor. Planning for the benefits of market integration without serious thought about how to manage the potential downsides of markets is a recipe for disaster.

For example, simplifying one’s farm to focus on only a few key crops for which there is “comparative advantage”, and then using the proceeds to buy food, clothing, shelter and other necessities, works great when the market for those crops is strong. But what happens when the food you need to buy becomes more dear than the crops you are growing, for example through food price spikes or a shift in markets that leave one’s farm worth only a fraction of what is needed to feed and clothe one’s family? In the world’s poorest countries, where most food security and agricultural development work takes place, there is little capacity to provide safety nets to vulnerable citizens that might address such outcomes.

This is not a call for the provision of these safety nets (microinsurance is very interesting, but a long way from implementation).  While useful and, in some contexts, critical, they are, in the end, band-aids for a larger conceptual problem – the framing of market engagement as a panacea for the problems of agricultural development and food security.  Often, such programs also presume a lack of existing safety nets at the community or household level – a sort of “we can’t make things worse” mentality that marks much development thought. However, farmers in these countries have long operated without a state-level safety net. They hedge against all kinds of uncertainties, from the weather to markets.  For example, one form of hedging I have seen in my own work is an emphasis on growing a mix of crops that can be sold or eaten, depending on market and weather conditions.  If, in coastal Ghana, you are growing maize and cassava as your principal crops, you can sell both in years where the market is good, and you can eat both in years where the market turns on you. I have referred to opting out of markets as temporary deglobalization, where people opt in and out of markets as they gauge their risks and opportunities.

Forcing farmers away from this model, toward one that focuses on enhancing the economic efficiency of agricultural production by reducing the focus of a country and its farmers to a few crops that are their “comparative advantage”, and which they should sell to purchase the rest of their dietary needs, removes the option of turning away from markets and eating the crops in conditions of years where the markets are not favorable.  This is even more true when some of that newly reduced crop mix only takes value from sale on global markets (i.e. cocoa) and/or which cannot be eaten (i.e. cotton). In short, such restructuring in the name of economic efficiency makes people dependent on the political structures of the state that govern the markets in which they participate.  Most of our work takes place in the Global South, where the state rarely has the capacity to step in and help in times of crisis.  It is pretty easy to do the math here: done wrong, food security programs principally framed around ideas of economic efficiency can enhance state capacity to extract value from farmers without a comparable improvement in the delivery of services or safety nets.  This is an acceptable outcome if you are trying to compel people to submit to the state and the markets the state regulates, which is one way to boost measurable GDP and state revenue. However, it is really bad if you are actually trying to improve people’s food security.

The key points and principals here:

1)   Are you addressing food insecurity or strengthening the state’s capacity to raise revenue and measure economic activity? These are not the same thing – generally, they are at odds with one another, as making agricultural practice easier to see and measure only serves to improve the capacity to extract revenues from farmers, without any guarantee of improved services proceeding from those revenues.

2)   Economic efficiency is a desirable characteristic of agricultural livelihoods, but in the absence of safety nets cannot be the organizing principal of food security interventions. All else being equal, it is better when farmers use their scarce resources as efficiently as possible. However, the measurement of efficiency must take place within an assessment of the various risks currently managed through “inefficiencies” – as many such inefficiencies are in fact parts of robust, community- and household-level safety nets.

3)   Food security programming should be able to identify the difference between an inefficiency and a critical part of a community- or household-level safety net.  Regardless of the consequences for economic efficiency, programs and projects should not destabilize these until such time as new, reliable safety nets exist to take their place.

4)   Opting out is OK. Farmers should be allowed to structure their farms such that they can opt out of markets if things turn bad, even if this limits their total incomes in “good”/optimal years. This should not be assessed in terms of the average outcome, when best and worst cases are averaged.  Your best case is some more money. Your worst case is severe deprivation and death. These are not equal. Averting the latter is more important than achieving the former.

If food insecurity is not about global food shortages, what is it?  Following the a vast body of literature and experience addressing food insecurity, it is the outcome of a complex interplay between:

  • locally-accessible food production
  • local livelihoods options that might provide sufficient, reliable income or sources of food
  • local social relations (which mobilize and create social divisions by gender, class, age, etc.) which shape access to both livelihoods opportunities and available food within communities and even households
  • structures of governance and markets in which that production takes place
  • global markets for food and other commodities that can impinge on local pricing.

Changes in the natural environment play into this mix in that they generally impinge upon locally-accessible production and on global markets. The experience of the Famine Early Warning System Network (FEWS-NET) provides evidence to this effect.  FEWS-NET builds its forecasts through a consideration of all of these factors, and as it has gained resolution on things like local livelihoods activities and market pricing and functions, its predictive resolution has increased.

Despite decades of literature and body of experience to the contrary, it seems that the policy world, and indeed much development implementation, continues to view issues of hunger as the relatively straightforward outcome of production shortfalls that can be addressed through equally straightforward technical fixes ranging from changed farming techniques to new agricultural technologies such as GMOs.  This view is frustrating, given its persistence in the face of roughly five decades of project failures and ephemeral results that evaporated at the end of “successful” projects. More nuanced work has started to think about issues of production in concert with the distribution function of markets.  However, the bulk of policy and implementation along these lines couples the simplistic “technical fix” mentality of earlier work on food security with a sort of naïve market triumphalism that tends to focus on the possible benefits of market engagement with little mention or reasonable understanding of likely problematic outcomes.  Put another way, most of this thinking can be reduced to:

increased agricultural production = increased economic productivity = increased food security and decreased poverty

The problem with this equation is that the connection between agricultural productivity and economic growth is pretty variable/shaky in most places, and the connection between economic growth and any specific development outcome is shaky/nonexistent pretty much everywhere unless there has been careful work done to make sure that new income is mobilized in a specific manner that addresses the challenge at hand.  Most of the time, the food security via economic growth crowd has not done this last bit of legwork. In short, the mantra of “better technology and more markets” as currently manifest in policy circles is unlikely to advance the cause of food security and address global hunger any more effectively than prior interventions based on a version of the same mantra.

These issues present us with several key points about the problem we are trying to solve that should shape a general approach to food insecurity:

1)   Because food insecurity is the outcome of the complex interplay of many factors, sectoral approaches are doomed to failure.  At best, they will address a necessary but insufficient cause of the particular food insecurity issue at hand.  However, in leaving other key causes unaddressed, these partial solutions nearly always succumb to problems in the unaddressed causes.

2)   Production-led solutions will rarely, if ever, address enough significant causes of food insecurity to succeed.  Simply put, while production is a necessary part of understanding food insecurity, it is insufficient for explaining the causes of particular food insecurity situations, or identifying appropriate solutions for those situations.

3)   Increased production is not guaranteed to lead to economic growth. The crops at hand, who consumes them, the infrastructure for their transport, and national/global market conditions all shape this particular outcome, which can shift from season to season.

4)   Economic growth does not solve things magically. Even if you can generate economic growth through increased agricultural production, this does not mean you will be addressing food insecurity. Programs must think carefully about where the proceeds from this new economic growth will go in the economy and society at hand, and if/how those pathways will result in greater opportunity for the food insecurity.

5)   Embrace the fact complexity takes different forms in different places. In some places, markets will be a major cause of insecurity. In other places, environmental degradation might play this role. In still other places, failed governance will be the biggest issue driving food outcomes.  In nearly all cases, though, all three of these factors will be present, and accompanied by others.  Further, the form this insecurity takes will be highly variable within countries, provinces, districts, communities and even households, depending on the roles people play and the places in which they play them.  There is no good template in which to fit a particular case of food insecurity, just a lot of causal factors that require extensive teasing out if one hopes to explain food outcomes and therefore address the problem.