Response from Oxfam: Governance, land grabs and tricky statistics

by Ricardo Fuentes-Nieva and Marloes Nicholls

It is encouraging to read the post from Aid Thoughts. We appreciate the time he put into Oxfam’s analysis on large scale land deals. Indeed, we were hoping that our blog would spark debate and bring more attention to this topic.

As a quick summary, we took two databases, the Land Matrix and the World Governance Indicators and found that land deals are more likely to occur in countries with lower levels across different governance indicators.  We specified that “This analysis is only the first step towards a more in depth research project. Next steps include a more in depth analysis on the determinants of the number and location of deals

Aid Thoughts seems to take issue with the use of this kind of analysis when they are so preliminary. There are two things to say to this:  Firstly, and as Aid Thoughts acknowledges, there is other evidence in the development literature that points to the fact that land deals are concentrated in poorly governed countries. Our conclusions were not based only on our analysis and we used the best evidence at hand (both internal and external) to generate a better understanding of the problem (which Aid Thoughts actually helped with his critical review). So, we stand by our decision to publish the preliminary results.

Now, there are a couple of things to discuss on the technical front of his critique. Here are some:


1) Investors or governments?

AidThoughts replaces governance indicators with income per capita because they better explain the existence of land deals. This leads him to suggest that “Maybe investors aim for countries who are more willing to sell off land, not because they are poorly governed, but just because they are poor.” This is an interesting idea but if we put aside the regression tables and reflect for a moment, is it sensible to think that land investors are attracted to countries for being poor? Why would investors be attracted to the characteristics of poverty, such as poor infrastructure, limited public services and low levels of education and health? A more interesting hypothesis that AidThoughts raises, and which we think is worth exploring too, is that it might not  be investors who target countries, but bad governments who sell the land of their citizens.


2) Truncated sample bias.

AidThoughts recognizes that running OLS with two control variables, as reported in Table 3, is not serious analysis (and yet he managed to muddle the significance of the estimators in his table). But what’s really puzzling is that, in order to prove his point, he then goes on to throw the entire kitchen sink of governance indicators into the next table (Table 4). These indicators are highly correlated amongst them, and it is difficult to find a sensible explanation to specify the model that way.

He then goes on to say of this table:

“In column (1), prior controlling for income, only one of the relationships we expected to see has returned: countries rated low on the rule of law index are more likely to have land deals. Political stability/violence is also associated with land deals, but unfortunately that wasn’t part of Oxfam’s theoretical model. Now, voice and accountability is positively correlated with land deals! Of course, most of these relationships vanish when we toss in income, although it is worth noting that the rule of law measure keeps its significance and sign. So the relationship between governance and land sales seems to be a lot more complex than the Oxfam brief is suggesting.”

That’s a lot of explanation for a badly specified model that includes highly correlated regressors. But that’s not even the most puzzling part of that table. AidThoughts then tries to explain the number of land deals with the same variables but he does not correct for the truncated sample (look how his sample drops from 212 and 183 in the first two columns to just over 50 in the last two). Ignoring the bias in the observed sample is a mistake and something we had identified as a problem, and that’s why we suggested exploring  a double hurdle estimation to understand the issue better.


3) Reported land deals bias.

Aid Thoughts briefly mentions the potential problem of bias in the Land Matrix, but we don’t agree that he identified the right direction of bias. He argues that land deals are more likely to be reported in developing countries by diligent activists than in developed countries like the UK. On the contrary, we argue that land deals are much less likely to be ignored in richer countries with freer press, more access to information and better organized civil societies. Does Aid Thoughts seriously believe that a land deal can be more easily concealed in the UK than in the DRC?

Overall, we are very encouraged by Aid Thoughts’ response. He mentions that he can be convinced of the problem with more data and more, better data is on its way according to conversations we’ve had with the people managing the Land Matrix. So here’s our proposal for Matt: let’s work together – rigorously and objectively – on this issue in the next few months to try to better understand what’s driving the land rush. The problem deserves as much attention as we can give to it.

Land grabbing: whatever you do, don’t mention the G-word.

Large scale land purchases get some more media attention, this time from Jonathan Glennie over at The Guardian:

“A new report on land acquisition by the Munden Project/Rights and Resources Institute brings an important angle to the land “grab” debate. Rather than focusing on the ethics of land grabbing, the report makes the business case for working with local communities, arguing that failure to inform or fairly compensate affected locals heightens the risks to investors. Why? Because affected communities start to make life difficult for abusive or lazy companies, leading to massive unexpected costs or even an eventual full-scale retreat.

What is slightly disconcerting is that Glennie managed to write an entire article on land grabs while only using the world “government” once. NGOs and the media have largely painted the land grabbing story as a situation where evil companies are parachuting in and snatching land away (for example, check out Oxfam’s recent campaigning). In reality, land acquisitions which circumvent local property rights are only possible when governments themselves are incompetent, corrupt or overly-impatient. Of course campaigners realise this, but it’s much easier to set this up as story of evil capitalism than it is of governance, the latter being harder to sell and even harder to treat. I’m not trying to pick on Glennie for leaving out a lengthy discussion of governance in his article, but it would be nice for people to start using the g-word a bit more.

Governance, land grabs and tricky statistics


“I’m a family man- I run a family business. And I heard your town scored low on the World Bank’s governance indicators.”

The last decade has been marked by a sudden increase in large scale land purchases in developing countries, a `land rush’ which has purportedly been driven by concerns over food security, food prices and a growing market for biofuels. The speed, size and lack of transparency over many of these deals, as well as their implications for the welfare and food security of those already living on the land, has led many to dub these large scale purchases as “land grabs.” This is a rather loaded term, but has successfully (and unfortunately) framed the context as one where anonymous, uncaring investors are systematically snatching land away from the poor and needy.

News reports suggest that at least some of this is happening – following the excellent Let’s Talk Land Tanzania for just a few days reveals how problematic some of these purchases have been. Yet, despite the ruckus these deals are creating, we still know precious little about their size and scale, the motivations and expectations of investors, the welfare impact on those in “grabbed” countries and the welfare impact on those in “grabbing” countries.

This lack of knowledge should be alarming rather than disarming, but while this is the perfect time for careful, dispassionate analysis and data collection, many have chosen to instead reinforce the simple “good” vs “evil” story I highlighted above. Take, for instance, this media briefing which Oxfam released last week, based on preliminary research on the relationship between country governance and land deals.

The two Oxfam researchers, Ricardo Fuentes-Nieva and Marloes Nicholls, use data from the World Bank’s Worldwide Governance Indicators (WGI) and the Land Matrix, which gathers data on media reports of land deals, to show that countries that had any land deals between the years 2000 and 2011 had significantly lower WGI scores than those that hadn’t had any. Here is the figure which they use to make their case:


Again, this figure reveals that, across the four governance indicators considered by Fuentes-Neiva and Nicholls, countries with land deals consistently score worse than those without. How does Oxfam interpret these results?

Oxfam believes that investors actively target countries with weak governance in order to maximise profits and minimise red tape. Weak governance might enable this because it helps investors to sidestep costly and time-consuming rules and regulations, which, for example, might require them to consult with affected communities. Furthermore in countries where people are denied a voice, where business regulations are weak or non-existent, or where corruption is out of control it might be easier for investors to design the rules of the game to suit themselves.

So we have a pretty clear story here, right? Well, maybe not. Let me give a bit more structure to the above results by showing them as a series of bivariate regressions of the probability of observing a land deal in any given country between 2000 and 2011 and the average governance indicators for this period (the same data used in the Oxfam briefing).


Each column shows the results from regressing the probability of the country having at least one land deal during this period on each measure separately: voice and accountability, regulatory quality, rule of law and corruption (note that higher is `better’ for each of these measures). So far so good: in isolation, each of these variables is significantly* and negatively correlated with the probability of a land deal (i.e. countries that score poorly on each of these indicators individually are more likely to sell off land).

Yet, it’s a little strange that each of these seems to have about the same magnitude of an effect. We might expect some indicators to matter more. Also, for some reason, the Oxfam brief has left out two other WDI measures: political violence/stability and government effectiveness. Here is what the authors say about this exclusion:

Two of the Worldwide Governance Indicators – political stability and the absence of violence and government effectiveness were excluded from the analysis since there is no evident mechanism that would lead these aspects of governance to improve prospects for  investors.

OK – so we have a somewhat solid theoretical reason for excluding these variables. Presumably, we should not see the same negative correlation between these two WDI measures and land grabs. Table 2 below includes two extra columns in which I re-run the above results, but including both of the excluded indicators (PS and GE).

Continue reading

Bad things and the GDP fallacy

There are many who are (quite rightly) worried about whether or not economic growth is sustainable. This has led to a number of attacks on Gross Domestic Project (GDP) as a measure of economic progress. One of the arguments that is repeatedly made is that things that we, as a society, would consider to be bad, lead to an increase in measured GDP. Consider this video of Oxfam’s Katherine Trebeck (video starts at 3:50 – watch it for a minute):

Trebeck, who is arguing that disasters, both big and small, add to GDP, is quoting economist Mark Anielski:

The ideal economic or GDP hero is a chain-smoking terminal cancer patient going through an expensive divorce whose car is totalled in a 20-car pileup, while munching on fast-take-out-food and chatting on a cell phone. All add to GDP growth. The GDP villain is non-smoking, eats home-cooked wholesome meals and cycles to work.

I would write a long post on why this is a fundamentally misguided reading of GDP, but Alex Tabarrock has already done it more succinctly than I ever could:

Imagine that you are your friends are going to see a jazz concert but on your way to the concert you have a little disaster, a fender bender. Instead of seeing the show, you and your friends have a miserable time waiting for the tow truck to come to have your car fixed. Spending on the tow truck and the auto repair counts as GDP but it does not add to GDP because it is counter-balanced by a decrease in spending on jazz, wine and cheesecake. Nothing Tyler says (see above) about gross substitutability changes this fact.

Consider a bigger disaster, the 9/11 attack. First, the point already mentioned, the resources used in the cleanup count as GDP but don’t add to GDP to the extent that they would have been employed on other projects. Now it is true that some of the workers could work overtime which they otherwise would not – this would tend to increase measured GDP more than real GDP since leisure is not measured in the national income and product accounts. Even this factor, however, must be balanced against the overwhelming fact that the destruction of the twin towers meant that tens of thousands of the most productive people in the United States were forced into unemployment or death. Since GDP can also be measured as the sum of wages, rents, interest etc. the immediate effect of all the unemployed and dead was to reduce GDP. Similarly, Hurricane Katrina has destroyed more jobs in New Orleans than it has added (and not all the added jobs represent real additions) hence the Hurricane reduced measured and real GDP.

There’s probably little else that people (including economists and including me) get wrong more than trying to figure out what gets counted as GDP. Tabarrock hasn’t completely diverted worries though – he’s assuming the balance sheets cancel out immediately, when borrowing and saving comes into play, there is a lot of spending which goes towards bad things which, on a year-to-year basis, will look like GDP growth, where the “displacement” effect he discusses is divided over subsequent years. Also, GDP won’t accurately take into account global externalities. Finally, GDP itself will still comprise a lot of bad things at the end of the day (if the car crash is perfectly offset by a drop in spending on jazz and wine, nothing has changed).

Still, the point is that the standard “bad things increase GDP” argument doesn’t always work, once we begin to think the problem through a little more carefully.

Update: a friend replies over Twitter with

@aidthoughts and if the vegan cyclist consumes less expensive leisure and needs less income therefore works less hard and is just as happy?”

I give up, Aid Thoughts will endorse the Happy Planet Index from now on.

Aid as policy


“”The Empire is evil”? Don’t you realise what a silly statement that is? The Empire is actually a complex system of carefully targeted programmes and government departments. You should be asking specific questions like: “Is the Empire’s Death Star project effective at curbing population growth?””

Lee Crawfurd over at The Roving Bandit recently wrote a compelling post about why the question “Does aid work?” is fundamentally flawed.

The question “does policy work” is jarring, because we immediately realise that it makes little sense. Governments have about 20-30 different Ministries, which immediately implies at least 20-30 different areas of policy. Does which one work? We have health and education policy, infrastructure policy (roads, water, energy), trade policy, monetary policy, public financial management, employment policy, disaster response, financial sector policy, climate and environment policy, to name just a few. It makes very little sense to ask if they all collectively “work” or are “effective”. Foreign aid is similar. Aid supports all of these different areas of policy. My colleagues and I at OPM work on aid-financed projects that support most of these different policy areas in different developing countries.

Lee, as he admits himself, is taking his cue from the combined work of Esther Duflo, Abhijeet Banerjee and Dean Karlan. Some policy questions are becoming more and more answerable: does X work in a given context is something that can be tested and applied. Lee is asserting that since aid is just used to fund policies, thus the question of whether aid works just boils down to the complex task of determining whether or not individual policies work.

Yet, when you examine this assertion a little further, it starts to fall apart. Let’s imagine we lived in a world where we, development economists from aid-giving countries, figured out all the good government policies. We knew exactly which actions developing country governments needed to take to save children’s lives, promote income and job creation, reduce hunger and conflict and so on. In the world which Lee has presented to us, policy works, because we knew what all the best policies were. Would aid work?

It certainly wouldn’t be guaranteed to. Aid isn’t just policy – it’s the transfer of financial resources and technical expertise from one country or entity to another. That transfer is inherently non-trivial: it can create huge differences in power, has the potential to distort the recipient’s decision-making, creates opportunities for rent-seeking and often is used for completely political purposes. We cannot, for instance, only judge a US-funded conditional cash-transfer programme in Afghanistan solely on its microeconomic impact – it has to be viewed within the context of the US’s ongoing military intervention in that country, and its likelihood of long-term success. The recent scrap between Rwanda and its donors over the security situation across the border in the DRC again shows that aid is vastly more complicated than simply choosing effective programmes.

Lee acknowledges some of these differences and potential problems, but then dismisses them as things which are hard to gather robust evidence on. This preference to stick to what we know is somewhat admirable and tempting, but ultimately dangerous: it is incredibly difficult to gather widespread, robust evidence on the effects of aid on the macroeconomy or on local political economy. This should make us more, rather than less, wary of possible deleterious effects.

I’m as equally horrified as Lee by the recent attention that right-wing attacks on aid have been getting in the UK, and I completely agree with him that aid cannot always be  judged as a whole. The question, “does aid work?” doesn’t get us very far in life, especially since we have little concept as to what metric we should be using. That said, we have to tread carefully around the argument that small, neat questions are sufficient for success. I agree that aid should be considered more carefully as a bundle of heterogeneous flows and relationships, but I also believe that “aid” is unique in several key ways, and it is only healthy if we continuously question whether the the things that make aid unique also undermine its effectiveness.

How policies end: not with a bang, but a whimper

Masimba Tafirenyika describes how dire the food security situation in Malawi has become:

Once again Malawi finds itself in a tight spot. A food crisis set off by erratic rains, rising food prices and economic hardships is slowly unfolding. For the first time in several years, the country’s ability to feed its citizens is at risk. Sadly and unexpectedly, Malawi has lost its hard-earned status as an agricultural success story — it used to produce enough maize for its people to eat and still provide a surplus to neighbours. Many are now wondering what went wrong and whether there could be lessons for other African countries.

More than 1.63 million people, or 11 per cent of the population, are facing severe food shortages, according to the World Food Programme, a UN relief agency. Malawi needed $30 million to the end of 2012 to cover the shortfall.

As Tafirenyika hints, this stands in stark contrast to reporting on Malawi over the past few years, where it was heralded as a shining example of how to tackle food security. Five years, ago Celia Dugger wrote in the NYT how the country’s president, Bingu wa Mutharika, despite the protests of many, “ignored the experts” and subsequently dealt with the country’s hunger problems by drastically scaling up its fertiliser subsidy programme. Malawi subsequently enjoyed a spate of bumper harvests and many were quick to tout the large-scale subsidisation as being both a success and worth of replication in other countries. Most notable was the support of Jeffrey Sachs, who’s incessant belief that the fertiliser subsidisation was a policy holy grail led him to write an oddly-appreciative obituary for Mutharika, who died at the end of a thuggish, repressive and disastrous second term in office.

Meanwhile, hunger returns to Malawi, but we have not yet established a convincing narrative. Many economists (including a few on this blog) have pointed out, time and time again, that the fertiliser subsidy programme was fraught with pitfalls, both political and practical. While the recent crisis is probably too complex to fully substantiate these concerns, now would be an appropriate time for the fertiliser advocates to turn their attention to the food situation in Malawi, and begin to ask why. Otherwise, we risk touting a policy that might actually have been a complete failure, or at the very least lacked the sort of robustness that anti-hunger policies desperately need.

Ask not what your country can do for you


“Sorry Bilbo, I was going to take you on this *amazing adventure*, but then I checked your expenses from last year, and you seem to be spending your entire budget on food, not travelling.”

Economists can sometimes be a little sceptical of asking people what they want. If we’re trying to provide and finance a public good, for instance, we might be worried that beneficiaries will understate their value of that good to try and get away with paying less for it. Others – often those in the behavioural science camp – can be wary that people may not be reasonably informed as to what is good for them, or might let cognitive quirks and biases undermine their prioritisation.

Over at the African Can End Poverty blog, this scepticism seems to have been extended to Tanzanian businessmen, as Jacques Morisset argues that we should pay less attention to what local firms claim are policy priorities:

Allow me to illustrate. According to the entrepreneurs operating In Tanzania, electricity is their major constraint (85 per cent) followed by access to finance (52 per cent), taxes (37 per cent), and administrative red tape (25 per cent). Source: World Bank. Investment Climate Assessment, 2009. Surprisingly, labor and transports costs are only at the bottom of their concerns (less than 10 per cent). According to this ranking, the priority should be therefore given to reducing electricity costs, increasing access to finance and reducing taxation.

A closer look at the firms’ financial balance sheets provides a different picture. In reality, electricity counts for a marginal share of firms’ operating costs in Tanzania (see Figure). For example, it is equivalent to only 3 per cent for a standard firm operating in the apparel sector. In other words, a decline, say, of 50 per cent in electricity prices would only reduce its costs by 1.5 per cent – hardly a high number for such a big effort. By contrast, transport and labor costs are equivalent to 41 per cent and 38 per cent of its total operating costs. This means that reducing transport costs by only 4 per cent would achieve the same gains for the enterprise than cutting by half its energy costs.

I’m not entirely convinced by Morissets argument: he only presents data on the current breakdown of firm’s operating costs, but no evidence on how firm electricity usage might change if prices did come down. This is a little like arguing that that since poor, stunted children in a rural village only appear to consume maize, there’s little point in subsidising the cost of protein-rich foods.

Morisset admits that electricity access might be an issue, but then goes on to make his argumet based on the static view: that we should target inputs which are currently the most costly for Tanzanian firms. Perhaps this it the right course, but a difficult argument to make without more information on how firms change their behaviour when relative prices change.

Random thoughts left lying around

There has been much talk of economists starting up a trial registry for randomised interventions, or at least promoting the use of pre-analysis plans. One of the chief reasons for doing this is to curb data mining – if researchers make it clear up front which hypotheses they plan to test, this will reduce the incentive to report new results, discovered only after the researchers have had time to dig around.

While I think trial registries are worth a try, I have already discussed my worries their effects on the quantity of viable research (even if quality increases). These concerns aside, my question here is: why are trial registries primarily associated with randomised trials? Shouldn’t we also be moving to an equilibrium where all empirical research begins with a published pre-analysis plan?

I suppose the main hurdle is honesty here – for any dataset which already exists, it’s easy for me to download it, mine the data, then base my pre-analysis plan on empirical results I already know to exist. Furthermore, for any given dataset, the number of potential  hypotheses (and thus the number of pre-analysis plans which can be written by different researchers) is very large. This suggests that there is something special about writing a pre-analysis plan before the data is even collected, rather than before someone opens up Stata.

Ropey use of picture editor notwithstanding…

Here at Aid Thoughts, we tend to be on the cynical side of of the ‘blind optimism/dead-eyed cynicism’ divide that cleaves the development world (and there was a time when my professional responsibilities would not have prevented me from aiming a sharp, angry jab at certain famous development economists at this point).  One thing, though, that we have never disputed the value of, is having good, clever, questioning but ultimately hopeful people working day and night at unpicking all the difficult questions that we have to deal with on a daily basis.

So, it’s a pretty good thing that those four adjectives would be the first ones I choose when asked to describe Matt (well, okay, they’d come after ‘geek’ and ‘awesome’, but then they’re normally taken as read with him). So given that he’s got just 8 days before he submits his dphil and embarks on what will no doubt be a brilliant career, I’ve returned for one more Aid Thoughts post with a simple message for a change:

Matt, kick ass in your dphil and get a real job, you loafer. More people like you are needed.

Get your assumptions out in the open

Oxfam has just released a new report calling for a moratorium on land deals in developing countries. Well worth a look – this should be subject to a robust debate. Lacking the time for more substantive analysis* (see end), let me turn to comparative advantage and look a little closer at one their killer facts:

Indeed Oxfam’s calculations suggest that the land acquired between 2000 and 2010 has the potential to feed a billion people, equivalent to the number of people who currently go to bed hungry each night.

Sounds like a lot of people. The defence of this calculation is tucked away in the footnotes:

The country and area of individual land deals for the purposes of agriculture, forestry, and livestock, covering a total of 40.3 million ha, were obtained from (downloaded 25/07/12). The potential annual cereal production on acquired land was then calculated for each country by summing the product of the area of each deal and the average national cereal yield (data source: (downloaded 25/07/12)). The food energy available from the potential cereal harvest on acquired land in each country was calculated by multiplying the potential production volume by the kcal available from one tonne of cereal in the given country (obtained by dividing the annual food energy supply by the annual food supply quantity, in both cases for cereals excluding beer (data source: Ibid.)). The number of people that could potentially be fed from acquired land in each country was then calculated by dividing the potential annual supply of food energy by the product of 365 days and 1,800 kcal (the FAO’s global minimum daily energy requirement per capita). National totals were then summed to arrive at a global total. On the assumption that the vast majority of the land acquired in the past ten years could be used to grow food, whether or not investors intend to use it in that way, and that the publicly available data is a reasonably representative sample of the total database, a conservative estimation was made that if about 40 million ha could feed about 240 million people, then 203 million ha is likely to have the potential to feed more than 1 billion people

So there’s an assumption here that the land being sold could, if left alone, supply food with the same yield as current production in the country it was purchased. I think this depends on assumptions over the availability of labour to farm this land if it were left free and the marginal product of labour (i.e. would we expect average yields to increase if people left some farms to take up the free land). Oxfam seems to be relying on a pretty optimistic opportunity cost to these land deals – that the counter-factual is a world in which this land sprouts average yields instantly and international food distribution gets the food to the right people who need it.

Of course Oxfam’s calculations may not be considering the counter-factual of no land deals – instead they might just be pointing out the value of the land, in terms of feeding potential, is quite high. This notion is reinforced by the fact that a large chunk of the land deals are for the purpose of growing food to feed people in other countries. A debate about the impacts of these land deals should also consider the impacts on the hungry in investing countries, as they are part of this one billion figure. Anyway, I’d like to hear your comments about the underlying assumptions.

Klaus Deininger, Rabah Arezki and Harris Selod have a recent paper showing that land deals more likely to happen in countries with poor land governance and tenure security. While the Oxfam report does point this out, the violation of the rights and lack of compensation paid to displaced landholders might be a more solid starting point than numbers generated primarily to alarm people. Then again, I suppose that’s the goal of these reports.

*Apologies for the lack of posting – I’m currently in the last couple of months before submitting my PhD, so expect I’ll be able to return full-force by the end of the year.