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).


This is somewhat perplexing – `we’ have no theoretical basis for why political stability or government effectiveness, yet we see the same negative correlation for these two measures, indicating that countries that score poorly on these are also more likely to sell off land. At this point, one begins to wonder if there isn’t something else driving this relationship, something other than measures of poor government. Given the set of countries we are comparing include rich OECD countries like the United Kingdom and the US, perhaps we aren’t really picking up a relationship with bad governance, but something else, such as national income (a typical omitted variable bias problem).


Table 3 repeats the same specifications in Table 2, but this time including  the log of average per capita GDP (over the same time period) as a control. Note how none* of the WDI indicators are significantly correlated with the probability of selling land once we’ve accounted for national income. 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.

Obviously, running OLS regressions with a single control isn’t really serious analysis, but I’m just trying to demonstrate that killer facts which are based off of simple correlations can be incredibly misleading. To further illustrate this, let’s get a tiny bit more complex and roll all of these indicators into the same model and see what happens:


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. Yet, perhaps we’re not doing ourselves any favours by comparing countries who choose to sell land to those that don’t. Why don’t we examine how many land deals occurred for countries that decided to sell land?  Columns (3) and (4) show the results of regressing the number of land deals in the 2000-2011 period on our measures of governance and income, restricting the sample to countries that had at least one land deal (the second part of a hurdle/selection model). No significant relationship appears to hold. This is strange – if we expected investors to actively target a group of countries with poor governance, we would also expect investors to discern between these countries when choosing where to invest.

I’m sure you can find many ways to criticize the oversimplified approach I’ve taken here.** That’s fine – this is the point of this whole exercise – statements like “investors are actively targeting governance-poor countries” requires a substantially more nuanced analysis than what has been provided by the Oxfam team. To be fair, Fuentes-Neiva and Nicholls state that they plan to take this analysis further, although they might have held off on releasing an alarming “media briefing” until after they had done this.

The hypothesis that investors are targeting countries with less regard for local property rights is not a crazy one. It has been suggested before in an empirical study by Rabah Arezki, Klaus Deininger and Harris Selod, using the GRAIN database of land deals. However, even Deininger et al. hesitate to put too much emphasis on this result, admitting they are dealing primarily with correlation rather than causation:

Although more detailed work at project level would be required to establish a causal link, a correlation along these lines suggests that, for much of the investment demand considered here, long-term security of tenure has been less of a concern for investors.

There is a reason that these authors are being cautious: conventional wisdom suggests that investors are risk averse enough to avoid countries where property rights are weak or uncertain. If it is so easy for investors to collude with dodgy governments to expropriate local land, it should be equally easy for these same dodgy governments to renege on their promises and take back the land at any point in time.

While Arezki, Deininger and Selod are rightly pointing out that the negative correlation between land governance and investment suggests that these concerns are not at play, it doesn’t guarantee that investors are actively seeking out poorly-governed countries. If we imagined a very simple world where investors chose countries at random to target, it is inevitable that countries with governments that show little concern for local property rights are going to be the first ones to secure a deal.

Furthermore, the same negative correlations in the Oxfam study hold when we consider only local deals (land acquisitions by firms in the same country they operate) rather than transnational deals. This suggests that correlations between land deals (which, I should reiterate, are not consistent in the Oxfam study) and governance are more about dodgy governments supplying land to investors rather than investors travelling to countries with dodgy governments.

Finally, we haven’t talked about the biases of the Land Matrix itself – while we might expect a diligent activist to record a local land deal in the Philippines, is anyone bothering to do the same for the UK? A simple measure of “are there any large scale land deals taking place?” might just be picking up “is your country one which people are bothering to record things in the Land Matrix?”.

The land rush certainly deserves our attention and concern just as much as Oxfam is suggesting, but we should be cautious when simple statistics are used to promote complex and potentially-misleading stories. Is it possible that investors are actively targeting countries with poor land governance? That’s something I could be convinced of with the right data, but certainly not with the analysis that has been presented here.

When I have some more time, I’ll try and take Oxfam’s analysis a little further and exploit the dynamic nature of the Land Matrix/WGI data to see how land deals change over time.

The .do file I used for the above tables is here. The WGI data I used is here. The specific Land Matrix data I used is here.

*See below

**I should note that the above results stand up to alternate specifications (probit) – keep sample sizes constant, and alternate ways of measure the number of deals (total or log) and income. 


Edit: Thanks to a coding mistake, the tables mis-report the significance levels of the coefficients. Instead of one star being the 10% level, one star is actually the 5% level, and so on. This doesn’t qualitatively change the results, although it is worth nothing that in Table 3 both regulatory quality (RQ), political violence (PV) and government effectiveness (GE) are significant at the 10% level. I’ll fix this later.

3 thoughts on “Governance, land grabs and tricky statistics

  1. Sam Gardner

    February 14, 2013 at 10:44pm

    If the property rights after land grabs are not secure (and probably they are not) than the selling of the land boils down to a stupidity tax, with additional negative effects for the people living now on the land.

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    March 1, 2013 at 8:27am

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