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  • 10 mins
  • Level 1: Introductory

Why Poverty: The Great Land Rush

Updated Thursday 6th September 2012

Get insights into different approaches to food security and land rights in Africa and other nations in this video


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There’s a powerful story to be told about the conflict over land between the Malian government backed by powerful agro business interests and small rice farmers.  At the core of this struggle is a common theme, it’s what should be prioritised, development for the many or the rights of the few?  The agro businesses flocking to Mali are producing sugar cane and biofuels for export, but the Malian government will benefit from the rents from the land, which can be used to develop the country most particularly to overcome food insecurity for the many.  In this video we’ll frame the conflict in terms of food security for the many or land rights for the few.

To explore and debate this theme through the UN Development Programme’s Explorer tool we need a data variable that can represent food insecurity and another to represent land rights.  Looking at the data variables on the UN DP site there is no data for food insecurity and land rights, so we’ll have to use a proxy variable.  A proxy is a data variable that can stand in for the data we want that’s a close match.  Let’s start by selecting under-5 mortality rate to stand in for food insecurity, because lack of food hits the young hard.  If there is food insecurity it’s often the young who are the first to succumb.  I’ve chosen the percentage of the population that are urbanised as the proxy for land rights, because where land rights are insecure farmers and their families often move to the cities to find alternative livelihoods.

Now let’s run the animation which allows us to track the changes for all countries from 1980 to 2009.  The first thing to notice when watching the animation is that the points move right and downwards.  This means that between 1980 and 2009 under-5 mortality rates fell, the downward shift, and the percentage of population urbanised increased, the rightward shift.  The second thing to notice is that in 1980 when the animation starts the countries were more spread along a rough line from the top of the Y axis to the end of the X axis.  This means there were greater differences among the countries for under-5 mortality rate and percentage of population urbanised as the points were not tightly clustered.  At the end of the animation in 2009 most of the countries are clustered towards the bottom suggesting they’ve successfully reduced their under-5 mortality rate to a level they can’t easily bring down further, but there is still great variance in how urbanised their populations are.

The relationship between under-5 mortality rate and percentage of the population urbanised is stronger now, because the points are tighter together.  But we can’t say that a drop in the under-5 mortality rate causes greater urbanisation or that greater urbanisation causes the under-5 mortality rate to fall.  It could be down to chance.  We don’t have enough evidence based on the two indicators plotted in the diagram to establish a cause and effect relationship.  What we can say is that there is a relationship between the two variables.  Let’s drill down now to look at Mali.  By placing the cursor on a point the name of the country will appear.  We can highlight Mali.  The size of the points is dependent on the population of that country and the colour relates to the level of human development in that country,  with red most developed and blue least developed, which we will consider shortly.  Let’s run the animation again and this time concentrate on Mali.

We see that Mali’s under-5 mortality rate drops from 299 to 199.  Similarly the percentage of Mali’s population that are urbanised rises from 18.5% to 43.7%.  Another way we can explore the theme of development of the many or rights for the few is by looking at the pressing need for development more broadly within Mali.  One of the most widely used indicators for the level of development in a country is the Human Development Index.  The Human Development Index (HDI) measures the average achievements of a country in health, education and income.  The data from the three dimensions, health, education and income, is merged to produce one value for each country.  The scores range from zero to one.  A country with a poor HDI or poor human development will be nearer zero and a country with a good HDI or good human development will be nearer one.  We can see how Mali fares against all other countries now.  Each coloured line represents a country, with Mali the heavy orange line.  As you can see Mali scores quite poorly for HDI, which is shown in the first line graph.  With the other three graphs breaking HDI into its component indicators: health, education and income.  Development is very pressing in Mali.

Finding a way to look more closely at rights in Mali is more difficult, but perhaps one indicator could be the ratio of women to men in the parliament or legislature of the country.  This is because the participation of women in a society can provide a gauge on the observance of human rights more generally.  The ratio of women to men in the parliament is one window on this.  What we see is that the female/male ratio in the Malian parliament over the first 11 years of the new millennium has marginally worsened.  In 2011 only one in ten members of the parliament were women.  This means that women play a marginal role in the Malian parliament, which suggests that women’s rights are not robust in the country.  We can infer that other rights are likely to be similarly weakly defended.

While our data story hasn’t provided a definitive answer it’s demonstrated that Mali is in great need of development, that fewer people are dependent upon the land for their livelihoods now and that women play a very small role relative to men in the running of the country.  It appears the Malian government does attempt to prioritise the many over the few to deliver increasing development.  It demonstrates that development can be both positive and negative bringing benefits for some and harm to others.

What do you think about the insights revealed by these stats?  Visit the OpenLearn site to share your views and see credits and links for all sources used in this video.




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