The maps that lead to you

12 March 2015
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(Please excuse the cheesy Maroon 5 reference; I’m a devotee of terrible puns)

I’m trying to teach myself some new tricks so that I can be better at telling stories with data. I’ve been tinkering with QGIS, a free and open source geographic information system, or GIS. Basically, it’s a fantastic software tool that allows you to do things with maps.

You can get map data from different sources. I am using shapefiles that you can download from the Municipal Demarcation Board (MDB) website. The MDB is the best source of political maps: maps that show national, provincial, municipal and even ward boundaries. 

So, what happens when you run the shapefiles through the QGIS machine? Well, after a couple of weeks of trial and error, you can make a map like this:

South African municipalities, grouped by province

South African municipalities, grouped by province 

It’s not bad – the lurid purple I used for Limpopo could be toned down, but it’s reasonably pretty and not too hard on the eye. (There are web resources that will even help  you choose the best colour palette for your maps, which is something to consider as a next step.)

If you want to tell a story about the municipalities (or provinces) you need to add some data to your map – normally political, economic or development data. I used data from the National Treasury website, which is a great source of information for government finances.

I created a proxy for financial risk in municipalities using municipal budget data. I divided the revenue that municipalities receive from ‘Transfers and Subsidies’ by the total operating revenue. This percentage of total revenue is a measure of how dependent a municipality is on external revenue sources (which are usually transfers from national government).

Now, look at the same graph below, but with the municipalities coloured yellow, orange and red to show the increasing levels of financial risk:

Municipal grant dependency

Municipal grant dependency

Most municipalities derive less than half of their operating revenue from transfers and grants. They’re yellow, and most of the municipalities in Gauteng, the Western Cape and the Free State fall into this category.

Those municipalities which are moderately dependent on transfers get half to three-quarters (50 per cent to 75 per cent) of their operating budgets from grants. They’re coloured orange. The red municipalities depend on transfers for over three-quarters (75 per cent) of their budgets.

Most of these at-risk municipalities are in the Eastern Cape and KwaZulu-Natal, but every province except for Gauteng has at least one red or orange municipality. There are smaller pockets of orange and red in parts of the North-West, Limpopo and Mpumalanga.

There are other ways, maybe more accurate ways, of measuring financial risk in a municipality. But the pattern of the orange and red in this map is very similar to at least two other patterns.

Here’s the first similarity: I crunched some service delivery numbers in 2009 that measured trends in municipalities’ delivery of basic services (electricity, water, sanitation and rubbish removal). The data analysed then were the Census (2001) and Community Survey (2007), also at the municipal level.

I ranked the municipalities in terms of their provision of water and sanitation services. The 30 worst-performing municipalities , i.e. those with the lowest percentage of households receiving water and sanitation, were almost all from the Eastern Cape and KwaZulu-Natal. One or two were from Limpopo and the North-West. They were all the same culprits that I recently diagnosed with financial riskiness.

That’s not so unusual, I hear you say: we could assume that financial dependency and a service delivery backlog could go hand-in-hand. You are right, but here’s the third graph which sets the cat among the proverbial winged vermin:

Map of the old South Africa, with independent homelands

It’s not a complete match, but the resemblance is striking. Most of the Transkei, Ciskei and KwaZulu overlap those Eastern Cape and KwaZulu-Natal municipalities. It’s the same story with Bophuthatswana in the North-West and you can make an argument for Venda,Lebowa and KwaNdebele in Limpopo and Mpumalanga.

(The next step would be to superimpose the two maps, of course. Maybe that’s another post for another time.)

Let’s agree that this comparison can become very contentious very quickly. If this was a Buzzfeed article I would have led with ‘You Won’t Believe The Politically Explosive Comparison That This Nerdboy Made Between Different Maps’, but this isn’t Buzzfeed. We’re here for science, people. Science above all. Science and terrible puns.

I’m going to give you my opinion on the relationship, for what it’s worth, and hope that we can dodge any and all shitstorms, quagmires and red herrings in our discussion. We have to acknowledge the past and its effect on the present, but let’s do it in service of the future.

There is a big, fat link between the separate development under apartheid and the under-development of the independent homelands. I’m not here to name names. Let’s acknowledge the link, and try and understand it in a constructive way.

I saw the link between the last map and the poor provision of water and sanitation when I first did the research. I thought: why were these municipalities still so bad in 2001 and 2007? Overall, the Department of Water Affairs and Forestry did a lot to reduce service backlogs around that time. The department was headed by Ronnie Kasrils between 1999 and 2004 when the biggest reduction in backlogs was reported. How did these municipalities manage to fall through the cracks?

My theory then (and now) is that it was easiest to clear the backlogs in urban and peri-urban areas, around the metros and the larger local municipalities. There was a good infrastructure base already in existence in these municipalities, with a tax base to maintain and expand infrastructure where needed. The larger townships in these municipalities that were under-serviced in 1994 were high-density and close to the existing infrastructure.

The backlogs in the larger municipalities were the low-hanging fruit for national government. I would have spent the budget in a similar way if I were Kasrils, trying for the biggest bang for the taxpayers’ buck.

How does my theory tie in to the graph on financial dependence? Does it suggest that the independent homelands didn’t have robust, functioning economic nodes? Does it say anything politically about these areas?

I only took history up to Standard 7 so I’m not an expert on these matters. Here are some of my thoughts on the high-risk/low-performing municipalities:

  • Many  score poorly in terms of political stability: they don’t have permanent executive staff and some have been under administration;
  • Post-1994, they seem to have low-priority status for national and provincial government. Alternatively, their backlogs were just too big to eradicate in a decade or so; and
  • I should investigate the previous point and not make baseless accusations.

What do you think? What would you like to add to the story? What do we do to make the next chapter a better one?

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2 thoughts on “The maps that lead to you

  1. Mariana Tomalin

    Hi I was wondering if you perhaps have the shape files for the old homelands, please or do you only have the map?. We are working on a coastal mapping project and the shape files will be useful to track land owners changes.

    Reply
    1. Admin Post author

      Hi Mariana

      I don’t have them. The Demarcation Board might. I will ask around and see if I can help.

      Paul

      Reply

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