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>>Hans Rosling: I'm just going to sum up a little, having listened to this. And I'm starting
where we were. Look at this graph. These are all the countries.
I have monies down here. $400, $4,000, $40,000. Remember, two zeros difference in income across
the countries of the world. Zeros in the end is the most important number on the paycheck.
Every agrees on that. The number -- which number is in the beginning
is not so important. It's the number of zeros you have which is important.
Here I have the proportion of young people. And we heard that the Arab world, not Africa,
had that amazing higher proportion. But what I want to compare is three countries
here: Denmark, Malaysia, South Africa, and Uganda.
And when you look at it today, it seems like South Africa, Malaysia, and Denmark are much
more similar because they have almost the same number of zeros on the paycheck. On the
average paycheck. But they're different types of paychecks in
South Africa, we heard. Whereas Uganda is quite low down here, and
yet we heard that the middle-income people start to grow very fast in Uganda.
This is one more of these things: You get the aggregate statistics, you have to drill
down. We have to even now -- from having just numbers
available, they must be available in a way we can understand it.
The first thing I do here is go into my favorite number of children per woman.
So I color by one number of children per woman. And look here. Where it's blue, it's where
there are 2.5, South. Africa, 2.5. South Africa is a world average. If someone
comes from outer space and wants to see "How are you living in the world? I just have half
a day to visit," let's send them down to South Africa because you have the whole stuff as
a representative sample down there, you know. Whereas here in Uganda, it's 5 to 6 children
per woman. Can you see that this group of countries,
about 16% of the world population, still have that big number of children?
And why children are not growing is because this group is compensated by so many countries
here that have less than 2 children per woman. Lowest of all, Hong Kong. One child per woman.
They were in a part of China where Mao Tse-tung never had a one-child policy.
But there's something special with that. Emerging markets get few children and really invest
in them. Here it's another situation. Yet you are right
that the middle class is growing very fast in Uganda.
So I have to drill down and I have to get this into income distributions.
Let me go over to look at this. This is yet another of these prototypes which
Daniel and Gapminder is working on, to go one step further from information in graphic
to understanding. Here's once more the income. A hundred dollars,
a thousand dollars, $10,000, $100,000. You see, when we have the income distribution
in people, we need four zeros to show the world.
Because there are some Donald Trumps over there, you know, which have quite a high income.
And there are -- in parts of East Nile, in northern Uganda, war-torn, very poor, you
have people all the way down there. So how can we make this world distribution
comprehensive? This is South Africa. The orange. You can
see South Africa in 1970, this is during apartheid, they covered the whole distance.
Amazingly, they covered it. This was Uganda. They were on the poorer side.
Malaysia was a little better here, but also a developing country.
And Denmark. I picked Denmark because it had a suitable size here, but it's just representative
of west Europe and it's over here, so we said this was the western world and this was the
developing world. But look what has happened. I'm going to gradually
change the income distribution on the world, and this is how it happens, and how countries
move. And you see average moving in some countries,
distribution moving in others, and then we end up here, and suddenly Malaysia moved over
from this end to that end. That very successful Muslim tropical country
has moved over here. And Denmark is here.
And within the distribution of South Africa, you have one Denmark, you have one Malaysia.
It's inside South Africa. Whereas Uganda goes largely outside, yet you
have the growing middle class here. Indeed, you have it. And it's growing fast, because
it comes from almost zero. It comes from almost zero. And they are really entrepreneurial.
But in East Nile up to what now will be southern Sudan, you know, you have dreadful poverty.
Take this segmentation into consideration when you draw conclusions.
Here, even people may not afford those cheap bed nets. You have to give them for free.
You have to give them for free. Here, you can start subsidizing them.
Here, people can pay for them entirely themselves. You have to think in segments. And we still
need aid and we need donations for free things over in this end.
Here people can run their own business. And both of these are within Uganda.
We have so interesting -- we have the software programs for the cell phone to collect survey
data, and one of my Ph.D. students became a professor in Norway. He applied to the Norwegian
Research Council for money to develop this. Not aid money; just pure research money. And
he outsourced it and his colleague, a professor in computer science in Kampala, is developing
with a fantastic group of software developers in Uganda, and they are now planning on how
they would put it. You can have so much in Uganda, but see how
many few Ugandans? There's no Donald Trump in Uganda yet. There's
no one who has made it all the way there. But in South Africa, there are people who
have made it sort of all the way. This is what I would like to leave you with.
This enormous distribution in the world. And don't think western world/developing world.
Don't think the world and sub-Saharan Africa. Don't think Uganda.
See all the different opportunities in the same time -- free bed nets, subsidized bed
nets, people can pay for their own bed nets -- within the same country.
And that means that we have to break down the data to make sense of it.
Thank you very much. [Applause]