Lesson video

Hello, geographers.

My name is Mrs. Griffiths and today's lesson is called, "Measuring Development".

So we're gonna be thinking about different measures of development, both social and economic, thinking about their pros and cons and also considering whether one measure of development is really enough or whether we need to use a combination of them.

So let's get started.

And our outcome for today is, I can understand the different ways in which social and economic development is measured and the limitations of individual economic and social measures used.

So that's what I want you to be able to say by the end of the lesson.

So we have some keywords here, like development, the progress of a country in terms of wealth, use of technology and human welfare, gross national income, GNI, which is a measure of goods and services produced by a country including income earned abroad, which may be divided by the total population to give GNI per head.

Life expectancy, average number of years an individual can expect to live at birth.

Worldwide, this doubled from 1900 to 2021.

Human development index, a UN measure of development calculated using education, life expectancy and income data.

So look out for those keywords or key terms within our lesson.

How is our lesson structured today? Well, it has three parts.

Firstly, how useful is average income? Secondly, what do social measures of development tell us? And thirdly, which measures help us understand inequality? So firstly, how useful is average income? Development is the progress of a country in terms of wealth, use of technology and human welfare.

And if we look at this definition, it includes social as well as economic progress.

It reflects the fact that quality of life is as important as the growth of an economy or arguably more important given the purpose of growth is surely to make people's lives better.

There are global variations in social and economic development and a range of indicators may be used to measure development, including income.

How does income vary around the world? Well, here we have a map of World Bank income groups.

Now, as shown on this map, the World Bank classifies countries by gross national income, GNI per head, which is a measure of goods and services produced by a country and also, it's divided by the population of that country, which is why we have this idea of per head.

And we can see there are four different income groups that are mapped here by colour.

How does the world bank break these countries across the world down into four groups? Let's have a look at what those groups are.

So you can see these groups are organised by GNI per head and I can see in brackets we've got dollars PPP.

So what's that all about? So PPP means purchasing power parity.

Incomes have been adjusted to reflect the local cost of a standard basket of goods.

So that means comparison across countries of income is fair.

What do you notice about the pattern of income distribution? Well, I've added the equator here to the map to get you thinking about distribution.

Now, you might tell me that high income countries appear to be more in the Northern Hemisphere, though not exclusively in the Northern Hemisphere if we look at say Australia and New Zealand or Chile and Uruguay in South America.

You might also tell me that low income countries are concentrated in regions of Central, Eastern and Western Africa.

But I would say to you also, are there any issues with using this map to find out about economic development? And my hint is, it uses two colour families if you like.

So you've got the green family and the purple family.

The world appears to, at first glance, be divided into two groups.

So the rich green group and the poor purple group.

Why is this a bit misleading? Well, almost half of all countries are in fact classified as middle income countries by the World Bank.

So they're either lower middle income or they're upper middle income.

These countries are home to three quarters of the global population.

Is there also an issue with using GNI per head as a measure of wealth of countries worldwide? What do you think? Well, this is how it's calculated, isn't it? Gross national income divided by total population.

Using the mean average as a measure of a country's income may be misleading.

It doesn't tell us anything about how a country's income is actually distributed within that population, so between its people.

So maybe that's not telling us very much about income development and perhaps what percentage of the population is living on the poverty line.

We don't know what's going on within each country.

So check for you here.

Gross national income per head is calculated by dividing the income of a country by its population.

What type of average is this? And if you said it's the mean, well done.

True or false, the map of GNI per head shows us that the world divides into two categories, rich and poor.

Is that true or false? And if you said false, can you explain your answer? The answer we had was that World Bank uses GNI per head to categorise countries into four groups, high income, upper middle income, lower middle income and low income.

Three quarters of the global population lives in a middle income country.

So it's a gross simplification to talk about just rich and poor.

Two practise tasks for you then.

Can you calculate how many times larger the GNI per head is in Sweden than in Indonesia? And you've got a table of data there to use.

Secondly, how useful is GNI per head if you wanted to compare how wealth is distributed within Sweden and Indonesia? I'd like you to explain your answer to that second task.

So grab a pen, pause the video and then when you're ready to check your answers, press play again.

How'd you get on then? Here's our working out of this calculation then.

So we got 56,996 divided by $15,014.

So that's the GNI per head of Sweden divided by the GNI per head of Indonesia.

And the answer is 4.

73.

So what I've done is, I've rounded that down and I've said GNI per head in Sweden is 4.

7 times larger than in Indonesia.

So it's important to show your working if you can with these sort of questions.

How useful is GNI per head if you wanted to compare how wealth is distributed within Sweden and Indonesia? Explain your answer.

Well, your answer might include something like this.

GNI per head is the mean average income within a population.

It implies that everyone has the same income, but of course that's never the case.

This is why it is not useful for comparing the distribution of wealth or income within the country, so within those populations.

So if your answer looks something like that, well done.

Let's have a look at this second question then today.

What do social measures of development tell us? Well, social measures of development relate more directly to quality of life and we have a range of different measures which I'm going to talk us through.

So we've got birth rate, death rate and within that, a subset is infant mortality rate, life expectancy, people per doctor, literacy rate and access to safe water.

So what percentage of the population has access to safe water? So these are the social measures of development that we're gonna consider.

Firstly, let's have a think about birth rate and death rate.

Well, what are they? The number of births or deaths for every thousand people in a population per year.

These rates can be used to compare countries, but how useful are they? Well, if we take the birth rate and we actually subtract the death rate, our calculation gives us something called natural increase, which is how much the population is changing according to births and deaths, but nothing to do with migration.

Now, natural increase or in some cases decrease is when a population grows in size, as I say, ignoring migration, and many lower income countries have a youthful population and therefore a high birth rate and lower death rate.

So from that calculation, we can infer something about a population, but I would argue that these are pretty imprecise measures of development.

We've got better social measures.

So if we look at something like infant mortality rate, it's the number of deaths of children under the age of one for every 1000 live births.

It's actually more useful than that overall or what we might call crude death rate as a measure of the current quality of healthcare, which is arguably a really good measure of social development.

This is because the death rate is more dependent on the age or demographic makeup of a population.

So if we stick with infant mortality rate here, we have a graph of how it's changed from 1949 to 2022.

The graph shows the fall in infant mortality rate over time in a selection of seven countries around the world.

So they've all fallen in this time and dramatically so.

It's a good news story around the world, the change in infant mortality rate.

What else stands out to you when you have a look at this graph? What else would you offer up as a piece of analysis? Well, if I add this vertical line at about 1995, we can see that over the last 30 years, there's been a decrease in infant mortality rates in almost all countries, consistently declining, suggesting that healthcare has improved over this period of time.

Within that, we've still got those different levels of infant mortality rate, and these are some countries with some of the highest infant mortality rates around the world.

In lower income countries, infant death is still more common due to a lack of access to healthcare and poorer living conditions for some in the countries.

Also, it's worth remembering that not all infant deaths are recorded.

So official data may actually underestimate the real numbers, which is a key limitation of this measure when we look around the whole world.

How reliable therefore is this data? And if I pick out one particular case study, so if we think about Afghanistan, we can see the data I've got up in that table is from 2022.

Now, in 2023, an unofficial survey conducted by charity workers of health workers across Afghanistan, reported an increase in infant mortality.

At this time, under the Taliban government, official data collection systems were not functioning.

So not only had there been that uptick in infant deaths, but actually, the official figures were not recording it.

Okay, so three other measures of social development and I want to offer up some possible limitations as well as perhaps considering their value.

So doctors per thousand people.

That sounds like a really useful measure of healthcare, doesn't it? I guess what holds that back is that you might have a lot of doctors, but they might not be equally distributed across the country.

Similarly, that raw score doesn't really show us what percentage of the population can actually afford to go to the doctor.

Literacy rate appears to give us a really good idea of how well educated the population is until you remember that actually census data is how that information is collected.

So there might be one question on the census that asks something like, "Can everyone in your house read and write?" Now, is one question enough to adequately assess the real ability of people in the house? Probably not, and if it's completed by one member of the household, similarly it might be a little bit inaccurate.

Access to safe water, if we're thinking about percentage of households in a country, sounds like a really good measure of social development, because we can think about health and you know, exposure to waterborne diseases if you don't have access to safe or improved water sources.

But actually the problem is where you've got a score for a whole country, there might be a big difference between rural and urban populations.

So definitions also vary between this idea of access, what access actually means, and it doesn't always mean pipe to the home.

So that's another problem when you're comparing different countries.

So you can see all these social development measures have limitations.

Check for you here.

A problem with using the percentage of people with access to safe water as a development measure is there may be a big difference between rural and urban areas.

Is that true or false? And if you said, well that's true, can you explain why? So our answer here is a high score may mask data relating to people in rural areas in LICs who are much more likely to lack access to safe water, making it an unreliable measure.

So one score for the whole country doesn't really show us what the difference might be between urban areas and rural areas in low income countries.

Okay, so I want to introduce you to something called the human development index, which is produced by the United Nations, and here we have the scores for countries around the world mapped for 2022.

It's a choropleth map so the darker the colour, the higher the score or the more developed the country.

So the UN's HDI combines different measures of development, incorporating social measures, including life expectancy, as well as some economic measures.

And I'm gonna show you which one's in a moment, but let's just remind ourselves, life expectancy is the average number of years an individual can expect to live at birth.

And another good news story for you here, worldwide, this has doubled between 1900 and 2021.

Interesting to look at that pattern of the human development index.

It doesn't exactly mirror the map we looked at earlier in terms of World Bank income groups.

So perhaps I'll leave you to have a look at that in some detail.

But when we think about those high income countries in the Middle East and particularly in South America, they appear to be missing here when we look at the high scoring countries for the HDI scores.

Okay, so what does UN's HDI include? So the UN looks at whether people have a long and healthy life, whether they are knowledgeable and whether they have a decent standard of living and for long and healthy life, they're looking at life expectancy at births in years.

In terms of knowledgeable, it's looking at expected years of schooling for those of school entry age and mean years of schooling for adults age 25 and older.

So that population education is behind them.

A decent standard of living is measured by our old friend, GNI per head.

So let's have a look at a selection of countries.

This is the HDI score we have on the left-hand side and we have those different components that are fed in to the formula to come up with an HDI score.

Sweden was ranked joint fifth of more than 190 countries in the UN's 2022 HDI.

Indonesia was ranked 112 and Burundi was in the bottom 10 ranked 187.

And if we look at their HDI scores, they really are quite different.

What are the implications of this data? Well, with more than a quarter of a billion people, Indonesia is one of the world's most populous countries.

So if you were the United Nations, you'd be particularly concerned about perhaps the largest populations and the human development index scores for those largest populations, as well as the smallest populations.

But I suppose you'd have to think about where you're gonna spend your UN agency money.

So Burundi has just 13.

2 million people compared to Indonesia's quarter of a billion.

Sweden, Columbia are high income countries, but their HDI scores show key differences.

Almost a 10 year difference in life expectancy between those two countries.

And Swedish kids can expect 4.

6 more years at school.

So it's really interesting to have that breakdown data, as well as the overall HDI score to see how they're perhaps shaped by these different measures they've used.

In Africa, Nigeria is a newly emerging economy, an NEE, as Egypt and South Africa are.

By contrast, Burundi is a lower income country.

So one of the world's least developed countries.

And this links arguably to past levels of education.

If we look at mean years of schooling, we can see they're quite different when we're comparing Nigeria and Burundi, very low HDI scores and quite low mean years of schooling there in Burundi.

Okay, check for you here.

What's the difference in life expectancy between Sweden and Nigeria? Pause the video and tell the person next to you.

And if you said, "On average people in Sweden can expect to live for 29.

9 years more than in Nigeria," you were absolutely right.

Another check for you.

A limitation of the UN's HDI is that it draws on different aspects of social and economic development.

Is that true or false? Well, that's false, but can you explain why? That's right, while the HDI does combine data on life expectancy, education and income, it's a strength, not a limitation, making it more useful than using a single measure to compare countries.

So it's something that factors in social and economic measures, isn't it? Well done.

Okay, practise tasks for you.

I've got two for you to do.

The first one says, "Use these key terms to complete the paragraph below comparing different measures of development and quality of life." So we've got this gap fill here, we've got some words to use.

We're gonna look at that in a second, but first I'll just show you the second task.

So compare the level of development of two countries of your choice.

Hint, I'd like you to refer to social and economic measures.

So two tasks.

Grab a pen, pause the video and then restart the video when you want to hear what the correct answers are or suggested answers are.

Okay, how did we get on? So question one was our gap fill.

Let's read our paragraph as it is completed.

GNI per head is simply an economic measure of development.

It tells us a limited amount about quality of life, which is much more than material wealth.

The UN's HDI provides a broader picture of development as it includes income alongside social measures about education and life expectancy.

From the HDI score, we can infer what the likely skills and health of a population is.

If you used the right words in the right place, I'm sure you did, well done.

And then secondly, we had our comparison to write.

Now, this student has chosen Sweden and Egypt and they've compared the two.

Should we read through their answer? Sweden has one of the highest levels of development in the world.

The country was ranked in the top five of 193 countries in the human development index, 107 places higher than in Egypt.

With A GNI per head of $56,996, Sweden is an HIC and therefore much wealthier than Indonesia with a GNI per head of $12,046, meaning Indonesia is less economically developed.

People in Sweden can expect to live on average 83.

5 years, which is 15.

2 years longer than in Indonesia.

I can infer that healthcare is much more developed in Sweden.

It's also notable that children in Sweden benefit from five more years in education than those in Indonesia.

And I think what I like about that answer, is it's data rich.

They use a lot of data from that table, calculated some differences and made some very specific comparisons.

So if your answer looks something like that, great.

Okay, the third question we want to answer today is, which measures help us to understand inequality? Which measures help us understand inequality? Now, quality of life, as I'm sure you know, is much more than housing, but housing is an important aspect to look at, because it provides our basic needs like rest and it's the site of family life.

It may be used therefore as an indicator of wealth if not development.

Where do you think in the world these homes might be located? So I've got four images there taken from Dollar Street, where do you think they are in the world? Well, if I told you they were all from Columbia, so they in South America, so we've got four images taken within the same country, would you be surprised? So this information about four families demonstrates the range of income found within a single country.

And we've got there the monthly household income underneath each photograph.

Note, there may be a contrast in income between rural and urban areas.

In part, the result of differences in the cost of housing in these places.

Let's find a little bit more out about these four households then.

Let's meet the families that live behind those four front doors.

So here's the first family, the second, the third and the fourth.

And I've retained that monthly income data so you can see how much they earn.

How do you think these people earn a living? Well, I can tell you the job role of one of the parents or carers in each family.

In order as they appeared, we have a tailor, a parking attendant, an accountant, and an office worker.

Now, that gives us a little bit more information about these families, but I'm sure you have lots more questions for them, as do I.

So photographs and descriptions of job roles are qualitative data and it can be useful when we're investigating development.

By contrast, quantitative data is numerical and it's also very useful when we're investigating level of development.

So we've been using quantitative data already, haven't we? And I've got another map here based on quantitative data for you.

This is a global map of inequality of income.

It maps the share of country's wealth received by the richest 10% of the population.

So we've got this recognition that not everyone within a country has the same income level, but the question is, how rich are the richest? What's the real concentration of wealth in rich people's hands, I suppose? And we've got an interesting pattern there, which again, doesn't really necessarily mirror our HDI map or our World Bank income groups map, but we've just been talking about Columbia and that's the one that jumps out at me, quite a dark coloured country there in the north of South America.

It's falling into the 60% band, which means that the income share, the richest 10%, must be 60% or more.

This map is important, because it allows us to compare the level of inequality between countries.

And in Columbia, the richest 10% receives over 60% of the country's income, which is why it jumps out.

By contrast, in Sweden, the richest 10% of the population receive 33.

8% of the country's income.

So only half as much.

Quick check for you here in terms of what we've just been talking about.

The richest 10% of people in Columbia receive a third of the country's income.

Is that true or false? Pause the video and tell the person next to you.

And if you said false, could you explain why? Well, if you were telling me the richest 10% of Columbia's population received 60% or almost two thirds of the country's income in 2022, you'd be absolutely right.

So almost double, two thirds not one third.

Why is this, why have we got this inequality of income? Well, one reason might be corruption.

So corruption is the illegal or dishonest behaviour and often relates to people in positions of power.

Monitoring theft and bribery involving government officials or judges accepting illegal payments is difficult to do.

So we have to kind of look closely at data and think how accurate is this data? If the data is quite scarce, we may have questions about how accurate or inaccurate it is.

The choropleth map I have here was produced by researchers at V-Dem in Sweden, or they produced the data and they've created this index of corruption that includes what they call petty, as well as grand theft, meaning instances of corruption that were both big and small.

The index has been used to create this map of political corruption.

Again, it's a choropleth map.

The darker the country in colour, the higher the level of political corruption.

So we got quite a variety across the world.

The UK received a score of 0.

05 compared to say Columbia, which was 0.

3 and Indonesia, which was 0.

77.

So quite a big range across the world there and this is perhaps one of the reasons for inequality, helps us to understand inequality.

Political corruption results in increasing inequality as it affects the poorest most who lack power.

True or false then.

The bribery of government officials affects distribution of wealth and quality of life in some countries more than others.

Is that true or false? Tell the person next to you.

And if you said true, can you explain why? How do you know this? Well, the political corruption index shows us that the bribery of officials, as well as theft by officials, varies between countries and regions.

This theft results in more inequality as it affects the poorest most who lack power.

So the more bribery and corruption that's going on, the more inequality we have within the country.

So the poorest don't have access to justice for example in the courts if judges are being paid off.

Okay, so two practise tasks for you, here's the first one.

Suggest a key term to match each definition below.

And we have three definitions, which I'm gonna need you to read through and have a think about.

What key term or key word have we've been using in this lesson that fits those three definitions? Three different words we're looking for.

Second task for you is gonna be, which measure of development tells us most about inequality? I'd like you to discuss this question with a partner.

So grab a pen to do that first task and then tell your partner in answer to the second task or have a discussion about it, and then I'd like you to replay the video, press play again when you want to hear my views on this.

Okay, so suggest a key term to match each definition.

We've got the word political relating to politics, which is the activities of the government or people who try to influence the way a country is governed.

Corruption is the illegal or dishonest behaviour often related to people in positions of power and inequality, our kind of key theme for this section of the lesson, is an unfair situation within a society where some people have more opportunities, money, et cetera, than others.

So if those were your answers, congratulations.

Secondly, I wanted you to have a discussion or have a think about this.

What were your ideas on this? I'll tell you what our ideas were.

So GNI per head is not useful, given it's simply the mean average for a country and therefore does not inform us about the distribution of income within it.

By contrast, income share of the richest 10% does inform us about the concentration of wealth within a country.

So you might have decided that actually, that was the best measure of development in terms of telling us something about inequality.

In terms of kind of understanding that inequality, the political corruption index is useful as we can infer if there's a difference in access to opportunity between rich and poor within a country, though the problem is that data's scarce and so it may be inaccurate.

You might also have told me, kind of thinking about the whole lesson, that inequality exists between countries, as well as within them, and that's sort of what we've been looking at today, isn't it? The inequality of economic and social development across the world.

So well done for having a think about that task.

It wasn't an easy one.

We've covered a huge amount.

Let's think about summing up, what have we been looking at? So there are a range of different measures of development, but all whether economic or social, have limitations.

So they've got pros and cons and we've gotta be aware of those limitations when we're using that data.

GNI per head is the mean average income of a country and may be misleading as it provides no information about how wealth is really distributed within a population.

The UN's HDI is a useful measure for comparing countries as it combines data about life expectancy, education and income.

In many countries, the gap between rich and poor is huge and political corruption amongst other factors, limits progress to the poorest who lack power.

So we covered a huge amount there, haven't we? Well done for taking part and doing those practise tasks and I look forward to seeing you again soon.

Well done.