Configuring the World: A Critical Political Economy Approach University of Leiden by Richard Thomas Griffiths. Roilo Golez notes. Coursera.

Configuring the World: A Critical Political Economy Approach
University of Leiden
by Richard Thomas Griffiths
Lecture 1.1: Configuring the World
Hi there, and welcome to this, the very first lecture in our course Configuring The World. I don't know about your experience, but one of the earliest books I remember receiving was a child's atlas. [It had] big, bold print countries populated by exotic beasts, and inhabitants in strange and colorful costumes. Still later, I had a globe where from the comfort of my room, I could let my mind follow my finger as I traced the route to faraway places. But at some stage, the fascination dimmed. For me, it happened at secondary school, where my color blindness proved a bit of a problem (well, actually, a major handicap) when it came to deciphering all of the various hues of greens and browns and reds (Yeah, what reds?).
For most of us, the world eventually
became too familiar, and we settled for
a one page representation that looked
more or less like this one. (My Chinese
map of the world, by the way, spins it
round so that China is nearer the
center.) This is the Mercator projection,
named after the Belgian cartographer
Gerardus Mercator, who in 1569
produced this view of the world. He was
faced with the question of how to
portray a 3D object in 2D space, because
it's a globe, as we move away from the
equator to the pole so the surface area
decreases as a constant rate. Mercator
resolved the problem simply by increasing the distances at the same rate. Then with a set of tables, it would be easy to convert a measurement between two points back to their true distance. This meant basically, with such a measure and the set of tables, sailors could calculate the distance between two points on the map because that's what Mercator wanted, a map of the sea, not a map of the land.
But, as for the land, the further you moved away from the equator, so the areas distorted at the same rate, of the other distances. Most of us can live with that, and anyway, why bother to change it? We probably wouldn't do anything with a different map anyway. A long time ago we've already internalized the map, and the locations and information it projects to basically suit our own purposes. For most of us, our view of the world is by now well established. It's been shaped by our knowledge, our prejudices, our interests, and it differs from the view of the world from other countries and other cultures.

The map you're looking at (left) was drawn by Saul Steinberg in 1976, and it caricatures the image of the

The map you're looking at (left) was drawn by Saul Steinberg in 1976, and it caricatures the image of the world as seen from New York. It portrays downtown Manhattan in detail. It shows the rest of the USA as a desert, with a few points of interest, and on the distant horizon, you can barely discern Russia, China, and Japan. It's a parody, and the format's been copied for many different countries, and the viewpoint of many different statesmen. It's not new to say that our view of the world starts with ourselves. It's always been this way, and we might as well be honest and stop pretending.

You're now looking at the oldest world map ever discovered. The Maikop vase is 4,500 years old. It was discovered in 1897 in the Western Caucasus. It portrays the Kuban River region. It shows two rivers flowing into a lake in the foreground, where wild animals are grazing.
Various cattle roam the middle ranges, and in the distance, a forest, fruit trees, and distant hills and mountains, and beyond that, who knows?
Let's look at one more map, this one just over 950 years old (see next page). It's a Turkish map projection by Mahmud, al-Kashgari, and it's oriented so that the top faces east. The map is interesting for its use of different symbols and colors for mountains, cities, deserts, and the like. Notice, the closer to home the more detailed it is, but it does name most of the countries in North Africa and Asia, including China and Japan at the top, and when one gets to the north, it simply has the inscription, uninhabitable, because of excessive cold. Most of the maps of that time had dark, unknown places which were either left uninhabitable, or were filled with strange, imaginary creatures, actually just like our own worlds. For them, like us, what you see depends on where you stand. But it shouldn't determine where you should be looking.
So in this course, we're going to make a start on configuring the world, and that process must begin with recognizing the limitations in our own view. It's not enough to recognize that our view may be distorted and that there are other views. We must start by assuming that our view also belongs to the category other.
Now, to configure the world, we need two things: a framework of questions, and data to answer them. For the framework, we will start with a state controlled view. If you noticed, the modern version of the

Mercator map we saw at the beginning was framed as states, not forests, rivers, and hills. Then we'll start by adding some data, checking what we really know, compared to what we think we know. We're going to begin with size and wealth, and this is what we're going to be doing for the rest of this week. Now, we've put the maps that you've seen in a special visualization together with some others that I hope you're going to enjoy.
Lecture 1.1.1: Visualization: World Maps
Hi there. Welcome to the very of the visualizations that accompanies this series of lectures. In this one, I want to give you a chance to have a closer look at the maps I used in the lecture, and also to introduce you to some others. While teaching this course, I've become fascinated by world maps that pre-date our modern world view. Modern image started to take shape in the 15th Century as European sailors mapped down the West coast of Africa and then, so called, discovered America. And don't forget that
one of the advantages of a visualization is that you can always pause at an image you want to view in more detail.
Well, let's start with the all too familiar Mercator Projection. (See map in above Lecture.)
The next visualization is the bronze Maikop vase, with a full map representation, which we also looked at in

The next visualization is the bronze Maikop vase, with a full map representation, which we also looked at in the lecture itself. (See picture and graphic in above Lecture)
I want to show you this silk map (below), which was discovered in Hanon province in China in 1973. It dates from about 160 BC. It's interesting because of its accuracy (it was probably drawn on a grid, although you can't see that,) and also for its intimate use of symbols.
Now this (at right) is a map devised by Ptolemy, a Greek geographer living in Egypt. We don't have any surviving maps, but we do have these grid measurements. And these were used in the 1400's in order to reconstruct his world view. Note the belief at the time that the Indian Ocean was an enclosed sea, a belief that persisted for another 1,000 years or more.

Now this next map (above) is one of my favorites. It's a copy of a Roman map dating from about 3 or 400 AD. It's made up of 12 panels, 40 centimeters high. And there's a total length of almost seven meters. It's shows the entire Roman Empire. The panel I've chosen shows the area where I live. And the gash near the bottom is the Mediterranean.

Now dating from almost the same period, is the Madeba mosaic map of the Middle-East (452-470 AD), discovered in 1884 in a church in Jordan (bottom of previous page.) The map was intended for Christian pilgrims. I particularly like its 3D portrayal of Jerusalem,
which I've enlarged for you.
Now, then we've come to the Kashghari map that you saw in the lecture (see previous lecture, not reoriented), in which we we've reoriented now to the north and I've indicated some of the main locations for you.
Now we turn to an Arab map, created by Muhammad Al-Idrisi in 1154 (below.) It's orientated so south is at the top, but if I invert it, it'll be more familiar. The Mediterranean, is on a better scale than the version by Ptolemy, and there's much more detail in the Indian Ocean. If you look at the top there, Britain does seem to have suffered.
Now here (next page) is a typical Christian medieval map, this one dating from 1265 AD. It's oriented to the east. At the center is Jerusalem, and the top half is occupied by Asia. Bottom left is Europe and the bottom right is Africa. The map itself is filled with place names, bits of biblical history including Adam and Eve, and The Garden of Eden if you look just inside the world's circle at the top. And the unfamiliar parts, for example in Africa, are filled with mysterious fantasy creatures. It's a medieval world. But, it's

also our configured world. It's filled with some detailed knowledge, some associated pieces of information and with bits of imagination and fantasy to fill out the rest. Well, I hope you've enjoyed this trip to the past. And if

you have any examples of your own, put some URLs and a little bit of context on the thread that we'll create

you have any examples of your own, put some URLs and a little bit of context on the thread that we'll create in the forum. Let's see what sort of collection we can build up together.
Lecture 1.1 and 1.11. Sources:
Lecture 1-2: Political Economy and Data
Hi there. In the last video, we saw how we tend to distort our world picture with our own preconceptions. But in this video, we're going to explain why we'll need the basic data we'll be using in the rest of the lectures, and also how they fit into the analysis we'll be undertaking later in the course.
Already we've seen in the previous video, how the Mercator projection distorted geographical area, and therefore, it distorts the size of states superimposed upon it. But why should states matter?
? Well, there are several pretty good reasons. Firstly, and if necessary, they defend us.
that govern most of our actions inside their borders. and provide us with collected goods. And states collect and collate data most often at the national level. For this reason, social scientists who are interested in comparisons also construct much of their data at a national level as well.
One of the first sets of data we need to examine is population. States have been counting their citizens since before the first millennium, partly because they want it as a base of taxes, and partly to recruit manpower for large scale projects like pyramids or for membership of the army. We're also interested in population because it offers us a quick guide to the size of states, to their economic and military
. We're also interested because we regularly divide different data by population, to reduce it to a . Many measures are expressed in per capita terms, ‘per capita’ coming from the Latin, meaning per person. Social scientists generally assume that population data is accurate, but we'll see how well founded that belief is in the next video.

Why should

they be the unit of our analysis states intercede on
our behalf with other states
States tax us
States also provide and enforce the rules
potential common unit
One item that's regularly expressed in per capita terms is a country's output or national income. National income is a generic term. What is most commonly measured is a subcategory of national income called gross domestic product, which is a measure for a country's output, usually over a calendar year. Throughout history, states have generally had a pretty good idea whether the economy was doing well or badly, but they rarely tried to capture it in one single number like GDP. States only began, and that is only one or two states, to collect national income data in the 20th century. And the
Calculating national income is far more complex than just counting people, and the .
We're interested in national income for several reasons. Once we've converted it to a common currency like the dollar, it provides an indicator of how large a country is in
economy. If we divide it by the labor force, we get a good idea of a country's or competitiveness. If we divide it by population, we get an idea of the at the disposal of its citizens. And on this last basis, we used to make statements about a country was. We used to, but not anymore.
Anyone who's traveled abroad will have had the experience that the country visited seems expensive, or alternatively, it's cheap. The country has different purchasing power depending on the country where it's spent. For example, a Euro will buy you much less in Switzerland than in Thailand for example. So converting national income into current dollars is going to give a misleading picture. In the 1970s, economists started experimenting by calculating new to obtain a better basis for . But note very carefully now that any
. They're now joined by new difficulties, but by now, directed by the World Bank, the sophistication of current comparisons has improved immensely. But even so, there still remain some problems when we want to measure economic growth or to make other comparisons involving changes over time.
Now the use of purchasing power parities has provided us a clearer measure for comparing levels of consumption between countries. But the capital income however measured is still an average. It doesn't tell us much about the degree (definition) of poverty. The World Bank tried to monetize poverty by expressing it as the number of people living below a certain figure, for example, a dollar a day expressed of course as purchasing power parity dollars of a certain year. At the same time within the United Nations development program, efforts were made to broaden the definition of poverty so that it included more than the simple level of income. As a result, they constructed a human development index which took account of factors such access to education and health as well as describing living standards.
So let's sum up then: population, economic size, per capita income, economic growth and poverty. These are all variables politically economist employ when they try to configure the world, and over the next four videos, we'll examine each of these in turn and try to assess the accuracy of the data, and to configure the world through each of these different lenses.

practice only became common after the WWII. room for error is much, much larger
relation to the rest of the world productivity
level of wealth
purchasing power parities how rich or how poor
national income comparisons errors in the original calculation
still remain
Lecture 1-3: Population
Hi there. In the last video, we saw why the state was so central to the analysis that we're doing in this course. We also saw why we needed to collect a basic set of data. Well in this video, we're going to configure the world in terms of population. We're going to examine its growth and its distribution over the 20th century. And we're also going to assess the accuracy in measuring it.
On the 11th of October, 2011, the world's seven billionth citizen, Danica May Camacho, was born in the Philippines. By the end of the day, though, she'd been joined by at least four other claimants, one in India, one in Canada, and two in Russia, but at opposite ends of the country. Later, the UN Secretary General Ban Ki-Moon conceded that the choice had been symbolic, that the date chosen had been arbitrary, and that he didn't know who the seven billionth citizen was and or where and when he or she had been born. And as if to prove the capricious nature of democratic forecasting, Danica May had been in such a hurry to be the seventh billion citizen, that she was actually born at two minutes before midnight on October the tenth.
Seven billion inhabitants! Back in
. But not only had the world’s population exploded over the 20th century, it had been accompanied by a marked shift in its distribution. The largest relative gains were in Africa and Asia, and the greatest relative decline was in Europe. The causes of that growth in Africa and Asia had been a large fall in the death rates, and this was because of the impact of modern medicine, and the control of killer epidemics, the major beneficiary being the young, who then survived and had children of their own. Now these same factors also impacted on Europe, but here they were also accompanied by a fall in the birth rate, as women delayed the start of child bearing and reduced family size. The effect in many European countries, and in Japan as well, was to reduce the birth rates below
replacement levels.
All of this presents . Countries with a
to the labor markets, while countries with a
, and the increased costs of health expenditure that this entails. And they have to do both of these with a much smaller potential productive base.

much smaller potential productive base.

Population is seen as one of the simplest numbers. People are people, and they can be counted. And for this reason, they're supposed to be more accurate than the other data that we have. But this second assumption depends largely on the efficiency of the statistical agencies responsible for assembling the data. In the poorer countries especially, they have fewer resources that they can divert to these kind of activities, and generally, the less trustworthy the results. Often births and deaths remain unrecorded, especially in remote or rural areas. And a census is costly, and is often politically fraught as an undertaking. It's not just a question, then, of the funds devoted to counting population that matters. The political context can also play a role. For example, when politics is tribal, there may be incentives to inflate the census returns, if the country's demographics determine the distribution of parliamentary seats, or form the basis for government expenditure. For example, in Kenya, there'd been massive upheavals in 2009 that led to 1,000 deaths and more than half a million people displaced. The count in
1900, it was estimated that the world population stood at 1.6 billion.
In 1960, it was still only three billion
two kinds of challenges
high birth rate have to find productive
employment for new entrants lower birth rate will have to
cope with an aging population
the northeast was nullified because it was felt the figures had been inflated. In Nigeria, the UN has completely ignored the census data altogether, and produces regularly its own estimates on the basis of extrapolation. For almost all countries, the most recent data everywhere is probably pretty close to reality.
But this isn't necessarily true at a local level, and this is important. I always tell my students, be very careful when the disaggregated data does not add up to the aggregated data. For example, in Shanghai, only one year before the official census in 2010, the authorities estimated the city's population to be 19.2 million. It turned out to be 23 million. Many more migrants from the countryside had stayed on than had been estimated. But the effect of this error was that the authorities had somehow misplaced the equivalent of the entire workforce of Bulgaria.
You probably haven't heard of Newham in London. It's in the shadow of the Olympic Stadium. In 2009, the authorities had estimated the population to be 246,000. The census results, 2012, revealed a population of 308,000, an error of 25%, which had a direct impact on levels of funding. And the reason was that migrants into the area were staying longer than they had a decade earlier.
The police, by the way, estimated if you added the illegal migrants, you'd have a figure closer to 320,000. Illegal or irregular migration is another source of democratic uncertainty, also on a national scale. Since these
people have evaded being identified, there's no real way to count them. Most estimates of illegal migration are derived from the numbers caught. But that might actually reveal the success or failure of enforcement,

are derived from the numbers caught. But that might actually reveal the success or failure of enforcement, rather than the numbers actually successfully entering the country. After all, they're not caught. The estimate for illegal migration in the European Union ranges from 1.9 to 3.8 million. And for the United States, the estimate is 11.5 million.
So let's pull all of these ideas together. We've seen that the We've seen that this was accompanied by a
We've also looked at why this growth occurred, and pointed to the problems that that has entailed. And we described some of the factors, institutional and political, that have influenced the accuracy of the statistics. In the next video, we'll start to examine the world's output, as measured by its GDP, its gross domestic product. Now, in order to help you configure the world population, we've prepared a visualization, a map of the world's demographics. We invite you to have a look at it now.
Lecture 1.3.1: Visualization: World Map of Population
Hi there. In this visualization we're going to focus on the world's population in 2013. In this bar diagram (top, next page,) I've ranked by population size all the countries in the world with a population above 1.5 million. This is the cutoff point that we're going to use throughout these configurations. I've listed China and India separately, so as not to distort the scale too much. On this scale, the halfway point is around 11 million. And we've divided the map into ten equal parts known as deciles. With 152 countries, the first 10% and 20% will have 16 countries, and then all the rest will have 15.
Well, here they are. We've already seen China and India with over a billion each. USA, Indonesia and Brazil come next. And then we go below 200 million with Pakistan, Nigeria, Bangladesh, Russia and
world's population has more than
quadrupled since 1900.
shift in its distribution towards
Africa and Asia.

Japan. With the Philippines, we drop below 100 million. Ethiopia, Vietnam, Germany make up the 15. And Egypt comes in at number 16. From here onwards, we'll slowly develop the map. In each case, I'll mention the countries at the opposite end of the range, but without naming the rest. You can always slow down or pause the visualization if you wish. (Final map with all deciles is pictured here.)
So the next decile spans the range between Iran and Argentina. The third decile spans the range from Algeria with 39.2 million and Ghana, with 26 million. After that, we reach the range between

Mozambique and the Netherlands, and we complete the top half of the range with the span between Kazakhstan, with 16.4 million, and Greece with just over 11 million. So, now we've reached the middle of the

Kazakhstan, with 16.4 million, and Greece with just over 11 million. So, now we've reached the middle of the range, called the median in statistics. And the remaining countries are compressed between 11 million and 1.5 million. So we're just going to run through the rest of the maps through the deciles without further commentary.
So that was the world map of population in 2013. I hope you enjoyed it. The data used to create it is available to you in the CTW database accompanying this course.
Lecture 1.4: Output (GDP Current Values)
Hi there. In the last video, we spent some time looking at the growth and distribution of the world's population in the 20th century. We explained the dynamics of change. And we looked at the difficulties in compiling the data. Well in this video, we're going to configure the world in terms of output, GDP or Gross Domestic Product. We'll look at its distribution, and we'll asses the accuracy in measuring it.
On the 6th of April, 2014, the head of the Nigerian statistical bureau announced that his country's output was 89% higher than had previously been believed. He was proud to announce that the country had passed South Africa, as the largest economy on the continent. Of course, on the ground, nothing at all had changed. But what about the results of all the earlier calculations that employed the earlier data?
We'll return to this question later in the video. Statisticians, don't actually measure output. They measure transactions. If no money changes hands, it's not recorded, and if transactions are not recorded, they don't get measured either. To complicate matters, not all transactions are included. Illegal transactions, for example, are deliberately excluded. And, to provide a final touch, they're not interested at all in transactions per se, but in the value added between each transaction.
Needless to say, constructing national accounts is a hugely complex operation, involving the collection of data from a vast array of sources and compiling them into a coherent set of numbers. We've shown this in more detail in the visualization that accompanies this video. So, just imagine then, all over the world statistical agencies are engaged in the collation and compilation of national accounts. In order to make comparison easier, the most often the dollar, . We use this form of calculation when we're assessing the impact of countries on the world economy, less so when we're looking at their relative incomes or their relative spending powers.
The first thing to note is that the distribution of the world's GDP stands in stark contrast the distribution with population. Despite the explosive economic growth of China and some of the other developing countries, the world economy remains dominated in size by Europe, North America and Japan. In per capita terms, the richest countries in the world are also concentrated in these regions. We'll see in a moment that there are possibilities of wide margins of error, especially among the poorer countries. But even if we adjust for these, it wouldn't significantly change the overall picture.
results are usually expressed in a common currency,
expressed in current values
We've observed that calculating GDP statistics is a complex exercise. It requires a sophisticated infrastructure of data reporting and registration, and that costs money. So it'll be no surprise to learn that the greatest difficulty in obtaining accurate data is among the world's poorer countries.
[Assesment / Sources of Error] One obvious problem lies simply in the task of data collection, with an underpaid staff and under equipped offices. With UN agencies demanding answers and statistical bureaus just simply unable to supply them, it didn't wonder that one researcher who described the results as simply random numbers.
A second source of error lies in the informal sector. For example in the 1990s, officials in Tanzania estimated the size of the informal sector as anything between 30% and 200% of GDP. In the end they decided to hike

the size of the informal sector as anything between 30% and 200% of GDP. In the end they decided to hike their GDP estimate by 62% to take this into account.
A third source of error is simply fraudulent reporting, not by businesses, but by government themselves. In the wake of the Euro crisis for example, the Greek government has been accused of misrepresenting it's GDP figures in order to hide the size of its debt.
A final source of problems are legitimate re-estimations. And this is where the Nigerian case is interesting. The country hadn't adjusted the baseline for its calculations for over 20 years. It also based its GDP on very small sample of businesses. Remedying both these deficiencies resulted in that 89% boost to its GDP figures. But it’s not the first African country to have done this. So far, 12 countries have reported the results of rebasing exercises. And many more are still to come. All these efforts at improving statistical accuracy must surely be welcomed.
Implications. My point is this. Let's accept that with some exceptions, the richer countries tend to produce better statistics. But many of the
at the poorer countries. And it's here where the haphazard and disjointed. So the
And what therefore, is the
, where any improvements are of data at any point in time? What is , as we do when we talk about economic growth? on this basis, regardless of how neat and tidy the statistical outcome might appear to be? As we'll see in this course, social scientists spend a lot of
validity of any effort to look at changes over time
time and ingenuity in constructing data, for different social science variables. But statistical exercises undertaken by social scientists are aimed
what is the value of any ranked series
Okay, let’s tie all of this together. We've looked at how world output is measured, and we've pointed to the broad outlines of its distribution. We spend a considerable time, looking at the difficulties in estimation, especially among the poorer countries. And we've underlined how this affects the use of GDP indicators, in any statistical exercises. Well, we've tried to configure for you the size of the various economies. We invite you now to look at our visualization of the world map of GDP. In the next video, we'll look at how the world output is
estimated so it's better to reflect, well, real world output. errors are high
validity of any statement made
they tend to ignore the

possibility that a basic data set like GDP, might get so totally unsuited for statistical analysis

.

Lecture 1.4.1: Visualization: World Map of GDP Current US Dollars
Hi there. In this visualization, we'll turn our attention to the world's GDP in current dollars. Since current dollars, real dollars, give an indication of the command over the world's resources, this is the favored measure for showing the relative size of the world's economies. But before we look at the data, let's take a closer look at how the numbers are calculated.
Basically, there are three different routes to the same number. Since everything earned in a society is equal to everything consumed or saved, and since everything consumed in a society must be equal to everything produced, it stands to reason that income equals expenditure equals production.
But the data should also be calculated in each of three different ways as well. And in each case, using different sets of data, they should all come to the same result. Now even in richer countries, this often

requires an error term to balance the measures. But simply to look at the information needed makes it easier to see why in countries with a less developed administrative infrastructure, it is difficult to produce reliable statistics.
When we look at the range of country incomes, the gradient is much steeper than it was for population. In this diagram, you'll notice we've removed the top four economies so as not to compress the range too greatly. In the diagram, I've ranked by GDP size all the countries in the world with a population above 1.5 million. The data for 2012 has a few countries missing, and you can see them here. Since there are 143 countries, we've divided the map into ten equal parts with 14 in each except for the first three which have 15.
So, let's get started. The first decile is headed by the United States, followed at some distance by China and Japan. Germany, France, and the UK come next, followed by Brazil and Russia. Italy, India, and Canada are next and by the time we reach Australia, we're talking in terms of the economy that's less than 10% the size of the United States. Spain, Mexico, Korea make up the rest. Indonesia that leads the next SR, is a little more than 5% the size of the United States. And the range now extends to the United Arab Emirates, whose GDP level is less than 2.5% of the USA. Nigeria, by the way, has its unrevised statistics in this group. But you can see, there are still many middle-sized European economies. The third decile stretches down to Iraq with a GDP of only 1.3% of that of America. And by now a pattern is emerging of a mixture of small, richer states with bigger, poor ones. So, we'll run through the rest of the data without much comment. Don't forget, you can always slow it down to make the viewing easier.

So, that was the world map of GDP. I hope that you enjoyed it. The data used to create it is available to you in the CTW database accompanying the course.
Lecture 1.5: Output: GDP PPP
Hello again. In the last video, we spent some time exploring the basis for calculating a country's GDP. We sketched the distribution of world GDP in current dollars. And we explored the difficulties in compiling the

sketched the distribution of world GDP in current dollars. And we explored the difficulties in compiling the data. We stressed how errors contained in this exercise might make the data unsuitable for sophisticated statistical analysis.
In this video, we're going to configure the world in terms of output, or GDP again, but when adjusted for differences in purchasing power. In the last video we stopped our discussion of the calculation of GDP in current values, and then converting them into a common currency. But in order to make comparisons over time, it's necessary to . Statistical officers do this by constructing a . This is made up of a selection of goods weighted so that their relative values affect their relative importance in the economy. The result is called Real GDP. In International comparisons it's usually anchored to a currency the dollar, at the exchange rate prevailing in a particular year.
For many social scientists, this didn't go far enough. They observed that there were also structural difference in prices between countries. They pointed out, quite correctly, that in poorer countries, money seemed to go further. And they made the valid point that since most goods produced in a country were consumed in a country, this difference in purchasing power was important. What they wanted was a set of data measured in a common currency that had been adjusted to take account of the Purchasing Power Parity. In other words they're there to eliminate these structural price
separate out the changes produced by fluctuations in prices special price index called a GDP deflator
differences. So you'll recognize these because they'll all be expressed as something like 2012 US Dollars PPP.
Key Remarks: Now before we see how this happens, I want to say three things. Firstly, PPP Dollars do not exist. The economy functions in real current currencies. An Indian spending Rupees in his own country might get a consumption boost by PPP figures, but everything else will seem more expensive all the same. Secondly, the PPP calculations do not start from scratch. Any flaws or errors in the original estimates will be carried over into their conversion into PPP values. And third, the official calculations of GDP did not start on any scale until the 1950's. In these early days, much of the information available was patchy and of dubious quality. And in many poorer countries it still is today. All the GDP statistics from before the 1950s is the result of reconstructions, often with data that was never really intended for that purpose.
The GDP figures were originally used for purposes of wartime planning and post-war reconstruction. And they retain their usefulness as governments try to adjust their policies to smooth out the path of economic development. In 1968, the World Bank and the University of Pennsylvania, which has since continued on its own, started an International Comparisons Project. Comparison started with only ten countries. But the range and depth of coverage has since improved substantially. Now, many comparisons over time uses PPP adjusted data, especially for per capita comparisons and for economic growth. PPP adjusted data is also used in discussions on poverty, because it reflects the purchasing power inside a country.
Difficulties in Assessment: It's important to note the difficulties that such an exercise entails and the faults in the earlier efforts. The first difficulty is that to establish comparable prices, you need comparable products. The patterns of consumption tend to vary among countries. Let's take a Big Mac. A big Mac in China is 43% cheaper than in the United States but a Star Bucks coffee by contrast is only 4% cheaper. The lesson of course is Star Bucks is more at market in China than is McDonalds. But a bigger question is do the Chinese consume much of either of them?
A second problem is not just selecting the comparable products, but also choosing representative locations. There's little point in focusing on the towns, where presumably most of the comparable products are likely to be found, when most people still live in the countryside.
Now I've started with these two criticisms because they were at the source of a huge row in the United Nations. In 2007, the World Bank cut back the estimates for the size of the Chinese and Indian economies by
almost 40%. This was because of faults in the construction of the earlier 1995 price comparison. 1995 was better than the previous effort, undertaken in 1985. Now I mentioned this because

better than the previous effort, undertaken in 1985. Now I mentioned this because

. This is because it was the year chosen by OECD economist Agnes Madison, who did much of the pioneering work in this field. But there was
The values from 1990 are extrapolations from 1985. And
surveyed. The price differences discovered there assume to prevail over the neighboring countries as
long run growth statistics stretching back before 1970 and even back into earlier centuries are
expressed in PPP values of 1990
no comparison made in 1990.
in 1985, only 62 countries were actually
well. And the reason why there was no survey in 1990 was because it was decided to take a break so they could overhaul the whole system.
Well, in April 2014, the latest results of the PPP calculations have been published. And these were based on surveys conducted in 2011. Even with much improved data, the World Bank concedes that the estimates still contain a margin of error. Its own recommendation is that differences less than 5% should be discounted. But the error margins could be as much as 15% in countries of dissimilar size and dissimilar economic structures. Will anyone take any notice? Well they haven't before.
Okay, let's sum up then. In addition to the difficulties inherent in the original GDP estimates, we now have to add the complications in international price comparisons. But there are still problems and uncertainties in the results. In the next video, we're going to look at how these
new PPP estimates will fit into the debates on poverty. In the meantime, we've taken the brand new published PPP data, and used it to configure the world along the lines of per capita incomes. So why not look at our visualization of the world map of GDP. PPP.
Lecture 1.5.1: Visualization: World Map of GDP PPP
Hi there. In this visualization, we're going to turn our attention to the world's GDP, and measured in dollars adjusted for purchasing power parity, or PPP.

Every five years the World Bank recalculates the benchmark. It did so in April 2014. The data is benchmarked for 2011, and insofar as our accurate, this is probably the best moment to make a comparison.
Now we've already seen the data's adjusted to take into account structural differences in prices between countries, and therefore they provide the best measure for real differences in per capita GDP. Although in the recently released newspaper headlines, screaming about China catching up with America, and China and India overtaking America, this actually says nothing about the ability to buy resources on world markets. But it does say a lot about how far the dollar goes, when goods are bought inside a country. So we're going to stick with what the data is meant for, comparisons in domestic purchasing power.
With 137 larger countries for which the World Bank has comparable data, each decile is 13, except for the first seven, which are 14 each. The top decile comprises a mixture, all rich states and rich developed economies, often medium sized economies. So, let's work down the list, we start with Qatar, Kuwait, Singapore, Norway, United Arab Emirates, Switzerland, Hong Kong, and only then the United States. With a per capita income of just under 50,000 of both PPP and current dollars, the United States was actually the reference point for all of the calculations. Then there follows Saudi Arabia, the Netherlands, Austria, Ireland, Oman, and Australia with $42,000. The next decile covers a range down to around $30,000, It includes most of the rest of Western and Northern Europe, as well as Canada and Japan. The third Diesel, takes us down to around $20,000 and it includes most of the rest of Europe, Malaysia, Kazakhstan, and Chile. The next two deciles take the range down to around 10,000, mostly countries from Central and South America, the Middle East, and North Africa and only just getting in slightly about

the modal income we have China. So let's scroll through and pause at the bottom 30%, at this point the per capita income is around 3,600 dollars. There are still some Asian countries in the mix, the largest being Bangladesh, but as we move downwards the fields increasingly dominated by sub Saharan Africa in countries, and even in mentioning the margin of error of around 50 percent, we're unlikely to propel them out of this bottom region.
Well, that concludes our look at the world's per capita GDP, once it's been adjusted for differences in purchasing power. The detailed data, as well as the per capita data without the adjustment, in other words, in current dollars, are in the database accompanying this course.
Lecture 1.6: Poverty
HI there. In the last video, we say how GDP was adjusted to take account the differences in domestic price levels. We explored the difficulties in compiling the data and we saw how it could add an extra dimension of error to the national income estimates. Now in this video, we'll see how international bodies use this data to measure poverty and how some of them attempted to construct new measures entirely.
Having invested so much in constructing the PPP GDP data, the World Bank was the first to use it to define poverty.
. Note first that the , because this would have had the effect of ignoring the income divide within a country. And secondly, the target is consumption, not output. Using this criterion, the World Bank estimated that 42% of the population of developing countries lived in poverty. And in 2005, it raised the poverty line to $1.25, now measured at 2005 PPP dollars. And on this new basis, it estimated that a quarter of the population in developing countries was
now living in poverty.

In 1990, the World Bank defined poverty as the number of people consuming less than
$1 a day at 1985 PPP dollars target isn't per capita GDP
When the UN formulated the , it incorporated the $1.25 target as one of its indicators. It compared to 1990 by 2015. Now it should be noted before you go any further that the World Bank uses many more indicators than this, and both work in alleviating global poverty. The $1.25 figure is a headline figure intended to grasp the attention of the world's public. But it's always been more than that. From the 1960s, from the development decade, it's been dominated by the GDP data and investment ratios. GDP numbers, modified or not, were mechanically used to measure progress on almost every front. And some authors argue that human advance shouldn't just be a question of GDP movements.
In line with this thinking, the constructed a .
The human development index is made up of three components weighted equally, the basis for its calculations being changed frequently, the last time in 2011. Health was represented by life expectancy at birth. Knowledge was represented by the average years of schooling and by the expected years of schooling to give some credit to countries introducing educational reform. And living standards were represented by per capita gross national income, adjusted from PPP. The gross national income is a variant of GDP and its use was introduced in 2011. The effect is to widen the differential between rich and poorer countries, but it’s much more difficult to calculate.
Now the UNDP has calculated HDI back to 1980. Between then and now, all countries in the world except the Democratic Republic of the Congo have improved their position largely because of increased life expectancy. Looking at the global pattern, richer countries tend to dominate the top end of the spectrum. But many oil rich Arab states dropped down the order. The bottom end of the spectrum is occupied by the countries from sub Saharan Africa, with one exception, and that exception is Afghanistan.
Assessing the HDI: Now the human development index is an extremely inferential index. It's often quoted in the press and in academic publications. And it's often used by social scientists in statistical exercises. It's
been savagely criticized, sometimes fairly, and sometimes not. It's what we call a Millennium Development Goals

Millennium Development Goals aimed at halving extreme poverty
dimensions like access to education and health. UN Development
Program
human development index which it also launched in 1990
composite index
where different aspects are fused together to give one result and indices like this are .
always
On the question of , the HDI comprises three elements, each accounting for one third. But is
open to criticism on three grounds: weighting, standardization, and selection weighting
this fair? Is
education? Is
account of quality. Once you have the ratings, there's always a substitution game you can play. What is the tradeoff between an extra year of life and a small tweak on the GDP data? Nobody by the way, questions the GDP or GNI data itself.
Standardization is always a problem when you take variables with different dimensions. The years of life what nought to 90? The years of learning what, 4 to 10, or to 12 and do we include post secondary education? And per capital GDP? Where do we start, several hundred dollars? Where do we end? All of these need to be standardized to fall inside the same range. Do you insert upper limits? Do you
GDP overrepresented
Human development should include other
, because wealth also determines access to both health and , because it's been driving the index forward and it takes no
education over-represented
compress the gradient, a log scale instead of a simple number scale? And the answers to these questions all feed back into these substitution games. Now the UNDP has been particularly sensitive to criticisms of this
kind and it's regularly altered the treatment of the variables employed. As we've seen, the last of these changes was in 2011.

Criticisms on weightings and standardization are possible in all composite indices. And the UNDP has defended itself by pointing out that the HDI is simple and transparent. But it's always ducked the question whether it adequately reflects human development.
The most persistent criticism has been on the of the dimensions to be included in the index. What, for example, about , where is it? Well to be fair, when the UNDP tried to do this in 1992, it ran into such a storm of protest in the UN that it almost lost its funding. Okay, well, what about inequality within nations? Well, again to be fair, at the beginning, the data simply wasn't available. It is now, and the UNDP has constructed an index showing the extent to which HDI scores are affected by inequality. It's not a bad effort, but it still contains many of the drawbacks implicit in the original. What about gender? What about real desperate dollar a day poverty? Well in 2011, the UNDP also published two new indices covering each of these dimensions. I don't want to be unkind, but to be honest, I would wait for the inevitable and absolutely necessary revisions before even trying to use these.
Well, let's sum up now. We've seen how PPP calculations have been used in the description of poverty, either by themselves or in composite indexes. We've also seen how the human development index was constructed, and we've criticized it, pretty seriously. Now taken together, the videos this week have configured the world along different dimensions- population, output, income, and poverty that are
commonly used in our own configuration of the world into big, small, rich, and poor, and a jolly good job too. But they're also employed by political economy analysts, all too often uncritically. This basic data is all too often slotted into sophisticated statistical models without pausing to ask whether it's suitable at all, and this surely nullifies the point of the whole exercise.
Next week, we look behind the concept of globalization. Where did it come from? What does it involve? And should we worry? Meanwhile, we built a visualization of the world map of poverty and we'd like you to look at it next.
Lecure 1.6.1: Visualization: World Map of Human Development Index
Hello again. In this visualization we're going to look at the results for 2012 for the Human Development Index compiled by the UN Development Program. If you recall, and as you can see here, the index was a composite one embracing three dimensions. In the lecture itself, we express several reservations about its construction, so don't forget that. The index covers a range from 1 to 0. The median, or halfway point, is at 0.7. The range in the top half of the index is more compressed than at the bottom half. There
selection
human rights and democracy

are a few countries missing, as you can see here. With 146 larger countries, each decile is 14, except for the first six, which are 15.
So which countries are at the top of the index? Well nine of the countries in the top decile were also in the top 15 of the list for purchasing power parity GDP. These include six medium size European countries, Norway, the Netherlands, Ireland, Sweden, Switzerland, and Denmark, as well as Australia and the United States coming second and third respectively, and Hong Kong. These are joined by Germany, New Zealand, and fifth and sixth place respectively, Japan, Korea, and Israel. The richer countries dropping out of the index are Qatar, Kuwait, Saudi Arabia, Oman, and Singapore. The next decile comprises most of the rest of the richer European countries. It's now that you see Singapore and Qatar come into the decile. The third decile picks up a few remaining European states, and we start seeing some of South American countries appearing, as well as Belarus, Russia, and Saudi Arabia. Now let's scroll through the middle range. Don't forget, though, you can always slow it down and pause it at any point of interest. Entering the last three deciles, with a score of 0.519, we have Kenya followed by Bangladesh and Pakistan, Myanmar, Nepal and Papua New Guinea, also feature in this segment. But the rest is Sub-Saharan Africa. Only Haiti breaks the Sub-Saharan African presence in the bottom 20%. And don't forget, this is also a range in which one's faith in the detailed rankings shouldn't be too solid.
Well that concludes the visualizations accompanying this first week of lectures. I hope you've enjoyed them. And I also hope you'll take a more detailed look at the database, especially if you're focusing on a particular region, whether you're going to do the advanced track or not.

Week 1 Required Readings and Database Link:
Richard Griffiths, 'Readings Week One – Part 1: Population and GDP Current Values' Click here to read Richard Griffiths, 'Readings Week One – Part 2: GDP ppp and Poverty' Click here to read
Configuring the World Database Week 1: Size, Wealth and Poverty. Click here to read
The above notes are provided by a student of the Coursera course “Configuring The World”, offered by Leiden University. They were produced without compensation, and are the property of the University of Leiden.
Week 2: Trust
2.1 Trust and Social Capital
Imagine for a moment that you can trust no one, no one at all. What's your life likely to be like? Would you leave the house? Would you go out at all? Could you work for anyone? After all, who would pay you? Would you dare carry money? In fact, would money mean anything? Basically, you would wander around in a state of almost permanent fear and terror. And so would everyone else. Life as we know it would grind to a halt.
Okay. This is utterly unrealistic. So imagine now that the only people you can trust are your immediate family and a few very close friends. What is your life like now? Well you could now engage socially and

economically, but you'd want to keep your important activities as much as possible within your trust radius. You may form temporary alliances with other groups. But these would always be subservient to that closed trust circle. These are the people with whom you would share your knowledge, your transactions, your plans for your future, and your rewards. In fact, most of your activities would be aimed at binding these people ever closer to you.
You can probably imagine what a state like this would be like. You may even live in one. It would be marked by clientilism, the favoring of regular business contacts. It would be characterized by patronage, the favoring of family and protégés. It would be permeated by the favoring of friends. And it would be riddled with corruption like giving or taking of bribes to secure a deal. Although it doesn't often figure in political analysis, trust is the glue that holds societies together.
The main proponent of social capital was a political scientist called Robert Putnam. In 1995, he published an article called “Bowling Alone,” which he later expanded into a book. Central to Putnam's thesis is the membership and density of voluntary organizations, since these are the networks and the building blocks of social capital. Like many social scientists, he also holds that personal trust is directly linked to trust in institutions, or to put it in social science terminology, interpersonal trust is linked to generalized trust. In addition, he distinguished between networks that provided bonding capitalism, closed groups where you met your sort of person, and those providing bridging capital, where you mixed with others.
Trust is linked to a wider and more popular concept called ‘social capital’. Just as economists have devised a concept called human capital, defined as one's raw hours of labor on a task, plus all the skills and experience that you bring to the task, political scientists devised a concept called social capital. This covers one's human interactions, plus the range and intensity of one's network of relationships. Embedded in social capital is the idea of trust. But whereas the idea of human capital goes back to the 1950's, the idea of social was virtually unheard of until the 1990's. One rather unkind observer suggests they coincided with the end of the Cold War and the blow that this sent forward to the specific international relations perspective that had dominated much of political
science. Since there is no one as inventive as a political scientist who's lost his paradigm, we suggested social capital was pressed into service to fill an intellectual vacuum.
Well, I confess. I secretly sympathize with this view, but I don't think it conveys the whole story. Many of the components of social capital and trust rhetoric had already been bubbling slowly in a branch of economics called Institutional Economics, which emphasizes the role of agglomerations, networks, and state holders. At a time when hyperglobalization rhetoric was boasting the triumph of markets, and viewing institutions as impediments, so an alternative discourse emerged, built around the centrality of formal and informal institutions and the conditions necessary to make them work, including trust.
Bowling clubs were a form of the latter, and for Putnam, a jolly good thing too. Bowling Alone contrasted the increased popularity of ten pin bowling with the decline in the memberships of bowling clubs. It was a metaphor for what he perceived was happening in American society as a whole. Membership of civic organizations was everywhere in decline, and this undermined the formation of social capital and the nurturing of trust. This fragmentation of society posed a threat to democracy, posed a threat to America's authority in the world, posed a threat to its economic preeminence, posed a threat to just about everything.
‘Bowling Alone’ and an earlier work applying these ideas to the evolution of Italian democracy over a period of seven centuries were both heavily criticized. But it made no difference to their popularity, especially among policymakers. I suppose this says something about the links between academia and policy making. We academics fondly imagine that our work may perhaps, just a little, influence policy

policy making. We academics fondly imagine that our work may perhaps, just a little, influence policy making. But policy makers usually have their own preconceived ideas, and they, more usually they're civil servants, just look for some academic work that legitimizes them. Oh, well, c’est la vie.
Okay, to sum up, we established that trust was central to society. We've distinguished between interpersonal trust and generalized trust. We've examined the rise of social capitalism, and we've explored the concepts of bonding and bridging capital. In the next video, we'll look at how to measure trust in different societies.
2.2 Measuring Trust
In the previous video we looked at the centrality of trust in society, and we saw there was a link between interpersonal trust and generalized trust. And we looked at the links between social capital, and the ideas of bonding and bridging capital. In this video, we are going to see how social scientists have tried to measure trust in different societies. We are going to look at some psychological experiments and we will explore the “trust question,” and explain the concept of sampling to you. That’s quite and agenda.
If trust is central to the formation of society, and if it’s evident that there are different levels of trust in different societies, social scientists will want to measure it. One way is through social psychological experiments. In 1993, researchers at the University of Minnesota devised a trust game and tested it with 32 pairs of students. All of the students were given a fee of $10 for participating in the experiment. Half of the students were taken to separate rooms and told they good keep their fee, but if they wanted, they could give some of it away. Whatever they gave away would be trebled and given to a stranger who would be told where it came from and could return some if he wanted to. Now these strangers were the second group of students, also in separate rooms. They also had had
their fee, but they were now given extra from their unknown partner and were told they could keep some of it or return some of it.
So let’s have a look at the results. The students started with $10, and gave away on average $5.15. This meant the receiving group got $15.45+. The average amount they returned, however, was only $4.66. Only 40% of the first group received a positive payback from their gift. The rest lost out. When the experiment was repeated, but this time telling all the participants the results of the previous run, the amounts gifted increased slightly, but the payback now swung into positive territory, climbing up to just under $6.50.
The researchers suggested that the different outcomes could be explained by the fact the first experiment relied purely on socialized norms of behavior, those inherent in the students, whereas in the second experiment they had actually learned something and were able to make strategic calculations. This led to an increase in mutual trust.
Variants of this game have been played ever since, usually beginning by asking participants if they trust other people, and linking this to their observed behavior. But before leaving this experiment, let’s have a look at a couple of points. The results differed if the sums involved were larger. The results also differed if the participants were drawn randomly from the population. The students knew that the other group were also students, and this probably influenced their behavior. Finally, the calculation need not always enhance trust.
In one variant of the game, the sum given away was not returned to the individual, but was put into a common pot from which they would all benefit, rather like a voluntary form of taxation which would be
spread out afterwards. The game is then played in several rounds, and the results are announced after each round. As the game progresses, what is interesting is that the amount being given decreases, and those that gift nothing actually increase. In other words, they are avoiding paying taxes and allowing

those that gift nothing actually increase. In other words, they are avoiding paying taxes and allowing others to do so.
Now a second experiment is known as the “dropped wallet test,” devised by Reader’s Digest in 1996. They dropped a dozen wallets in each of 20 European cities to see how many would be returned. Each wallet contained $50 in local currency, an address card, a family photograph, as well as other personal items. They subsequently repeated this experiment in different locations, most recently in 2013 when they visited 15 different world cities.
Let’s look through the results. Helsinki came out best with 11 of the wallets returned. Scandinavian cities generally do well in these tests. Next came Mumbai with 9, followed by Budapest and New York with 8 each. Amsterdam and Moscow followed with 7 a piece, though I often wonder how we would have done if we used unlocked bicycles instead of wallets. Berlin and Ljubljana came next with 6, and after that you have a less than 50/50 chance of seeing your wallet again. So let’ run through the rest. London and Warsaw had 5 each, Bucharest, Rio and Zurich had 4 each, Prague had 3, and at the bottom of the list, Madrid returned only 2 wallets.
Since 1996, social scientists have been dropping wallets all over the place, which is quite expensive, actually bearing in mind that there is less than a 50/50 chance of ever seeing them again. Social scientists have gotten around this problem by asking people if they expect to have their wallets returned, and measuring the results that way. Save’s a lot of money!
Actually asking people is the more normal approach to ascertaining knowledge about trust. In 1956, a social scientist, Maurice Rosenberg, devised what has become the standard ‘trust question’. It goes as follows: Generally speaking, would you say that most people can be trusted, or you cannot be too careful when dealing with other people? Since 1981, this trust question has been included in what is known as a ‘ world values survey.’ These surveys ask about 1000 respondents in a whole host of countries, a whole series of questions on their attitudes on a whole range of social issues. There have been 6 waves of this survey so far. The results of the most recent one were published in April 2014.
Now the next question we need to ask is whether experiments with 12 wallets or 30 pairs of students or even 1000 respondents can actually say something about a country as a whole. The answer is yes. You get it by what we call sampling. First of all, you have to define a population. This is a statistical term meaning the entire entity. In this case, it is the adult population [of a country.] The idea of sampling is that any subgroup should show the same characteristic as the population as a whole, but the sample must be of sufficient size, and it must be random.
Let’s take an example. Let’s say that society is made up equally of men and women. Choose four people at random, and you should get two men, and two women. But you could get 3 men and 1 woman. The sample is simply too small. But choose 100 people at random, and you should get close to 50 men and 50 women. You might get 49/51 or even 48/52. So there is always a margin of error or a confidence level in your results. So you can ask a population whether it trusts other people or whether it shouldn’t be too careful when dealing with other people.
To sum up, in this video we have looked at two trust experiments, we’ve introduced the trust question, and we’ve discussed the idea of sampling. In the next video, we’ll look at the result and see how reliable they are.
2.3 Trust Results and Criticism
In the previous video, we looked at trust experiments and we introduced you to,, the trust question. We also saw how through sampling it's possible to get results by asking a limited number of people. In this video we're going to review those results, and we will certainly question their reliability.

video we're going to review those results, and we will certainly question their reliability.
The World Value Survey is a veritable fount of information. It's widely used in social science research, in every way. About 1,000 respondents are surveyed in 50 or more different countries. And some other question repeated in each wave. The trust question is one of those. It’s always been included in the surveys from the very beginning.
Let's refresh our minds again what it is. Generally speaking, would you say that most people can be trusted or, you cannot be too careful when dealing with other people? Now the director of the World Value Survey has collated all the results into one single index in which he subtracted the percentage who answered you can't be too careful from the ones who answered most people can be trusted, and added the sum to 100. Basically, results above 100 indicated that society was on balance, trustful. Below 100, there was a majority urging caution in dealing with others. Before the most recent wave, only about 25% of those questioned believed that most people could be trusted. Well, in April 2014, the latest results were published covering 56 countries, five of them for the first time. Of the 122 larger countries for which data is available, only 11 have a majority of respondents willing to urge that you can trust your fellow citizen.
Let's have a look at these in a little more detail. Topping the list are in order Norway, The Netherlands, and Denmark. Sweden and Finland come in fifth and sixth place, respectively. So this groups together the prosperous medium size northern European welfare states. New Zealand, Switzerland and Australia also have a majority of trusting respondents. I'm sure you can all think of several reasons why these countries should share these characteristics. You most certainly will by the end of this course.
Splitting these countries are three others. China comes in fourth place. Saudi Arabia and Vietnam are ninth and tenth place respectively. There is a tendency among some social scientists to treat these countries as outliers, genuine but freak results that fall outside the expected pattern, and to exclude them from their analysis. They're all effectively one party states with strong continuity in leadership. They're all relatively homogenous. And they're all societies with strong state control over the media. But there are plenty of other states with these characteristics as well that do not produce trusting respondents. We'll look through the rest of the results in the visualization at the end of this video.
Assessment. In looking at the outcomes, I want to start by asking some questions you should ask of any survey data. And then we'll raise one question specifically about this set of trust data.
The first question you need to ask is whether the sample size is large enough. Well, even for data sets of less than 20, there are statistical tests of probability for their accuracy. And all social scientists would agree that 1,000 is really a pretty large sample. So that's not a problem.
The second question we need to ask is whether the sample itself is random, is the survey random in design, and are the respondents chosen at random? Looking through the technical notes on the survey, I was a little uncomfortable when it described the possibility in having to choose a handful of respondents from two villages, one large and one small, they would actually allocate more places to the larger village. But the survey said that was all. But even then, you shouldn't be doing that.
My suspicions became more solid when I read at the top of the collated results the following, “all data should be taken with care, since the sample distributions by education and other social democratic variables in some countries may diverge substantially from their respective population distribution.” Now that is a big problem.
A bigger problem lies with whether the respondents are random. Taking apart in a survey like this is not something you undertake lightly. There are over 200 questions, many of them requiring you to rank opinions on a graded list of 1 to 5. It's going to take a couple of hours. So you may ask your respondents

opinions on a graded list of 1 to 5. It's going to take a couple of hours. So you may ask your respondents randomly, but they don't agree to participate randomly. When my students in Beijing did a small two minute survey, some people deliberately walked away to avoid the students all together. But 40% of those who did stop refused to take part. Now, who are they? Are they ones without time, or are they ones who don't trust surveys? And if they're the ones that don't trust, really a sample survey is only a sample of those willing to be surveyed.
Now a third question is whether responses actually have an opinion on a specific issue at all (value of the answers.) I mean an answer is dragged out of them regardless. But after a while, in two hours, you're going to go on automatic pilot, or you're going to start giving the answers that you think the questioner would like to hear. And the phenomenon intensifies the longer the survey gets, because for many questions, I think the answer is probably, I haven't got a clue, I haven't thought about it.
Let's take a question 11, for example.
“Here is a list of qualities that children can be encouraged to learn at home. Which, if any, do you consider to be especially important? Please choose up to five.”
And then they hold up a list: independence, hard work, feeling of responsibility, imagination, tolerance and respect of other people, thrift and saving money, determination, perseverance, religious faith, unselfishness, obedience, self-expression. You got an opinion on that? Well, there are 200 more to come.
Now there's a final problem specifically to the trust question. What was the question? You've seen it. Generally speaking, would you say that most people can be trusted, or you cannot be too careful dealing with other people? But who are the other people in the question? Now a survey in the United Kingdom asked exactly this supplementary question, and it found that those who answered that you could trust other people, 40% of them had known people in mind, and only 10% thought of people outside their closed-circle groups. Those who urged caution, the numbers were reversed. When my students repeated the exercise in a pilot survey in Beijing, they found exactly the same pattern. So within the trust survey, the people are in fact answering not one question but two different questions.
So let’s sum up then. In this video we introduced you to the World Value Survey. And we looked at the results of the trust question, the trusting end of the spectrum. We also examine some of the problems involved in trusting the trust results. In the next video, we'll see what assumptions social scientists have made about trust, and which hypotheses have they developed on the causes and effect of trust in different levels of society. Meanwhile, I invite you to take a look at the visualization of the world map of trust that we've prepared.
2.3.1 Visualization: World Map of Trust
The world values survey routinely asks whether you think that most people can be trusted or whether you can't be too careful in dealing with other people. The sixth and latest wave of data was released in April 2014. These new results have been used to update the existing database. We've added several countries to the database for the first time. You can view the results yourself in the database collection available for this course.
The index is constructed by deducting the non-trusting from the trusting and adding the score to 100. A score above 100 reveals a society on balance, to be trusting. The results cover quite a spectrum, but it's interesting that only 11 countries are on balance trusting.
Topping the list are Norway, the Netherlands, and Denmark. Then comes China. It may seem a surprise, but the survey conducted by my students in Beijing pointed in the same direction. Next followed Sweden, Finland, New Zealand, and Switzerland. But then comes Saudi Arabia and Vietnam. And the

Sweden, Finland, New Zealand, and Switzerland. But then comes Saudi Arabia and Vietnam. And the list is closed with Australia and Germany.
The second decile contains Canada, Hong Hong, Yemen, homogeneous by the way, but still involved in a civil war, Japan, Kurdistan, Kazakstan, Singapore, the Dominican Republic, and Belarus. Belarus homogeneous but in deep economic problems. Ireland, United States, Austria. Hong Kong also figures here.
The third decile includes Iraq which is a huge surprise to me. Thailand, which has tumbled since the previous survey and whose polarized politics have led to a militarized coup, and a few largely European states.
Just as I expect that you've been, as I am, puzzled by some of the results. But, don't forget, remain a little bit skeptical of the whole exercise. I leave that judgment, though, over to you. The detailed outcomes are in the database accompanying this course.
2.4 Causes and Consequences
In the previous video, we looked at the results of the trust question. To be fair, we were pretty critical of large surveys in general, and about the trust question in particular. In this video, we are going to look at what social scientists actually do with the results. We’ll look at some of the assumptions they make. We’ll examine some of the plausible hypotheses about the role of trust in society.
There is a large body of literature on what determines trust. It has divided itself into three mutually incompatible schools of thought. There are those who argue that trust is deeply, culturally rooted, that it belongs almost to the values learned in early childhood. Among the evidence they cite to support this claim is that trust levels in immigrant groups reflect those in the home country, rather than the host country, even after several generations.
Other social scientists believe that trust is a learned phenomenon that is part of one’s process of socialization. Robert Putnam is one of these. He and others cite the evidence of the link between trust and institutional membership and participation in civic society.
There is yet another group that believes that trust is learned, but they contend that the mechanism is not socialization, but one of confidence. They point to the evident relationship between well ordered societies and reported levels of inter-personal trust.

The World Values Survey collates the results of the trust question in the form of a single index on a separate web page. Some of the observations date from the turn of the millennium. They are 15 years old. Does this matter? It does not matter if you believe that trust attitudes are relatively constant, and fluctuate at most within a small range. That seems to be the assumption underlying their use. Culturalists span their expectations over generations. Institutionalists discuss changes taking place over decades. The only breech that the governance school has discovered is the deep changes in trust accompanying major regime changes such as the collapse of communism at the end of the 1990’s.
Does this belief withstand closer examination of the recent data? In many instances, the latest World Value Survey do indeed coincide well with the results of earlier surveys. There are exceptions. Here are some examples. The Netherlands, which is drifting in an economic malaise since the financial crisis of 2008 has actually improved its index by a whole 25 points. Thailand, which once formed part of the explanation that high trust level is reflected in its traditional Buddhist values fell by 18 points, no doubt because of the political problems in the country. But there again, Egypt, which has been through at least one political and social revolution since the Arab Spring, has remained unchanged. By contrast, Jordan, possibly under the impact of the Syrian refugee crisis, has seen its trust score change 34 points. The largest change of all is the collapse of trust in Ecuador, from 72.7 to 14.5, taking them from 22nd in the world to 7th from bottom.
A second assumption made by social scientists is that there is a direct link between interpersonal trust and generalized trust, faith in government institutions. The evidence for the latter is not as widely available as for the former, nor over a similar time span. But there is support in local and regional studies for this assumption. I however have a sneaking suspicion that those answering this question will have difficulty is separating the institution of government from the actual government in power.
Throughout this lecture we’ve argued the pivotal role played by trust in society. Now let’s try to operationalize that assumption with a series of hypotheses. These hypotheses will follow a track leading from homogeneity in society to levels of trust, from levels of trust to the quality of governance, and from
quality of governance to economic growth and prosperity.
First, we could argue that the more homogeneous a society is in terms of ethnic composition, religious

First, we could argue that the more homogeneous a society is in terms of ethnic composition, religious diversity, and income and wealth equality, the higher is likely to be its level of trust. Large differences within society make it more difficult to engage in activities that allow the creation of bridging capital. The presence of a clearly defined outsider pushes people in associations that encourage inward looking bonding capital.
Second, we could argue that the higher the levels of the trust, the better the quality of governance. In a high trust society, you will allow non-group members to act on your behalf, in the belief that they will act in the interest of society as a whole, and not for the narrow sectional interests of their own.
Thirdly, we could argue that good governance will lead to better economic performance. The fact that governments will operate efficiently and predictably will create conditions of confidence, and alter the planning scenarios for investment. Citizens will be willing to defer immediate consumption in the form of savings or taxation for the certain expectation of returns in the future. Investment
scenarios by business will improve, and the extra capital will act as a transmission belt for economic growth and prosperity.
Of course, we can always reverse the causation. Prosperity allows society to divert more resources to good governance. Economic growth allows greater expenditure by government without competing with current consumption. Extra levels of public provision, especially in education, also contribute to higher levels of trust. Moreover, knowing that institutions work removes the need for bribery and corruption, and this too would filter back into enhancing levels of interpersonal trust.
Confidence in good governance in terms of openness and transparency, as well as the efficient provision of public goods would also reduce the incentive for social groups, however defined, to grab shares for themselves. This again will reduce the relevance of homogeneity as an operational factor in society.
Let’s sum up then. In this video, we’ve looked at the assumptions made about the causes of interpersonal trust. We’ve looked at whether trust levels are stable, and whether interpersonal trust and generalized trust are linked. We’ve also examined the causal chain linking homogeneity to trust to governance and economic progress. And we’ve looked at the reverse causation. In this video, we’ve continually talked about links between factors. Such links may be logical. But the foundation of much of social science, and particularly political economy, is that they are also statistically verifiable. In the next video, we’ll examine how this is done.
2.5 Correlation and Regression
In the previous video, we spent some time looking at the possible causal connections between trust and other social, political and economic variables. In this video, we will see how social scientists try to establish and verify such links. This is a strict scientific process, employing statistical techniques known as correlation and regression analysis.
Let's start then with a list of countries for which we have measurements. We'll call these measurements x and y. These could be anything. It doesn't matter at all. The first question to answer is, is there any connection between the two?
How do we go about it? The first thing we want to do is to plot them on a graph, one on the horizontal axis and the other on the vertical axis. We'll do it twice with different examples. The top graph shows no relation
whatsoever between the two. But in the one below, you can already see a pattern emerging. But how close is that relationship? Do we have a simple way of expressing the degree of closeness? And the answer is that we do,

way of expressing the degree of closeness? And the answer is that we do,
and that relationship is called correlation. What correlation does is to
place a statistical measure, which it calls small r, between the two. And r
can vary from zero, where there is no relationship at all, to r equals 1, for
complete unity between the two measures. Our top graph will be close to
0, the bottom one close to 0.7. If both variables increase or decrease
together, we talk about a positive correlation. We give it a plus sign. On the other hand, if an increase in one is accompanied by a decline in the other, we talk about negative correlation, and we give it a minus sign. In our bottom graph then, we have a positive correlation.
So far, we've made no judgments on what causes what. We can take the analysis further when we make a hypothesis that x is actually the cause of y. When we do this, we automatically make the implicit hypothesis that there might not be any relationship at all between the two. And this is called the Null Hypothesis.
So, let's get back to our graph. We assume that changes in x cause changes in y, and we have the causal variable on the horizontal axis. The next challenge is to draw a line through the graph that provides the best fit for all the observations. I've taken our graph and tried to draw a line, in fact two lines that seem best to fit the data. One is in red. The other is in blue. And they both seem to do the job quite well. But that's not really scientific.
What I need is a formula that will allow me to draw what really is the
best fit line, a line that minimizes the distance between each of the
data points. And the hypothetical line or relationship I'm trying to
establish. Such a formula exists, but I don't need you to know it.
Nowadays, a computer does it for you. This line is called the Least
Squares Regression Line. The regression line is usually expressed as a
formula which that stipulates how high or low on the Y axis the zero
value of X begins, and the direction and gradient of the line. (Note that I've extended the axes since the relationships expressed in the regression line should hold for the missing data as well.)
If I add the results of ten more countries they should show the same pattern, and it should also predict the pattern for any other matching set of data juxtaposing x and y. For example, this could be the data for
the same countries, but for 2013 instead of 2012.
But how sure are we of this relationship? How confident are we that

But how sure are we of this relationship? How confident are we that
this is not a chance result? Well basically, our confidence depends on
the closeness of the relationship, the correlation, and the number and the range of the observations. There are statistical tables for doing this. But nowadays, they're embedded in computer programs. And such tests can confirm the degree of confidence you can have, statistically, in the result, what confidence, for example, that the data for the following year for the same countries would show the same relationship, or confidence that the same relationship would appear with a different group of countries. So, after seeing our r value and the regression line formula, social scientists should also tell you the confidence level. And depending on that confidence level, you can go ahead on the basis of the supposition that x causes y. Confidence level is usually 99%. But sometimes, 95% is okay. And this is all you need to know for now.
But note. First, this is a purely statistical relationship. Second, we still need to check that the initial data is accurate. Third, we need to check whether the hypothesis is plausible. Fourth, we need to ask ourselves whether there might not be a reverse causation. And last but not least, we need to check whether the author gives us the confidence level or error margin in the results. There should always be one, but often there isn't.
Now despite all of this, there are still disagreements among social scientists. Why should that occur? Well sometimes the data is incomplete. How many countries are there in total in the comparison? Is there a bias in the ones that are missing? Often the truth is uncertain. Time after time, variables are entered into the calculation ignoring the fact that they have error margins of their own. And again, the historical periods chosen for comparison might be different, and therefore the quality of the data might have changed in the interval, as it often does.
Another reason is that the data is chosen as a proxy for reality, an artificial construction, labeled as representative for something else. But does it really cover the issue as it's claimed?
So, let's sum up now. In this video, we've examined the way in which social scientists try to establish statistical relationships between sets of variables. We've dealt with correlation, regression and confidence levels. Now, that's not bad, but we need to internalize these concepts, because they're absolutely necessary whenever anybody tells you that more of x leads to more of y. And believe me, they're telling you this all the time.
The above notes are provided by a student of the Coursera course “Configuring The World”, offered by Leiden University. They were produced without compensation, and are the property of the University of Leiden.

Leiden.

Week 3: Society and Fragmentation
3.1 Ethnic Fragmentation
Hi there, and welcome back. Last week we looked at the central idea of trust, and diversity in society. We suggested that diversity would make creating bridging capital more difficult. But this would have negative impact on levels of trust. On the other hand, in a society with an efficient and impartial government, trust would be higher and group differences would matter less. Well, in this video we're going to focus on ethnicity. And we'll see why it still remains such a sensitive issue. And then we'll discuss how it's actually measured.
ETHNICITY & MEASUREMENT We all know what is meant by ethnicity, or do we? Most of us would start with race or color. But after that, it almost immediately spills over into culture. Is an African the same as an Afro-American? No. But they do have the same race. Is a black American the same as a white American? No, but they do have the same culture, although they experience it differently.
Ethnicity then is an identifier, but it's also a self-identifier, and this may have several layers. In many places in Africa you may identify yourself with the dominant culture or you may emphasize your particular sub-group. Ethnicity may also be how others identify you, whether you like it or not. In the Balkans in the 19th century, ethnicity was a matter of history, dialect, music, dance, and even embroidery. We'd all have been quite sweet were it not that these exercises to claims by Greeks, Serbs, Bulgarians, Romanians to the territories of the disintegrating Ottoman Empire. I suppose there was a time in 19th century Europe, when the romantic revival represented a genuine search for an identity and a heritage unspoiled by the Industrial Revolution. But this soon turned into native Nationalism. And any innocence it might once have had drowned in the blood and mud of ethnic conflict. Darwin's theories of evolution also lost their scientific detachment when they were used to profligate the idea of racial hierarchy. And this served to underpin the spread of empires throughout the world in the 19th Century, and justify imperial domination and exploitation. And from Darwin's theories too spread the pseudoscience of eugenics, and improving the genetic features of the human race through selective breeding, sterilization, euthanasia, and later mass extermination. This toxic mix of racial prejudice fueled the anti-Jewish programs of the 19th century, and the racial politics of Nazi ideology, which culminated in the slaughter of millions of innocent victims. It cast a dark cloud over almost any neutral discussion of ethnicity. And if we do need a reminder of the association of ethnicity with mass murder, we have a couple from the 1990s, the Rwandan genocide for example, or the mass ethnic cleansing that accompanied the wars in former Yugoslavia.
So, it's quite a surprise when in 1997 two world-bank economists, William Easterly and Ross Levine,
instructed an ethno-linguistic fragmentation index. So let's have a look at what that index is. Now the index they used was a technique formulated by two economists, Herfindahl and Hirschmann. It's very easy to calculate, easier than to actually pronounce. You line up the variables in a line, and you count

easy to calculate, easier than to actually pronounce. You line up the variables in a line, and you count

each of them in percentages of the whole. Then, you square each one, which means that you multiply each number by themselves, add them all together and divide by a hundred, or 10,000 if you want the results in decimal. The lower the number, the more homogeneous or concentrated the country. But note, some authors then deduct the results from 1, which reverses the relationship, but such is social science for you.
Easterly and Levine argued that ethno-linguistic differences explained a significant part of “Low schooling, political instability, under developed financial systems, distorted foreign exchange markets, high government deficits, and insufficient infrastructure.” So, where do they get their numbers from? Well, the ethnic data came from a Soviet Atlas, translated Atlas of the Peoples of the World, published 33 years earlier, which provided data for 112 countries. However, there's no description of the methodology. A critical appraisal of the atlas in 2008 concluded that it very much underestimates the degree of diversity. For example, it managed to classified Ruanda as ethnically homogeneous. I don't need to remind you again of the resulting massacre of 500,000 to 1 million Tutsis. Well, Easterly and Levine’s was a pioneering study, but it was hampered by doubts over the ethnic data. Typically, nobody seemed to say much about the other variables.
In 2002 another group of economists led by Alberto Alesina, at the time at Carnegie Mellon, returned with a new index. And this one's been widely used in subsequent research, so it's quite an important index. One change they made was to separate ethnicity and language (we'll be dealing with the linguistic components in the next video.) They also expanded the country coverage to 190 countries, and they changed the source for ethnicity from the original outdated Soviet atlas to a range of more contemporary sources. These included the Encyclopedia Britannica, which was a data source for 124 countries, and the CIA Fact Book, which provided another 25, and a variety of other sources made up the remainder. So the sources were more up to date and more comprehensive.
But where do those sources get their data? Well, most of it comes from census returns and other counts. We already saw in the video on population that census counts in Africa were deeply influenced by tribal struggles for power, representation, and resources, and that this could lead to over-counting, sometimes on a large scale. But it's not just in Africa that counts of ethnicity are suspect. In Western Europe, many countries have stopped holding regular censuses, partly because of the resentment toward some of the questions and mostly on race and ethnicity. Another problem with self-reporting is a genuine confusion over the answer in societies where marriages are no longer always within ethnic or racial boundaries, where the respondents' children have been born and raised in the census country. It may be very difficult to answer. What's your nationality? What is your ethnicity? Census returns have little room for the phenomenon of shared identities.
These questions are often shared, sold by legal frameworks. And this introduces another problem, namely that of legal definition. We've already highlighted this again in the case of Africa. But the problem doesn't end there. The Netherlands for example has a very high proportion of nonresidents. The Kingdom even has a foreign monarch, has had for decades, and will have again when the current king abdicates. Why? Well, because Dutch law defines a foreigner as anyone with one foreign parent.
A final question is does it all matter? Does counting the distribution of ethnicities actually say something about their social mobilization, or the discrimination they may experience? Does it perhaps match up more whether ethnicities live in mixed communities, or live in separated groups?
Is it fragmentation that matches or is it domination? We might show up as relative homogeneity, when you're counting the numbers.

So let's sum up all we've looked at in the moment. In this video we've explored the phenomenon of ethnicity, and we've criticized the attempts to measure the degree of fragmentation. In the next video we'll do the same with language. In the meantime, we invite you to view a visualization of a world map of ethnic fragmentation.
3.1.1 Visualization: World Map of Ethnic Fragmentation
In 2002, group economists led by Alberto Alesina, constructed an ethic fractionalization index, based on contemporary sources. In the lecture, we expressed serious doubts about the validity of the whole exercise, but we still feel obliged to show you the results. So, remember, a large measure of caution before attaching too much confidence in what you're going to see. The index is expressed in a range of one to zero, with the lowest number expressing the greatest degree of homogeneity, and the highest, showing the greatest diversity. We have data for only 145 states. The first decile shows the two Koreas and Japan as ethnically the most homogeneous. Hong Kong is also in the top decile, as well as six European states. Also relatively homogeneous are Tunisia and Bangladesh, followed by Australia and Haiti. The next decile includes another seven European states, and China also falls into this segment. We'll now let the rest past your review until the final two deciles. Now, we've reached the ninth decile. One or two Sub-Sahara African countries have appeared before, but they're beginning to dominate, and the final decile is made up entirely of sub Saharan African countries.
3.2 Linguistic Fragmentation
In the previous video we looked at ethnicity and we examined attempts to measure it. We also described the Herfindahl-Hirschman Index. We'll be using this same index in this video. But this time we're going to be focusing on linguistic diversity.
LINGUISTIC DIVERSITY If ethnicity had seemed complicated, language may offer a back doorway into the same sort of questions. Indeed, one author refers to differences in languages as cultural fractionalization. So, having seen the difficulties we experienced in measuring ethnicity, you could

have been forgiven for thinking, that languages will be much easier. All you have to do is to see what language people speak. Well, if only that were the case!
Let's start with the idea of your mother's tongue. Is that the language spoken at home, or the language generally used? Think of someone in a migrant family, first or second generation, who may indeed speak his or her mother's language in the home. But the host language, of course, will be spoken outside. Or think of multinational communities that are genuinely bilingual, as in the case in Wales, where everyone that speaks Welsh can also speak English, and often has to. Similarly in Belgium, many citizens can converse in either French or in Flemish. And in mixed families they may do so at home as well. In Africa, too many language groups are so similar that people can freely switch between them.
That brings us, naturally, to a second problem. When is a language a language? When is it a dialect? This is essential if we're trying to establish linguistic diversity. The usual criterion employed is one of mutual intelligibility. A language does not count as a separate language if it can be understood from another language. But have a look at Scandinavia. Norwegians can understand both Swedish and Danish, and Danes and Swedes can understand each other, although the Danes have a bit more difficulty. And yet they all claim to speak separate languages, and they are always usually listed as such.
So, let's have a look at the evidence then. The paper produced by Alesina and his associates in 2002 used exclusively The Encyclopedia Britannica. From this source they managed to distill 1,055 language groups for 201 countries. They choose to ignore the evidence collected by the Ethnologue Project, a group of linguists interested in preserving languages. In the 2013 edition of their handbook, they listed over seven thousand languages, 7,105 to be precise. We've got an obvious discrepancy between the two sources. Well, fortunately, the Ethnologue offer a further breakdown. They have 682 languages as official languages, officially recognized as such by some national or international authority. They categorize a further 2,500 languages as vigorous, which means they're used in face-to-face communication by all generations. Another 1,500 or so languages are defined as developing. So, these 4,700 languages are spoken by almost 99% of the world's population.
So we don't need the rest to suspect that the encyclopedia's been a little enthusiastic in compressing the language groups. I did a second test for myself. According to Wikipedia, Papua New Guinea, with over 850 languages, is the most linguistically diverse place on Earth. The ethnology project nuances this

850 languages, is the most linguistically diverse place on Earth. The ethnology project nuances this picture a little. 12 of the languages are already extinct, 36 are dying, and a further hundred also are in trouble, all presumably because they don't have many speakers. And because of that, they're unlikely anyway to impact on a fragmentation index, where calculated as such, the small percentage in the total doesn't count for much. Now, the Ethnologue calculate Papua's fractionalization score at 1.990, making it indeed the most fragmented country on earth. Alasina and Associates calculated 0.35, making it less linguistically diverse than the Netherlands.
One way of resolving this discrepancy is to introduce a concept of language distance. It's not a difficult concept to grasp. French and Italian are closer to each other than either of them is to English. But all three are closer to each other than any of them is to Chinese. Now, linguists construct linguistics trees to capture the degree of similarity and differences between languages. By applying criteria of vocabulary and syntax to the world's languages listed by the Ethnologue database, one doesn't have to make a crude distinction between language and dialect. The effect of this basically is
to decrease the diversity in Central Africa where most languages are rooted in different versions of Bantu, and to increase the range in Latin America, where there's a large gulf between the European languages and the native languages stemming from before the conquest. The result of this exercise leaves Papua New Guinea with a score of 0.598 and third in the world, and the Netherlands now has a much more believable score of 0.13.
We could say that we could now conclude the discussion, but there's one more question we have to address. All of this data relates to native languages. None of the data makes any attempt to capture the languages spoken by first or second generation migrants. In fact none of the studies even mention it as a problem. But if languages form a mean of communication in society, and migrant groups don't speak the host language, it's certainly going to damage the formation of trust. One solution in the past was for the host population to translate the information, and in this form, it would act as a way of socialization. When I visited the local history museum in Chicago, I was struck by a poster calling the workers to go on strike. That's nothing unusual, but the poster was in English and in German.
Another solution is simply to wait for the problem to disappear. The second generation would speak their native language at home, their host language outside. The third generation would learn a few sentences to talk to grandmother, and by the fourth, it would be totally assimilated. But this model no longer works. Because transport costs have fallen, every generation has the opportunity to return to their home country. They might even migrate back. As a result there's an incentive in maintaining native language fluency. And again as migrant communities plug into satellite television, they recreate more of their home culture around themselves. And this, again, reduces the incentive to adapt linguistically. Much of the relative linguistic homogeneity in Europe conceals a potential social and economic problem, and one that might undermine the high trust goals that they still have, and they still, for the time being, manage to register.
So let's sum up then. In this video we've looked at the phenomenon of linguistic diversity, and we've looked at the difficulties in defining it and measuring it. In the next video we're going to turn our attention on religion. Meanwhile, we'd like you to look at a visualization of the world's map of linguistic diversity that we've constructed for you.
3.2.1 Visualization: World Map of Linguistic Diversity
In this lecture, we suggested that the index for linguistic fragmentation constructed by Alasina and his
associates was being too drastically compressed in its linguistic categories. We also introduced you to the Ethnologue project, and we suggested that might've gone too far in the other direction. And in the end, we settle for an index that took into account the language distance in this definition, and it's on this

end, we settle for an index that took into account the language distance in this definition, and it's on this index that we're going to focus our attention. The index is expressed in a range of one to zero. The lowest number expressed in the greatest degree of homogeneity, the highest showing the greatest diversity. We have data for only 148 states. The sixth decile is still fairly compressed. The observations fall within a range of 0.05. It includes China and Indonesia, as well as Mexico and Argentina, and Belgium, France and the Netherlands. The next decile covers a wider range, namely 0.1, and here we find Russia and Vietnam. The next decile covers the same range again, virtually 0.1 percent, and here we find Thailand, Miramar, Sri Lanka and Afghanistan. The ninth decile widens slightly. Here are seven African countries, including the Democratic Republic of the Congo, the Central African Republic, Uganda, Nigeria, South Africa, and Kenya, and also in this segment are India
and Israel. The final decile covers a much wider range. It includes, in order of greatest fractionalization Namibia, The Republic of the Congo, Iran, Singapore, Guatemala, Kazakhstan, Malaysian, Qatar, Shad, Proper New Guinea, United Arab Emirates and Bolivia.
Figure 3 World Map of Language Fractionalization - Alesina
Now that you've seen the map of linguistic diversity, measured by language distance, we want to show you by way of comparison, how the map would have looked if we used the Ethnologue data.
3.3 Religious Fragmentation
In the previous video, we looked at the idea of language and dialect. We saw the difficulties in measuring them. In this video, we're going to do the same with a much more contentious issue of religion. But before we start, I want to say a few words. I will not be making any comments on the characteristics inherent in different religions, and whether they're compatible or not with economic growth or democracy. In the West, the sociologist Max Weber writing in 1903 identified the rise of capitalism with the Protestant ethic. It's a departure point still favored by many historians. But these

arguments were countered by those who argued that he ignores evidence of scientific advancement under Catholicism, and that many of the attributes that he focused in religion owed their origins to other socio-economic phenomenon. There's a similar tendency today in some circles to argue that Islam as a religion is incompatible with economic growth or political modernization. I want to make sure this is a view that I do not share. But that doesn't matter. It's not the departure point we're taking in this video. What we're looking at is the degree of fragmentation in religious beliefs.
For most people their experience of faith and the supernatural is intensely personal. It's for this reason that in theory at least the impact on trust might be greater than other variables. The belief in a shared destiny after death from which others are excluded is a powerful force in enhancing bonding capital.

And this belief could be reinforced by participation in religions and festivals. Indeed it's when faith is shared with others that this relationship becomes a religion. So religion may be considered a shared belief system. It's exercised through a pattern of shared rituals.
How do we get the data necessary for an analysis? Well again, the first way is to ask people. But the problem is they may not answer truthfully. Simply because religion is so intensely personal, many people consider it certainly not the business of the state or civic authorities. Other people may choose to hide their religious affiliation for fear of discrimination or persecution. So in the same way as questions into ethnicity were resented, so also questions on religion contributed to the criticism of national censuses.
Another route is to ask questions about the visible dimensions of religions, and to measure participation in religious services and festivals, attendance at the church and the temple. The problem here is that, especially in small communities, religious services also serve as social functions. Alternatively, participation in church rituals may bring with it economic benefits, and nonparticipation may risk exclusion. So, the frequency of attendance may say very little about the depth of religious fervor, or the intensity of religious belief.
There's one source that's more than happy to provide us with numbers, and that's the faith bodies themselves. Almost all of them keep a watch on their own membership, and keep a keen eye on the opposition. The problem with this source is that once one's been accepted into the church, there's little possibility of leaving it. Faith authorities tend to consider you a member for life.
Despite these evident handicaps, the team led by Alesina used as their source for religious fragmentation The World Christian Encyclopedia. The Encyclopedia, however, has been accused of overzealousness on several counts. Firstly, especially in rural Africa, it has the habit of including everyone within the range of a church or a mission as a member of the church. A second drawback is it tends to underestimate syncretic cults. These are belief systems that combine Christian beliefs with cults of African origin. In Bolivia, for example, the encyclopedia records that the population is 93% Christian, whereas alternative sources suggest that 43% actually hold syncretic beliefs. Similarly, in the Dominican Republic, the encyclopedia estimates over 98% is Christian, whereas an alternative source suggests, that just over 50% are. In a similar way, the encyclopedia tends to underestimate animistic cults, which are common in Sub-Saharan Africa. Again, a couple of examples. In Angola, it estimates the percentage of the population following animistic cults at 19%, opposed to 34% from alternative sources. Similarly in Burundi, it suggests that animism was followed by 25% as opposed to 39% of the population in alternative estimates. Despite these drawbacks, social scientists at the moment seem to have little alternative to using the World Christian Encyclopedia as a source for
religious fragmentation. Before leaving the question of religion, there's one check we can make about the importance of religious fragmentation. Presumably if religion is not experienced as an important factor in daily life, then the question of fragmentation will lose its relevance. An opinion poll in 2009 asked exactly this question of citizens in 114 countries around the world. In contrast to the vast polls conducted by the world value survey, which we criticized so much in the previous lecture, this one was limited in scope. And research suggests that this type of simple short survey elicits more truthful and more considered answers. The poll though suggests that 84% of the population do consider religion playing an important part in their lives.
Let's sum up now. We suggested that there are limitations in the sources employed, and we also
suggested that religious affiliation and religiosity are not the same. But what we haven't done is say anything about fragmentation itself. This we've done in the world map of religion that we've prepared for you. And we invite you to view it next. In the following video we're going to look at the issue of income and wealth inequality.

income and wealth inequality.

3.3.1 Visualization: World Map of Religious Diversity
In the lecture, we voiced some reservations on the sources employed in the construction of an index for religious fragmentation by Alesina and his team. But we have no alternative to offer. The index is expressed in a range of one to zero, with the lowest number expressing the greatest degree of homogeneity, and the highest showing the greatest diversity. We've got data for only 147 states. Several Muslim states cluster the more homogeneous ends of the scale. Now, at the end of the scale, the fragmentation of protestant churches is also evident, but whether that's the result of the sensitivity of the source, The World Christian Encyclopedia, is open to question.

Well now you've seen the map of religious diversity. We'd like to pause for a moment at another issue. In the lecture we raised the issue of secularization, and fairly commonly assumed in northwest Europe that religion here is playing ever smaller roles in people's lives. It is often assumed here that this is a good model for behavior elsewhere. Well, there are a lot of gaps in the next map. But, it offers very little support for the spread of secularization theory.
3.4 Income and Wealth Inequality
In the last video, we looked at the fragmentation of society along religious lines. We examined the limitations and the sources, and we also looked at the degree of religiosity. In this video we're going to

limitations and the sources, and we also looked at the degree of religiosity. In this video we're going to turn our attention to the question of income and wealth inequality.
Intellectually, the issue of income and wealth inequality has been on the political agenda ever since Karl Marx was writing in the middle of the 19th century. The 1950s, Simon Kuznets, one of the pioneers in DDP calculations, placed it firmly on the historian’s agenda. He argued that income inequality increases in the early stages of development, but that once a certain level of income has been reached, it starts to decline. In the 1950's, we didn't know much about levels of income in earlier periods, let alone it's distribution. So economic historians started work on reconstructing national accounts. What we found seemed to confirm Kuznets' income equality beliefs. It increases until the eve of the First World War, or the 1920's in the United States. But then the trend was reversed.
Now I haven't traced exactly when income inequality made the transition from academic and policy making circles to the general public. But nothing prepared me for the public reception of an almost 700 page book published in English in March 2014. In the United States, it's been several weeks at the top of the US nonfiction best sellers list. Thomas Piketty's book, Capital in the Twenty-first Century, says nothing that was not known before. Nor is it true that before Piketty arrived on the scene, and I quote him, “No one has ever systematically pursued Kuznets’ work, no doubt in part because historical and statistical study of text records falls into a sort of no-man’s land, too historical for economists, and too economistic for historians.” You can look it up on page 17.
I told Mr. Piketty, when I took up my chair at the Free University Amsterdam in 1980, my colleague Jan De meere was already publishing his results on wealth distribution in seventeenth and eighteenth century Holland, based on tax records and on wills. I'm glad to get that off my chest. I hate this kind of pretentious academic arrogance. So let's get back to Capital in the Twenty-First Century. It quite clearly struck a chord in a public ready to hear its message, having spent five years struggling to climb out of the recession caused by failures in the financial sector. Citizens in western societies are obviously now beginning to turn their attention to the winners of the capitalist system.
Before we look at income and wealth in equality, we have to ask ourselves how do we measure it? When data is particularly fragile and one doesn't have a full range of data across a whole population, you can work with the top or the bottom segments. Sometimes this might be called quintiles, when the population is divided into five equal parts, or deciles when it's divided into ten. So this could lead to statements like, in 1910 the United States top decile received 40% of the total national income, to cite Piketty. Occasionally one might find the two measures being combined. The proportion owned by the top, and the proportion owned by the bottom. In this case we have what is called a quintile or decile income ratio, depending on the size of the segment chosen.
A far more sophisticated measure of inequality is what is known as a Gini Index. It juxtaposes the cumulative percentage of total incomes earned or wealth held by the
population, and the cumulative percentages of people earning that
income, or holding that wealth. The horizontal axis measures the
cumulative percentage of people, from the lowest to the highest incomes. The vertical axis measures a cumulative percentage of income and wealth held, with 100 at the apex, and 0 at the other. Now, if one plots a line at 45 degrees, one obtains a line of complete equality. Anything less than complete equality produces a curve
below the equality line, and this is known as the Lorenz Curve. Now,
the Gini Index is obtained by dividing the total area above the Lorenz Curve, area A, by the total area altogether, A plus B. And the result will be within a range of zero and one. The closer the distribution is to equality, the closer the index will be at zero.

to equality, the closer the index will be at zero.
Before we examine Tomas Piketty's argument, what is it that he measures? Well for incomes, he takes what we call primary incomes. These are incomes before taxes. And they also exclude state- funded payments like unemployment pay, disability payments, and state-funded pensions. These are all transfers that favor the lower income groups. Piketty himself, around pages 246 to 250, suggests that if we were to take this into account, the share of total incomes of the lowest 50% in the United States would rise from 12% of the total to between 17 and 18%.
For wealth, he takes personal wealth. This wealth is inheritable and transferable. But it has the effect of excluding wealth locked up in collective pension schemes. In Switzerland and in the Netherlands the sums involved in these are quite considerable. But then, neither of these countries are included in Piketty's analysis. For differences in tax regime, social security payments and pensions regimes will all affect comparisons between countries and differences over time, particularly between the start of the 20th Century and the start of the 21st Century. I'm not saying that you shouldn't produce these sort of statistical series. But you should always and continuously refer to this bias in analyzing the results.
Okay, what is it that Thomas Piketty suggests? Well first, he focuses not on the Gini index or even the top decile, but of the very top 1%. In the United States in 2010, these controlled 20% of the income. The top 10% together controlled 50%. The comparable figures for Europe were 10% and 35% respectively. These figures for the United States put it right back to where it was in 1900. Not so for the European countries he analyzes, but they are heading in the same direction. But once again, this is nothing new. Joseph Steiglitz was saying the same thing. He also focused on the top 1% in his book, The Price of Inequality, published in 2012.
Second, Piketty seems to argue that the United States is exceptional in the degree of its income inequality. And that might be true among the few advanced Western countries he examines. But the index for the United States is 0.45. The data, especially from lower medium income countries, shows an even more skewed distribution. The latest research in China, for example, suggests that the figure there is 0.55.
Thirdly, Piketty projects a series forward, and here he's more speculative. He argues that most of the increase in inequality comes from ownership and wealth rather than returns from labor. He foresees the return of capital continuing to outstrip the growth of output, and the problem continuing to

grow. But plenty of others do not agree with this analysis. They suggest that the observed fluctuations in capital reflect changes in its market value rather than changes in its volume. I don't. Okay, so for you economists among you, let me say this. The problem is that Picketty uses wealth and capital interchangeably. Now for inequality, you're dealing with wealth. And you're interested in its market value because it measures claims on resources. But for output growth, you're talking about capital output ratios. And this requires a constant price calculation.
Finally, Piketty's gloomy worldview stems from the fact that he's focusing on in-country inequality, and only on a handful of larger, high-income Western countries. Yet thanks to the strong growth of the BRICS (Brazil, India, China and South Africa) and other non-Western economies, inequality on a global scale has probably declined.
So let's sum up now. In this video, we confronted the question of income and wealth inequality. We saw how it could be measured. And because it made such an impact, we tended to focus exclusively on the published book by Thomas Piketty. In the next video, we'll look at the possible impact of being highly divided or highly diverse in a society. Meanwhile, we've constructed a visualization of income and wealth inequality, and we invite you to look at it next.
3.4.1 Visualization: World Map of Income Inequality
In the lecture, we voice some reservations about the recent book by Thomas Piketty. His data was limited to a handful of rich, western countries. What he suggested was that using a GINI index, labor income inequality in Europe was 0.26, and that the United States stood at 0.36. That left the question of what the picture is elsewhere in the world.
For several years, the World Bank has been assembling information on poorer countries. The results are based on income data from households, derived from household surveys, not from national tax records. The compilers of the index admit that it is what I would call a dirty data set. But they argue that if they aim for perfect compatibility, they'd have to eliminate too many countries. And that if they tried to correct the data in some way, they might be inserting even more biases than the ones they were trying to eliminate.
There are two main issues remaining. The first is that there's no distinction between single earner households, and multiple earner households. And the second is that there's no account taken of non- income benefits, such as free education, and primary healthcare. The compilers themselves therefore caution researchers who use these data to interpret the results carefully. We've taken the data only from
the years 2010 and 2011, which gives us 60 countries. The index is expressed in a range of 0 to 100, with the lowest numbers expressing the greatest degree of homogeneity, and the highest showing the greatest diversity. We plotted the range for you to see. We've also indicated the Piketty estimates for Europe and the United States. And it's clear immediately that many less developed countries are in even

Europe and the United States. And it's clear immediately that many less developed countries are in even worse position than the USA, which was a cause of such concern to Thomas Piketty. Let's scroll through the map (next page). Already in the first decile, we're leaving Europe behind us, assuming, of course, that non-income transfers in Europe are more developed than those say in Belarus or Kazakhstan. In the fourth decile, we meet the GINI index for the United States. Its equivalent here would be Cambodia. And, again, you should argue that US welfare spending is more developed than it is in Cambodia. By the seventh, you can see Macedonia entering here. And in the next decile, you'll see Malaysia. But from here on, the greatest inequality levels are concentrated in Central and South America, and in Sub- Saharan Africa.
3.5 Inequality, Fragmentation, and Trust
In the last video, we examined income and wealth inequality. In earlier videos, we've also looked at fragmentation along ethnic, linguistic, and religious lines. So now what I want to do is examine how they relate backwards to the phenomenon of trust. And remember, it's always easy with hindsight to view a situation of a dysfunctional government or economic stagnation, and to find some societal disconnect that can be used as an explanation.
SOCIETY AND TRUST The object of exercising quantification is to establish whether there are gradients in inequality and fragmentation, and whether these are statistically comparable to gradients in the performance of other variables such as trust or governance or growth. These majors must also be remembered, also reflect the choice of mechanism, whether we're interested in general inequality, or whether we're focusing on polarization at the extremes, or whether we're interested in populations that are mixed, or whether they are living geographically separate. In each case, there'll be a separate measure available for the calculation. Bear in mind too, and this is very important, that the trust data is suspect, that the governance indicators all contain error margins, and that the national income data, and
therefore the growth data for poorer countries, are all extremely dubious. And much of the analysis is about poorer countries. So, put all of these observations and reservations together. It'll be no surprise to learn that surveys of the literature confirm the different fragmentation indices and different samples of countries and different time periods all yield different results. So I suggest that we dispense with the

countries and different time periods all yield different results. So I suggest that we dispense with the statistical models and exercises and concentrate on the mechanisms by which these phenomena affect levels of trust in society. But just because we ignore the outcomes of statistical analysis does not mean that there is no real mechanism underpinning these societal relationships. It’s just that we don't actually have the statistics to prove it.
Okay, let's start with income and wealth and equality and work backwards towards trust. Income and wealth and inequality may be expected to influence trust levels in several ways. At one level, the poor in society may look at the rich with a degree of powerlessness, not to say resentment. And this may prompt them to disengage from civic organizations. Alternatively, if a society is more equal, its members will look at each other with a degree of mutual recognition. And this will generate an image of a shared fate. And this shared image may make its members feel more disposed towards taking common action to solve problems. And this in turn, will promote trust.
If we look at other elements in fragmentation, then different ethnic groups may exhibit different material cultures that express themselves in different styles of clothing, in different foods, and in prohibitions on certain types of food. This will react directly on trust by reinforcing images of difference. Similarly, differences in languages will inhibit communication, most obviously in direct person to person exchange. But the differences will go deeper. Different language groups will have access to different news media, will get exposed to different political messages. And this again will enhance and perpetuate cultural differences and inhibit the construction of trust.
Finally, if we look at religiosity, the links of trust can run in two directions. There's a positive side. Religious teachings emphasize the benefits of generosity and reciprocity towards others, and they may disapprove of antisocial behavior like dishonest and theft, and these teachings will be internalized and pass through the generation. In such, a way they'll contribute to expectations of similar behavior in others. Another mechanism lies in the repeated attendance of rituals, which helps create a shared sense of community and therefore also to enhance trust. On the other hand, it's possible to elicit other mechanisms that militate against trust creation. The first is that religious teachings prescribe a route to salvation for its members, and provide the believers with a sort of sacred umbrella that's not shared by non-believers and members of other faiths. And this will create a clear divide between insiders on the one hand, and outsiders, reinforcing bonding trust at the expense of bridging trust. The second link runs through the attitude of the outsiders themselves towards a spectacle of groups united by exclusive belief systems, and engaging in strange and unfamiliar rituals. There'll be a tendency to mute or to view members of other religions with suspicion, distrust.
Now before leaving this lecture, there's one issue that needs to be addressed. Almost all the analysis that we have examined assume that any quality and diversity are endogenous. That means that they can be explained entirely from within the explanatory model. But this isn't always true. Income inequality, for example, may derive purely from the operation of capitalist market forces. But they may equally be the outcome of societal preferences deriving from other historical and cultural factors. It could be that these factors explain not only the differences in redistributive policies, but also the differences in trust levels that produce them in the first place. Equally, it's possible that some of the ethnic and linguistic diversity may have stemmed from geographical consideration, that early in history, for example, land endowments and resources determined whether populations settled and acquired layers of cultural attributes, or whether they migrated, and formed a more dispersed pattern of ethnic identity.
On the other hand, many ethnic differences within countries, especially in Africa, came not from
something internally in the definition itself, but by the definition of national borders. And these were drawn by the imperialist powers, in the 19th century with scant regard for tribal composition of the areas. In addition, the impact of ethnic divisions may have been not so much in the statistical variables of fractional polarization, but the way in which colonial institution favored some tribes above others, or

of fractional polarization, but the way in which colonial institution favored some tribes above others, or favored settlers at the expense of the existing populations.
This brings us to our final consideration. The impact of ethnic, religious and linguistic fractionalization depends, to some extent, on real or perceived differences in welfare. What we need, but what we don't yet have, is international comparative data integrating income and wealth inequality with these different variables.
So let's sum up then. In this lecture, we've looked at diversity and inequality in society and we've traced their relationship to trust. We've seen that trust is intimately bound with the question of governance. And so next we're going to turn our attention to the phenomenon of governance and its link to economic growth, welfare and prosperity.
These transcripts were provided by a student of the course “Configuring the Global Economy.” They were done without compensation, and remain the property of the University of Leiden.

Week 4: Governance
4.1 Good Governance
Over the last couple of weeks, we've been looking at concepts of trust and fragmentation, and their relationship to each other. In this series of lectures, we're going to look at the origin of the concept of governance and its application to the problem of development aid. We'll look very closely at attempts by the World Bank to define governance and also to measure it. And then in three separate videos, we'll look at detail of three dimensions of governance: democracy, the rule of law and corruption. And we'll link them to issues of trust, growth and economic development.
Before we can do anything of this, we have to define what we mean by governance. So here comes the official definition, generally speaking: it describes the processes by which institutions provide outcomes. Those institutions could be tribes, villages, businesses, corporations, governments, international organizations, or NGOs. And the outcomes can be in the form of physical goods and services, laws, rules and regulations and enforcement mechanisms. In our case, the focus is on states' government, so we can define government as a process by which national governments decide upon their goals, and deliver the goods and services expected of them.
In the case of good governance then, the state should do some of the following things, actually do all of them. It should take citizen's demands into account when formulating its policies. It should do this in an open and transparent manner. It should provide goods and services efficiently and effectively, and shouldn't be siphoning off funds into the pockets of those supposedly providing these services. It will
regulate outcomes and enforce its laws and decisions fairly, efficiently, and without bias and favor.
Bad governance, of course, is the opposite. In the state of bad governance, the state will do the following, for example. It will implement policies that are in the interests of the minority, or in the

following, for example. It will implement policies that are in the interests of the minority, or in the interests of a clique. It will deliberately hide and falsify its decision making processes. It will implement efficiently only policies in its own interest. And it will make sure that it creams off surplus cash whenever it can. It will apply regulations so as to favor its clique and the highest bidder, and protect them against the enforcement of law, and it will bias decisions against its opponents and use the instruments of state as weapons against them.
So why should any of this concern the World Bank? Well, it was only after the Second World War that states began giving money to other states that didn't happen to be their colonies. Immediately after the end of the Second World War, the United Nations began an aid and relief program, which included the provision of raw materials needed to jumpstart the war ravaged and war damaged economies. This was followed in 1948 by the American aid program to Western Europe, known as the Marshall Plan. About the same time, the World Bank was created to provide structural development funds to poorer countries.
In the 1950s, the US began bilateral aid programs towards its allies, whilst Russia did the same. Russian aid was initially directed towards China, and later Africa. Towards the end of the 1950s, when the accent of the Cold War shifted away from military confrontation, the Americans called on their Western allies to share the aid burden both bilaterally and through their contribution to the World Bank.
In all of these years, the main analysis of development economics had focused on what was called the ‘two gap model’ to explain underdevelopment. The less developed countries were caught with two shortages, investment capital and foreign exchange, and foreign aid would alleviate both shortages. The favored strategy for aid was to direct funds towards promoting industrial development, preferably large scale projects. Eventually, and no time span was specified, the benefits would trickle down to the rest of the population. But by the end of 1970s and the 1980s, one overall conclusion was becoming obvious. Aid was failing to promote growth. At this point of time, two developments began to converge that would change the aid paradigm.
1. First, there were a series of financial crises in Latin America. These countries had been growing, but in fits and starts, and prone to repeated crises. The response of the IMF was to link its financial aid to demand for government reforms.
2. Secondly, sociologists began to argue that a major problem with the aid effort was one of ownership. The recipients did not identify themselves with aid projects. Aid should be more a question of partnership, leaving more initiatives with the recipients, and this shift in perspective placed a new emphasis on how aid was managed. It called for more attention to be paid to the social conditions at the local level, and greater efficiency and effectiveness at the national level. Efficiency was defined in sense of value for money, no corruption. And effectiveness was defined in the sense of becoming viable, viable in terms of competing in world markets.
In 1989, the term ‘Washington Consensus’ was first coined to describe this new approach. It represented a set of policy measures favored by the IMF, the World Bank, and the American government. Among the main measures it advocated were the following: control of the size of government spending, the phasing out of subsidies to inefficient sectors, the freeing of controls over trade and foreign investment, the introduction of pro market reforms, and the protection of property rights. This new emphasis reflected a major change in the world economy. Globalization was accelerating. Back in the late 1940s and early 1950s, there had been very little private investment available. Government funded aid programs formed part of the solution. In the 1980s, following three decades in which dollars had hemorrhaged out of the United States, and following the relaxation of capital controls, the world economy was awash with capital. If countries could find the key to unlock foreign direct investment, they could tap into a pool of funding that far exceeded the amounts of foreign aid that was available by a government. Good governance was to be that key. So all one needed now was to find some way of measuring progress

governance was to be that key. So all one needed now was to find some way of measuring progress towards it.
Let's sum up now. We've defined the concept of governance, and we've framed some expectations about good and bad governance. We reviewed the history behind foreign aid thinking. And we saw how the emphasis changed from the provision of investments funds, to a concern with governance. In the next video, we'll look at how the World Bank attempted to quantify differences in governments among nations.
4.2 Measuring Governance
In the previous video we introduced the concept of governance, and we saw how good governance became important in the discussion on foreign aid effectiveness. Now we're going to examine how the World Bank, which has as its mission the funding of development program, how it attempts to measure international differences, and the quality of governance.
But first, let me start with a little story. In 1982, Daniel Kaufmann was awarded his doctorate in economics from Harvard, and he joined the World Bank. Since he'd grown up in Chile and Latin America, his first mission was to the slums of Columbia. There he witnessed first-hand the paradox of how such wealth and such abject poverty were able to coexist in the same country or in the same city. The answer, he perceived, had less to do with economics than with the abuse of power. Our missions to Africa served to reinforce his conviction. The problem is that the World Bank is an international body under the United Nations. This makes it difficult to openly criticize the political system of a member state. After the collapse of the Soviet Union, Kaufmann was sent to the Ukraine to help oversee the reforms being put into place following the end of state directed central planning. And again he was impressed with the rampant corruption he encountered there. So he and his team began to develop indicators that helped define and measure the differences in forms and context of corruption. By this stage, Daniel Kaufmann would become director of the World Bank Institute, a research body affiliated to the World Bank. And in 1996, it published the first annual World Bank Governance Indicators. Kaufmann's tactic was to conceal highly sensitive political questions in technocratic language. In this he was only partially successful. However, it did allow him and his team to continue.
So let's have a look at what these indicators were. There are six separate indicators and they follow the political process from the formulation of policy, to its execution, and implementation. It's a three step process, with two indicators for each step. Inputs into the policy process are measured by voice and accountability, and by political stability and the absence of violence. The process of making and implementing policy is measured by government effectiveness and regulatory quality, and the outputs are measured by the rule of law, and control of corruption. The index is scored from plus 2.5 to -2.5, with zero representing the world average for that particular year. Those are the indicators. That's sort of how they're measured now.
The first thing to note is they are composite indices. They combine different dimensions into one number. The indicators they use are survey sources, but unlike the world value survey, these aren't opinion polls, and they are not random. The sources contain the impressions and the anecdotal evidence of outsider leaks and NGOs. So a lot depends on their impartiality. That's the raw material going into the mixture. We've got a mixture of impressions and evidence, corruption is getting worse, or on average, I've paid 10% in bribes.
The second step is to put all of these responses into some sort of coded rank numbers. For example, one is good, seven is bad. There again, there's another subjective element.
Next the various components need to be weighted for their relative importance. We've already seen some

Next the various components need to be weighted for their relative importance. We've already seen some of the problems that can arise from this when we looked at the human development index.
Kaufmann and his team avoided this problem by not assigning equal weights, but to give extra weights to those observations that clustered close together, and therefore less to outsiders. But this
has three effects. (1) It makes the whole process less transparent. (2) It places a lot of weight on your confidence in the World Bank team. (3) It does allow for the measurement of statistical error.
Let's have a look at this last point. Any statistical example allows for the calculation of the measure of uncertainty or an error term, but the governance indicators are unusual because they actually do so. What it reveals is that especially at the lower end of this spectrum, error margins are surprisingly large. At the interactive site, viewers are shown an outcome of the chosen indicator and its range of error. It's set at a standard 50%. In other words, there's a 50-50 chance that the result lays outside the range. The site also offers the viewers the alternative of a 95% certainty. It shows an even larger range. And there again, there's a 50-50 chance that it lays between those two observations. This wider bracket easily covers 10% of the countries surveyed, so it's not really surprising that the World Bank urges caution when using the results. Unfortunately it's a warning that's all too often ignored.
Now, I like the World Bank indicators. Their site gives links to all of the sources used. It's a treasure trove for B.A. and M.A. papers. The team's also very quick to address criticism. Some critics call this attitude defensive, but I think it's always better to have two sides of the debate. But that doesn't mean that I don't share some of the criticisms that have been made.
The first is that centering the indicators on a different average every year makes the comparison over time very difficult, other than in terms of relative change.
Second criticism is that the sources have a bias towards business. The bank would reply that their job is to grow countries, so this requires a primacy of economic aspects, but trust is not just a question of getting the economics right.
And thirdly, the bank is also biased towards market oriented policies. It doesn't like state enterprises. It doesn't like labor market interventions which often offer an alternative and viable path to growth. We'll come back to these criticisms later.
Now, one final point. Although the World Bank indices are important as a focus of debate, and in the articulation of policy, the World Bank itself uses a far wider and nuanced range of data when it makes its policy, and its site offers this data free and easily accessible. (editor’s link: http://data.worldbank.org/ )
So let's sum up then. In this video we've seen how the World Bank came into the business of measuring governments. We saw the structure of the indicators and the inputs, processes, and outputs, and we looked at how the indicators were constructed and formulated, some reservations and criticisms in their construction and their use. Over the next three videos, we'll examine in more detail the three indicators most used by social scientists, voicing accountability or democracy, the rule of law and the control of corruption.
4.3 Democracy and Growth
In the previous video we saw how the World Bank came into the business of measuring governance. We saw how the indicators were constructed, and we voiced some quite considerable criticisms. Well, in this video we're going to focus on the question of democracy. We'll look briefly at the World Bank Indicator for Voice and Accountability, as well as other indices for democracy. And we'll see how democracy is supposed to affect economic growth.

Let's start with the World Bank Indicator for Voice and Accountability. It suffers the same drawbacks as the other indicators. It employs over 20 international and regional sources. And the result is comprehensive, perhaps too comprehensive. There are so many elements included that it will be difficult for a social scientist to disengage which bits of the index are supposed to have what kind of effect. This means it's also very difficult to extract policy recommendations from the indicator.
There are alternatives available. The oldest index is that first published by Freedom House, an American organization founded in 1941. The index has been published annually since 1973. It's a composite index with fixed weights. It's made up of political rights, which make up 40% of the index, and civil liberties, which takes up the remaining 60%. It's based on a poll of experts, who are asked 25 questions, answered on a range of zero to four. Based on these scores, countries are ranked on a scale of one to seven, where the lowest score represents the greatest freedom. The first problem with the index is there are only 32 experts that are listed. This places doubts of the range of expertise that they're supposed to represent. The second one is that having carefully calibrated the possible answers to the questions, the results are pressed into a range of only seven categories.
Another alternative is offered by the Democracy Index, compiled by the Economist Intelligence Unit. This, too, is a composite index, but with 5 components, each counting 20%. Here, civil liberties count for 20%, election processes and pluralism for another 20%. Both of these, then, are elements in the Freedom House index. It then includes political participation, political culture, and the functioning of government. It too is based on experts’ opinions to 12 questions in each category, each with a simply yes-no answer. Results are expressed on scale of 1 to 10. The outcomes of all these indices will be reviewed in a separate visualization, which you can view after this video.
Why should democracy help economic growth? Well, the first link is between the granting of political rights and the granting of economic rights. Most important of these are property rights, the right to the use of one’s own land, capital and labor and rights of contract the guarantee against sanction contracts once entered into are enforceable. Once free from arbitrary charges and confiscations, and protected against the willful abuse of agreements, individuals will be freed of the necessity to hold secret reserves, and they'll be able to invest those in the future.
The second link is that if citizens are able to decide on their own decision makers, they will also exercise control over their actions, making sure that they'll act on their behalf, and not fulfill their own agendas or line their own pocket. This in turn will ensure the better provision of public goods. These are tangible goods and services, and intangible services such as regulations and control. They will also ensure that democratic forces control the actions of other powerful groups in society, businesses slurping subsidies or trade unions demanding protection.
Finally, one assumes that if access to and participation in the political process is open and transparent, and that as a result, government discharges its functions fairly and effectively, it would make ethnic, linguistic and religious differences less important politically. As a result, it will reinforce levels of generalized trust.
On the other hand, do we need democracy for growth? Authoritarian straight rule, however undesirable from a western viewpoint, is also capable of delivering economic growth. Just look at China over the past two decades. Economic rights can also be enforced by right wing dictatorial regimes, such as those that characterize Chile in the 1970s and 80s, and Peru in the 1990s. State led
industrialization may still provide growth through policies that are not market enhancing. It may be possible that they're not sustainable in the long run. But at least when and if the revolution comes, we'll be against a backdrop of higher levels of economic development.

So the final question we need to ask is whether social scientists have actually established any links between democracy and growth. The answer is no. The strongest link is between democracy and levels of income. Richer countries tend to be democratic. But this might simply mean that they can afford it. For the rest, there are weak statistical links in just about any direction you want.
Why is this (why are there no links)? It's partly because social scientists use different measures for democracy, and they use different economic models. Secondly, they ignore the margins of error contained in the democracy index. And just because one isn't specified, doesn't mean that the error doesn't exist. And thirdly, it's also because, as we've seen in the first lecture, per capita GDP estimates, and therefore growth estimates for the poorer countries, are notoriously unreliable. This will undermine any correlation and regression exercise. Finally, you have to recognize that the process of economic growth is so complex, and contains so many components, that it's difficult to isolate one variable from the rest.
Allow me if you will one anecdote to explain this last point because it's going to come up again and again in the other video. One of the debates in economic history in the 1960s was whether America needed the railways in the 19th century to grow, or could have grown without them. And the answer was that it didn't. And soon economic historians were showing that they weren't really necessary in Germany, either, nor in Italy, nor in any of the other countries. Nor were they needed in Czarist Russia. One historian suggested that all of the traffic that had been carried by railways could all have been conveyed by horse and wagon, until another historian calculated that this would require the entire grain acreage of Russia just to feed the horses, let alone the people. Motto of this story: in any complex process, the contribution to the whole of any single component is likely to be small, and therefore very difficult to capture statistically.
So let's sum up then. In this video we've looked at various indices for democracy, and we've analyzed the path by which democracy would be expected to influence growth, but we also saw the statistical verification was weak. In the next video we'll do the same for the rule of law, meanwhile we'd like you to explore a visualization of the world map of democracy that we've prepared for you.
4.3.1 Visualization: World Map of Democracy
In the lecture, we looked at the world's level of democracy through the World Bank's Governance Indicator for voice and democracy. We also looked at a couple of others. We rejected the Freedom House index, but we did have some sympathy for the democracy index constructed by the Economist Intelligence Unit. But this coverage was too wide. So what we're going to do here is visualize the world using the World Bank data, and show just one last map by way of comparison of the Economist's results.
The index is expressed in a range from minus 2.5 to plus 2.5, the best performances being positive, the worst, negative. Zero represents the world average for 2012. Data's available for all the 152 countries. The first decile is all western states in Europe, North America and Australasia. Although the United States, Germany, France and the United Kingdom are all in this decile, the remainder is dominated by wealthy small or medium-sized states. In the second decile, we still retain a European
dominance, but South America, with Chile and Uruguay, and East Asia, with Japan, Taiwan and South Korea, now appear. The third decile increases the regional representation. We see the large states like India and Brazil up here, and towards the end of the range of the fourth decile, we pass through the world average (see map on the next page).
The Economist Intelligence Unit (EIU) has constructed a composite index with five components, each counting for 20%. As we said in the lecture, strictly speaking, only two of these, electoral processes and political participation, cover the same ground as the voice and accountability indicator. So we shouldn't really expect a strict match between the two sets of results. And if you look closely, there's some

really expect a strict match between the two sets of results. And if you look closely, there's some slippage between the decile, but there's no real great shift in the picture.
4.4 Rule of Law and Growth
In the previous video, we analyzed the paths by which democracy could be expected to influence growth. But we saw that the statistical verification was weak. In this video, we'll do the same for the rule of law. We'll see how the rule of law fits into our expectations on economic growth.
The very first point to note is that the World Bank indicator for the rule of law is not actually about the rule of law as most of us would define it. It does not measure human rights. It says nothing about the independence of the judiciary, or the principal of equality before the law. It says nothing about the right
to a fair trial, and fair punishment. And it does not imply that all citizens are treated equally. It's all about economic rights, about contract and property rights. And the World Bank makes no secret about this. All the sources and all of the question are biased in that direction. And as we saw in the last video, the World Bank is committed to promoting market led economic growth. It's constructed an index that

World Bank is committed to promoting market led economic growth. It's constructed an index that answers this particular need. My complaint's not about the construction of the indicator, but about the labeling, we would have avoided a lot of confusion if the index had been labeled differently, call it the ‘rule of economic law’, for example.
If we want an index for the rule of law as we understand it, we have to look elsewhere. Now this gap can be filled by the World Justice Project, an independent group of lawyers founded in the United States in 2006. It publishes its own annual rule of law index. The index again is a composite one, based on eight separate elements, weighted equally. To be honest, just as the World Bank voice and accountability indicator we reviewed in the last video, this index is a little too comprehensive for its own good. Half of the index includes what we'd happily understand under the rule of law, e.g., limitations on government powers, fundamental rights, access to civic justice, and an effective criminal justice system. But the other half of the index lumps together items considered separately by the World Bank governments indicators, i.e., order and security, open government, the absence of corruption, and effective regulation. The index mixes results from its own opinion polls with expert polling, both of which are conducted on an impressively large scale. But the results are only available for 99 countries. The final results of both indicators are available in a separate visualization. You can look at after this video.
Why should the good observation of the rule of law promote economic growth? The logic starts with what is often the most difficult point, an independent judiciary. The appointment of judges should be transparent, and at least, not too biased by political preference. If the judiciary's not independent or neutral, the rest quickly becomes a sham.
Now in turn, the independent judiciary ensures that legal institutions function efficiently and effectively. This also applies to the economic sector. So it expects all the benefits to flow that arise from the protection of property rights and contracts, that we reviewed in the last video.
There's a third link that's been suggested, that runs directly through foreign investment. Foreigners especially like transparent and predictable judicial systems. It removes one source of uncertainty in their projections into the future, and it encourages them to invest more and earlier than they would otherwise have done.
Finally there's a feedback link, through levels of trust, especially if you believe that constantly observing the efficient management of judicial affairs socializes people into more trusting modes of thought and behavior.
The question now arises, does any of this work? Can social scientists demonstrate any relationship between the rule of law and economic growth? And the answer is, well, yes and no. One study did suggest there seemed to be a link between a narrow business interpretation of the rule of law and economic performance in poorer countries, and the link between economic performance and a wider interpretation of law in more developed countries. But the authors themselves warned that the results were extremely sensitive to the time periods and the countries included. Well, no surprise in that. For the most part, however, the weak links are weak, or nonexistent.
As usual, we could look for the faults firstly in the immediate rule of law indicator. Do they capture everything? Are they too amorphous? Do they ignore the local level? Well, they do. We can also ask is economic growth too complex? And we can also look at the data they use, the data that they're focusing their attention on the poorest countries on the planet. Social scientists tend to ignore the fact that the data
is suspect economic growth data. And that's the poor current data. Earlier data is even more suspect than the rest.
So let's sum up then, in this video we have seen how the World Bank looked at the indicators for the rule of law, and we have looked at alternative indicators, and we have seen how the rule of law could be

of law, and we have looked at alternative indicators, and we have seen how the rule of law could be expected to influence growth. Not surprisingly, we saw that the statistical link was weak.
4.4.1 Visualization: World Map of Rule of Law
In the lecture, we looked at the world's levels for the rule of law for the World Bank governance indicator. We saw that it was primarily focused on business or economic law. We also looked at the World Justice Project, which contained more dimensions, possibly too many, but we would have used it for the basis of our analysis, were it not for the fact that it only covers 98 countries. So, what we'll do, therefore, is visualize the world using the World Bank data. Just remember there is a bias in the interpretation. Then by way of comparison, we'll use the World Justice Project in our final map.
The World Bank index is expressed in a range of minus 2.5 to plus 2.5, the best performances being positive, the worst negative. Zero represents the world average. Data's available for 152 countries. Many of the countries that topped the voice and accountability map are also in the first decile here, where they're joined by Hong Kong, Singapore and Cameroon. Cameroon's is surprising - it was at the bottom one third in the previous map, so I suppose it just underlines the fact that autocratic regimes can deliver business friendly environments. The second decile holds fewer surprises. The third decile picks up a lot of oil-rich Arab states. We had Qatar in the previous decile. And now we can add Oman, United Arab Emirates, Kuwait, and Saudi Arabia. In the fourth decile, we pass through the world average.
The World Justice Project has constructed a far more comprehensive index of eight components weighted equally. Although it ranges a little wide, it is much more representative of the rule of law than the narrow focus of the World Bank. Unfortunately, it's missing data for over 15 countries, including all of western Asia, which has all the Arab states, almost all of middle Africa, half of West Africa, and a few states elsewhere. And they're not all potentially bad at the bad end of the spectrum. For some reason, the list of the missing includes both Switzerland and Ireland.
(both maps on next page for comparison)

4.5 Corruption and Growth
Hi there, in the previous video we saw how the World Bank looked at indicators for the rule of law, and how the rest of us looked at it, and how the rule of law could be expected to influence economic growth, but we also saw that the statistical verification was weak. Well, in this video, we're going to do the same

but we also saw that the statistical verification was weak. Well, in this video, we're going to do the same for the control of corruption.
Let me start then with a story, as it was told to me, by way of illustration of the mentality behind corruption. I was in the northwest corner of China, Xinjiang. I was teaching there. I didn't often have
the chance or opportunity for private conversations. But one afternoon, the director of one of the institutes took me for a drive to the Heavenly Lake, a local beauty spot. We had a very pleasant and wide ranging discussion that touched on the question of corruption. Imagine you are a business man coming to see me, he said, and I am a senior official in the ministry. This is what I say to you. “I am a senior official. I have much power. But I am a government employee and I'm not paid much money. You have lots of money, but you have no power. Without my approval you're going to get nowhere. But with my signature on this paper, you have a chance to make even more money, lots more money because my action has allowed you to do so. But why should all that money go to you? Should I not be allowed to share even a little of it?” In fact, he added, I wouldn't even have to say that. You and I would both know the game we are playing.
Corruption is difficult to measure, because it involves the taking of bribes and favors. And it's almost always conducted in secrecy. Often, it's highly illegal, and it's highly sensitive. Note for example, the indicator is called the control of corruption, not simply corruption. This name somehow implies that states are at least trying to control it.
The usual approach to measuring corruption is through business opinion surveys, since it involves those paying or receiving bribes. But here, there are even more problems than usual of comparability. After all, how much is a business willing to admit to? The World Bank uses these sources to compile its own indicator, in the way with which we've become familiar, and the last two videos we've given you an alternative indicator. But this time there's no reason to believe that the results will be any different. There is one indicator, a very authoritative one, that the Bank itself uses. That's the indicator prepared by Transparency International, its Corruption Perception Index.
Transparency International was founded in Germany as an independent organization, dedicated to the elimination of corruption. It started publishing its own index in 1995.
One criticism levied at both indices is that they focus on business corruption, usually the payment of bribes for contracts, or small regular extortion's, to smooth everyday business. But they both ignore the equally damaging phenomenon of political corruption. This can range from jobs for party members to secret funding of candidates in return for support for favorable pieces of legislation or fat, juicy contracts.
The second criticism is that it focuses attention on the bribe takers, not the bribe givers. It's usually the businesses in these squeaky clean western countries at the better end of the rankings that are the ones paying bribes. And of course it's in the banks of those western countries where the illicit gains are deposited. In a small effort to expose this side of corruption, Transparency International has also constructed a bribe payers index. And we've included this, together with the corruption results, in a separate visualization. You can look at after this video.
A final criticism is that we're dealing with a very Western definition of corruption in condemning practices that may not be considered abnormal elsewhere in the world. A prince in his own country uses
his position to smooth your way through the difficulties you may encounter trying to secure a lucrative contract. Does he not deserve a small fee for his services?
So how does corruption actually influence growth? Well the obvious answer in the narrow sense is that it increases the cost of doing business. It reduces profits and therefore reduces the incentive to invest. It

increases the cost of doing business. It reduces profits and therefore reduces the incentive to invest. It acts as a form of tax.
Now, if that was all that was involved, business could simply include it in their calculations. Far more corrosive is a form of corruption where the incidence is unpredictable, in the import of central machinery or competition for contracts, or the prolongation of a particular nonsense. In this form, corruption acts as a major infringement of property rights.
Another factor is that when considerable sums are creamed off from government contract, it actually reduces the provision of public goods. You get fewer roads. You get un-modernized facilities for your tax money, or for your foreign aid, and this too inhibits growth.
The final root is a feedback loop into trust. Persistent exposure to the routine of corruption is extremely damaging to the reputation of institutions, and it must have an effect of undermining levels of generalized trust in societies.
Among all of the governance indicators, corruption is the only one that produces significant results, at least when related to long-run growth. Its impact is particularly strong in lower income countries, where, unfortunately corruption is most endemic.
How can one reduce corruption? Well, the obvious answer is to eliminate its causes. But sometimes those are deeply embedded in the political culture, the political elite culture of a country. Another answer is to increase the chances of detection and to enforce stricter penalties, but this merely transfers the problem to another dimension of good governance, efficient institutional controls and open and transparent government. A final suggestion then is to increase public sector pay. But this is exactly what poorer countries cannot afford to do.
Before we leave this whole problem, let me make one final, personal observation. In 19th century Europe, corruption was also widespread, and the movement towards reform came first locally, from the improving working classes and the middle class. It emerged with public parks, with civic libraries, anti- drunkenness campaigns, and the intolerance of local officials and cliques improperly enriching themselves. As these local movements coalesced into national political parties, so corruption on a national scale was also tackled. It's easy to explain, but it's difficult to replicate.
So let's sum up then. In this lecture we've seen how the World Bank became convinced of the centrality of good governance, and the question of economic development in poorer countries. We've seen how the World Bank defined good governance, and how it measured it. And we've looked at some of the dimensions of good governance and how it could be expected to impact on good economic growth. We also looked at three dimensions of good governance and how it could be expected to impact on economic growth.
4.5.1 Visualization: World Map of Corruption
In the lecture, we looked at the world's level of corruption through the World Bank's Governance Indicator. And we saw no reason to consider any other alternative. It does incorporate the famous Transparency International data in its own work. The index is expressed in a range from minus 2.5 to plus 2.5, the best performances being positive, the worst negative, zero represents the world average. Now the range is different from the previous two in a couple of interesting dimensions. The
world average shifts at top, so that fewer countries are above it. But the top performers in this indicator do much better compared to the average than in the other two maps we've been looking at. And also by the way, those three data sets we haven't. On the other hand, the worst performances are less far away from the average than they are in the other indices. Data is available for 152 countries. There's a great deal of information to be teased out of comparing the performances of a country or a region, along these

deal of information to be teased out of comparing the performances of a country or a region, along these different governance indicators. But I'm afraid you'll notice, the very top and the very bottom will remain fairly constant throughout.
The above notes are provided by a student of the Coursera course “Configuring The World”, offered by Leiden University. They were produced without compensation, and are the property of the University of Leiden.

Week 5: Economic Development 5.1 State Failure
Last week we saw how the World Bank became convinced of the centrality of good governance in the question of economic development in poorer countries. We saw how it defined good governments, and how it measured it. We looked at how social scientists try to link some of the dimensions of good government, democracy, and the rule of law and corruption to the question of economic growth. This week were going to focus our whole attention on the question of economic development and development assistance.

focus our whole attention on the question of economic development and development assistance.

We'll start with a look at the concept of state failure. After all, this is the nightmare scenario of a failure to accomplish economic development. In the next lecture, we'll look at the question of who gives aid to whom and why, to quote the title of a well-known article. But since that follows the big money flows, we'll look in the third lecture this week at the eight main donors, not in terms of absolute size, but in terms of their generosity in relation to GDP. And then, in the fourth lecture, we'll turn our attention to the crucial question of whether you can promote good governments through the medium of foreign aid. The current fixation with state failure dates from the end of the cold war and the disintegration of the Soviet Union, and problems at the same time in Haiti, Somalia, Sudan, Liberia and Cambodia. A failed state, it was argued, posed three challenges:
1. A challenge for its own citizens, deprived of the public goods they could expect from a state.
2. A challenge to the neighbors that might be caught up in any spillover effects, not least from the refugees,
3. The challenge to the international communities in still fate of the lawless space, where crime and especially after the bombing of the twin towers in New York in September of 2001, crime and terrorism could flourish.
Yes, after 9/11, failed states were labeled the most powerful threats to American security. And the World Bank was right there to help. It established a low income countries under stress program (LICUS for short) to tackle the question of states failure. And once we have a problem, you can be sure that someone's going to try to measure it.
One of those prominent measures is a Failed State Index compiled jointly by the influential magazine Foreign Affairs and the Fund for Peace. It was first published in 2005. It's a composite index comprised of 12 components, with an average of 14 separate elements in each. Half of the components refer to social and economic indicators, and the other half to political and military indicators. The compilers of the index tell us that it's constructed by data mining, searching millions of documents using sophisticated computers to quote the results.
Data mining is a useful technique involving the searching and analysis of vast quantities of data, often without questions in advance, to throw up rather unexpected relationships or hot spots for further research. But I'm less sure of its use in compiling an index, where everything is reduced to one number. But let's get back to the index itself.
Each component is given a score out of ten. The scores have been added, so that the maximum is 120. The higher the score, the more failed is the state. It will be no surprise for you to learn that Finland is the least failed state in the world, and Somalia the worst. There are several criticisms that we can make of the index:
The first problem lies in the source of the millions of documents, the BBC, the CIA, CNN, New York Times and National Public Radio. They're all English language, American or British sources. Analyzing millions of documents might remove the danger of systemic bias, but not when the selection itself is biased.
Secondly, there's no attempt to define failure. Is it measured in terms of sovereignty, i.e., the state fails when it cannot control the presence of troops or insurgents? Or is it measured by the ability of the state to fulfill its functions in the provision of public goods?
The failed state index solves this problem by incorporating all of these dimensions. But in solving this problem, it creates another. The index is awfully cluttered. Some of the elements could be seen as consequences of failure, e.g., refugees, out migration, external intervention, that reduce state legitimacy. Some of the elements, on the other hand, provide only a context. At least three, and possibly five of the 12 components are actually derivatives of poverty. But being poor doesn't automatically lead to state failure. And yet, fully 70% of the countries covered in the index are now classified as being less stable, or worse. This
conflation of context cause and consequence in the same index limits its ability to predict state failure. But that is the ambition of the index, to do exactly that, and therefore, to help prevent it.
Well, let's have a look. As late as 2011, there were 47 countries more likely to fail than Syria. As late as 2013, there were 116 countries in greater danger of failure than the Ukraine.

A better but less well known index is the Global Peace Index, constructed by an independent think tank allied to economist intelligence unit. It measures the peacefulness of a country internally, which approximates the stability or fragility, and externally which refers to the state of its international relations.
Only the first part of the index is relevant to us, and the authors kindly released the results to us for this video. It too is a composite index, but based on a limited number of verifiable sources. You might not like what's used, but at least you know what's used. The main advantage of it is much more real. It deals with things like crime, death, terror, and the activity of the internal security forces, all the kind of things that we would associate with an endangered state.
So, in this video we've described the rise of state failure as a policy concern. We've looked at two approaches to measuring it. Let me say one thing. State failure is a complex issue. In almost every case, what could not have been anticipated in advance could always be explained afterwards. So, I'm not really surprised at the weakness that tends to measure the chances of failure without knowing the outcomes. In the next lecture we're going to turn our attention to the international aid effort.
5.2 Who Gives Foreign Aid, To Whom and Why
In the last lecture, we saw how, in the 1990s, state failure emerged as a policy concern, and we looked at two attempts to measure it. In this lecture, we're going to examine the question who gives aid to whom, and why? This was the title of an article published by Alberto Alesina and David Dollar back in 2000. Back then, I liked the title so much that we used it as the title of a conference on the history of foreign aid that we held right here in Leiden.
We'll concentrate our analysis on official development aid. Officially, it is aid given by governments. It doesn't cover aid donated directly from citizens. Development aid is quite distinct from humanitarian aid, which is directed at famine relief and refugee assistance. Alisina and Dollar took the aid data covering the period from the early 70's to the early 1990's, and compared the direction of aid flows with several other variables. These included trade openers, democracy, civil liberties, colonial status, foreign direct investment, per capita income at the start of the period, voting patterns in the UN, and the position in the Middle East. There are some criticisms we can make of the variables themselves. Some of them were crude and others were suspect. And if you really want to take your GDP PPP estimate seriously in 1970, then you have to note that the price comparisons that year were based on a grand total of only ten countries.
So what did they discover? Well, the results were heavily influenced by the fact that three quarters of the aid is from just five countries, the United States, Japan, France, Germany and the UK. What Alisena and Dollar tried to do is to see how far the aid flows diverged from expected distribution. They suggested that being open and democratic were good. If you are open, it would result in 20% more aid. And being democratic would increase your aid flow by almost 40%. More important still was to have a long colonial past. This increased the aid flow by 87%. In fact, being a non-democratic colony received more aid than the democratic non-colony.
The same held true for openers. Countries voting in the United Nations with Japan received a massive 172% more aid. Interestingly enough, voting with the USA made no particular difference. But this was because the American aid flow is dominated by its involvement in the Middle East. If you were Egypt, you'll receive 480% boost in your aid flow. And being Israel was best of all. You received over 400 times the expected aid.
Now, on the basis of this analysis, Alisina and Dollar concluded that one reason why aid didn't seem to work was because aid flow was determined more by political and strategic considerations than with the promotion of politic and economic reforms. But, that was all over a decade ago and in a period still shaped overwhelmingly by the Cold War.
There've been two recent articles published in 2011 and 2014 that follow the same questions posed in the original Alisina and Dollar article. They've extended the period covered, and they expanded the number of variables investigated. So how has the passage of time affected the conditioning of aid flows? Well, aid now does seem to flow more to the poorer countries. Countries with better human right record also get better rewarded, but not equally so. The flow of aid tends to follow trade flows and the voting in the pattern of the

rewarded, but not equally so. The flow of aid tends to follow trade flows and the voting in the pattern of the United Nations. And this suggests that the donor self-interest is still an important consideration. Finally, and this comes from the earlier analysis, aid flows disproportionately to countries already receiving aid from others donors. There's a sort of darling effect. Being able to attract aid helps reinforce the confidence in other donors in giving it.
The most recent article published in World Development in 2014, earlier this year, focuses on changes in the conditions and perceptions in the donor countries, rather than the situation in the recipient's country. What do they say? Well, they suggest that as the donor countries themselves became richer, so their aid effort relative to their GDP tended to increase. They also found that aid patterns, once established, tended not to alter much. And they explained this by a mixture of bureaucratic inertia and the medium term nature of many of the project, and also a desire to be seen as a stable pattern. This study rejected any darling effect. In fact, this suggested the opposite, namely that when one country was committed, the others tended to steer clear. This disagreement could be the result of a better coordination of aid efforts in the more recent period, as well as possibly some methodological differences. They found no support for a former colony effect, but again, this could be because the variables were radically different. And finally, and interestingly, they found no relationship whatever with the war on terror.
Okay, let's sum up now. We've looked at the recent literature on aid allocation. All of these studies use standard techniques of multi variant regression analysis. So we've got no weird, self constructed indices to contend with. Nevertheless, we have suggested some of the raw data is weak. So, although the insights are interesting, they should be treated with caution. But there remains one big problem. The analysis is determined by the size of the aid flows, and therefore, effectively, by the behavior of the big five donors. And their motivation is imputed from their perceived behavior. But while the big five are large aid givers, they're not generous aid givers. None of them get close to the 0.7% of GDP aid target established by the United Nations. So in the next lecture, we're going to concentrate on the four countries that did reach that target in the 1970s and early 1980s and which since then, have never fallen below it.
5.3 The Real Aid Givers
In the previous lecture, we looked at the recent literature on aid allocation. We saw how the analysis was determined by the behavior of the big five donors. We also commented that the motivation is imputed from their perceived behavior. In other words, what they did is what they intended to do. In this lecture, we're going to look at what I call the real aid givers, those that regularly hit the 0.7% of GNI aid target established by the United Nations.
Where did that 0.7% target come from? For much of the 1950s, the largest aid giver had been the United States. It had been responsible for the Marshall Plan. And it had provided most of the initial capital for the World Bank. By the end of the 1950s, it still provided almost 40% of bilateral development aid. But by the end of the decade, three things were beginning to change. Firstly, the United States was experiencing balance of payments problems. Secondly, African countries were gaining their independence, so there were more countries looking for aid. And thirdly, the Soviet Union was entering the foreign aid field, and securing footholds of interest in Africa.
As a result, the American government called on its allies to share the aid burden. Coincidentally, the United Nations declared the 1960s to be the ‘Development Decade’. It developed an aid target for 1% of gross national income by 1970. The result was disappointing. The figure reached by the OECD donor countries in 1970 was 0.34%. So the UN now revised its target to 0.7%, a doubling of the actual level reached in 1970. The target's still there. You can see it enshrined in the millennium development goals. 20 years of development assistance have yielded very little by way of results. Aid recipients were still mired in poverty, and many large scale projects were proving economically
unviable, running under capacity, and expensive to sustain. But by the 1950s, 1960s, new ways were opening
for a new strategy. The so called green revolution based on new hybrid crops, insecticides, and fertilizers were demonstrating that investment in rural areas could be worthwhile. You don't have to wait for the trickle- down effect to relieve world poverty. And the World Bank now shifted its emphasis to a more rural strategy, aimed at relieving the poverty of the poorest.

In 1975, Sweden and The Netherlands were the first countries to meet the 0.7% target. Norway's aid effort hit

In 1975, Sweden and The Netherlands were the first countries to meet the 0.7% target. Norway's aid effort hit that target the following year. And Denmark reached it in 1978. And they've stayed there ever since. Meanwhile, the OECD effort as a whole has managed to fluctuate around 0.3%. At this stage in the 1970s, Norway and the Netherlands, especially, were at the head of a movement to establish an economic order. This would redress the systemic bias against the trade returns of poor primary producing countries. Without being too cynical, I think that this was a triumph of rhetoric over substance. I doubt whether either of the governments would have been prepared for the sacrifices that a new economic order would entail. By 1980 anyway, all four countries had also met another U.N. aid target, namely directing 0.15% of their Gross National Income towards the least developed of the poorer countries.
Why out of the whole wide world should these be the only countries to consistently maintain such a high level of commitment to foreign development assistance? Several answers have been suggested. Firstly, following their experience in the Depression of the 1930s and in the Second World War, there was general support for a strong international order, both for security and for economic interests. Secondly, it's been suggested that they needed a Third World approach to sort of counterbalance their otherwise pro-Western security and economic policies. Thirdly, there was and still is strong public support for such policies. This is derived from the influence of the churches and the mainstream social democratic ideology. So adopting a high profile on third world issues served both domestic and foreign policy interests.
This link between domestic and foreign policy is interesting. All four countries were heavily dependent on foreign markets. All four countries had large redistributive welfare budgets. The link between these two factors has been suggested by the work of Peter Katzenstein. He suggests that large social sectors were a way of sharing the risks of adjustment necessary for smaller states like these to remain competitive. One consequence is that they're all relatively egalitarian societies. And not surprisingly, they also taught most of the analysis of interpersonal and generalized trust indicators. And as we've seen, they're also extreme generous aid givers.
The link between these factors has been offered by Robert Ruggie. He suggested that foreign policy aims were a reflection of domestic policy approaches. That's interesting. But there's also a reverse flow.
Looking in the mirror of one's own foreign policy reinforces its self-image and strengthens its domestic institutions. After all, giving aid makes you feel good about yourself. A colleague of mine, an anthropologist, has described the Dutch aid effort in terms akin to a religion. The 0.7% norm is an article of faith. And there is a whole church made up of NGOs and other dependent lobby groups determined to keep it there.
One final reflection by my good friend, Helga Farrow, professor of international history in Oslo. In the world of big states and hard policy, he said, it's a relatively inexpensive way of getting to the top of what is really a pretty good list to be at the top of.
In this lecture then to sum up, we described how the UN came to set a target for the foreign aid effort. And we saw how only four countries reached that target and adhere to it for the next 30 years or more. We looked at some of the motives ascribed to them. But we stayed at the interface between economic structures and domestic policy, and the relationship between domestic and foreign policy. In the next lecture, we'll look at the question of aid effectiveness, and we'll ask ourselves whether it's possible to grow good governance on the back of the aid effort.
5.4 Aid Effectiveness
In the previous lecture, we saw how the United Nations established development aid targets for the donor countries. We examined the real motives behind the four countries that actually reached the norms in the 1970s. It actually stuck to them ever since. We also highlighted the link between economic and governance structures, and between foreign and domestic policy.
In this lecture, we're going to look at whether development aid is effective, particularly in respect of the efforts of the World Bank to encourage better governance. We'll analyze this question at three levels:
1. The evidence from econometrics studies,
2. a comparative study on efforts to encourage voice and accountability,
3. and finally a local case study in water management and reforestation in West India.

3. and finally a local case study in water management and reforestation in West India.

If there's any agreement in the literature, it's that aid is indeed most effective in countries with good governance and strong institutions, and that making governance reform a condition for aid does not work. The logical conclusion is that donor aid strategy should concentrate on countries with good governance and strong institutions. But if everyone did this, it would mean abandoning the very poorest people, living in weak and corrupt states, the very ones who need the help the most.
This brings us to what is termed the ‘Micro-Macro’ paradox. It was formulated by Paul Moseley in 1987. This means that aid can often be seen to help local populations in very positive ways, even economically, but it doesn't show up in macroeconomic statistics. More aid did not seem to lead to more growth. It could also be that poor stagnant economies received more aid because they needed more. That's what aid giving is supposed to be about. But it is equally likely that the econometric models used were incapable of capturing and disaggregating the variables involved in explaining economic growth. And finally, it could be because the growth data itself is rubbish, but you'll never hear anybody saying that. Meanwhile, many studies now shifted to local perspectives. They added to a substantial literature of microeconomics success that it was beginning to pile up. Studies casting doubt on whether development aid had any effect on growth were also building up. Indeed the literature is now expanded so far that there are models for analyzing the results of the models. And these new brands of literature suggest that, in the long run, aid does indeed contribute to growth after all, lots of aid, and very little growth.
Let's leave this range of inquiry and turn to the question of governance. Can aid agencies create the conditions for good governance? In 2007 and 2008, the U.K Department for International Development published the results of the efforts of seven donor countries to promote voice and accountability. In a total of 67 development projects in which they have participated, the donor countries were Belgium, Denmark, Germany, Norway, Sweden, Switzerland, and the United Kingdom. They concluded that even at a micro level, the ability to improve voice and accountability were limited and relatively isolated. They doubted whether any of the local successes could be scaled up. They also found no evidence that improved voice and accountability had made any contribution to the alleviation of poverty or any other of the millennium development goals. So, why did the efforts fail?
They listed several problems. First, they made a misguided assumption, that voice and accountability was even wanted, and that more effective institutions would somehow become more accountable. Second, it proved unable to find a strategy or even an entry point in the complex interaction of power relations formal and informal institutions. Third, there was a mistaken assumption that it was indeed one unified but unheard voice from the poor, and that at least among the poor, all voices will be equal. This proved very far from the case. Finally, they'd assumed that there'd be time to construct governments’ frameworks without bringing the time table for the implementation of the projects into difficulties. These are pretty chilling conclusions. This is really what happens. David Mosse was employed as an anthropologist on a British development project in the hills of west India. The project had two aims, to improve water management in the villages, and to reverse the deforestation of the neighboring hills that had led to the water problem in the first place. Mosse was attached to the project as an anthropologist, but he turned his skills to analyze his own development workers. In 2005, he published the research in a fascinating and painfully honest book entitled Cultivating Development. How can I best convey it's essence to you? Well, analytically, Mosse divided his team into what he called sociologists and engineers. The sociologists wanted to make sure that everyone was involved in the decisions so that the project would have local ownership. The engineers wanted to dig irrigation canals and plant trees. The local headman in the village wanted his work done first. So the sociologists held their meetings, and meetings, and even more meetings, especially for women who didn't turn up at the other meetings. The engineers waited, and they wanted to start work. And the headman wanted everything to start with him, which was exactly what the sociologist did not want. And the villagers who had to keep living there long after everybody had left didn't want to upset the headman. So, after interminable delays, what actually happened? Well, the headman got his work done first. The villagers got their water management. And the
reforestation was forgotten. And the governance of the village went on just as before.
It's difficult not to be depressed when reading the literature on aid effectiveness. But even though academic literature is layered with resigned cynicism towards foreign aid and the foreign aid industry, it's difficult not to be impressed by the vision and determination of those working to improve the life of their fellow man. Next week, we'll turn our attention to the international framework of institutions designed to manage global

week, we'll turn our attention to the international framework of institutions designed to manage global problems. We'll move away from the context of the problem oriented approach and enter the world of Critical Political Economy.
The above notes are provided by a student of the Coursera course “Configuring The World”, offered by Leiden University. They were produced without compensation, and are the property of the University of Leiden.
Week 6: Globalization
Lecture 6.1 Globalization: The Debate
This week, we're going to configure that world in terms of globalization. So in this first video, we're going to discuss what the term actually means. And we're going to look at the debates surrounding it.
Before we do that, I want to read you an extract from a book by John Maynard Keynes, called The Economics of the Peace (1919). Keynes was a member of the British delegation to the Peace Conference after the end of the WWI. He wrote a biting book on his experience there. But that's not why I want to read it. I want to read this particular element from it. Let's remember though, that Keynes is a very privileged man from a very privileged sector of society, from an incredibly privileged nation. And he writes:
“What an extraordinary episode in the economic progress of man, that age was that came to an end in August 1914.” Then he goes on and he describes what actually it was like. “Inhabitants of London could order by telephone, sipping his morning tea in bed,” (I told you he was from a privileged class) “the various products of the whole Earth in such quantity as he might see fit, and reasonably expect their early delivery upon his doorstep. He could by the same moment, by the same means, adventure his wealth in the natural resources and new enterprises of any quarter of the world, and share in its prospective fruits and advantages. The goods secured forthwith, if you wished it, cheap and comes with all means of transit to any country or climate without possible through other formality, could dispatch his servant off to get the necessary money and then proceed abroad to foreign quarters without knowledge of their religion, language or customs,” (the British never seem to change,) bearing on him coined wealth upon his person. (And he'd be very upset if anybody interfered.) “Most of all, this state of affairs was normal, certain and permanent, except in the direction of further improvement. The internationalization of this world was nearly complete in practice.”
That is Keynes' view of globalization on the eve of the WWI. If you search Google Scholar for the year 2013, only for that year, for books and articles with ‘Globalization’ in the title, spell it with a Z and an S.
You get over 2000 hits. Try it in Chinese, you'll get 1600 options, 110 in French, 50 in German. But if we move back in time before Google was even invented, people like me had to search through published databases. My favorite then, was the Journal of Economic Literature. It's now available electronically. If you go there, you'll find that there's not been one single article with the word Globalization in the title, published before 1984.

published before 1984.

Definition of Globalization. Now globalization is the sort of term that everybody understands, but where no two people will agree on a definition. Is it a question of more international contact or connections, or does it imply a greater dependence or interdependence on those international contacts? Is the word ‘international’, as we've used it here, sufficient? Or should we distinguish between local and regional, and the more truly global? Should we distinguish among the different dimensions of globalization, the economic dimension, the cultural sphere, and if there is a governance? And if it is economic, to what should we attach most importance, to trade, to business, to labor, to communication? And if it's governance, where should we be concentrating, incorporation among governments, on the role of international bodies, or on the influence of civic society and the NGO's? And finally, within all of this, where does it leave the nation state, the unit on upon which we've lavished so much attention last week, and which remains the focus of our course?
In 1999, a team led by David Held, of the Open University, published a book called Global Transformations, which described the parameters of the discussion, and which still largely holds true for today. They divided the different authors in three separate camps: hyperglobalists, skeptics, and transformationalists. The first disagreement among them is on the very nature of the globalization experience.
What is Globalization? Hyperglobalists see the present globalization as something new and truly unique. They would argue that market forces have undermined state control over national economies, and are weakening the authority of nation states.
Skeptics used to argue that current globalization resembled that of the earlier period, 1870-1913. And they argue that in some respects this was even more truly global than what we're experiencing today. This is the passage I was referring to in the piece I read to you from Keynes. They also consider that market forces can still be brought under control, if, and this is a big if, the main international actors can agree on collective action.
Now the transformationalists sit in the middle, they say globalization is more complex than mere economics, or the freeing of markets. It also involves sociological and cultural factors. They refuse to commit on the direction of where it's heading, or whether the process is reversible or not.
Is Globalization Beneficial? Not only is there disagreement on the nature of the process, they also disagree whether it's beneficial or not. At one extreme again, you get the hyperglobalists. They argue that markets decide the optimal use of the world's resources, and that globalization is bringing the world's citizens a wider range of products, at ever lower prices. Poverty exists, they concede, but because governments persist in maintaining protection, and deprive their citizens of benefiting fully from the developments of globalization. And with the market come the other benefits of Western civilization, such as Democracy and Human Rights.
The skeptics on the other hand, argue that processes already gone too far. It's been driving down employment and wages in developed economies, and it penalizes the vulnerable in less developed countries. Far from enriching countries, the penetration of Western culture is homogenizing local cultures and aggravating the conditions for cultural conflict.
Control by Nation States. Another source of disagreement is on the ability, or even the desirability, of nation states to do anything to change the course of events. Calls by skeptics for states to protect
the vulnerable, have to confront a reality. The perspective legislation or higher welfare expenditure, will lead to capital reallocating itself to states with lower standards, and lower taxation, taking even more

lead to capital reallocating itself to states with lower standards, and lower taxation, taking even more jobs and income with them. Hyperglobalists and others, argue that the nation state is already being bypassed. The world economy is coalescing around production and service hubs or agglomerations. And these are already functioning independently of the states that are supposed to be controlling them. Transitionalists and some skeptics would respond that globalization is not making the state irrelevant. But it does place a new premium on what the state supplies in terms of public goods and good governance.
Summary. Now let's try and pull all of this together. We've seen how difficult it is to define exactly what should be understood by Globalization. And we've sketched the outlines of the debate of the nature of the process, the benefits it's supposed to confer, and the role if any, for national governments. There are no unambiguous answers.
What do I think? Well, you should never ask a historian to predict the future. But when the future becomes the past, a historian will explain why it was always inevitable. And with that thought, I'll leave you until the next video, where we'll explore globalization in the field of trade.
Lecture 6.1.1 Visualization: World Map of Economic Globalization
Hello again and welcome to this next series of visualizations. In this one we're going to map the world in terms of globalization. There are several indexes available, but the one we've chosen is made by the Swiss Economic Institute in Zurich, and is known by its Germans initials of K-O-F. This latest version was released in April 2014 and provides data for 2011.
The index is what we call a composite index. It's made up of three components, economic, social and political. This kind of index always brings problems. Do we really want these three components lumped together? Do we want them weighted in this way? Are we happy with the individual elements that make it up? Now for this reason, we're going to focus on only one part of the index. And since in this course, we can only handle the economic components of globalization, it's here that we're going to concentrate.
The economic globalization index has two components weighted equally. Half deals with international economic transactions, and half with restrictions. I could quibble with some of the measures in the weightings. For example I find it strange that trade should be less than less of a quarter of the actual flows, but count for over half of the restrictions. But basically I can live with the index as it stands. The index is listed from 100 to zero. 100 is the most globalized. The gradient's fairly even except for the extreme top and the extreme bottom, which means that there are probably going to be overlaps where the deciles cross, but it's unlikely that countries will jump more than one category.
So which are the most globalized countries? Well, Singapore comes out on top, followed by Ireland and the Netherlands. There are also eight more medium size European states, in order, Belgium, Hungary, Finland, Austria, Sweden, Slovakia, Portugal, the Czech Republic and Denmark. The next decile sees a much wider geographical distribution. Europe still contributes five countries. But elsewhere, there's Malaysia, New Zealand, Australia, Canada and Peru. The third decile sees this widespread continue. But now Italy and France make an appearance.
Now, let's move down quickly. Don't forget, you can also slow down the presentation, or even pause at a part of the map you find more interesting. The fourth decile's still very diverse. The fifth decile continues this diversity. But we're now halfway through. It's only in the next decile we find the United States. The
seventh decile sees Russia and Brazil. The eighth sees the appearance of both China and Japan. And the last two segments see India, Pakistan and Bangladesh as well as Argentina. Nepal, Ethiopia and Burundi close the list as the least globalized states. I don't know about you, but for me this was the least predictable of the maps we've seen so far.

The details of the data we've used are in the database that accompanies this course, and we've also included the results of the social and political sub-indexes. But take a very careful look at their composition before you use them too confidently.
Lecture 6.2 Trade
Hi there. In the last video, we looked at the concept of globalization. We examined the debate on the nature of the process, on its benefits, on the role, if any, for the nation’s state. In this video, we are going to be looking at the national trade. We’ll look at the barriers that can hinder trade growth and we'll look at some of the explanations of why some countries experience more trade growth than others.
Criticisms of Trade Statistics. Now, there are, first of all, several problems involved with international trade statistics. The first one is that whereas national income is the sum of values added, where the only part that counts between the transactions is the additional value, in international trade, the total value of a product is counted every time it crosses a border. A second problem is that when a country exports a finished product to another country, a proportion of its value may well have originated further back down what we call the value chain.
Let me give you one true example. If the Chinese exported iPod to the United States, it will cost $150. That figure will appear in China's export statistics and in its balance of payment statistics. But only $4 of
that value is added in China. The R and D and the design values originate in the United States, and the parts come from the USA and Japan.
A third problem is that trade is only counted when it crosses a border. In Africa, where cross-border trade is often unrecorded, this can lead to major distortions. But finally, there are bigger problems in Africa. Official trade statistics have frequent gaps. Only six countries have a complete series of annual
statistics dating from 2000 to the present, and many of the other statistics don't conform to international definitions or standards. In such cases, the gaps have to be filled from the statistics of other countries, and that's really far from satisfactory.
Government Policy Trade Barriers. So, why does international trade grow? Well, many reasons, but

world trade can't grow if it's discouraged or disadvantaged by high cost penalties that operate to discriminate against foreign goods. In the past, most of the literature placed the emphasis on trade barriers erected by government policy. So let's have a look at some of these.
The first of these is tariffs, taxes levied on imports. Once tariffs have raised the price of imports relative to domestic goods, it's left for supply and demand to determine how much is bought or sold. In Western Europe, and the West in general, the average tariff on industrial goods was just under 3%, but the West did charge about 11% on agricultural products. Among developing countries, tariffs are generally higher, and the highest is in South Asia. It charges 13% on industrial goods and 30% on agricultural products.
The next barrier is import quotas. These are limits placed on imports regardless of prices or demand. In Western Europe, most of these were phased out in the 1950s, but in the 1970s, they were reintroduced for textiles. Elsewhere, they still persist.
A third measure is what we call foreign exchange controls. These are often introduced when countries come into balance of payment difficulties or have speculative movements of capital, but they are powerful weapons of trade manipulation. If an importer can't get his hands on foreign currency to pay for the goods, very often, the transaction cannot take place.
The fourth official control, a so-called non-tariff barriers, usually in the form of technical barriers, such as minimum safety standards. They could be hygiene regulation against infected food product. They may have a legitimate function, but they will always have a negative impact on imports, and often deliberately so.
And finally, there are rules on what are called government procurements, or purchases made by governments. Many governments only buy from domestic producers, arguing that their hard earned tax revenue should be best used to boost national output and employment.
Transaction Costs. In addition to government imposed measures, there are other impediments to international trade. These are called transaction costs, and they measure the other incidental costs incurred in imports. The first of these obviously are freight costs, although of course, those needn't necessarily be higher than the costs of moving a good inside a country domestically. The second are time costs. For example, if you want to import a container into a high income country, it will stay in stock for an average of ten days. In Uzbekistan, Chad and South Sudan, the average delay was over three months. And the final cost is the cost of assembling the administrative documents. And these are also far higher, for example, in Sub-Saharan Africa than in OECD countries. This may have
afforded some measure of protection against Western competition in Africa, but these same high costs strangle their own exporters when they wish to break into world markets.
Motor of Growth. A lot of attention in the literature concentrates on the removal of barriers to trade. But once they are reduced or out of the way, the real motives of growth lie elsewhere. One way in which trade can grow is to have fast growth in one's traditional trading partners, especially if this growth there is transformed into import demand. Since much of this trade is neighborhood trade, this dynamic has been translated into gravity models of trade. This adds distance, connectivity and cultural similarity to the explanation.
Another way to perform comparatively well in international trade is to have a domestic production structure that's concentrated on products (specialization) in which world demand is growing fast. In that case, all you have to do is to keep a constant market share. If you have a concentration in the product which has fast growth, obviously then, you'll experience faster growth of international trade.
The final way to experience relatively fast trade growth is to increase one's competitiveness. The only

The final way to experience relatively fast trade growth is to increase one's competitiveness. The only sustainable way to do this is to produce more goods for the same amount of inputs, and this requires access to more capital and to better technology. One short cut to get that is through foreign direct investment.
Summary. Let's pull all of this together now. In this lecture, we've been looking at the international trade. We've looked at the barriers to trade and we've looked at the explanation for differential trade performance. In the next video, we'll turn our attention to foreign direct investment. Meanwhile, we invite you to view the visualization of the map of world trade that we've prepared for you.
Lecture 6.2.1 Visualization: World Map of Trade
Here we're going to map the world in terms of international trade. We'll start by looking at the largest countries engaging in world trade, both exports and imports. And we'll also look separately at merchandise trade, which is trading goods and trading services. We'll then pause at the main inter regional flows. And finally we’ll map the
world in terms of trade dependence of individual countries. Remember, you can always pause the visualization at any time, and look at the information in more detail.
Let's start by looking at these bar charts
of world merchandise exports. I've
taken the top 30 countries, because
beyond that we're dealing with small
percentages below 1%. However, all
the information used in preparing these
charts is in the database. The
immediate striking point in the chart is the position of China, as the world's leading exporter. More to the point, although you can't see it, China is the world's largest exporter of manufactured goods. As you slide down the list, we pass the largest industrial countries, interlaced with energy exporters,

Russia, Saudi Arabia, United Arab Emirates, and then increasingly after Mexico, some of the larger developing economies begin to appear. Note however, that Hong Kong and Singapore owe their high position largely to the proportion of re-exports in their totals.
If we turn now to merchandise imports (below), we find the United Stated in the leading position, followed by China, and then the world's industrial countries. Again, Hong Kong and Singapore are high on the rankings, because of re-exports. Totals differ slightly, partly because imports figures also include freight costs, and partly because of timing. Goods sometimes leave ports long before arriving at their destination. The world market for commercial services is not smaller than that for merchandise trade. Here, the export trade is dominated by the United States, the UK, Germany, and France, which together account for over 30% of the market. Only then do we get China and India, and after that, the list tends to be dominated by the developed countries until we reach the 25th place, where we get Thailand and Turkey, Brazil and Poland.

If we turn to imports, it's interesting that the largest exporters of international services are also their largest international consumers.
Now we come to an interesting map (above) of the direction of world trade, albeit for 2011. It was prepared by the WTO, and it shows inter-regional trade. But be very careful. It omits intra-regional
trade. That's trade between countries within a region. For example, the large trade flows within Europe, and within the European Union are missing. And so are two other large trade flows in Asia. So what you see in the map covers slightly less than 50% of the total of world trade flows. But it's still interesting. The map shows the dominance of Asia-Europe, and Asia-North America trade flows in both directions, and the energy dependence of Asia on the Middle East.

In the next set of maps, we've got data for 141 larger countries. We're going to exclude Hong Kong and Singapore, because of the large element of re-exports in their data. That leaves us with 139

countries. Let's look at the importance of trade in individual economies. What we've done is we've added the exports and imports together, and expressed the total as a percentage of GDP. Note though, that there is an element of double counting. So, because of this, we add both values, and they can be very, very high. Even after eliminating Hong Kong and Singapore, the trade dependence can reach over 180% of GDP. As we scroll through the decile maps, there's not a great deal that emerges by way of a pattern, either in terms of regions or in terms of development levels. So, what I'm going to do is, just to highlight the appearance of the 30 big merchandise exporters that we saw at the beginning of the visualization. In the first decile, we get the Netherlands, Belgium, the United Arab Emirates, and Malaysia. The second decile, we actually get Korea. In the third decile, we get none. In the fourth decile, you find Germany and Saudi Arabia. By the fifth, the half-way mark, we can add Switzerland, Sweden, and Mexico. So, where are the rest? Well, they're not in the sixth, the seventh only unearths Norway. The 8th decile, with the dependency now dropping below 50%. We find, in order, Italy, France, Spain, China, and the United Kingdom. The 9th decile, gives us Indonesia, Russia, and India. And it's only the last decile, that we discover Australia, Japan, the United States, and Brazil.

Lecture 6.3 Foreign Direct Investment
Hello again. In the last video, we concentrated on International Trade. We looked at the nature of trade barriers. We examined the possible motives of trade growth. In this video, we're going to look at the trends of International Foreign Direct Investment, or FDI as it's called, look at the problems, its measurement, and we'll explore some of the reasons behind its growth.
FDI Definition. Foreign Direct Investment involves the purchase, or expansion, of a business in one country, by a business in a foreign country. It can take several forms. It can involve the purchase of shares, a merger, the establishment of new business facilities, and finally, enlargement of existing foreign business. But note, it does not include the purchase of local or national government bonds.
Data Sources. The data on FDI is usually solicited from individual companies, and this is where the problems start. Let's look at the United States, which is the largest owner of FDI stock in the world. It owns almost 22% of the total world Foreign Direct Investment. The authorities there collect annual data, and every five years they hold a benchmark survey. The annual surveys only target the larger firms, the argument after all that they account for most of the FDI. In the benchmarks surveys, they take a wider range of firms. But, they also then have three different forms. And the detailed information is only
solicited from firms with a turnover of more than $150 million. If this is the situation in the United States, imagine what happens as we slide down the scale towards less rich states and less efficient administrations.
History. Immediately after the WWII, there was really only one source of foreign capital. That was the United States. It was only when Europe had replenished its depleted reserves of foreign exchange at the end of the 1950’s that it began to re-enter the FDI market. But after that, the volume of annual FDI has grown very, very rapidly. And today it stands at $1.3 trillion.
Initially, three-quarters of this FDI went to other developed economies. As late as 1990, the share of FDI going to developing economies was less than 20%. But since then it's grown steadily. Today, it's well over 50%.
Determinants of FDI. So, what determines Foreign Direct Investment? Well before answering that question, it's useful to distinguish between three different forms. The first takes the form of investment in the broadly similar activities, as those of the investing company. For example, a car company might invest in assembly and production facilities abroad. We can call this horizontal investment. The second is towards investment activities higher or lower in the production chain. For example, an oil drilling firm might branch into shipping, refining and retail outlets. We can call this vertical investment. And finally,

might branch into shipping, refining and retail outlets. We can call this vertical investment. And finally, we have examples of firms that shift foreign direct investment and even their headquarters, to profit from differences in regulatory regimes and tax levels. I suppose we can call this tactical investment. For example, the iconic Swedish furniture giant, IKEA, almost 350 stores in 43 countries and earnings of $4 billion, is not based in Sweden. It's based in the university town in Leiden in the Netherlands. Actually, it's about five minutes cycle ride from where I live.
Now for each of these different forms, there are different determinants. But one factor uniting them all is a regulatory framework in the home country. Although the international financial system, established after the war, witnessed the freeing of commercial transactions, the freeing up of
payment for trade and associated services, many countries maintained controls over capital flows, until deep into the 1980s. One exception was the United States. The United Kingdom was also an exception. It freed up its FDI, but only to countries traded in sterling, which meant basically its colonies and some of the Commonwealth.
Now, let's move specifically. A second factor determining FDI, especially horizontal FDI, is the desire to leap frog international trade barriers, and to get access to markets on the same basis as domestic producers. But, as the impact of trade barriers diminishes, so then does the power of this explanation.
And this brings us to a third factor. In situations where trade barriers don't play a major role, then they use the same kind of gravity models, as used for International Trade. Explanations are
based on the size of markets, for the products concerned, and the geographical and cultural difference. Add to this some economic specification for cost differentials, and much of the horizontal FDI flows can be explained. This is a sort of North- North trading.
If we look at horizontal FDI towards less developed countries, then the balance of explanations needs to shift away from the accents on markets, and towards an emphasis of the type of enterprise, and the fact or advantage. Is it labor intensive? Are there low labor costs? But here, you need to ask the question, why the preference for ownership, rather than outsourcing? Why own the firm, rather than get somebody else to do it for you? One important factor here is the knowledge intensity of the product. If you own the business, you can also control access to the technology, and therefore preserve conditions of monopoly.
But these factors are unlikely to operate in the same way for vertical integration, especially since it started shifting so markedly towards developing countries. In this case, the explanation would lie in gaining access to raw material supplies, and securing that access, by investing lower down the supply chain.
And then that final category of tactical investment. I like my IKEA example, but there's not much evidence that such considerations play an important role in overall patterns of FDI locations. IKEA is an exception rather than the rule. It's a shame really. It's a nice story.
Summary. Okay, let's pull this all together now. In this video, we've looked at the rise of Foreign Direct Investment. We've examined some of the factors, that could explain its growth and distribution. In the next video, we're going to turn our attention to financial markets. Meanwhile, we've prepared a visualization of the world map of FDI, and we'd like you to look at it now.
Lecture 6.3.1 Visualization : World Map of FDI
Hi there. Welcome to our welcome to our visualization of the World Map of Foreign Direct Investment. Since most FDI is confined to a relatively small number of countries, we're going to focus just on the top 30 countries involved, involved both as a source of funds, and as a destination for those funds. The data for all the countries is included in the database accompanying this course.

for all the countries is included in the database accompanying this course.
We're going to divide our analysis into two parts, stocks and flows. When we talk about stocks, we're looking at the accumulated ownership of foreign assets built up over the years. When we talk about
flows, we're looking at where an investor places their money in a particular year. The year we're going to be examining, the latest year for which data is available, is 2012.
If we look at the bar diagram for the stock of outward investment (top next page), we can see that United States still holds an impressive 22% to the world's FDI assets. This has fallen from the peak of 45% in 1986. Even so, it remains far ahead of the United Kingdom, the second placed economy. Hong Kong, in fifth place, is interesting. It functions as a gateway to China, and as late as 1989 it held only 0.5% of the world's FDI. The British Virgin Islands, a nice little tax paradise that appears in 14th place, was too small even to register in the statistics before 1988.

On the inflows stocks diagram (bottom, previous page), United States is also the world's largest destination for FDI, though it still has a substantial outward balance. It is then followed by Hong Kong, whose function as a conduit of France towards China substantially diminished since 1980s. Looking down the list you find countries like India and Indonesia that have largely built up their position since the turn of the millennium.

Now let's turn and look at which countries are the most active foreign direct investors, in 2012. And here we see, United States still the world's largest player, with investments of almost four times the size of that of China in third place. China's activity as a foreign direct investor dates from around the turn of the millennium. Russia in eighth place began even later, about a decade ago. There were other countries, such as Cyprus, that probably acted as a conduit for Russian funds long before then.
Looking at the inward flow of funds (top of next page), United States still holds an attraction for foreign investors, followed by China and Hong Kong. Brazil and British Virgins have only come to the attention of investors in the past four or five years. Russia's increased popularity on the other hand, dates from about a decade ago.
You have to remember that the flow data is for one year only. 2013 could significantly change the picture, certainly for specific countries. The Netherlands for example, before the recent financial crisis, was always amongst the largest foreign investors. They'd actually reduced its foreign asset holdings in 2012, and it could probably bounce back, when the new data is released.

Lecture 6.4 Financial Markets
Hi there. In the last video, we looked at the growth of foreign direct investment, and we examined some
of the factors that explained its growth and its distribution. In this video, we're going to trace the growth of international financial markets. We'll try to split it into different categories and keep the explanations simple, which is not always easy. And then we'll look at some of the explanations for its growth before turning to try to estimate its current size.
Definition of Financial Markets. What are financial markets? Well so far, we've looked at transactions in

Definition of Financial Markets. What are financial markets? Well so far, we've looked at transactions in goods and services, and by implication, the cash that changed hands to effect the change in ownership. We've also looked at transactions to acquire increased business assets abroad, and again, by implication, the cash that's changed hands. Financial markets cover cash transactions for what is left. But what is left?
There are four main categories. The first of these are Bonds. These are fixed income, fixed term loans, usually issued by governments, both national and local, but occasionally also by business. The second category is Equities. Equities refer to the ownership of assets, including company stocks and shares. The third category is referred to as Derivatives. These are financial contracts that derive, note the word ‘derive’, their value from the performance of another asset. These might take the form of futures, options, and swaps. Many of them involve some sort of insurance against future price changes. And finally, we have foreign exchange transactions, simply the buying and selling of currencies.
It's generally agreed that financial markets have expanded rapidly, especially since the 1970's. But, there's little consistent data to measure exactly when and how this occurred. General agreement, however, that it's grown fast, much faster than world GDP, much faster than world trade, much faster even than world FDI. And in my opinion, if there's a radical departure from the previous period of globalization at the end of 19th century, it lies precisely in the growth of the international financial market.
Persistent skeptics of globalization would respond to this in two ways. They'd say that most bonds and equities are still traded nationally and that much international financial trading is largely regional, or at the most, shared among the richer nations of the world. But, they too would agree that it's grown explosively.
Explanations For Growth. There are many factors that help explain this growth, but we'll generalize about them in four categories: the available currency, government policy, technology, and innovation.
Available Currency. First you need an international currency to become available. Traditionally, most foreign exchange used to be held by national banks, although some international companies might hold onto some as trading reserves. After the Second World War, when dollars were scarce, any surplus dollars earned from the United States were used to replenish the foreign exchange reserves of national
banks. By the end of the 1950s, most European National banks held sufficient dollars. But still, the American balance and payment deficit continued to pump money into the world economy. Right up
to today, the US is still running a deficit. These reserves were accumulated in private banks and other financial institutions where they were used for international transactions.
Policy. The second category is government policy. Increasingly in the 1980s, governments began to remove controls over financial markets, allowing foreign banks and other financial institutions to establish branches in, and to trade in each other's market. The IMF also used its leverage in bailing countries out of financial crisis to insist on increased deregulation in this area as well.
Technology. Third, this was the era of increased speed in international communications. The one sector that's been utterly transformed by the increasing computer speed and transmission times is financial
institutions.
Innovation. Finally, with all that cash available, with lax regulation, even laxer supervision and virtually no enforcement, and with the means of almost instantaneous communications throughout the world, financial institutions derive new products which they could sell, and nowhere was this more apparent than the market for derivatives.

than the market for derivatives.
Size of the Financial Sector. So, how big is the financial sector? Well, basically, we're dealing with very, very large numbers. So, let's have a look at the trillion, one thousand billion. And don't forget that a billion is one thousand million. So, a trillion is one, followed by 12 zeros. Let's run through some of the numbers.
Bonds, if you remember, are fixed interest, fixed term loans. The size of the international bond market, in other words, the total accumulated value of all bonds at the end of 2013, totaled $22.8 trillion. Net issues in 2013, that's the balance of new issues, were half a trillion.
Equities refers to the ownership of assets, stocks and shares. In January 2014, the total monthly traded value for equities, domestic and international, on the main stock markets of the world, was $4.6 trillion. If that level were maintained over a year, we'd get a total in the region of $50 trillion.
The total turnover and nominal value of derivatives, financial contracts whose value depends on the performance of another asset, was $1,886 trillion in 2013. The problem here lies in the fact that when you have a derivative, you only pay a small percentage with probable future values. So the actual money changing hands is much less than this.
And then we have foreign exchange transactions, the buying and selling of currencies. Since 1989, we've had data on this from the Bank of International Settlements. In April 2013, the daily value of currency transactions was $5.3 trillion. If we multiply this by 350 (allow the traders a few holidays) we get an annual value again, of $1,855 trillion. Again, you could argue this isn't really the true value of transaction. Much of this is simply a swap, a like for like exchange. But nevertheless, a Dollar is not a Euro, so there is a transfer of real ownership.
These are all huge numbers, but what do they mean? The question we have to ask ourselves is, how does all of this relate to the rest of the world economy? This is a question that we're going to answer in the next video.
Summary. So let's recap on what we've done in this video. We've divided the financial market into four types of transaction. We've examined its growth, and we've tried to explain it. And we've attached some numbers to its current estimated size.
Lecture 6.5 The Globalized World Economy
Hi there. This week we looked at the discussions surrounding the concept of globalization. We've examined the main international components of the world economy. We looked at international trade, foreign direct investments, and financial markets. In this last lecture we're going to bring all of these together and relate them to GDP. And then we're going to pose the question, what exactly are the implications of this for society.
In trying to piece together the world economy, we're faced with one big problem. All the components have been calculated in different ways and for different purposes. It's almost impossible to put them together in any consistent and in any accurate way. But, just to say that we can't say anything accurately doesn't mean that we can't say anything at all.
Let's start with a baseline number. Let's take GDP, which for all its shortcomings, is still the best measure we have for the output of goods and services in a society. In 2012, the world's GDP in current dollars, stood at $72.2 trillion. Now the value world trade in that year was $18.2 trillion. And here we confront our first problem. In calculating GDP, the only part of a transaction that counted was the value added. In foreign trade statistics, the whole value is added every time. So there is a degree of double counting in this number. Next then, we can turn to foreign direct investment. And here, at least, the

counting in this number. Next then, we can turn to foreign direct investment. And here, at least, the recorded statistics present no problems. And the value of FDI, 2012, was $1.45 trillion. So, that basically deals with the real economy, and its global dimension.
Now we turn our attention to the financial sector. Let's start with equities, stocks and shares. We have a figure for end year total evaluation of $52.5 trillion and a trading volume of about the same amount, $50 trillion. But foreign ownership is not likely to be large, so let's say 10%, and that would give us an international trading figure of $5 trillion. When we turn to bonds, we have a figure for the end-year value of assets internationally held, which was $22.8 trillion. Now if we assume that the behavior mirrors that in equities then we could take a trading volume of about $20 trillion in a given year. For derivatives now, we had a total turnover of the nominal value of 2013 of $1,886 trillion. But we noted
only a small down payment only changed hands. So how small is small? Well, the Bank of International Settlement is trying to establish a minimum ratio of around three percent, lower for some transitions and higher for others. If we take this as a ratio, we get a trading figure of 56.6 trillion dollars. But note that if it does go wrong, then the investor can get stung for the whole amount. And finally, we arrive at foreign exchange transactions where we put on a value of $1,855 trillion dollars. But much of that, so we're told, shouldn't count since it involves the swapping of currency. But it does involve the transfer of real assets, real assets with real values, real assets with real values, and real values that can and do change. So I don’t think we should be quite so cavalier and say it doesn’t really matter that the dollar is a euro.
Now, these numbers are mind-bogglingly huge. Remember that a trillion is one, followed by no less than 12 zeroes. But it's still money, so let's try and put it in an easier context. The most common way to do this is to relate it all to GDP. So, for example, people say that foreign trade is equivalent to 25%
of world GDP. Foreign direct investment would be equivalent to 2% of world GDP. Now a rough estimate for the internal trade and equities would be 7% of GDP. International bond trade would be equivalent to 28% of GDP. And our very nice and very kind adjustment in derivative trade would still be 78% of GDP. So, so far, the value of transactions in the financial sector already exceeds the total value added to the world economy in one year. And now we need to add currency transactions, which by itself are 25 times bigger than GDP. Did I just say that? Twenty five times bigger. And again, the numbers are just becoming meaningless.
It's money we're talking about, so let's start all over again. Imagine that our GDP is a globe, it is in fact the planet earth. And on top of that, we start layering our globalization components in $100 bills. Okay, let's run quickly through the numbers again. Let's start with foreign direct investment. $1.45 trillion. In one hundred dollar bills, the pile would reach 1,584 kilometers into space. We'd be at the upper end of low earth orbit and already we will have passed the International Space Station below us. At foreign trade, $18.2 trillion. And this would reach almost 20,000 kilometers into space. We would be at the distance at which GPS satellites are parked. And then we have the financial sector. I did up that. $5 trillion for equities, $20 trillion for bonds. And the 55 trillion changing hands for derivatives. And we reached 93,000 kilometers into space, and by now we're about one-third of our way to the moon. And we haven't even had foreign exchange transactions yet, 1,855 trillion. By now the pile of notes stretches 2 million kilometers into space. We can easily get to the moon and back. That would get to the moon and back twice over and still have a small fortune left. If we simply carried on, we'd be on our way to Mars. In fact, if we'd done this entire exercise in $1 bills, we'd be at Mars already, and be on our way to
the next planet. So around the core of a globalized real world. Buying and selling real goods and services and investing in real businesses. We have a much larger world of financial markets involving infinitely larger sums of transactions.
But where do we find these numbers in the GDP statistics? Well, GDP calculations deal only with the value added to the stock of wealth, generated then by an economy. So all of these financial transactions

value added to the stock of wealth, generated then by an economy. So all of these financial transactions appear in the labor costs and profits generated by the financial services industry. In developed
economies, with large financial service sectors, like the UK, this can account for up to 10% of GDP. In America, the United States, the figure is a more modest 7% of GDP. And these numbers also include all the insurance, mortgage and banking services that we consume domestically. So we have a situation where transactions, exceeding in multiples of what we would deal with in the real world, make a modest contribution to a relatively small sector in relatively rich countries. Huge volumes, for small margins, but entailing massive financial risks that affect us all.
I started this series of videos with a reading from John Maynard Keynes and I'd like to end with one. This time, I want to read from Susan Strange, Casino Capitalism (1986.) Susan and I have spent a bit of time together, at the European University Institute. She is a fascinating person who came from journalism into the economics game, and actually writes well. In her book Casino Capitalism, which was published in 1986 only two years after globalization began its penetration of economic literature, she wrote the following.
“The western financial system is rapidly coming to resemble nothing as much as a glass casino. Everyday games are played in this Casino that involve sums of money so large, that they cannot be imagined. At night, the games go on, on the other side of the world. In
towering office blocks that dominate all the great cities of the world, rooms are full of chain smoking young men, all playing these games. Their eyes are fixed on computer screens flickering with changing prices. They play by intercontinental telephone or by tapping electronic machines or with computer algorithms to date. They are just like the gamblers in casinos watching the clicking spin of silver ball on a roulette wheel. And putting their chips on red or black, odd numbers or even numbers. .....These bankers and dealers seem to be a very different kind of man working a very different kind of world from the world of finance and the typical bankers that older people remember. Bankers used to be thought of as staid and sober men, grave-faced and dressed in conservative black pinstripe suits, jealous of their reputation for caution and for the careful guardianship of their customer's money. Something rather radical and serious has happened to the international financial system to make it so much like a gambling hall. What that change has been and how it came about is not clear.”
Well, it might not be clear, but one big thing has happened. It has huge consequences for us today, and we've gone through the effect of that with the most recent financial crisis. And underlying this is a loss of trust.
The above notes are provided by a student of the Coursera course “Configuring The World”, offered by Leiden University. They were produced without compensation, and are the property of the University of Leiden

Week 7: International Organizations
7.1 Global International Organizations: Origins
This week, we're going to examine the role that international organizations play in the world economy. We're going to do this by developing several of the strands that we've examined already, earlier in the course. In week two, we looked at some of the elements that contribute to the current levels of globalization, such as trade and finance. In week three, we focused our attention on the question of trust in individual societies. And, staying at a national level, we saw in week four, how levels of fractionalization and inequality contribute to the building or undermining of levels of trust. Week five raised the question of whether trust could be built by creating a climate of good governance. And finally, in week six, we looked at the question of whether by external assistance, you could grow poorer countries. Except for the lectures on globalization, we concentrated our debate at the level of the nation state. All of these issues can be raised at the international level, but with one huge difference. Countries may have policy aims that they hope to realize at an international level, but they have far less control over the outcomes.
Origins of International Organizations. In this first video, we're going to trace the roots of the current system of international organizations. Just for historical accuracy, and I am a historian, I have to mention that the first truly international organization was the International Telegraph Union created in 1865 to establish common standards for international telegraph communication. Close on its heels, came the General Postal Union, created in 1874, to establish common rates for international postage, to ensure that post in one country was actually delivered in another, and to establish the precedent that the country in which the mail was posted, and the stamps were bought, that they could keep the revenues. Both of these bodies still exist today, under the umbrella of the United Nations.
But the roots of the current international order lie in the failure of international organizations in the interwar years. After the end of the First World War, the victorious nations had in 1920 created the League of Nations. This was an international body designed primarily to guarantee peace and security, by encouraging negotiation and arbitration to resolve international disputes. By the time it collapsed into a Second World War, it was evident that the League had catastrophically failed to fulfill this primary aim.
Several reasons have been offered for this failure. First, the fact that the United States had failed from the start to join the organization robbed it of some of its legitimacy and clout. But given the fact that the American policy was becoming increasingly isolationist anyway, it's difficult to say what difference its membership would have made to the course of events. Second, when countries considered their expansionist national ambitions were being threatened, they simply left the organization. Germany did this in 1933 when the Nazis came to power. Japan walked out in the same
year after the condemnation of its invasion of Manchuria. And Italy abandoned the League in 1937, following the invasion of Abyssinia.
Less well known. but equally important. are the activities of the League of Nations in the field of economics. After the dismemberment of the Austro-Hungarian Empire at the end of the First World War, the successor states adopted aggressive protectionist trade policies, as they tried to re-create viable national economies. The league held a succession of conferences designed to bring down the level of import tariffs, all without success. Again, after the onset of the great depression, the league tried again without success, to hold the upward drift of restrictive trade measures such as tariffs and quotas, as

without success, to hold the upward drift of restrictive trade measures such as tariffs and quotas, as countries try to isolate their national economies from the downward global spiral. Once again, following the devaluation of Sterling in 1931, the league tried and failed to discourage the manipulation of exchange rates to secure national trade advantages. And finally in 1933, it called a large international conference in London, designed to bring all of these issues together and link them together. Well, it collapsed. And when it collapsed, the league finally abandoned its ambitions in this direction.
Again, several reasons have been advanced to explain the failure. First, there always seemed to be a problem about agreeing on a strategy towards tackling trade and financial issues. At a slightly deeper level, the ground work for discussions was never adequately prepared in advance. The league never had sufficient staff. And more important still, nobody seemed to see the need for a bigger staff. League officials never saw it as their task to prepare detailed recommendations, partly because it was reluctant to interfere with domestic policy matters. This reluctance to overstep some invisible line between commercial policy on the one hand, and general economic policy on the other, also contributed to an artificial compartmentalization of problems. Commercial policy was an integral part of economic policy as a whole, or at least it was rapidly becoming so.
Among American policy makers, surveying this collapse of collective security and the disintegration of the world economy, there was a general mindset that linked the war directly to the depression. The great depression had contributed to a rise of protectionism. And behind these protectionist barriers, dictatorships have been enabled to emerge, and this in turn, had led directly to the war. Post-war policy should be directed at avoiding any reoccurrence. You've also got to remember that the ruling Democrats led by President Roosevelt, had already promoted widespread government intervention in the national economy, in the form of the New Deal. They were ready to employ the same approach to international problems. So, during the various meetings among the allies held in the closing years of the war, President Roosevelt gave a high priority to the creation of a New World Order, one to which the United States would be committed, and one which would also include the Soviet Union. This work was continued after his death.
Anchoring the entire structure would be the United Nations. Its highest body, the Security Council, would be primarily responsible for maintaining world peace. That's one aspect, however, we won't be discussing in this series of lectures. Trade and employment issues would be entrusted to an international trade organization. Monetary questions would fall under the remit of an international monetary fund, and problems of post war reconstruction will be tackled for two years by a UN relief and aid administration. And when its mandate had lapsed, responsibility for promoting economic development would fall to the International Bank for Reconstruction and Development, commonly known as the World Bank.
Let's sum up now. In this lecture, we've seen how the failure of international organizations to preserve peace and promote prosperity in the inter-war years, had prompted a change in the American view of the new world order, and how this in turn had led to the creation of new specialized agencies under the umbrella of the United Nations. Over the next three videos, we'll examine in turn the development of these agencies in the field of trade on the one hand, and finance on the other. And in the final video, we'll reflect on what lessons we can draw from their experience.
7.2 Global International Organizations: Trade
In the last video, we looked at the origins of the current international global order. We saw how, after the First War World, the hopes of peace and prosperity that had been based on the creation on the League of Nations had been shattered. We also saw how American policy makers, already used to government intervention in their own domestic economies, were willing to consider the creation of stronger and better global organizations to manage the world economy. In this video, we're going to see how they translated these ambitions into reality, on the governance of international trade. We will examine the

translated these ambitions into reality, on the governance of international trade. We will examine the achievements of this policy, and the evolutions of the institutions responsible.
It's important to realize that the initial American ambitions in the field of trade were far more ambitious than the eventual outcome. In 1947, the Economic and Social Committee of the United Nations convened an international conference on trade and employment, to be held in Havana. It's interesting to note that international trade was deliberately linked to considerations for maintaining domestic full employment and promoting industrial development among poorer nations. The conference indeed reached an agreement on an ambitious set of rules governing tariffs, quotas, subsidies, state trading, cartels and international commodity agreements. Governing the whole structure was to be an international trade organization with its own investigative arm, and policy decisions taken by majority voting.
In March 1948, this agreement was actually signed by 53 countries, but it was then that things started to go wrong. For the Americans, the agreement had been negotiated by a Democratic administration. Congress was under the control of the Republicans, and they were resentful about sacrificing sweeping powers, especially Congress's own power, to an international organization. As a result, the administration held off from presenting the agreement for ratification. And as long as the United States was unwilling to ratify its own creation, everyone else waited, and waited, and waited. And when a Republican, President Eisenhower, was elected, the plans for ratification were quietly forgotten. The international trade organization was never formed. Instead the world had to wait until 1995 for a permanent organization to govern world trade.
Meanwhile, in 1947 a provisional framework for agreeing tariffs had been negotiated, and in January 1948 it came into effect for 23 founding countries. The General Agreement on Tariffs and Trade provided for nondiscrimination among its members, and created procedures for negotiating tariff reductions and rules for the creation of free-trade areas and customs unions.
The tariff reductions are usually conducted on the rounds, under what are called the principal supplier rule. Basically what this involves is that the larger suppliers of goods will approach representatives of their main markets, and ask for improved access in the form of lower tariffs. And then they'll make concessions in return. In this way, a network of provisional bilateral agreements will be concluded among the major trading partners. When these are all folded into each other and the benefits extended to all Member States regardless of their participation, under the non-
discrimination principle, you have an agreement. The United States generally joined in when Congress granted the President a limited time mandate, usually three years, to take part in negotiations.
By the early 1960's, the argument began to gain ground. The development in the so-called terms of trade, in other words the failure of commodity prices to keep up with those of manufactured goods, meant that the less developed countries were losing out from the growth of international trade. The initial international trade organization had had a mandate to tackle such problems, but GATT did not.
So the underdeveloped countries pressured the United Nations to call a special conference on trade and development, the UNCTAD. This met in Geneva in 1964. Aside from granting GATT members the opportunity to offer trade preferences to poorer countries, and obtaining some extra borrowing facilities
from the IMF, the meeting agreed to establish UNCTAD as a standing conference, coming together every four years. Aside from an early success in creating non-reciprocal preference arrangements for the poorest countries, UNCTAD conferences soon degenerated into confrontations between mutually antagonistic clubs of rich and poor, or North and South.
Meanwhile, it's not as though GATT had done nothing. On the contrary, since the 1960s, it had contributed to a significant reduction in industrial tariffs, especially among developed industrial

contributed to a significant reduction in industrial tariffs, especially among developed industrial countries. However, many problems remained. Agriculture protection remained pervasive, and new import restrictions often remained in sectors of textiles and electronics. Non-tariff barriers became more important in trade policy. Preferences towards poorer countries removed the pressure on them to reduce tariffs. This, by the way, didn't stop them from condemning the gap to the rich man's club. In addition, huge swaths of the economy, including purchases by governments and the whole service sector, seemed to escape the pressure to become more open. And finally, trade disputes, especially between the United States and Europe, were allowed to fester without being resolved.
It's partly because of these difficulties that the GATT was replaced by the World Trade Organization in 1995. One important change was to establish WTO as a permanent organization, with a permanent structure and a supervisory function. It also established a dispute settlement mechanism, with a possibility of imposing sanctions and penalties. This mechanism has been relatively underused, and the debate is still on-going whether simply having it there as a threat might possibly have made a difference.
And finally, the WTO's remit was extended to cover trade in services, and trade-related implications of intellectual property rights. Even so, the new organization has its problems, the least of which was the effort to conclude the round of trade talks which started in 2001. The only result to emerge so far is the agreement reached in Bali in December 2013 for a reduction in bureaucratic barriers to trade. All the other problems bedeviling the GATT seem to be carried over into the WTO. In addition, it's much less ambitious in its agreement, than the original failed international trade organization. And trade policy still tends to be seen as separate from other concerns, such as employment, development and the environment.
So let's sum up then. In this lecture we've looked at the emergence of an international trade organization after the war. And we've seen how its ambitions were never realized. In its place, world trade came under the aegis of the GATT, which did succeed in reducing industrial protection, but not much else. The efforts of the less developed countries to link trade concerns with questions of
development in UNCTAD also failed. And then we saw the emergence of the WTO with a wider remit and strong capacities than the GATT, but it still has to demonstrate its capabilities. In the next video, we'll turn our attention to the world's financial system.
7.3 Global International Organizations: Finance
In the last video, we saw the stillbirth of the International Trade Organization. In its place, world trade came under the remit of the GATT, which succeeded in reducing industrial protection, but not much else. The efforts of less-developed countries to link trade policies to development in UNCTAD also failed. And finally, we witnessed the emergence of the WTO with a wider remit and stronger capacities. It still has to demonstrate what it's capable of. In this video, we're going to look at the attempts to manage the world's financial system.
Managing the World Financial System. In July 1944, delegates from 44 countries met at a resort hotel in New Hampshire. They established a new regime for the world's financial system that still bears its name, The Bretton Woods system. It was designed to prevent a re-occurrence of the problems that had bedeviled the 1930s, at least from the American viewpoint.
After the financial crisis in 1931, many countries had controlled access to foreign currency, and this would allow them to manipulate their trade for political purposes, i.e, for warfare. So the first thing the Americans insisted upon was that all currencies be can freely convertible in to each other. At the same time, the dollar was made convertible to gold at an exchange rate of $32 an ounce. In this way, all currencies were also linked to gold. The Americans were also obsessed by what they call competitive devaluation. When the dollar devalued in 1933, sterling, which had devalued in 1931, drifted

downwards as well, and so maintained its competitive advantage.
The new system was to be based on fixed exchange rates, parities which were to be maintained within very small and very strictly defined limits. Any deviation from them would only be allowed in exceptional circumstances. So finally, to prevent countries being forced to devalue because of speculation against their currencies, a fund, an International Monetary Fund, the IMF, was established, from which they could borrow. The fund was funded by contributions from the member states.
This was a system that managed the world economy until the early 1970s. In terms of managing exchange rates, it seemed pretty successful, at least between the main trading currencies, the Dollar, the Sterling and the main European currencies. After massive exchange rate realignment in 1949, exchange rates remained markedly stable. There were French devaluations 1957 and 1958, a small German revaluation 1961, sterling devaluation, 1967, French devaluation, German revaluation 1969.
But the rules have never been fully implemented. First of all, European countries have maintained the currency controls, even on commercial transactions, until 1959. And controls over capital movements persisted until the 1980s. Secondly, from the early 1960s, dollars began entering the system at a faster rate than central banks were willing to accumulate them. The causes of the dollar deficits were several. American inflation was higher than that of its main competitors. The government was spending more than it raised in taxes. American firms were investing abroad. But the effect was to allow the buildup of stateless capital in the hands of financial institutions.
Credible Commitment. There's a nice little concept in institutional economics called credible commitment. Basically, it means that I will believe that you're going to do what you say you are doing, when I see that you're doing what you say. What happened next is a good example. Since American policies were quite patently not consistent with those necessary to maintain the exchange rate, speculation built up against the dollar. In 1971, the Americans suspended convertibility, and a few months later devalued the currency as part of a currency realignment, similar to that of 1949. For a while, it looked as though the system might just hold together, but by 1973, most countries had let their currency float against each other. And the regime of fixed exchange rate came to an end.
The only part of the system that remained was the fund itself, intervening to help countries with fund payments problems, and helping them to get back on their feet towards a sustainable future, at least that's the official version. Critics of the IMF accused it of protecting the interest of international finance bankers and speculators, and it ends up pushing all the burden of re-adjustments onto the shoulders of those least able to bear it. What the IMF does is to offer financial assistance, negotiate a deal with creditors (and my pension fund is somewhere in that mixture,) and insist on stabilizing fiscal and monetary policy, often using the opportunity to impose some other reforms.
All of these things involve some temporary surrender of sovereignty, and that is generally resented. Certainly when the conditions attached to the aid packages are painful. The IMF therefore is seen as being undemocratic and bullying, and seems itself to be unaccountable to anyone. On the other hand, time is not usually a luxury people have in crisis situations. A financial crisis is no exception. Criticism is sharper when it extends to the measures imposed. In almost every crisis, government expenditure is too high, and so is the level of inflation. The correction however is painful. The criticism is often that the
IMF's measures are too fast and too severe, and that the downward pressure placed on the real economy actually impairs recovery, a criticism for example that's levied at measures imposed on Greece.
Further criticism is that some of the measures imposed go much further than are actually necessary to restore equilibrium, and impinge on a country's freedom to choose their own development strategies. The fund's pro-market policies often demand the sale of public assets, and reforms in tax and subsidy structures.

structures.
I actually lived through the IMF reforms imposed on the United Kingdom in 1976. The currency was collapsing, and inflation had reached an annual rate of 30%. As part of the measures to cut expenditure, the IMF forced the government to impose a public sector pay freeze. Real wages shrank, so did mine. And in the winter of 1978, a reaction set in in the form of a series of debilitating public sector strikes. The electricity workers, the dustmen, the firemen, and other emergency services all ground to a halt. It was a thoroughly depressing experience, and I resented every moment of it. But I do admit it did mark a turning point.
Let's some up now, in this lecture we've seen how the management of the financial system was intended to avoid a re-occurrence of the 1930s. We reviewed its main features. We saw how it existed until the early 1970s. We then saw how the world switched to a regime of floating exchange rates, and how the IMF was the only element to continue as a fund to relieve countries with acute payments problems. We then reviewed the criticisms levied at the fund and its operations. In the next video, we pull together some of the ideas surrounding the effects of international organizations on state behavior.
7.4 Global International Organizations: Reflections
So far this week, we've examined the origins of the United Nations system of international organizations. We paid particular attention to the creation and operation of those directed for trade and finance, respectively. We started the week by referring to the triangle of fragmentation, governance, and trust. The international community is more fragmented than any national society could ever be. Its membership differs vastly in economic size, in population size, and in military might. Their communication is conducted in a myriad of foreign tongues. Their cultures have been shaped by thousands of years of history. Their citizens pray to different gods, and their day to day existence ranges from obscene luxury to dire abject poverty. This fragmentation of experience far outweighs that that is found within the borders of any single nation state.
In this video, we are going to ask what role, if any, does international government have. Why do international organizations survive at all? Can they make a difference? If so, for whom?
Standing in the aftermath of the death and destruction of the Second World War, it was difficult to be optimistic on the future of the myriad of organizations created under the new United Nations umbrella. The dominant paradigm of political scientists at the time was a belief termed ‘realism.’ The world, it was argued, was in a state of almost permanent anarchy. And the only guiding principle for nation states must be the promotion of their own national interest. International organizations (IO) would exist only for as long as they didn't interfere with the pursuit of national interest, and as long as they provided some service towards that goal. The expectation was that would not be for long. And yet, they still survive today.
Now at this stage, the realists modified their position and became neorealists, or new realists. International organizations had survived, they had argued, because they did convey some real benefits. One tangential benefit was information. At least they provided a regular check on what other parties were thinking, or saying what they were thinking. The second belief was they provided a regular forum for interaction. The organization existed with rules, procedures, agendas and meeting places. And all of this was much easier than having to start afresh every time. The third benefit was that international organizations were predictable, and for the
larger parties, controllable. In the Security Council of the UN, the larger powers made sure that they were represented, and that they had a veto. The United States and Europe happily made sure that they controlled the top positions in the World Bank and the IMF. And if that wasn't enough, the voting rules were fixed, to ensure that they would always have a sympathetic majority.

were fixed, to ensure that they would always have a sympathetic majority.
To take one example, in the IMF the United States controls 16.75% of the vote. The EU collectively, represents almost another 30%. Other friendly powers control slightly under 12%. The chances of being out voted are remote. The BRICS, for example, collectively control 11.03%.
A final benefit worth mentioning is that international organizations provide a system for monitoring whether agreements are kept. If one party in an agreement reneges on its obligation, it often undermines the commitment of others. And this monitoring is better done by a neutral third party than by one of the parties involved.
This pretty minimalist view of international organizations was challenged right from the start, and from several angles. There were those who argued that collaborative behavior could actually
operate for the benefit of all, creating win-win situations. Benefits did not have to be obtained at each step in a series of one-up games. Depending on the range of issues, it was possible to benefit from what was called diffuse reciprocity, gains and benefits further down the line. And this in turn would help create compliant behavior.
Another argument was that statesmen have actually grown to like international organizations. At a basic level, it allows them to strut on the world stage and to raise their profile against domestic contenders for power. But it also provides the possibility for agenda setting. They can raise the stakes in what is essentially a domestic matter that might otherwise face difficulties in passing through parliaments, by making it part of a larger international set of decisions.
Others have argued that continuous participation of organizations could socialize its members. The benefits of this process ran in two directions. Some emphasized how officials working together to solve problems would extend their experience to other problems that they faced, and advocate similar solutions. This line of thinking was known as neo-functionalism. On the other hand, working together also facilitated the production of a coherent shared framework of discourse and observed behavior. And this could even help contribute towards policy change within an organization, independent of the direction of participating countries. Of course, the states could always block this at a later stage.
Now, this picture of shared rituals, experience and discourse is one that we recognized when we were looking at issues of trust in governance on a national scale. It is an attractive one, a community of high-minded diplomats, working together to solve common problems. But are they? Or is this all simply a veneer over a system whose dynamics lie elsewhere? It's a system empowered by movements of money, and controlled by those who hold access to most of it. Or is it not controlled by anyone at all?
The above notes are provided by a student of the Coursera course “Configuring The World”, offered by Leiden University. They were produced without compensation, and are the property of the University of Leiden.

Week 8: The Locus of Control
8.1 Sub-State Actors: Cities
In the previous lectures, we've portrayed a world of global economic government. Now notwithstanding some considerable doubts at the time of their creation, its main institutions have not only survived, but have recorded some very real results, although in limited fields. The financial system has adapted to crisis management, but is still pretty hopeless at crisis avoidance. The trade system has lowered world protectionism, but still seems to satisfy neither the rich nor the poor. Although we didn't examine them in the lecture, we could also have pointed at the security system that managed to prevent a global conflagration, but has to stand by and survey almost continuous conflict or warfare somewhere in the world. I could have pointed at development agencies that even now have failed to unlock the secret whereby billions of the world's populations could be lifted out of poverty.
Now if, by international action, states are capable of controlling the global forces responsible for, and yet at the same time, threatening their security and prosperity or chance, then, for nation states working on their own, nation states, if hyper-globalist rhetoric is to be believed, are ready to be swept aside by the remorseless march of globalization. So, in this series of videos, we're going to leave the level of the nation state and international organizations behind us. And we're going to configure the world in four different dimensions, in no particular order. We will start now with the substrate actors and look at the cities. Then in other videos, we'll look at non-state actors such as big business and advocacy groups, as well as supra-state actors. And, we'll focus there on the European Union.
I have to confess some difficulty in making the choice of unit for this lecture. Many states offer statistics at the sub-state level, regions, provinces, municipalities. But, these are all arbitrarily defined. And, the data's often suspect. Then last year, I was lucky enough to attend a lecture by Benjamin Barber of “Jihad vs McWorld” fame, where he was discussing his new book, If Mayors Ruled the World. In this book, he argues that cities are the motors for change, that they are closer to their citizens, that they don't have hang-ups about borders and sovereignty, and that therefore the world would be better off if it were ruled by city mayors. So I've settled for cities.
Cities have a good record in economic history. Centers of learning and innovation tend to be in places where different streams of science and logic meet and merge, and where the dead hand of social control is the lightest. Merchant cities were particularly valued in this respect. And the decision by China in the 15th century to restrict access to foreign trade has been seen by some historians as a major factor in the origins of the great divergence between China and the West. The city-states of Renaissance Italy, the merchant towns of the Low Countries, and the industrial cities of the United Kingdom, Europe and the United States, drove forward the innovations that have made today's
world. But not all cities have been successful in the past. The ruins of the great ancient city kingdoms of the Middle East and of Asia offer testimony to a flowering of art and culture. But all were bled dry as the institutions of the ruling elite sucked out the available capital and resources for the purposes of luxury
and adornment.
Today, half of the world's population live in towns and cities. The top 600 cities account for 22% of the world's population, and yet generate 60% of the world's GDP. At the moment, the most productive of these are in the developed world. 380 city regions located there contribute 50% of the world's GDP. But the balance is shifting as large urban conurbations emerge in China, India and Latin America.

Cities are big, but that doesn't explain the dynamic of what makes them important. In his classic book, The Competitive Advantage of Nations, Michael Porter emphasized the importance of agglomerations, or clusters of skills and activities, in providing firms and businesses with what he called externalities, such as shared pools of skilled labor, reduced transaction costs, and the costs of obtaining information and concluding transaction. This idea of a creative soup that makes up the major cities is captured by the works of Peter Taylor, who's interested in documenting and quantifying the interconnectivity of cities. His work focuses not only on economic size of cities and their physical connection with the outside world, such as ports and airports, but also their position as host to cultural, social, and political institutions. So cities, big cities, are the real spaces where all the transactions in this whirling globalized internationalized world eventually come to rest. And these transactions extend into the social and cultural spheres. Cities basically are places where things happen. They're also becoming more democratic with local elections, local councils, and local mayors. An unlike the sleepy, small town image of local government, and I speak here from a British perspective, city authorities have to act, if only to prevent the entire conurbation from seizing up. And the leaders of big cities are beginning to become well known and popular, attracting public support and legitimacy.
In Alesina's book, The Size of Nations, he describes a tension between the scale of governance on one hand, and its legitimacy. Big nations can do things more efficiently, goes the logic. But, local entities identify less with it. So, are cities now the optimal size in nations in a globalized world? Well, Benjamin Barber will certainly try to convince you. Cities are beginning to establish the beginnings of a foreign policy. They collaborate and they compete. A good example of this is the collaboration of the C40 city initiative for climate change, the current membership of 63 cities whose aim is to share experiences in lowering green house gas emissions. And Barber cites over 30 other trans-border collaborative networks all with permanent secretariats and headquarters.
But, and there is always a ‘but’, are cities any more capable of controlling world events? Do they, any more than the governments they are supposed to supersede, have the financial resources to withstand the waves of speculation from edgy financial markets? Do they have the capacities to control international movements of illegal goods and criminal activities? Are they any more immune from corruption and cronyism than the states where they're located? And, is the world of city-states more immune from protectionist tendencies and petty squabbles than their counterparts in the 15th and 16th centuries?
Well, let's sum up. We've seen how cities were the main motors for technological change and scientific advance. Still today, they contribute disproportionately to the growth and prosperity of the
world economy. We saw how they were satisfying their citizen's aspirations, even more so than nation- states to which they belong. And we saw that there were proposals to pull them more fully into world governance, a proposition which I question. But, let's end on a positive note, for once. Barber writes, if mayors ruled the world more than 3.5 billion people, over half of the world's population, who are urban dwellers, and the many more in the ex-urban neighborhoods beyond could participate locally and collaborate globally at the same time, a miracle of civic “glocality,” promising pragmatism instead of politics, innovation rather than ideology, and solutions in place of sovereignty.
8.2 Sub-State Actors: Big Business
In the last video, we saw how cities have become the locus for economic prosperity and advance on the planet. They're also the space where economic activities happen. And their leaders are also attracting increased legitimacy. All of this has spurred Benjamin Barber to contemplate handing world leadership over to them, rather than leaving it in intergovernmental hands.
Now, cities may be the place where business is located. But where is it controlled? How does big business relate to national government, or to international regulation? These are questions that we're

business relate to national government, or to international regulation? These are questions that we're going to consider in this video.
So, let's start with multinational corporations. These basically can be defined as enterprises with assets, presumably productive assets, in more than one country. This means basically, that they have to coordinate their activities in several countries within a single business structure organization. I've already met multinationals in this course, briefly, when we were talking about poverty. We saw how their proponents argued that they brought scarce capital into a country. And with that capital came technology, employment and income. We even saw that they could help foster good governance and responsible governance.
So, how come they obtained such a fearsome reputation? Well let's start by going back to the definition. They coordinate activities in different countries inside a single business structure. This means that their business strategy is determined centrally at headquarters, regardless of the needs of individual countries, or the consequences of decisions in those countries. Now the opening of a new branch is usually welcomed. But the closure of a branch in the context of a global reorganization is often seen as callous and capricious. Also, by using the prices that they charge themselves for goods and services transferred within the organization, they can manipulate where profits appear, and therefore where they pay taxes.
But multi-nationals are also big, very big. You may have read, for example, that Wal-Mart, the largest multi-national in terms of turnover, is as big as Belgium (which, by the way, isn't true, since it's spurious to compare the total revenues of Wal-Mart with the value added within Belgium. But you get the idea, the fact that they command considerable resources.) Now they have a range of plausible alternative locations that places them in a strong position when dealing with governments. This allows them to extract a range of concession from governments, in the form of tax exemptions and waivers in legal requirements. In addition, they regularly use their funds and expertise to influence government legislation and regulation through lobbying. And, they also use campaign financing to assist the election of favorable governments. And, if officials and elites are corrupt, guess who pays the bribes? And finally, they have a rather unhappy history of assisting the overthrow of governments they don't particularly like.
So, multi-national companies are big and powerful. They also control a sizeable part of the international economy. For the year 2010, UNCTAD suggested that there are over 100,000 parent firms. 70% of them concentrated in richer economies. Together they control almost 900,000 foreign affiliates, almost 60% of those concentrated in less developed countries. UNCTAD has estimated that together they control about 60% of world trade, half of that representing trade within the multinationals themselves. The total revenues of the top 200 approach the equivalent of 30% of GDP. Now you could reduce this by a fifth, but it's still pretty big.
Multinational corporations are big, powerful and important. And these factors have to be considered when looking at the balance of power in any dealings with governments and international organizations or NGOs. But aren't we justified in seeing them as a common force, beyond of course the Marxist categorization of them all as capitalists? Or is this just a fantasy of conspiracy theorists?
Now at this juncture, I want to introduce you to an interesting piece of research conducted by the Swiss
Federal Institute of Technology, not a body normally associated with this kind of work. The researchers are complex systems theorists experienced in using advanced mathematics to model natural phenomena. And to be honest, their methods are way beyond the scope of my expertise. So in defense of what I'm going to show you, their results have been endorsed by the Influential New Scientist.
What they did was to go through a database of 37 million worldwide companies and investors. These things do exist. It is called the Orbis database. And from this, they extracted information on 43,000

things do exist. It is called the Orbis database. And from this, they extracted information on 43,000 multinational corporations. They then looked at the patterns of ownership among them and covered over one million ownership ties. They then linked this to size in terms of operating revenue and calculated a network of control over a sizeable chunk of world trader production. They managed to isolate a core group of 737 companies that controlled 80% of the revenues of the network. Within that group, they located a core of 147 corporations that controlled 40% of the network. And that was almost entirely, exclusively controlled and owned within itself. This degree of concentration far exceeds the concentrations in income and wealth that have captured the headlines in the debate on Thomas Piketty's Capital in the 21st Century.
We can be even more specific about the composition of this elite. Within the top 50, only five did not come from the banking and financial sectors. Given the explosive nature of these revelations, it's surprising that they've not been more widely debated in academic and policy circles. The world is characterized by an enormous concentration of control over its wealth and activities in the hands of a super elite of institutions. But the control is one of ownership. Question is, how far and how often is it used?
Well, ownership of shares conveys voting rights. But financial institutions don't usually attempt to influence strategic directions of companies in which they've invested. There's no evidence that they operate in concert. But with the domination of financial institutions among them, we might expect a preponderance of shareholder value, rather than long term viability in their thinking and dealings, and a certain uniformity in their message in dealing with governments. And finally, we saw the nature of connectivity in the financial meltdown of 2008, 2009. Well, here it is laid out before us. If things go wrong at this core, the impact would indeed be truly global.
Let's sum up now. We saw how multinational corporations, they're over 100,000 of them, dominate international trade, and how their ability to operate in more than one country poses problems for national regulations. We saw that an analysis of share ownership reveal that 80% of the revenues were controlled through share ownership by a mere 737 companies, and that 147 super entities controlled 40%. We then raise the question whether we should view them as a single phenomenon with similar aims and ambitions. We don't know if this power is used, or how it is used. But we suggested that such a preponderance of control without any counterbalancing power has potentially destabilizing impact for the whole world economy. Well, in the next lecture, we'll examine the role of civic society in the form of non-governmental advocacy groups.
8.3 Sub-State Actors: Transnational Advocacy Groups
In the last video, we looked at the power relationships between multinational corporations and national governments. And we looked at the concentration of control in the form of ownership, owner multinationals network, concentrated in the hands of a relatively small number of so-called super entities. We had to admit that we didn't know if or how that control was used. But we speculated that it represented a serious threat to the continuation of world prosperity.
Juxtaposed against this corporate world, we have civic society organized at various levels, local, national and international. Some organizations provide goods and services to the communities they serve. Others
act as spokespersons for specific interests. Many do both. Many are also organized at all three levels, their peak organization operating at a regional or international level. In total, there are about 25,000 international non-governmental organizations in the world. In this video, we'll concentrate on those espousing a specific cause or interest. In the literature, they've become known as transnational advocacy groups.
Some are professional groups representing teachers, lawyers, accountants and the like, but many

Some are professional groups representing teachers, lawyers, accountants and the like, but many represent major societal interests. Some are very well known. For example, Human Rights Watch and Amnesty International are active in the human rights field. Oxfam and Save the Children deal with humanitarian issues. Green Peace and Friends of the Earth represent environmental concerns.
The power of the people's voice against organized big business is a popular image, but what factors determine the success of advocacy groups? Well, the first thing to know is there are a lot of them, many with overlapping and competing ambitions. Not for nothing did we mention two examples for each of the three fields we introduced. But the fragmentation goes far deeper. In as far as these advocacy groups rely upon citizen support, this is more easily gained if the issue has some local resonance or if it's addressed in a proper cultural context. The result is the emergence of what's been called maps of grievance, where different groups are identified with different causes or different slivers of causes. Local and regional advocacy groups, therefore, tend to compete with existing transnational groups, squeezing the resources and blurring the focus.
Of course, once an advocacy group is formed, its success not only depends on its own organizational ability and strategy, but also on the permeability of the other organization it is trying to influence and the organization's strengths and tenacity of the influence groups ranked against it. In the case where it's pitched against corporate interests, transnational advocacy groups face a double imbalance. There is often an imbalance in the resources in terms of funding, access and expertise that could be mobilized by an advocacy group compared with that of organized big business.
But there is a second imbalance in the importance of the issue for the two parties. I don't mean here the importance to the advocacy group itself, the issue is always important to them, but to the citizens' interest and what they claim to represent. Let me take a simple example, and hopefully a neutral one, to illustrate what I mean. Several years ago, I worked on the question of why, when almost all economists condemn the European Common Agricultural Policy as illogical, inefficient and counterproductive, the policy seems so resistant to change. One thing to emerge was that the farmers' lobby was extremely well organized at both the national level, where it had been active very often since the agricultural crisis of the 1880s, and at the international level. Of all the interest groups examined, they were the most active, bombarding governments and parliaments with policy advice at both national and European levels. They were far more active and probably far better resourced than the consumer groups lobbying against them. But why was this the case? And this led me to look a little further. One of the things that GATT has done is to calculate how much of a farmer's income derives from what they call producers’ subsidy equivalents, in other words, how much protectionist measures contributed to their welfare. This amounted in the 60s, and 70s, 80s to almost half of their income. So no wonder they were so active. On the other hand, the extra burden imposed by these measures on consumers as a percentage of their expenditures was far, far smaller. Not only had the proportion of food in consumer budgets been falling over the last 30 years, but the proportion that farm gate prices, what the farmers receive, cost of what that represented in final market price when everything had been transported, processed, packaged and neatly arranged in a convenient shop, was relatively small. The sad fact is that for all the justification for the cause adopted by an advocacy group, it usually does not usually impact immediately on the life of a citizen.
This is the same whether it's the price of butter, the tortured cries of a prisoner in a godforsaken jail, the
starving child at the other end of a television documentary, or that little bit of extra carbon footprint that the car journey to the shops involve, even less, therefore, than additives for food, the exact safety standard, the legal responsibility of banks. For corporate interests, on the other hand, these questions do matter. They matter a lot. They immediately show up on the balance sheets, on the profit and loss accounts, and on the shareholder value. And they will use all their channels, the regular contacts with national officials as well as special pleadings with the relevant ministers and decision makers, to be heard. Corporate interest groups have deep reserves of patience and deep pockets of cash. The challenge

heard. Corporate interest groups have deep reserves of patience and deep pockets of cash. The challenge of advocacy groups is agenda setting, to raise the level of consciousness on an issue so as to galvanize a larger constituency and, more difficult still, to keep it there.
One of the problems apart from capturing the citizens' attention in the first place is the so-called free rider problem. It's difficult to sustain interest when any positive achievements are shared by society as a whole, regardless of whether citizens have even thought about the issue, let alone joined or helped fund any such campaign.
But let's finish on a more positive note. There are cases where international advocacy groups or networks have registered some success. The anti-apartheid movement succeeded in mobilizing government support that eventually forced policy change in South Africa. The movement against whaling, despite setbacks, has curbed the hunting of these animals to the brink of extinction. And the work of the Organization for the Prohibition of Chemical Weapons, based in The Hague, was rewarded in 2013 with the Nobel Peace Prize.
Well, we can sum up now. We have seen how globalization was accompanied by a growth of transnational advocacy groups and we touched on some of the conditions for success. We also investigated the imbalance in their position as opposed to that of corporate interests.
8.4 Sub-State Actors: Supranational Organizations
In the last two videos we concentrated on non-state tactics, multinational enterprises, financial corporations and transnational advocacy groups. This factor is international system. In this video I want to turn our attention back to the state, but in a form of organization where they share in making decisions and share in the consequences of those decisions.
In a period of globalization when according to some commentators, the power of the state is being eroded, group of states across the globe are trying to consolidate their positions by closer cooperation. Efforts of greater international cohesion are evident all over the globe from ASEAN in South- East Asia, Mercosur in Latin America, SADC in South Africa and I'm sure you could name many more. But the most ambitious, most advanced of these is the European Union. It has extended its membership from six countries in the 1950s to 28 today. And it's expanded its remit from the formation of a customs union to wider concerns of economic and monetary union, as well as tackling social and security issues. So in this video, only as an example, but we're going to concentrate on the European Union.
The European Union is supra-national. Supra, meaning above the nation. The concept implies the surrender of national sovereignty over certain issues. The state can no longer be certain about shaping its policies, thus the European ministers can reach decisions by qualified majority voting. And those decisions, once taken and approved by the European Parliament, automatically take the force of law in each of the member states. And a final feature of the arrangement is that only the European Commission is entitled to make any proposals. It controls the setting of the agenda for discussions.
The achievements of the EU are many. It's implemented a common market with no frontier barriers to trade, with shared regulations, with free movements of labor and capital, with common competition rules. It's constructed and partially dismantled the common agricultural policy. And it's formed a currency union among some of its members. It has also helped the transformation of the former socialist countries of East Central Europe, and has nursed them towards full membership. It is much stronger in international trade and financial negotiations, than had each of these countries acted independently. And perhaps most important of all, it has curbed nationalist, protectionist tendencies and beggar thy neighbor policies in the member states. Now not all of these achievements have been universally popular. But most would have been completely unthinkable in the early 1950s, when the first tentative steps towards European integration were made. And yet, the European Union is not really loved. Now there's a nice

European integration were made. And yet, the European Union is not really loved. Now there's a nice concept in political science literature called input and output legitimacy. Output legitimacy means that citizens are happy because they're getting the public goods they want. And input legitimacy means that citizens are content, because they feel they contributed towards the decisions being made. For a long time the EU has relied on output legitimacy. But especially after the Euro crisis, citizens have begun to question some of the policy choices that have been made. And at this point, the absence of input legitimacy comes into play.
But of course, you'd say, the European citizen is involved in decision making. Ministers representing them in the European Union have all been elected in national elections. But this idea of a mandated
democracy is somewhat contrived. And the citizens are also involved in the direct elections of the European Parliament. But that only managed to galvanize about 42% of the electorate entitled to vote, the lowest ever recorded.
Much of the problem lies that the issues discussed by the European Parliament. First of all, the EU doesn't spend much money, slightly over 1% of the Union's GDP. And so the usual tax and spend issues that form the day-to-day business of politics is missing. And the European Parliament cannot easily bring down the government, I suppose the European Commission, a body with one place reserved for a nominee of each member state.
But if democratic control and democratic legitimacy is weak, who does make EU policy? Well, most analysts would argue that the main players are the member states. And despite lurid headlines to the contrary, no one single large power determines the overall direction. For a long time it was suggested that the French-German axis was necessary to get things done, or more recently that Germany has been the most powerful force. But there's little evidence of consistent domination by any power or group of powers. It's interesting that small states, or at least the academics studying smaller states, seem to be quite in favor of the European Union, certainly in comparison with a situation where they'd be exposed to big power politics in the context of bilateral negotiations.
But let's stay with the question of who does make policy. Well the simple answer is the national government and the European Parliament agreeing together, and the European commission which prepares and presents the legislation. So if you want to influence policy you should really approach all three institutions, preferably simultaneously.
At first sight, the easiest to influence is the national government through the national press, through political parties, and through the members of national parliaments. But by itself this route is the least likely to bring any rewards since there's still 27 other states to get on side.
So a much better way is to approach the officials in the European Commission and get the bits of legislation slotted in before it's even published - the levels of chemicals permitted, the banned substances, the safety stipulation, the exact concessions in trade negotiations - try to get them all there before anyone can do anything about it.
At the same time, you could tackle European Parliament specialists committees, established to examine fields of legislation. Parliament tends to vote in party blocks, so when one or two of those offer a new legislation, it is home and dry. There are 30,000 lobbyists active in Brussels, and the Commission works particularly closely with the business lobby. The Directorate in charge of trade negotiations, active right now for example in negotiating trade deals with India and the USA, works especially closely with big business.
Many of the so called expert groups formed by the commission are top loaded with business representatives, often with members' affiliations being deliberately misrepresented, an academic with

representatives, often with members' affiliations being deliberately misrepresented, an academic with ties to industry being labeled as independent for example. Not surprisingly, corporate business interests are conspicuously overrepresented in the expert groups called to consider taxation and customs union and the group advising on enterprise and industry, as well as the group advising the Secretary General which guides the overall direction of policy. Well paid firms of lobbyists offer briefing papers to the members of the European Parliament, and try to maintain links with those
involved in scrutinizing different types of legislation. In all of these areas, small and medium enterprises, trade unions and civic advocacy groups are seriously under-represented. If we add to this the fact that monetary policy is settled by the European Central Bank, in Frankfurt, and that is also under the sway and influence of financial interest, you can see that we really got a problem.
So let's sum up. In this video, we've looked particularly at the problem and achievements of supra nationalities embodied in the European Union. We've exposed the problems of input and output legitimacy. And we've questioned the disproportionate role of corporate interest in influencing policy.
If we tie together what we've been discussing this week, then we can say the following, political economy is about the relationship of the economy to politics and society, and much of what it discusses is related to power. You don't have to be a revolutionary to be concerned about the situation that we've described. These are issues that call for democratic control. They call for citizens to reassert their command of the societies in which they live. The lesson is really very simple. If you don't like the look of the world which we've configured, do something positive about it however small. Try to change it. It's time for us all together to start to reconfigure the world.
These transcripts were provided by a student of the course “Configuring the World.” They were produced without compensation and any errors are the fault of the transcriber. They are the intellectual property of Leiden University.