Hi there. In the last video you saw how we tend to distort our world picture with our own preconceptions. Well in this video, we are going to explain why we need the basic data we will 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 distort the size of states superimposed upon it. But why should states matter? Why should they be the unit of our analysis? Well there are several pretty good reasons. Firstly states intercede on our behalf with other states, and if necessary, they defend us. States also provide and enforce the rules that govern most of our actions inside their borders. States tax us, and provide us with collective goods, and states collect and collate data most often at the national level. And for this reason, social scientist were interesting comparison 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 wanted as a base of taxes and partly to recruit manpower for large-scale projects like pyramids or for membership of the army. Well, we are also interested in population because it offers us a quick guide to the size of states, to their economic and military potential. We're also interested because we regularly divide different data by population to reduce it to a common unit. Many measures are expressed in per capita terms. Per capita coming from the Latin meaning per person. Now, social scientists generally assume that population data is accurate. But we'll see how well founded that belief is in the next video. Now 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. Well 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's only one or two states to collect national income data in the 20th century, and the practice only became common immediately after the second world war. But calculating national income is far more complex than just counting the population and the room for error is much, much larger. Now we are interested in national income for several reasons. Once we have converted it to a common currency, like the dollar, it provides an indicator of how large a country is in relation to the rest of the world economy. If we divide it by the labor force, we get a good idea of a country's productivity or competitiveness. If we divide it by population, we get an idea of the level of wealth at the disposal of its citizens. And on this last basis, we used to make statements about how rich or how poor a country was. We used to, but not anymore. Anyone who's travelled abroad will have had the experience that the country visited seems expensive, or alternatively, it's cheap. A 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. But in the 1970s, economists started experimenting by calculating new purchasing power parities to obtain a better basis for national income comparisons. But note very carefully now that any errors in the original calculation still remains. 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 remains 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 provide with the clearer measure for comparing levels of consumption between countries. But per capita income however measured is still an average, it doesn't tell us much about the degree 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 as 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 political economists employ when they try to configure the world. Now, for 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.