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 data. And we stressed how errors contained in this exercise might make the data unsuitable for sophisticated statistical analysis. Now 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 separate out the changes produced by fluctuations in prices. Statistical offices do this by constructing a special price index called the GDP deflator. Now 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, and in international comparisons, it's usually anchored to a currency, the dollar, at the exchange rate prevailing in a particular year. Now for many social scientists, this didn't go far enough. They observed that there were also structural differences 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 the country were consumed in the country, this difference in purchasing power is 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, that they eliminated these structural price differences. So you'll recognize these because they will all be expressed as something like 2012 US dollars PPP. 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 1950s. 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. Now the GDP figures were originally used for purposes of war time planning and post war reconstruction. And they retained their usefulness as governments tried to adjust their policies to smooth out the powerful economic development. In 1968, the World Bank and the University of Pennsylvania, which has since continued on its own, started an international comparisons project. Comparisons started with only ten countries, but the range of depth and 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. So 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. But 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 Starbucks coffee, by contrast, is only 4% cheaper. The lesson, of course, is that Starbucks is more up market in China than is McDonald's. But a bigger question is, do the Chinese consume much of either of them? Now 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. And 1995 was better than the previous effort on the date in 1985. Now I mention this because long run growth statistics stretching back before 1970, and even back into earlier centuries, are expressed in PPP values of 1990. This is because it was the year chosen by the OECD economist, Angus Madison, who did much of the pioneering work in this field. But there was no comparison made in 1990. The values from 1990 are extrapolations from 1985. And in 1985, only 62 countries were actually surveyed. The price differences discovered there assumed to prevail over the neighboring countries as 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 are being 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. It's 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. But 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 add the complications in international price comparisons. But there are still problems and uncertainties in the results. Now in the next video, we're going to look at how these new PPP estimates were fed into the debates on poverty. In the meantime, we've taken a 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.