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BRICS and blocs

Beware of categorizations

Understanding the global economy has become more important for policymakers, given the increased interdependence in trade and capital flows. For the same reason, though, tracking the different economies has also become more complex. So it’s not surprising analysts find it convenient to group countries in blocs according to a characteristic or commonality. Examples include the G-7 (Canada, France, Germany, Italy, Japan, U.K., and U.S.), meant to designate the largest economies in the world, and the BRICS (Brazil, Russia, India, China, and South Africa), meant to designate the most significant emerging economies for their size and fast growth. And then there are the so-called PIIGS (Portugal, Ireland, Italy, Greece, and Spain), meant to designate European countries that were struggling to service their external debt a few years ago.

These classifications can be useful at certain points in time, but analysts and policymakers should keep in mind at least two important limitations. Countries in these blocs can behave very differently. And the classifications can very quickly become outdated, even if they continue to remain in use. I’ll illustrate these two limitations with FRED data for the BRICS.

Let’s look at real total GDP for these five countries, normalized so they all equal 100 in 1990. Using an index allows us to abstract from the large size differences of these countries and also gives a more transparent picture of how quickly each of these countries has grown between 1990 and 2014. The graph shows some large differences, indeed. China has grown dramatically since 1990—by a factor of 6. India is a distant second, growing by a factor of 4. Both Brazil and South Africa, in the middle, have doubled the size of their economies. Russia, which is last, has grown by barely 18% during the sample period; in fact, if anything, Russia’s economy was below its initial 1990 size for much of the 1990s and early 2000s.

So, should the BRICS be grouped together as a bloc? Only Brazil and South Africa behave in a reasonably similar way. Otherwise, these countries have big differences in economic behavior and their resulting relative importance.

A similar exercise could be done for the G7, where the relative importance of countries has also changed considerably. You may have known this already, but the G-7 no longer represents the seven largest economies: Canada and Italy have been replaced by China and India. And the internal rankings have also changed for the European countries, with Germany in 4th place, the U.K. in 5th, and France in 6th.

How this graph was created: Search for “real GDP at constant national prices for [country]” where [country] can be replaced by the actual name of the country you want. Select the units so that all variables are scaled by an index that sets the value of 100 for 1990. Choose 3 for the width for all lines.

Suggested by Alexander Monge-Naranjo.

View on FRED, series used in this post: RGDPNABRA666NRUG, RGDPNACNA666NRUG, RGDPNAINA666NRUG, RGDPNARUA666NRUG, RGDPNAZAA666NRUG

How much has China grown?

Uncertainty about the numbers

There’s some debate on how reliable the GDP growth rates from China are. In part, this worry comes from the pre-reform era in which all levels of production had to reach targets and may not have been entirely truthful. Also, the string of very high growth rates over the past two decades is unprecedented. Can FRED shed some light? Well, it has seven different series that measure GDP in different ways. One is from the World Bank, one is from the OECD, and five are from the Penn World Tables. Differences pertain to how currency conversions are treated. For example, there’s the issue that exchange rates may drift away from so-called purchasing power parity (PPP) and which side of the GDP equation is used. Indeed, technically, there are three ways to measure GDP: add up all output, all expenditures, or all incomes. All three should get to the same number, but in practice there are some residual errors. So what does this graph show? These different measures essentially come to the same conclusions, the differences being relatively small and not systemically biased in one direction. However, these statistics are based on information that is coming out of China. And, at least in the past, there was plenty of uncertainty arising from that.

How this graph was created: Search for “real GDP China” and select the relevant series, then click on “Add to Graph.” Click the “Edit Graph” button, then change the units to “Percent Change from Year Ago” for the lines that are not yet in growth rates.

Suggested by Christian Zimmermann.

View on FRED, series used in this post: CGDPESCNA666NRUG, CGDPOSCNA666NRUG, CHNGDPRAPSMEI, NYGDPPCAPKDCHN, RGDPESCNA666NRUG, RGDPNACNA666NRUG, RGDPOSCNA666NRUG

Shaking things up in China

During President Obama’s recent visit to China, even getting off the plane involved political upheaval: The New York Times described the mood as “tense” when disagreements between Chinese and U.S. officials compelled the president to use an alternative stairway to deplane Air Force One.

Chinese economic policy has also been tense for some time now, independent of their ability or willingness to accommodate a foreign 747. The graph above plots the Economic Policy Uncertainty Index from Baker, Bloom, and Davis for the U.S. and China. This index scans news articles about a country and records the frequency of phrases that connote economic policy uncertainty. When it’s high, the press is using language that suggests the government could change its regulations, spending, and/or taxes in the near future. As the authors point out, this uncertainty complicates planning and can adversely affect investment. It can also, however, reflect economic conditions themselves; as the economy sours, the political response is often uncertain as sides debate how best to respond.

Until recently, China and the U.S. tracked each other quite well, and such a connection might reflect common economic conditions in the two countries. But China did not share the U.S. experience during the 2001 recession; it shared only the rise in uncertainty. The bottom graph adds GDP growth to the mix, and the “pattern” we see has almost no pattern to it. GDP is slowing in China, but policy uncertainty seems to be hyperactive. Chinese GDP declined during the Great Recession, and since then the decline seems to have been smooth and slight. Policy language, however, has vacillated quite wildly. Perhaps President Obama should feel lucky his stairway remained in place as he descended.

How these graphs were created: Top graph: Search for “Economic Policy Uncertainty Index” and select the U.S. and China among the countries given. Convert both to a quarterly frequency for two reasons: The frequency of U.S. GDP is also quarterly, and the monthly swings in the Chinese index are so great they make it difficult to visualize the U.S. index. Bottom graph: Add two lines to the top graph: seasonally adjusted real U.S. GDP (converting it to a percentage change) and constant China GDP, which should give the U.S. dollar-denominated GDP (again, converting it to a percentage change). For both these new lines, go to the “Format” tab in the “Edit Graph” section and move the units to the right vertical axis. Note: FRED doesn’t have updated Chinese real GDP after 2014, but the latest figure from the National Bureau of Statistics in China puts growth at 6.7% in 2016:Q2, slightly lower than the 7.3% recorded in 2014, as shown in the graph.

Suggested by David Wiczer.

View on FRED, series used in this post: CHIEPUINDXM, GDPC1, RGDPNACNA666NRUG, USEPUINDXM


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