Chinese GDP calculation and seasonality

Always interesting to read how different countries calculate their economic outputs, particularly GDP. This recent news article covers some changes to the Chinese GDP calculations with aspects relating to seasonality.

http://www.cnbc.com/2015/09/09/china-gdp-data-calculation-method-to-be-changed-to-improve-accuracy.html

The relevant bits are:

“Now, China is calculating GDP based on economic activity of each quarter to make the data “more accurate in measuring the seasonal economic activity and more sensitive in capturing information on short-term fluctuations”, the NBS said.

Previously, China’s quarterly GDP data, in terms of value and growth rates, was derived from cumulated figures rather than economic activity of that particular quarter, the bureau said.”

Always good to go back to the original source which seems to be at: http://www.stats.gov.cn/english/PressRelease/201509/t20150908_1241554.html

in the sections

“1.4.1 Preliminary Accounting

As China’s quarterly GDP accounting is cumulative before 2015, the GDP preliminary accounting of 1-4 quarters is annual GDP preliminary accounting. Since the third quarter of 2015, China’s quarterly GDP accounting is completed quarterly, which means calculating the GDP of four quarters respectively, and totaling them up to produce the annual GDP preliminary accounting results. Annual GDP preliminary accounting is accomplished before 20 January. “

Would be curious to see some time series analysis of the outputs, or how they may deal with any changes in seasonality at this switch over.

GDP and updates

The article below is worth a read. It is not often you see these type of nitty gritty statistical issues reported in the mainstream media but it highlights an important issue for compiling and comparing estimates.

“Two years ago Ghana’s statistical service announced it was revising its GDP estimates upwards by over 60%, suggesting that in the previous estimates about US$13bn worth’s of economic activity had been missed.”
Read it all: http://www.guardian.co.uk/business/2012/nov/20/economics-ghana (published 20 November 2012)

While it also seems to be a side promotion for the authors book (which is always the case I guess) it also captures the issue of data quality both within and across different countries.

Compiling statistics such as GDP (in the National Accounts) is not a simple thing. In a lot of major economies there are teams and teams of highly qualified people putting these estimates together. You don’t see them but they are often hidden away in the back rooms of statistical agencies. These brave men and women of the statistical world – yes! don’t laugh! – are often classified as nerds and geeks because it can take an unhealthy obsession with the finer details of the data and nuances of source data to compile a high estimate of GDP. It is often the case that with such a complex area, individuals will have over 20 or 30 years of experience in specific aspects of what makes GDP tick. It is not an easy task. And it is often why they are locked away in the back rooms.

A quick aside – and lately it seems to be a thankless task as the debate about the usefulness of GDP versus well-being measures rumbles onwards. Maybe this will be a topic for another post…

In this example, the compilation of GDP estimates is a worthwhile exercise, but what it really shows is the importance of getting the fundamental basics of the estimates correct. It also shows how vital it is to have regular revisions to country estimates, particularly when new or updated historical data becomes available, such as the contribution of different sectors of the economy. There are many detailed international manuals and frameworks for GDP compilation which have been around for many decades and are updated on a reasonably regular basis. The issues described in the article above are captured in detail in these types of manuals.

The manuals cover a lot of detailed points but if the basics such as having some fundamental knowledge and understanding of key concepts, while also having access to timely and quality source data, aren’t in place then in the end it doesn’t matter what the manuals (or consultants, or booksellers) actually say.