Is Chinese Economic Growth Stalling?

Brian Sturgess - October 2011


The Data Problem

Manufacturing

The latest official figures show continuing strong growth in Chinese industrial output. The BNS reported that for the first half of 2011 the total value added of industrial enterprises  [2] had increased by 14.3% year-on-year, only slightly down from a rise of 14.4% in the first quarter of the year. All the 39 industrial divisions measured registered year-on-year growth. In August, the total value added of manufacturing was up by 13.5%, only slightly down by 0.5% from the year-on-year figure for July. Industrial profits for the first eight months of 2011 rose by 28.2% year-on-year. [3]

A much more pessimistic picture, which is completely at odds with the official data for industrial output, is emerging from other sources which provide measurements of manufacturing production activity.[4] The HSBC China Manufacturing Purchasing Managers Index (PMI) [5] calculated for September 2011 stayed steady at its August figure of 49.9 after rising slightly from the eleven month low of 49.3[6] in July, down from 50.1 in June. [7]   According to the press release accompanying the latest HSBC PMI figures:- “The stagnation of China’s manufacturing sector continued in September, with output growth constrained by lacklustre demand from both domestic and external clients. “

A similar picture was recorded by the official China Federation of Logistics and Purchasing (CFLP) for the second quarter of 2011. The CFLP calculated a manufacturing industry PMI of 50.7 for July down from 50.9 in June and 52.0 in May and 52.9 in April. This also suggested a slowdown in output. The most recent figures show that the CFLP PMI figure rose marginally to 50.9 in August and to 51.2 for September, but these changes are far too small to signal any recovery and are consistent with the indications of slowing output presented by the HSBC PMI.  However, the Li & Fung Research Institute, the company responsible for compiling and disseminating the CFLP PMI survey, stated optimistically that the figures “indicated that the manufacturing sector in China was expanding in a steady manner. Looking ahead, industrial activities will continue to be supported by local government’s accelerated efforts to build public housing and robust consumption demand.” [8] Both sets of PMI data are created using different samples and methodology, but both indicate a different story to the continued and uninterrupted growth suggested by official BNS estimates.

 

 

Services

The growth picture is more opaque in the services sector, where it is far more difficult to measure economic activity, but the existing evidence shows a closer agreement between official and private survey data focused on this sector. The BNS reported that the entire tertiary sector increased its value added by 9% in the first half of 2011, compared to 10% for secondary industries, including manufacturing, and 3.2% for primary industries. In terms of specific sectors, the BNS data reported, that retail sales of consumer goods rose year-on-year by 16.8% in the first half of 2011. The income of the catering industry was up by 16.2% percent while the sales of motor vehicles rose by 15.0%; that of furniture grew up by 30.0% and that of household appliances and audio-video equipment went up by 21.5%.

 

The mixed pattern of continuing against stagnating growth shown in the manufacturing sector PMIs was echoed in the surveys of service sector activity. The non-official HSBC China Services PMI has been volatile showing business activity rising from 51.6 in April to 54.3 in May and holding steady at 54.1 in June, before declining to 53.5 and to 50.6 in July and August respectively. September’s figure, however, shows a rise to 53. [9] In contrast, the latest official China Federation of Logistics and Purchasing (CFLP) figures calculated a PMI for the non-manufacturing sector of 57.6 for August, down from 59.6 for July which had been a rebound up from 57.0 for June, after falling down from 61.9 percent in May and 62.5 in April.[10] Overall this suggests that this segment of the Chinese economy is still holding up well and according to the CFLP was still maintaining relatively fast expansion.  In summary, both the HSBC Services PMI and the CFLP indicate that the tertiary sector of the Chinese economy is still experiencing growth, albeit at a slowing rate, but with highly volatile monthly directional trends .

 

GDP

The NBS have announced that the preliminary estimation of real GDP growth in China for the first six months of 2011 was a rise of 9.6% year-on-year. This contrasts sharply with the latest PMI composite figures (for manufacturing plus services) which suggest economic growth in China is slowing down sharply.

 

The HSBC composite PMI’s and a weighted average of the China Federation of Logistics and Purchasing (CFLP) manufacturing and non-manufacturing PMIs, although not a total proxy for changes in GDP, since some sectors are excluded, should still correlate reasonably well with growth in the total economy. The HSBC composite index, taking account of business activity for both sectors, assumes that the service sector accounts for 43% of GDP in China, rose slightly to 51.5 in September after staying steady at 50.4 in July and August, but this is still well down on the long-run series average of 54.6.The relative strength indicated in the HSBC PMI services sector was outweighed by the weakness signalled by the survey results in manufacturing. The CFLP does not produce a composite index, but using a weighted average of the August Manufacturing PMI and Non-manufacturing PMI produce, using the same ratios of sector economic activity as HSBC produces a ‘composite’ figure of 53.8 for that month, indicating a picture of continuing economic growth, but not to the same extent as the GDP data.

 

 

 

Can we trust Chinese data?

Given the significant divergence between the different data sources concerning the anticipated growth in the Chinese economy it is necessary to look for an explanation. The first possibility is based upon concern about the accuracy of the official data. In short, can the NBS data be trusted?

 

There has been much controversy for some time concerning the accuracy of official Chinese economic statistics. A recent revelation in December 2010 suggested that even senior Chinese politicians do not rely on official data. A Wikileaks cable alleged that Vice-Premier Li Keqiang had told the American Ambassador in 2007 that he considered GDP statistics for the Lionang, the north-eastern province he was then governor of, to be “man-made”. Another recent report suggested that China is under-reporting steel production by around 40 million tonnes a year with the objective of keeping open uneconomical and high pollution plants to supply local demand.[11]

 

To add to the fear that figures may be deliberately doctored for political reasons, there is also some distrust concerning the technical ability and adequacy of the resources available to the statistical authorities in China.  China releases GDP output data only a few weeks after the end of the reference period within the Special Data Dissemination Standard (SDDS) time frame set by the IMF for the timeliness of economic data. [12] However, given the size and complexity of the Chinese economy there are some concerns about the rapid release of preliminary GDP data with the contention that the data are, to some largely unknown extent, made-up. These data issues are explored below.

 

The existence of these fears and the size and importance of the Chinese economy together with the two different perspectives on the prospects for Chinese growth pose a serious dilemma. Which picture should be believed? There are several issues to consider.

 

First, what problems underlie the production of Chinese official statistics and are they being resolved.

 

Second, do the private and official PMI manufacturing surveys provide a more accurate picture or do they suffer their own problems?

 

Third, what other data is available and does this indicate whether or not it is better to rely on the PMI surveys or the official data released by the NBS?

 

The next section considers the first of these issues.

 

 

Official Data Compilation

Before 1985 China used the Material Product System (MSP) favoured by other communist countries which concentrated on measuring economic activity in the production of goods and commodities and included only those services which had a direct link with production. An example given by Pant and Blades (2007) is that freight rail transport was included as part of national income while passenger transport was excluded. However, despite the omissions Thomas Rawski (2000) considered that – with the exception of the wildly false reporting during the Great Leap Forward – this system produced a “wide array of reasonably accurate”[13] statistics, but between 1985 and 1992 preparations for the transition from MSP to United Nations System of National Accounts (SNA) were started and although much progress has been made some institutional and methodological issues relating to the old system remain.

 

The National Bureau of Statistics (NBS)[14] has since 1992 almost entirely adopted SNA conventions for reporting GDP. However, gathering reliable economic data in a country so vast, heterogeneous and rapidly changing as contemporary China is challenging.  One problem facing any country is the need to devote trained manpower to the task of collecting, auditing and analysing statistical data and Maddison and Wu (2002) estimated that the number of central NBS staff directly devoted to China’s National Accounts in the year 2000 was only 26 [15] although the NBS has made significant efforts since then to improve the standard and accuracy of national income accounting.   

 

It is clear that the National Bureau of Statistics has made continual efforts to improve estimates of GDP estimates and have identified and attempted to rectify methodological problems. These efforts have been explained by Xu (1999) and (2000) in terms of the need to progress on the implementation of SNA international national accounting standards. Many of these efforts have only increased the level of uncertainty about the accuracy and transparency of Chinese economic statistics.  In 2006, for example, the National Bureau of Statistics undertook a benchmark revision of national income and product accounts statistics based on the findings of the 2004 economic census. The revision covered primarily the years 1993-2004 with revised economy-wide and sector output values. Chinese GDP for 2004 was revised upwards by the National Bureau of Statistics by 16.8%.

 

 

Falsification
The NBS initially relied entirely on what is still referred to as the “regular reporting system” whereby output data was fed from managers of state owned enterprises to local party chiefs, then town, city and province intermediaries through to the NBS. This still plays a significant role in the data reporting process, and the number of links in the chain leaves scope for distortion. Carsten Holz (2008) noted that from 1996 until 2004 there was a growing discrepancy between the sum of GDP calculated at the provincial level and all-China GDP estimates. National estimates were consistently lower than the aggregation of the provincial figures and the difference had reached 19% of the national estimate by 2004. According to Holz (2008):

“The rising discrepancy coincided with a wave of reports on local data falsification in 1997 through approximately 2001. In response, the NBS, with support of the State Council and the Disciplinary Commission of the Chinese Communist Party Central Committee, in 1997/98 started a campaign against local data falsification. The continuing discrepancy between the national data and the sum provincial data all the way up through 2004 would suggest that the campaign against the “wind of falsification and embellishment” was not successful.”[16]

Moreover, the incentives for the 100,000[17] or so staff across all levels of government who feed this data up to the NBS are not well aligned towards accurate reporting. Politically motivated tampering is considered widespread, responding to a range of incentives that change with the business cycle and with government priorities.[18] Corruption and the manipulation of accounts and statistics for personal gain are also issues of concern. In July 2011 it was announced by Liu Jiayi, head of the National Audit Office that 16,000 government officials or leaders of state firms have been removed or demoted in economic accountability audits since 1999. Economic accountability audits evaluate the performances of leading Party and government officials and leaders of state-owned enterprises (SOE) in the management of public funds, national resources, state capital and social funds.


Service Sector Coverage
The service sector has long proved a source of difficulty and under-measurement of economic activity for the NBS. Services were virtually ignored under the Material Product System so when the NBS switched to the SNA in 1985, a new system had to be devised to collect data on government, personal, business and cultural services. A 1992 Tertiary Census was undertaken in 1993 which was the first survey of the country’s service activities which showed up many gaps, errors and omissions in reporting. As a result total services value added in current prices was revised upwards in for 1992 by 33.1%. Total GDP was revised upwards by 9.3%.

In recognition of the potential continued underestimation of tertiary economic activity as the China has undergone structural change in the years since 1992, the NBS has enlisted the support of the Asian Development Bank (ADB) to improve the measurement of economic activity in the services sector. See ADB (2002) and (2006). China conducted a broader nation-wide Economic Census in 2005 with 2004 as a reference year and found that the NBS did not have adequate information to extrapolate the results of the 1992 survey. These surveys bypassed the usual reporting system and gathered direct information, suggesting much economic activity was being overlooked. In 2004 the service sector was revised again up to 48.7%, raising total current price GDP for that year by a further 16.8%. According to Bishnu Dev Pant and Derek Baldes two economists at the Asian Development Bank in a report written in 2007 “most of the revisions were due to the failure to track the growth of services.”[19]

 

There are many different methods in use across the world for the estimation of real output and value added in service sectors. The 1993 SNA recommends the use of double deflation[20], but in China the NBS converts retail and wholesale trade using a single deflator, the Consumer Price Index, whereas most OECD countries deflate retail, wholesale and trade in motor vehicles using different deflators estimated for each activity. In order to improve estimates of real service sector activity, China needs to bring its existing price indices in line with recommendations by the IMF and the ILO for consumer and producer price indices. See ILO (2004).

 

There are strong indications that improved measurement of services could lead to further significant upward estimates of the size of the Chinese economy. For example the NBS, with the assistance of the Asian Development Bank, carried out a 2005 Beijing Pilot Survey of Service Activities for one province. The sample survey was confined to collecting information on two groups of services on which the NBS had not been able to collect enough information through its regular reporting system previously.[21] The Beijing Pilot Survey produced estimates of service activity value-added 21% higher and the total of employee compensation 51% higher than was estimated by the 2004 Economic Census.

 

 

Informal Sector Coverage
Measuring the formal service sector is not the only problem; there is also considerable unrecognised economic activity in the informal or grey economy. Cash only businesses are widespread in China, allowing unregistered producers and retailers who pay no tax to operate without showing up in official figures. Schneider (2002) estimated that the shadow economy in 1999/2000 was 13.1% as a proportion of GNP, which was lower than the average 38% experienced by the transition economies, but he noted that it was still dominated by communist controls.  It would be expected that as controls on economic activity relaxed the size of the formal economy might increase especially given the migration from rural areas to cities. Economists at the University of Macau have estimated the size of the urban informal sector in China at 28.8% of GDP[22], while a 2008 study sponsored by Credit Suisse and the China Reform Foundation sought to quantify this phenomenon by taking 4,000 survey samples on income and expenditure across 64 cities and 19 provinces. The authors of the latter study found an additional 9.3 trillion RMB in the economy - equal to 30% of China's GDP[23].

 

Conclusion
Despite the remaining problems it appears that China’s statistical capacity is improving, that the transition from MSP to SNA begun in the 1980s is almost complete, and that the NBS is behaving more like a statistical office should - with less direct political pressure and greater transparency. Direct reporting is playing a decreasing role, with a more widespread use of surveys being employed. Tom Orlik, now Beijing correspondent for the Wall Street Journal has noted developments in recent years which give cause for optimism in terms of transparency and political pressure on the NBS. [24] He has commented that the NBS have successfully dealt with problems of data discrepancies by engaging with interested parties transparently and providing acceptable explanations. In addition, Orlik notes that Chinese citizens have recently been placing increasing pressure on the NBS over widely disbelieved and incongruous wage and house price data, most notably through new media and technology. In short, although inevitably imperfect, Chinese official economic data appears to be improving and there are some indicators that where there are deficiencies the growth rate in the economy may be underestimated.

 

How accurate are Chinese PMI Data?
The growing difference between the official economic data and the two manufacturing PMI series  invites a critical consideration of the accuracy of the latter. The two PMI series appear to be closely related, but  [25] neither the HSBC nor the CFLP PMIs exhibit a robust relationship between the level of the indexes and industrial production since the joint movement, or correlation, between the PMIs and manufacturing output growth falls off over time. [26]The growing discrepancies between official NBS data and the level of economic activity indicated by the PMI data requires an explanation and there are a number of possible reasons why using PMI data has become problematic for measuring the strength of the Chinese economic growth rate. These problems are explored below.

  

The “Bullwhip Effect”

The Financial Times recently noted [27] that there is also a structural issue which may be affecting the accuracy of Purchasing Managers Surveys, which may be inherent given the occupation of the survey respondents when demand fluctuates rapidly in a relatively short period. This is known as the “bullwhip effect” and occurs as a result of supply-chain reactions. If an unexpected fall in consumer demand leads to retailers reducing orders to cut inventories this can lead wholesalers to under-order until stocks in the supply chain become scarce.  Suppliers then experiencing ‘stock-outs’ can over-order from manufacturers in response. This effect can ripple up and down the supply chain many times producing volatile PMI data. Excessive restocking process can lead to reactions which could bias the PMI towards a level suggesting that demand is contracting while GDP is still growing. This whiplash effect has been observed recently in the pattern observed in the European Purchasing Managers Index which fell from 52 to 34 before rising rapidly to 58 in February 2011 where it peaked before falling to around 50 currently. The same phenomenon may be taking place in China. In this case the recorded PMI changes from the surveys are reflecting slack and tightness in supply chains caused by purchasing managers policies. As the Financial Times commented - “To break the unhealthy cycle of glut and shortage, procurement managers need to stay calm when supply changes.”[28]

 

 

Sample Size

A second problem may be due to sample size and bias. The HSBC Manufacturing PMI, compiled by Markit, is based on data compiled from monthly questionnaires sent to purchasing executives in a sample of 400 companies. The panel is stratified by Standard Industrial Classification (SIC) industrial group and by geography. The comparable index for Germany, again compiled by Markit, is based on a greater sample of 500 companies, which begs the question of the reliability of basing estimates on a smaller sample on a much bigger, geographically dispersed and less internally integrated economy.

 

In 2010, the GDP of Germany measured in PPP terms was only 29% that of China. In other words, the average level of GDP being inferred per responding company was US$5.881 billion in Germany and US$25.214 billion in China, all measured in PPP international dollars. The official China Federation of Logistics and Purchasing (CFLP) is compiled by the CFLP using data collected by the NBS. The questionnaires are sent to 820 enterprises[29] , but although the higher sample size means that the average level of GDP per responding company is lower at US$15.374 billion it is still close to the national income of Armenia. Nevertheless, if sample size is a problem in using these indices it is one for both Chinese PMI series since the correlation between changes in the level of the two is fairly high. [30] In order to assess whether or not the sample size is too small, it is necessary to have additional information which is not available. [31]

 

 

Weighting

Another problem might be the weights used in the Chinese PMI series. Both the HSBC and the CFLP PMI series are composite indexes based on five individual indexes with the following weights: New Orders – 0.3, Output – 0.25, Employment 0.20, Suppliers Delivery Times-0.15 and Stock of Items Purchased. These weights are identical to those selected by the US Department of Commerce and the National Association of Purchasing Managers (NAPM) on the basis of the estimates which maximized the correlation between the PMI and GDP growth. The reweighting, discussed in Torda (1985) and Bretz (1990) replaced an equally weighted index in 1982 and have not been adjusted since. This begs the questions of whether weightings developed for the US may be inappropriate to China and that there may be a need to readjust weightings in response to major changes in the structure of an economy. A paper by Pelaez (2003) argued that the existing PMI is not optimally weighted and found that the production and inventories indices contributed nothing to the explanation of GDP growth.

 

 

Conclusion

Despite the common use of purchasing managers surveys in many developed countries, the performance of the two PMIs available for China suggests that although they may give an indication of economic activity in China, the size, growth and uncertainty arising from rapid structural change in the Chinese economy, suggests that at this stage they should not be relied on without considering other economic data series.

 

 

What other Data can be used?

The allegation made that Chinese Vice-Premier Li Keqiang considered GDP statistics to be “man-made” also noted that he preferred to use a range of more direct indicators. His top three were electricity consumption, rail cargo volume and bank lending.  The international newspaper, The Economist, accordingly compiled a “Keqiang Index” of these indicators for the decade from 2000. Interestingly, growth figures were more or less the same as the official data, albeit much more volatile.  The “Keqiang Index” also revealed a deeper plunge in GDP growth in response to the world economic downturn of 2008 and a more rapid and greater recovery for 2009 with predicted GDP growth twice the official figure that year. This was followed by a rapid convergence to the end of 2010.

 

The three variables that it is alleged Li Keqiang relied upon are currently showing a picture of a much less rapid slowdown than indicated by the PMI figures.

Electricity Consumption
Data for monthly power consumption in China is published by Chinese National Energy Administration. China has been facing power shortages in many provinces as demand for electricity outstrips supply despite an increase in generating capacity. [32]

The available data on electricity consumption shows a picture of strong growth from 2.837 trillion kilowatt hours in 2006 to 4.19 trillion kilowatt hours in 2010, although the year on year growth rate of 14.8% in 2007 slumped to 5.3% in 2008 and 6.3% in 2009, as a result of the economic crisis and global slowdown, before accelerating again to 15.0% in 2010. The latest forecast of electricity consumption made by the Chinese National Energy Administration (NEA) at the end of April is for an overall rise   of electricity consumption of 12% for 2011, up from their earlier forecast of 9% for the year’s growth in January. [33] Power consumption rose by 12% in the first six months of 2011, but consumption for the first half of 2010 was up 21.8% on 2009. [34] The latest power consumption figures show electricity use up by 10.8% in August 2011 from the same month the year before to reach 434.3 billion Kwh. 

 

Chart 1 which tracks electricity consumption data and industrial output on a monthly basis from April 2009 to July 2011 shows that the rate of growth year on year has been volatile, but although it has been slowing consistently since the sharp rise in 2009 as the Chinese economy bounced back from the slowdown the year before, is still indicating steady GDP growth and not a sudden sharp slowdown.  The relationship between the growth in electricity consumption and industrial output over this period is far stronger than that between the changes in level of the PMI and the growth in manufacturing output.[35]

 

 

CHART 1

 



 

Rail Freight

A similar picture of strong growth emerges from data on railway freight movements which are available from the Ministry of Railways [36]  which shows that 2,604 million tons of freight carried across the country in August, up by 7.8% from the same month in 2010. Freight volume in the previous three months, from May to July 2011, totalled 5.83 billion tons, up by 7.9% on the same period in 2010. Given the importance of freight traffic in industrial production, this data does not suggest the stagnation suggested by the manufacturing PMI figures. Passenger volume was also up strongly in August by 9.5% to 6,709 billion person-kilometers carried.

 

Bank Lending
Data for August 2011 released by the People’s Bank of China shows that bank lending increased to 548.5 billion yuan rising from a seven-month low of 492.6 billion yuan in July. However, China's broad money supply, M2, rose by 13.5% year on year slowing down from 14.7%.  However, official bank volume figures do not illustrate the significant amount of off-balance sheet financing which is occurring in China.  Indeed to track non-traditional lending, the People’s Bank of China proposed in February 2011 that monetary conditions be measured using "social financing," a broad category of credit that includes on- and off-balance-sheet loans and bond and equity issuance. In the first quarter of 2011, designated loans, or loans lent from one firm to another but facilitated by banks more than doubled to 320.4 billion yuan (US$49.6 billion) from the same period last year.

 

Conclusion
The divergence between the HSBC and CFLP PMIs and official NBS data concerning the current rate of growth of the Chinese economy, is difficult to explain. The balance of evidence suggests that the rapid, although slowing growth reflected by the official NBS data is the more reliable picture. The view that growth is stalling indicated by both PMI surveys of manufacturing activity is neither vindicated by the official data nor by other indicators of growth such as electricity consumption and rail freight volume.  Furthermore, there are a number of reasons why small sample PMI surveys may be less useful in an economy as large as China in addition to the flaws in these surveys when there are sudden decelerations and accelerations of growth such has been experienced by many economies in the last few years.

There are certainly shortcomings in NBS data, which is still subject to a considerable degree of uncertainty due to a multitude of potential biases, but this is generally improving. In addition to these general SNA shortcomings are the problems particular to the NBS: the consistent difficulty in adequately capturing economic activity in the tertiary sector; the reliability of the large numbers of staff feeding information to the centre; the lack of scope and sophistication in survey techniques in comparison to developed country statistical agencies; the political pressure which may at times be placed on the NBS by the government; and the lack of transparency throughout the process.

 

There are, however, a number of reasons why the Chinese economy may be growing faster in real terms than is indicated by the PMI survey data. These include measurement errors in estimating the size of China’s services and informal sectors. The discrepancy between the conclusions of the survey data based on the economic conditions facing purchasing executives and official data are much more marked for manufacturing, indicating a severe slowdown in the growth in industrial output, than for the services sector. If the services sector is bigger than the estimated of 43% of GDP used by HSBC and if it is growing faster, then this could provide a partial explanation of the differences in estimates. However, on balance and given the continuing investment in official data collection in China it seems likely that the NBS estimates are the ones to watch as of now.

 

 

 

 

 

References

ADB (2002), Technical assistance to the People’s Republic of China for Improving Services Sector Statistics, Asian Development Bank, Manila.

ADB (2006), Consultants Report on TA 4125: Improving Services Sector Statistics in China, Asian Development Bank, Manila.

Deaton, A., and Heston, A. (2009), Understanding PPPs and PPP-Based National Accounts, NBER Working Paper No. 14499

Dikhanov, Y., and Swanson, E. V. (2010), Maddison and Wu: ‘Measuring China’s Economic Performance’, World Economics

The Economist, “Keqiang ker-ching. How China’s next prime minister keeps tabs on its economy” December 9, 2010

Giles, J., Park, A., and Zhang, J. (2004), What is China’s True Unemployment rate? China Economic Review

Herd, R. (2005), The Chinese National Accounts: the Perspective of a User, Economics Department, OECD

Holz, C. A. (2004), China’s Economic Growth Statistics: Trustworthy in the Long Run, Less So in the Short Run, APARC Dispatches

Holz, C.A. (2008), China’s 2004 Economic Census and 2006 Benchmark Revision of GDP Statistics: More Questions Than Answers? The China Quarterly, Vol. 193, March.

Holz, C.A. (2008), How can a subset of industry produce more output than all of industry? “Measuring Productivity Growth in China, 1952-2007”

ILO (2004), Consumer price index manual : theory and practice. International Labour Office, Geneva.

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Maddison, A., and Wu, H. X. (2008), Measuring China’s Economic Performance, World Economics

OECD. (2005), China in the Global Economy- Governance in China

Pant, B. D., and Blades, D. (2007), Measurement of Services Sector Statistics in the People’s Republic of China: How can They be Improved? Asian Development Bank - ERD Occasional Statistical Paper Series No. 2 Nov 2007

Rawski, T. G., (2000), China By The Numbers: How Reform Affected Chinese Economic Statistics, prepared for conference on “Key Issues in China’s Economic Development and the Use of Statistical Data, Beijing, May 9-10, 2000.

Rawski, T. G., (2001), What’s Happening to China’s GDP Statistics? China Economic Review

Rawski, T. G., (2002), China’s GDP Statistics - A Case of Caveat Lector?

Rossi, V., (2005), The Chinese Economy: Risky Reporting, Chatham House International Economics Program.

Schneider, F. (2002) Size and Measurement of the Informal Economy in 110 Countries around the World, Paper was presented at an Workshop of Australian National Tax Centre, ANU, Canberra, Australia. http://www.amnet.co.il/attachments/informal_economy110.pdf

Subramanian, A. (2011), Is China Already Number One? New GDP Estimates, Institute for International Economics Real Time Economic Issues Watch

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Xu, X.C. (2006), Recent Progress in China on the SNA and Challenges for the New Revision. Paper delivered at the General Conference of the International Association for the Review of Income and Wealth, Joensuu, Finland.




[2] This is based on surveyed industrial enterprises. In January 2011, the National Bureau of Statistics had raised the cut-off size of industrial changed from an annual revenue from primary activities above 5 million yuan to 20 million yuan.

[4] There is not an exact correspondence between industrial output as measured by the BNS and manufacturing as measured by the PMI due to the exclusion of some sectors in the latter.

[5] This is based upon data compiled from monthly replies to questionnaires sent to purchasing managers in over 400 private sector companies.

[6] Index values close to 50.0 suggest slow growth or stagnation.

[12] The SDDS is explained at the following location: ww.estandardsforum.org/about_standards/special-data-dissemination-standard

[13] Rawski, T.G., China by the Numbers: How Reform Affected Chinese Economic Statistics, Conference paper onKey Issues in China’s Economic Development and the Use of Statistical Data”, Beijing, 2000,  p1

[15] Maddison, A., and Wu, H. X. (2008), Measuring China’s Economic Performance, World Economics, p20

[16] Holz (2008) p151.

[19] Pant and Blades (2007), p3.

[20] According to the OECD: ‘Double deflation is a method whereby gross value added is measured at constant prices by subtracting intermediate consumption at constant prices from output at constant prices; this method is feasible only for constant price estimates which are additive, such as those calculated using a Laspeyres’ formula (either fixed-base or for estimates expressed in the previous year’s prices)’  http://stats.oecd.org/glossary/detail

.asp?ID=674

[21] Classified by the National Industrial Classification these were Tenancy Services and Business Services (Code L) and Resident Services and Other Services (Code O).

[23] BBC News, “Figuring out China's real economic size”, 04 August 2010

[24] For example, in the first quarter 2009 another apparent divergence between GDP figures and associated indicators such as electricity consumption and tax revenue in early 2009 appeared to be developing. Unlike the similar divergence between indicators and the widely disbelieved growth rates around 1998, Orlik considers the NBS to have successfully dealt with the problem by engaging with interested parties transparently and providing acceptable explanations Orlik, T., “The rich get richer - NBS plans to revise wage data system March 6th, 2010.

[25] Over the period August 2006 and June 2011 based on the author’s calculations the correlation between the two PMI measures of manufacturing activity was 0.808.

 

[26] Over the period August 2006 to August 2011 both PMI indices show a close relationship with year on year changes in Chinese industrial production. Based on the author’s calculations changes in the level of the HSBC PMI and movements in industrial output  move closely together with a correlation of 0.759 between the two variables compared with a figure of 0.702 for the CLFP PMI. However, the relationship between the two PMI series and industrial output breaks down from 2009 onwards following the sharp fall and subsequent recovery in the rate of growth of Chinese manufacturing industry. The correlation between the HSBC PMI and monthly changes in industrial production falls to 0.399, while that between the CFLP PMI and industrial output falls to 0.525.

 

[27] Financial Times Lex Column, August 1, 2011

 

[28] Financial Times Lex Column, August 1, 2011

 

[29] The sampling method uses Probability Proportional to Size Sampling (PPS) which means the selection of enterprises surveyed is based mainly on the industry’s contribution to GDP and the representation of the geographical area.

[30] The correlation between the two series between August 2006 and June 2011 was 0.808.

[31] In particular the standard errors of the sample estimates without which it is impossible to assess how wide a margin of error must be placed around values of the PMI levels.

[33] No reason was given

[35] The correlation between the monthly change in power consumption and industrial output was 0.68 compared with 0.47 for the HSBC Manufacturing PMI and industrial output.

[36] http://www.china-mor.gov.cn