China has achieved tremendous progress in modernizing its economy and is increasingly integrated into the global economy. As the market plays a more decisive role in economic and financial developments, the Chinese government and market participants need accurate and timely information for sound policymaking and investment and consumption decisions. New requirements for data call not only for a broader range of indicators, involving all sectors, but also for more frequent release of timely and high-quality macroeconomic data. China’s economic and financial integration with the rest of the world (Figures 12.1–12.4) also suggests the need for cross-country comparable data to support comparative analysis, the coordination of global economic policies, and informed decision making.
Share of World GDP
(Percent, 2015)
Sources: IMF, World Economic Outlook database; and IMF 2016.Share of Foreign Exchange Reserves
(Percent, 2015)
Source: IMF, International Financial Statistics database.Contribution to Global Growth
(Percentage points)
Sources: IMF, World Economic Outlook database; and IMF staff calculations.Along with these developments, the Chinese authorities have continued efforts to modernize the statistical framework; particularly measures to strengthen the statistical system and enhance data transparency. This culminated with China’s subscription in October 2015 to the Special Data Dissemination Standard (SDDS) of the IMF, which positioned its statistical practices at a higher tier of the IMF’s data dissemination standards, an important step in the dissemination of more timely and comprehensive statistics. Box 12.1 summarizes key dimensions and elements of the SDDS.
As a member of the Group of Twenty (G20) nations, meanwhile, China has been involved in the G20 Data Gaps Initiative (DGI) (Box 12.2) and has made important progress in several key areas of the DGI framework.
This chapter reviews recent developments in China’s statistical system for producing and disseminating macroeconomic statistics and highlights statistical challenges facing the rapidly growing economy.
Recent Developments in China’s Statistical System
Macroeconomic statistics have one broad purpose: to serve decision making. The availability of comprehensive, reliable, timely, and high-quality statistics is essential for the formulation of appropriate macroeconomic and financial policies. Discussion here focuses primarily on the following macroeconomic data sets: real sector statistics (national accounts, labor market statistics, and prices), government finance statistics, external sector statistics, and monetary and financial statistics.
Real Sector Statistics
The National Bureau of Statistics (NBS) is responsible for compiling real sector data in China and has come a long way toward the adoption of the System of National Accounts (SNA) as a comprehensive framework.1 The first official accounts were compiled in 1952 in accordance with the Material Product System (MPS),2 with official SNA estimates produced from 1985. Accounts were compiled from 1985 to 1992 using both the MPS and the national accounts, although the latter were essentially derived from the MPS accounts using a conversion system developed by the United Nations Statistics Division. In 1992, the SNA replaced the MPS as the official accounts system. Since then, the NBS has concentrated on developing data sources and refining its procedures to directly estimate national accounts according to the SNA (OECD 2000). China’s participation in the IMF’s General Data Dissemination System in 2002 and subscription to SDDS in 2015 facilitated NBS efforts to improve the compilation of real sector data by doing the following:
IMF Data Standards Initiatives
These initiatives are designed to promote the dissemination of timely and comprehensive statistics. The standards have almost universal coverage and are intended to contribute to the formulation of sound macroeconomic policies and the efficient functioning of financial markets. Three tiers currently comprise the initiatives:
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The Special Data Dissemination Standard (SDDS) was established in 1996 to guide members who have, or might seek, access to international capital markets in providing their economic and financial data to the public (IMF 2013a). SDDS identifies four dimensions of data dissemination: (1) data coverage, periodicity, and timeliness; (2) access by the public; (3) integrity of the disseminated data; and (4) quality of the disseminated data. As of November 2016, 63 jurisdictions were SDDS subscribers. China subscribed to the SDDS in October 2015.1
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The General Data Dissemination System (GDDS) was created in 1997 to guide countries in providing to the public comprehensive, accessible, timely, and reliable economic, financial, and sociodemographic data (IMF 2013b). From May 2015, an enhanced GDDS (e-GDDS) superseded the GDDS, emphasizing the data dissemination aspect under the initiative. As of November 2016, 110 countries were e-GDDS participants. China participated in the GDDS until 2002, when it graduated to the SDDS.2
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The SDDS Plus was created in 2012 as the third and highest tier of the IMF’s Data Standards Initiatives to help address data gaps identified during the global financial crisis, including in the context of the G20 Data Gaps Initiative (IMF 2013c). As of November 2016, 11 countries were SDDS Plus adherents.3
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Conducting surveys on small industrial and commercial enterprises
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Assessing regional GDP data compiled by provincial statistical agencies
G20 Data Gaps Initiative
In April 2009, the G20 Finance Ministers and Central Bank Governors called on the IMF and the Financial Stability Board (FSB) to identify major financial and economic information gaps. As a result, in September 2009, the IMF and the FSB presented a report to launch the Data Gaps Initiative (DGI), along with a set of recommendations to be implemented in years to come (IMF and FSB 2009). Given the significant progress made in implementing the DGI recommendations, in September 2015 the G20 Finance Ministers and Central Bank Governors endorsed the completion of the first phase of the DGI and the start of its second phase (DGI-2). DGI-2 aims to strengthen and consolidate the progress to date, achieve the potential for data provision embodied in the initiative, and promote the regular flow of high-quality statistics for policy use. The Sixth Progress Report on the Implementation of the G20 Data Gaps Initiative (prepared by IMF and the Financial Stability Board) provides the latest status of the DGI progress and outlines the recommendations of DGI-2.1
DGI-2 maintains the continuity of DGI-1 while also reflecting on the evolving policy needs. Work on DGI-2 started in 2016 with particular focus on (1) finishing uncompleted work (sectoral accounts, government finance statistics); (2) starting regular collection of data under the new conceptual frameworks; (3) strengthening collection of data already covered by the DGI recommendations; (4) promoting the comparability of data sets; and (5) improving the quality, completeness, timeliness, frequency, and general robustness of data.
Monitoring risk in the financial sector remains central, but DGI-2 also raises the emphasis on the inter-linkages across the economic and financial system, reflecting the evolving policy needs to provide a complete picture of the economic and financial system.
The Principal Global Indicators website, hosted by the IMF, was launched as part of the DGI, which collects and disseminates comparable data for all G20 economies and selected non-G20 member economies.2
China, as a G20 country, has made important progress under the first phase of the DGI framework, and continues efforts to fully implement the DGI recommendations during its second phase. In particular, the country has been working through the G20 DGI to address some data gaps relevant for surveillance of financial sector risk and interconnectedness. These efforts created synergies with the authorities’ work programs for improving macroeconomic statistics. Annex 12.1 presents a heat map showing the DGI implementation status of all G20 countries. China assumed the G20 presidency in 2016 and its close involvement in the G20 DGI, which entered its second phase in 2016, will be critical to the continued success of the initiative.
1See http://www.imf.org/external/np/g20/pdf/2015/6thprogressrep.pdf. 2See http://www.principalglobalindicators.org.-
Compiling growth rates on a trial basis for industrial and agricultural production using the price deflator approach
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Introducing sampling survey methods for estimating output of agricultural products, other than grain crops, such as cotton and animal stocks
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Compiling price indices using a fixed reference base (2010) to bring them closer to international good practices
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Enhancing the implementation of the Statistical Law by conducting an annual nationwide inspection of statistical law compliance and publishing outcomes of the inspection
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Taking measures to improve data dissemination formats through regular publications, including the China Statistical Yearbook, China Statistics Abstract, China Economic Indicators, and the NBS website
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Expanding compilation of the producer price index (PPI), using a fixed base period
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Establishing procedures for collecting, compiling, and disseminating data on the labor market
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Improving the integrity and accessibility of data dissemination by publishing advance calendars and information on data revisions
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Compiling and disseminating quarterly data for discrete GDP (by production approach) at both current and constant prices
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Improving transparency in the dissemination of the consumer price index (CPI) and PPI
Despite progress, real sector statistics remain weak and have not kept pace with the emerging needs of the larger, more sophisticated, more market-oriented economy. The NBS and public commentators have identified shortcomings. Labor market and high-frequency data are often unavailable to the public. These data weaknesses might be better understood in association with the unique institutional arrangements under which China’s statistical system operates. The statistical system is highly decentralized, with a large network of statistical offices in local and provincial governments and closely linked to their structures, including planning activities. The system operates with less transparency than in many other countries, although data collection initiatives across several areas have improved in recent years.
National Accounts
The main gap in availability of national accounts is the lack of quarterly GDP by expenditure at constant prices. Expenditure data are available only annually and only at current prices. This gap is an obstacle in monitoring the planned shift from growth driven by exports and investment to growth driven by consumption.
External criticism has suggested that data are not always consistent within the system or with other indicators, and that national accounts still have a long way to go to align with international standards and best practices. Structural issues in the economy include a switch from state-owned industrial enterprises to market-oriented private service firms, emphasis on household consumption over investment, and the role of the small-scale and informal sectors for services. These developments present challenges for statistical measurement, requiring additional data sources, and revision of techniques and ratios. At the same time, the decentralized structure of the Chinese statistical system adds obstacles to making changes. Important gaps remain for domestic demand, especially private consumption and investment spending. One major problem with constant price GDP data by industry is the use of the single deflation method, which leads to significant over- or underestimation of GDP growth when movements in input and output prices are significantly different.3 Shortcomings exist in the deflation methodology, as price indices are often missing or incomplete, and they frequently do not match the related activity or expenditure category. Detailed breakdown of GDP (for example, GDP by industry of nine economic activities) is more limited than other G20 economies. The sources and methods used for compiling the national accounts are not very transparent and differences in trends shown by GDP and compared to some published quarterly and monthly indicators are not generally explained.
In recent years, China has published annual and quarterly GDP estimates in line with the revisions policy set by the authorities. Based on the recent history, the first estimate of GDP growth—published just two or three weeks after the end of each quarter—was not changed substantially in later estimates. Small revisions in quarterly GDP growth appear related only to seasonal adjustment factors and do not incorporate revisions to data sources. Box 12.3 details the recent history of China’s GDP revisions.
Although balance sheet data are lacking, the authorities are committed to producing a national balance sheet by 2020. Compilation of the national balance sheet would also contribute to China’s implementation of the G20 DGI recom-mendation on sectoral accounts, which is aimed at promoting the compilation and dissemination of sectoral balance sheets, flow of funds, and sectoral data more generally, starting with the G20 economies.4 These data are particularly suited for analysis of financial interlinkages and vulnerability of the households and nonfinancial corporate sectors.
Price Statistics
The NBS has recently improved transparency in the dissemination of consumer and producer prices. The National Summary Data Page contains monthly series of the CPI and PPI,5 with 2010 as the reference year, in line with SDDS requirements. More information about the coverage and compilation methodology, in particular CPI weightings, is needed to understand the characteristics of these data.
Since February 2012, three monthly residential property price indices (RPPI) for China have been available on the website of the Bank for International Settlements. No commercial real estate price indices are currently available. The NBS plans to expand the cities covered in the compilation of RPPI. Progress here should also contribute to China’s implementation of the Phase II G20 recommendation on RPPI, which also encourages production of long time series, development of a list of other housing-related indicators, and dissemination of the headline RPPI data through the Principal Global Indicators website (Box 12.2).
China—An Assessment of GDP Revisions
GDP Revisions Policy
The official revision policy of China’s GDP is outlined in the metadata posted on the National Summary Data Page.1 The preliminary estimate for a given year is published 15 days after the end of the year. This is made as the sum of quarterly estimates of the year. The preliminary verification is published 9 months after the end of the year, and final verification comes three months later. Quarterly data are revised in accord with the annual GDP revision cycle. The GDP revisions policy strictly adheres to the timeliness of source data received after 10 days, 8 months, and 11 months after the end of the year. Benchmark revisions are made to incorporate census data, changes in the calculation methods, international standards, and classification criteria. Many other countries have larger revisions because additional information becomes available over time, such as late identification of new enterprises, more complete data from detailed surveys and administrative systems, and reconciliation processes such as supply and use balancing.
The release calendar of recent GDP publications is aligned with the current revisions policy. Table 12.3.1 shows the GDP press releases published on the National Bureau of Statistics (NBS) website (in English) during January 2014–September 2015. The average timeliness of the preliminary GDP estimate was 19 days (slightly above the 15-day target). The preliminary verification and final verification for the year 2013 were replaced by the benchmark revision published in December 2014, which was based on the results of the 2013 Economic Census.
Revisions of Annual GDP
In recent years, China has not made substantial revisions to the preliminary estimates of annual GDP growth (Table 12.3.2). Small, downward revisions are noted in the second estimate (the preliminary verification) for 2012 and 2014, both signaling a reduction of GDP growth by 0.1 percentage points compared with the preliminary estimate. On the other hand, GDP growth for 2013 has remained unchanged at 7.7 percent.
China: GDP Press Releases Published from January 2014 to September 2015
China: GDP Press Releases Published from January 2014 to September 2015
| Preliminary Estimate | |
| January 21, 2014 | Annual GDP in 2013 |
| April 17, 2014 | Quarterly GDP in 2014:Q1 |
| July 17, 2014 | Quarterly GDP in 2014:Q1–14:Q2 |
| October 22, 2014 | Quarterly GDP in 2014:Q1–14:Q3 |
| April 20, 2015 | Quarterly GDP in 2015:Q1 |
| July 16, 2015 | Quarterly GDP in 2015:Q1–15:Q2 |
| January 22, 2015 | Annual GDP in 2014 |
| Preliminary Verification | |
| September 8, 2015 | Annual GDP in 2014 |
| Final Verification | |
| January 9, 2014 | Annual GDP in 2012 |
| Benchmark Revision | |
| December 19, 2014 | Benchmark revision of GDP for year 2013 (based on economic census) |
China: GDP Press Releases Published from January 2014 to September 2015
| Preliminary Estimate | |
| January 21, 2014 | Annual GDP in 2013 |
| April 17, 2014 | Quarterly GDP in 2014:Q1 |
| July 17, 2014 | Quarterly GDP in 2014:Q1–14:Q2 |
| October 22, 2014 | Quarterly GDP in 2014:Q1–14:Q3 |
| April 20, 2015 | Quarterly GDP in 2015:Q1 |
| July 16, 2015 | Quarterly GDP in 2015:Q1–15:Q2 |
| January 22, 2015 | Annual GDP in 2014 |
| Preliminary Verification | |
| September 8, 2015 | Annual GDP in 2014 |
| Final Verification | |
| January 9, 2014 | Annual GDP in 2012 |
| Benchmark Revision | |
| December 19, 2014 | Benchmark revision of GDP for year 2013 (based on economic census) |
China: Annual GDP Estimates for the Years 2012, 2013, and 2014
(Annual rates in percent, Constant prices)
Benchmark revision released in December 2014, based on 2013 economic census results.
China: Annual GDP Estimates for the Years 2012, 2013, and 2014
(Annual rates in percent, Constant prices)
| Year | PE | PV | FV |
|---|---|---|---|
| 2012 | 7.8 | 7.7 | 7.7 |
| 2013 | 7.7 | 7.7 | 7.71 |
| 2014 | 7.4 | 7.3 | … |
Benchmark revision released in December 2014, based on 2013 economic census results.
China: Annual GDP Estimates for the Years 2012, 2013, and 2014
(Annual rates in percent, Constant prices)
| Year | PE | PV | FV |
|---|---|---|---|
| 2012 | 7.8 | 7.7 | 7.7 |
| 2013 | 7.7 | 7.7 | 7.71 |
| 2014 | 7.4 | 7.3 | … |
Benchmark revision released in December 2014, based on 2013 economic census results.
Quarterly GDP—Revisions to 2013 and 2014 Quarters
(Quarterly rates in percent, seasonally adjusted in constant prices)
Source: National Bureau of Statistics website and publications.The 2013 benchmark revision altered the GDP estimates at current prices. The benchmark revision increased nominal GDP in 2013 by 3.4 percent. The nominal growth for 2013 was revised up, to 10.1 percent from 9.5 percent. Therefore, the 0.6 percent upward revision was due to an upward revision of the GDP deflator.
Revisions of Quarterly GDP
As for annual data, no revisions are made to unadjusted quarterly GDP data. However, revisions to seasonally adjusted data are generated by seasonal adjustment techniques. Table 12.3.3 presents the quarterly GDP growth series published between January 2014 and September 2015. The quarterly revisions during this period appear of limited size, unsystematic (see Figure 12.3.1), and comparable with revisions due to seasonal adjustment in other countries.
Quarterly GDP Growth by Month of Release
(Period: 2013:Q1-15:Q2. Quarterly rates in percent, seasonally adjusted in constant prices)
Quarterly GDP Growth by Month of Release
(Period: 2013:Q1-15:Q2. Quarterly rates in percent, seasonally adjusted in constant prices)
| Quarter | Jan-14 | Apr-14 | Jul-14 | Oct-14 | Jan-15 | Apr-15 | Jul-15 | Sep-15 |
|---|---|---|---|---|---|---|---|---|
| 2013:Q1 | 1.5 | 1.5 | 1.6 | 1.6 | 1.7 | 1.7 | 1.7 | 1.8 |
| Q2 | 1.8 | 1.8 | 1.8 | 1.8 | 1.8 | 1.8 | 1.8 | 1.8 |
| Q3 | 2.2 | 2.3 | 2.3 | 2.3 | 2.3 | 2.3 | 2.3 | 2.1 |
| Q4 | 1.8 | 1.7 | 1.7 | 1.7 | 1.8 | 1.8 | 1.8 | 1.6 |
| 2014:Q1 | 1.4 | 1.5 | 1.5 | 1.6 | 1.6 | 1.6 | 1.6 | |
| Q2 | 2.0 | 2.0 | 1.9 | 2.0 | 1.9 | 1.8 | ||
| Q3 | 1.9 | 1.9 | 1.9 | 1.9 | 2.0 | |||
| Q4 | 1.5 | 1.5 | 1.5 | 1.7 | ||||
| 2015:Q1 | 1.3 | 1.4 | 1.3 | |||||
| Q2 | 1.7 | 1.8 |
Quarterly GDP Growth by Month of Release
(Period: 2013:Q1-15:Q2. Quarterly rates in percent, seasonally adjusted in constant prices)
| Quarter | Jan-14 | Apr-14 | Jul-14 | Oct-14 | Jan-15 | Apr-15 | Jul-15 | Sep-15 |
|---|---|---|---|---|---|---|---|---|
| 2013:Q1 | 1.5 | 1.5 | 1.6 | 1.6 | 1.7 | 1.7 | 1.7 | 1.8 |
| Q2 | 1.8 | 1.8 | 1.8 | 1.8 | 1.8 | 1.8 | 1.8 | 1.8 |
| Q3 | 2.2 | 2.3 | 2.3 | 2.3 | 2.3 | 2.3 | 2.3 | 2.1 |
| Q4 | 1.8 | 1.7 | 1.7 | 1.7 | 1.8 | 1.8 | 1.8 | 1.6 |
| 2014:Q1 | 1.4 | 1.5 | 1.5 | 1.6 | 1.6 | 1.6 | 1.6 | |
| Q2 | 2.0 | 2.0 | 1.9 | 2.0 | 1.9 | 1.8 | ||
| Q3 | 1.9 | 1.9 | 1.9 | 1.9 | 2.0 | |||
| Q4 | 1.5 | 1.5 | 1.5 | 1.7 | ||||
| 2015:Q1 | 1.3 | 1.4 | 1.3 | |||||
| Q2 | 1.7 | 1.8 |
Labor Market Indicators
Major data gaps remain for labor market indicators. Employment data are compiled annually and disseminated within two months of the end of the year. The NBS has conducted a monthly labor force survey since 2009, but it is not publicly available. If publicly disseminated, survey data could provide timely information on both employment and unemployment. The registered unemployment rate for urban areas is available quarterly but these do not appear to truly measure unemployment because of the limited scope of the registration process. Wage data are compiled annually and disseminated within four to five months after the end of the year. To increase coverage and timeliness of wage statistics, the NBS is planning to add a survey of small establishments to an online quarterly survey of large establishments.
Reforms Under Way to Improve Real Sector Statistics
The NBS is aware of the shortcomings in the real sector statistics and has been taking steps to address some of the main problems. Reforms of official statistical systems are currently focused on four areas that the NBS has identified as shortcomings (Xu 2016): (1) compilation of GDP, for owner-occupied housing valuation, household final consumption, and valuation of research and development expenditure;6 (2) fixed-asset investment; (3) lack of integration of urban and rural household surveys; and (4) services sector statistical methodology and procedures.
To improve the statistical process, the NBS plans to undertake 10 measures to enhance data reliability (Xu 2016). These are (1) strengthening the business/ institution registry system, (2) establishing integrated reporting forms for enterprises, (3) adopting unified data processing software, (4) establishing an internet-based direct data reporting system, (5) integrating urban and rural household surveys, (6) adopting a comprehensive and standardized statistical survey for the services sector, (7) adopting a methodology to compile chain-linked indices, (8) raising the threshold of enterprises for the fixed investment and industrial enterprise surveys, (9) conducting data validation of basic information for enterprises with assets above a threshold value, and (10) establishing a data quality assessment and evaluation system.
External Sector Statistics
The State Administration of Foreign Exchange is responsible for compiling external sector statistics for China. Balance of payments and international investment position are compiled with reference to the sixth edition of the IMF’s Balance of Payments and International Investment Position Manual (BPM6).7 These data are disseminated on China’s National Summary Data Page. Overall, balance-of-payments transactions are recorded on an accrual basis. However, due to some limitations in sources, parts of the transactions data are recorded on a cash basis. Although the International Transactions Reporting System—which collects data on a cash basis—is still used as a data source, the State Administration of Foreign Exchange plans for extra surveys that will move collection to a full accrual basis.
Although China’s presentation of items for external sector statistics is in line with international standards, there is room for improvement in recording the international investment position, and no breakdown exists for foreign direct investment by equity and debt instrument in these data. As for the Coordinated Direct Investment Survey, inward data are reported consistent with the requirements of the survey, but further efforts are needed on the compilation of outward data. The Coordinated Portfolio Investment Survey was reported for the first time in December 2015, but further efforts would be welcome to report additional information (as specified in the “encouraged tables”).
The Reserves Data Template is disseminated monthly. It covers the monetary authorities that manage and hold the international reserves and the central government, which together with the monetary authorities, accounts for most of the official foreign currency obligations. Predetermined net drains on foreign currency allow for consistency checks with short-term external debt data as the former also includes debt for residents that is denominated in foreign exchange. Partial figures for currency composition of foreign exchange reserves were reported for the first time in September 2015, with data from June 2015 onward for inclusion in world aggregates published on the IMF’s website.
Government Finance Statistics
The Ministry of Finance is the official agency responsible for compiling and disseminating government finance statistics for China. The ministry compiles government operations data with monthly, quarterly, and annual periodicity. The annual series consolidate central government, provincial, local governments, and social security funds, while the monthly and quarterly data exclude social security funds. The data are compiled following the methodology in the Government Finance Statistics Manual (GFSM) 1986,8 and so are on a cash-basis only, which limits the analytical usefulness of the data. GFSM 1986 focuses primarily on a single balancing item, the deficit/surplus, and the government’s financing requirement, where the liquidity constraint rather than the sustainability of policy choices is seen as the most binding priority. Among the many shortcomings of the cash-based GFSM 1986 system, some key elements are (1) the lack of alignment with other macroeconomic statistical systems; and (2) the lack of accounting for arrears, interest on discounted bonds, in kind transactions, and consumption of fixed assets (“depreciation”).
The Ministry of Finance has recognized these shortcomings and has taken some initial steps to begin compiling and reporting to the IMF general government revenue data following the GFSM 2001 methodology. Detailed revenue data for 2003–13 as well as data on outlays by function have been compiled. However, to date no data are available on the economic classification of expenses, and this limits fiscal analysis. While the functional classification of expense provides information on the purpose for which an expense was incurred, a well-structured economic classification identifies the types of expense incurred according to the economic process involved. For example, compensation of employees, use of goods and services, and consumption of fixed capital all relate to the costs of producing nonmarket (and, in certain instances, market) goods and services by government. Subsidies, grants, social benefits, and transfers other than grants relate to transfers in cash or in kind, and are aimed at redistributing income and wealth. Such measures would support improved fiscal analysis in China.
The current GFSM 2001-based series lack data on transactions in assets and liabilities, gross debt, and balance sheet stock positions. Data about general government off-budget fiscal activities are also lacking on a monthly or quarterly basis, especially for local governments, including credit to local government financing vehicles. This limits fiscal analysis aimed at determining the net worth of general government (and public sector) units, which can be viewed as a stock position resulting from the transactions and other economic flows stemming from policy actions in all previous periods. Given China’s increasing exposure to the global economy and the resulting risks of changes in asset and liability positions owing to changes in currency composition, maturity breakdown, and counterparty exposures, developing these data should be a priority. Improvements in these areas of China’s government finance statistics would better facilitate fiscal analysis, while also supporting China’s efforts in implementing the G20 DGI recommendations.
Concurrent with the need to further improve the fiscal data, the availability of debt data that are internationally comparable for the general government and public sector could be enhanced. Because they carry obligations to make future payments, debt liabilities have the potential to create circumstances that render not only government and public corporations, but also the entire economy, vulnerable to solvency and liquidity problems. Moreover, as experience has shown—most recently by the international financial crisis that started in 2007—these vulnerabilities can have widespread economic costs, and not just for the initially affected economy. To this end, China, under the G20 DGI, has been reporting to the IMF/World Bank Public Sector Debt Statistics database following internationally agreed guidance on (1) the concepts, definitions, and classifications of public sector debt statistics; and (2) the sources and techniques for compiling these data.9 While the series provided currently only cover the central government, the provision of enhanced institutional coverage will further improve fiscal analysis in China.
Monetary and Financial Statistics
The People’s Bank of China (PBC) is the official data compiling agency for China’s monetary and financial statistics. It also compiles a wide range of other macroeconomic data and financial stability indicators.
Over past years, the PBC has made continual progress in monetary and financial statistics in accordance with the IMF recommended methodology in the Monetary and Financial Statistics Manual 2000.10 The most notable include the following:
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Expanding coverage of other depository corporations to include foreign-funded banks operating in China, and other financial institutions such as policy banks, postal savings bank, and finance firms that accept deposits or issue liabilities included in broad money
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Improving classification of financial firm subsectors in accordance with the Monetary and Financial Statistics Manual into central bank, other depository corporations, other financial corporations (consisting of insurance and pension funds, other financial intermediaries, and financial auxiliaries), leading to improved data on linkages between subsectors of the financial sector
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Regular reviewing and updating the “all accounts” reporting system for use by financial institutions in China to report data in standardized format for compilation of monetary statistics as well as other macroeconomic and financial stability indicators
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Improving data dissemination by releasing monetary data on a timely and regular basis on the PBC website in addition to publication of these data in PBC Statistics Bulletin (quarterly), and the PBC Annual Report
To meet emerging data needs arising from the recent developments in China’s financial system, the PBC also took initiatives in compiling new indicators. A major one is the compilation of the total social financing (TSF) indicator (Box 12.4). The TSF is not an internationally commonly used broad credit measure, but takes into consideration recent developments in China’s financial systems and some unique features of the economy.
Rapid developments in China’s economy and financial system have led to increasingly diverse channels of financing for the real sector, while traditional measures of credit volumes—for example, banks loans—have become of increasingly limited use to reflect the full size of financing to the real sector. In light of this, the PBC based the TSF indicator on a series of empirical studies and broad consultation with Chinese government agencies. The indicator is now closely monitored and analyzed for macroeconomic management and is also widely followed by the private sector and the general public.
Going forward, continued efforts would be needed for improving China’s monetary and financial statistics, particularly the adoption of the Standardized Report Forms for reporting monetary data to the IMF. The forms embody the IMF-recommended methodology for compiling monetary statistics and present data in a manner that facilitates cross-country comparison and the application of the balance sheet approach to vulnerability analysis. Compilation of data for other financial corporations in the format of the Standardized Report Form would also contribute to China’s implementation of the G20 DGI recommendation on cross-border exposures of nonbank corporations. These data provide useful information for analysis of cross-border exposures of nonbank financial institutions.
Total Social Financing Indicators
The People’s Bank of China (PBC) began compiling the total social financial (TSF flow data) series of indicators and release of data on a quarterly basis in 2011. Since 2012, the TSF has been published monthly.1
The TSF (flow data) is defined as the total amount of financing obtained by the real economy from the financial system monthly, quarterly, or annually. The real economy refers to nonfinancial corporations and households. The financial system refers to the entire domestic financial system, covering financial sectors and financial markets (Sheng 2014).
The TSF consists of bank loans in renminbi and in foreign currencies, entrusted loans,2 trust loans,3 undiscounted bankers’ acceptance, net issuance of corporate bonds, funds raised from the domestic stock market by nonfinancial enterprises, and other forms of financing. The indicator (TSF flow data) is intended to provide a broad measure of new funding from the financial system to the domestic economy during the reference period.
In February 2015 the PBC also released TSF stock data for 2002–14 on an annual basis. TSF stock data are defined as the outstanding funding provided by the domestic financial system to the real economy (nonfinancial corporations and households) at the end of the reference period. The domestic financial system has similar coverage as TSF flow data. TSF stock data cover four broad categories: (1) balance-sheet-related items of financial institutions, consisting of renminbi and foreign currency loans; (2) off-balance-sheet items of financial institutions, consisting of entrusted loans, trust loans, and undiscounted bankers’ acceptances; (3) direct financing (market-based) items, consisting of corporate bonds, nonfinancial corporations shares, and other equity financing; and (4) others.
1The indicator is also known as “Aggregate Financing to the Real Economy.”
2Entrusted loans are lending between nonfinancial entities facilitated by banks, whose existence is due to regulation prohibiting nonfinancial firms from making loans. The terms of lending are decided by the lender rather than the bank.
3Trust loans are between nonfinancial entities facilitated by trust firms, and follow a similar operational mechanism as entrusted loans.
To support macroprudential data collection, the PBC coordinates with the China Banking Regulatory Commission in compiling financial soundness indicators and reports these data to the IMF for dissemination (Box 12.5). China’s financial soundness indicators cover all core and two other indicators for deposit takers, and are produced semiannually. Continued efforts would be needed for improving the compilation of financial soundness indicators (FSIs), including, in particular, (1) compilation of FSIs for sectors other than deposit takers and (2) compilation of FSIs with the preferred quarterly frequency.
Financial Soundness Indicators
The IMF developed financial soundness indicators (FSIs), together with the international community, to support macroprudential analysis and assess the strengths and vulnerabilities of financial systems. FSIs provide insight into the financial health and soundness of a country’s financial institutions and its corporate and household counterparts. The IMF’s Statistics Department disseminates data reported by national authorities at the FSI website.1 As of November 2016, 117 countries and jurisdictions regularly report FSIs (data and metadata) to the IMF, including all G20 countries.
As of November 2016, the FSIs data set comprises 12 core and 28 encouraged indicators. The revised list of FSIs, reported to the Executive Board in November 2013, for future implementation includes 17 core FSIs and 35 encouraged FSIs, which resulted from IMF staff’s review of the current list of FSIs in response to users’ needs and financial sector developments.2
1See http://data.imf.org/?sk=9F855EAE-C765-405E-9C9A-A9DC2C1FEE47.
China also takes part in a financial access survey conducted by the IMF, which collects annual data on several important indicators that are aimed at measuring inclusive development in financial sector service.11
Challenges for Meeting Data Needs in a Rapidly Evolving Economy
China’s economic reforms have accelerated over the past few years and the 13th Five-Year Plan (2016–20) has reaffirmed the country’s commitment to move its ambitious reform agenda forward. This will continue to challenge statistical systems to meet ever-emerging data needs for policymakers and market participants. These challenges relate mainly to the following areas:
-
New data needs arise from continued structural reforms in the economy and financial system. For instance, as financial sector reform deepened, interest rate controls were fully removed in 2015. The full liberalization of interest rates in China calls for a set of comprehensive, indicative, and timely rate data. Also, the rapid development of the debt securities market requires more comprehensive, detailed, and timely data that are consistent with international methodologies and best practices.
-
As China moves toward a market economy, it may become increasingly difficult to have direct access to source data, as was the case for data collection from state-owned entities under the centrally planned economy. Comprehensive and effective source data collection will require application of more techniques (for example, sample surveys) as well as more direct data reporting (through census).
The SDDS Plus as the highest tier of IMF’s data standards (Box 12.1) includes rigorous data dissemination practices designed to further improve transparency and strengthen the international financial system and is open to all SDDS subscribers, especially those with systemically important financial sectors. After China has gained more experience with SDDS subscription and improved the compilation and dissemination of macroeconomic and financial statistics,12 it may be prepared to aim for the SDDS Plus.
Conclusions
China’s efforts to move toward international standards and best practices in its statistical system have accelerated the progress made in improving statistical capacity. In particular, the country’s participation in IMF’s GDDS from 2002 has led to the following:
-
The dissemination for the first time of a comprehensive set of documentation on compilation practice of China’s macroeconomic statistics
-
The formulation and dissemination of plans for improvements in macroeconomic statistics
-
Much improved interagency coordination and cooperation in addressing statistics-related issues
China’s subscription to SDDS in 2015 was a major advance in data compilation and dissemination. Under the SDDS, the country now disseminates a comprehensive set of macroeconomic data in accordance with prescribed coverage, periodicity, and timeliness. In particular, several important data sets have become publicly available under the SDDS. These include: (1) quarterly data for discrete GDP by the production approach (at current and constant prices); (2) data on general and central government operations, and central government debt; (3) official reserves assets; and (4) reserve data template.13
China’s statistical capacity developments have benefited from its cooperation with international and regional organizations and bilateral agencies over many years of capacity development. International cooperation will continue to contribute to the development of China’s statistical system and its integration with the rest of the world through familiarizing the authorities with internationally agreed statistical standards and best practices and assisting the authorities’ efforts to align China’s statistical system more closely with international standards. Box 12.6 summarizes the IMF’s technical cooperation with China in macroeconomic statistics.
As China has evolved into a major force in the global economy, interest has increased in monitoring domestic economic developments that carry global impact. Policymakers, business leaders, and foreign observers are all digging deeper into Chinese data to understand its complex and influential economy and keep informed of the effects of large structural transformation and policy reforms. With growing complexity and continued change, some of the conventional economic gauges have become less indicative, while additional data on the fast-changing “new economy” are needed to better understand it. Chinese data will need to evolve and continue to improve as the economy changes and grows.
Emerging data needs will drive continued progress in the statistical system. This progress applies to the scope of data compiled, the underlying methodologies adopted, and the data dissemination practices adopted. For macroeconomic analysis, management, and surveillance, particular effort should be taken to close data gaps in the following areas:
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GDP data at constant prices for expenditure components, which are critical for more accurate macroanalysis and prediction
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Industrial structure: that is, the breakdown of data on the industrial sector in national accounts, which is crucial to understand structural changes and the evolving relationship between conventional economic gauges and GDP growth
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High-frequency indicators of the labor market (especially in the private sector), which are important to better understand labor market dynamics and set macroeconomic policies
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High-frequency indicators of the services sector, which are key to tracking growth in the “new economy”
-
Borrowing by local government financing vehicles with monthly frequency, which is essential to monitor off-budget fiscal and quasi-fiscal activities
IMF’s Technical Cooperation with China in Macroeconomic Statistics
The emerging data needs arising from China’s economic reforms and developments and its integration into the world economy have motivated the authorities to reform the statistical system and establish infrastructure for macroeconomic data collection, compilation, and dissemination in accordance with international best practices. To facilitate this, the authorities continuously expand their technical cooperation with the international community. The IMF’s Statistics Department, among others, has been involved in China’s capacity development in macroeconomic statistics for many years.1 Figure 12.6.1 summarizes the Statistics Department’s capacity development during 2000–15.
The Statistics Department’s capacity development focuses on the review of current practices in data compilation, identifying areas for improvement in line with international methodologies and standards. The main source documents for these methodologies and standards are summarized in Table 12.1.2
In recent years, the Chinese authorities and the Statistics Department have developed new modalities of technical cooperation, including the joint International Conference on New Statistical Challenges Facing Central Banks with the People’s Bank of China (PBC),3 an on-the-job training program for one PBC staff and four National Bureau of Statistics staff to join the Statistics Department for six months,4 and PBC staff visits to IMF headquarters to attend seminars on data compilation and uses.
IMF’s Statistics Department Missions and Training Courses, 2000-15
Source: IMF Statistics Department.Note: GFS = government finance statistics; MFS = monetary and financial statistics.Manuals and Guides on Macroeconomic and Financial Statistics
Manuals and Guides on Macroeconomic and Financial Statistics
| Real Sector Statistics | Brief Description |
|---|---|
|
System of National Accounts (SNA) 2008
Quarterly National Accounts Manual—Concepts, Data Sources, and Compilation Export and Import Price Index Manual |
Provides a comprehensive analytical framework for compiling national accounts data. The 2008 SNA, the fifth version of the SNA, updates the 1993 SNA. Provides guidance to help countries establish or strengthen quarterly national accounts that meet user needs (currently being updated). Contains detailed, comprehensive information and explanations for compiling the manuals |
| Consumer Price Index Manual | Provides guidance on compilation of the consumer price index, which measures the rate at which the prices of consumer goods and services are changing over time. |
| Producer Price Index Manual | Provides guidance on compilation of producer price data, which measures the rate at which the prices of producer goods and services are changing over time. |
|
Practical Guide to Producing Consumer Price Indices
Handbook on Residential Property Price Indices |
Targets developing countries and focuses on practical solutions to the problems facing compilers of consumer price data in the developing world. Provides guidelines for the compilation of residential property price indices and explains the methods and best practices used to calculate this index. |
| Government Finance Statistics | Brief Description |
|
Government Finance Statistics Manual (GFSM) 2014
Quarterly Government Finance Statistics—Guide for Compilers and Users |
Provides an analytical framework for compiling government finance statistics to support fiscal analysis. GFSM 2014 updates GFSM 2001. Serves as a reference for compilers and users of government finance statistics. |
|
Public Sector Debt Statistics—Guide for Compilers and Users
Government Finance Statistics: Compilation Guide for Developing Countries |
Provides guidance for the measurement, compilation, analytical use, and presentation of public sector debt statistics. Provides detailed information and guidance on how to gradually introduce the guidelines of the GFSM 2001 and best practices into the compilation and dis-semination of fiscal statistics. |
| External Sector Statistics | Brief Description |
|
Balance of Payments and International Investment Position
Manual, sixth edition (BPM6) BPM6 Compilation Guide |
Provides analytical framework and guidance for collecting and compiling balance-of-payments and international investment position data. BPM6 published in 2009 updates the fifth edition that was released in 1993. Provides guidance on how the conceptual framework described in the BPM6 may be implemented in practice. BPM6 Guide updates the Balance of Payments Compilation Guide released in 1995. |
| International Reserves and Foreign Currency Liquidity: Guidelines for a Data Template 2013 External Debt Statistics: Guide for Compilers and Users | Provides operational advice to IMF members that subscribe to the Special Data Dissemination Standard regarding how to complete the prescribed (mandatory) monthly data template on international reserves and foreign currency liquidity. Provides guidance for the measurement, compilation, analytical use, and presentation of external debt statistics. |
| International Transactions in Remittances: Guide for Compilers and Users | Provides practical guidance on the compilation of remittances based on the concepts set out in BPM6. |
| 2015 Coordinated Portfolio Investment Survey Guide | Provides guidance to assist economies in participating in the Coordinated Portfolio Investment Survey. |
| Monetary and Financial Statistics | Brief Description |
| Monetary and Financial Statistics Manual and Compilation Guide (2016) | Updates Monetary and Financial Statistics Manual (2000) and Monetary and Financial Statistics Compilation Guide (2008), and combines the two documents into one volume (prepublication draft now available). |
| Financial Soundness Indicators Compilation Guide (2006) Handbook on Securities Statistics (2015) | Provides analytical framework and guidance for the compilation and dissemination of financial soundness indicators. Develops a conceptual framework for presenting statistics to improve information on securities markets. Updates Handbook on Securities Statistics 2015 and combines the previous three separate volumes of this handbook. |
Manuals and Guides on Macroeconomic and Financial Statistics
| Real Sector Statistics | Brief Description |
|---|---|
|
System of National Accounts (SNA) 2008
Quarterly National Accounts Manual—Concepts, Data Sources, and Compilation Export and Import Price Index Manual |
Provides a comprehensive analytical framework for compiling national accounts data. The 2008 SNA, the fifth version of the SNA, updates the 1993 SNA. Provides guidance to help countries establish or strengthen quarterly national accounts that meet user needs (currently being updated). Contains detailed, comprehensive information and explanations for compiling the manuals |
| Consumer Price Index Manual | Provides guidance on compilation of the consumer price index, which measures the rate at which the prices of consumer goods and services are changing over time. |
| Producer Price Index Manual | Provides guidance on compilation of producer price data, which measures the rate at which the prices of producer goods and services are changing over time. |
|
Practical Guide to Producing Consumer Price Indices
Handbook on Residential Property Price Indices |
Targets developing countries and focuses on practical solutions to the problems facing compilers of consumer price data in the developing world. Provides guidelines for the compilation of residential property price indices and explains the methods and best practices used to calculate this index. |
| Government Finance Statistics | Brief Description |
|
Government Finance Statistics Manual (GFSM) 2014
Quarterly Government Finance Statistics—Guide for Compilers and Users |
Provides an analytical framework for compiling government finance statistics to support fiscal analysis. GFSM 2014 updates GFSM 2001. Serves as a reference for compilers and users of government finance statistics. |
|
Public Sector Debt Statistics—Guide for Compilers and Users
Government Finance Statistics: Compilation Guide for Developing Countries |
Provides guidance for the measurement, compilation, analytical use, and presentation of public sector debt statistics. Provides detailed information and guidance on how to gradually introduce the guidelines of the GFSM 2001 and best practices into the compilation and dis-semination of fiscal statistics. |
| External Sector Statistics | Brief Description |
|
Balance of Payments and International Investment Position
Manual, sixth edition (BPM6) BPM6 Compilation Guide |
Provides analytical framework and guidance for collecting and compiling balance-of-payments and international investment position data. BPM6 published in 2009 updates the fifth edition that was released in 1993. Provides guidance on how the conceptual framework described in the BPM6 may be implemented in practice. BPM6 Guide updates the Balance of Payments Compilation Guide released in 1995. |
| International Reserves and Foreign Currency Liquidity: Guidelines for a Data Template 2013 External Debt Statistics: Guide for Compilers and Users | Provides operational advice to IMF members that subscribe to the Special Data Dissemination Standard regarding how to complete the prescribed (mandatory) monthly data template on international reserves and foreign currency liquidity. Provides guidance for the measurement, compilation, analytical use, and presentation of external debt statistics. |
| International Transactions in Remittances: Guide for Compilers and Users | Provides practical guidance on the compilation of remittances based on the concepts set out in BPM6. |
| 2015 Coordinated Portfolio Investment Survey Guide | Provides guidance to assist economies in participating in the Coordinated Portfolio Investment Survey. |
| Monetary and Financial Statistics | Brief Description |
| Monetary and Financial Statistics Manual and Compilation Guide (2016) | Updates Monetary and Financial Statistics Manual (2000) and Monetary and Financial Statistics Compilation Guide (2008), and combines the two documents into one volume (prepublication draft now available). |
| Financial Soundness Indicators Compilation Guide (2006) Handbook on Securities Statistics (2015) | Provides analytical framework and guidance for the compilation and dissemination of financial soundness indicators. Develops a conceptual framework for presenting statistics to improve information on securities markets. Updates Handbook on Securities Statistics 2015 and combines the previous three separate volumes of this handbook. |
Annex 12.1. Heat Map of DGI Recommendations
Heat Map of DGI Recommendations
References
Dippelsman, R., J. Josyula, and E. Métreau. 2016. “Fixed Base Year vs. Chain Linking in National Accounts: Experience of Sub-Saharan African Countries.” IMF Working Paper 16/133, International Monetary Fund, Washington.
International Monetary Fund (IMF). 2013a. The Special Data Dissemination Standard Guide for Subscribers and Users. Washington.
International Monetary Fund (IMF). 2013b. The General Data Dissemination System Guide for Participants and Users. Washington.
International Monetary Fund (IMF). 2013c. The Special Data Dissemination Standard Plus Guide for Adherents and Users. Washington.
International Monetary Fund (IMF). 2015. Balance of Payments Statistics Yearbook. Washington.
International Monetary Fund (IMF). 2016. Asia and Pacific Regional Economic Outlook: Navigating the Transition: Trade and Financial Spillover from China. Washington, April.
International Monetary Fund (IMF) and Financial Stability Board (FSB). 2009. “The Financial Crisis and Information Gaps.” Report to the G-20 Finance Ministers and Central Bank Governors, Washington.
Organisation for Economic Co-operation and Development (OECD). 2000. National Accounts for China Sources and Methods. Paris.
Sheng, Songcheng. 2014. The Theory and Practice of the Aggregate Financing to the Real Economy. Beijing: China Finance Publisher.
Xu, Xianchun. 2016. Research on China’s Official Statistics Issues. Beijing: Social Science Literature Publisher.
The authors would like to thank Michael Stanger, Marco Marini, Antonio Galicia-Escotto, Gary Jones, Longmei Zhang, Evrim Bese Goksu, Greta Butaviciute, and Lina Yu for their contributions and comments. This chapter also benefited from general guidance and valuable suggestions from Johannes Mueller and Alfred Schipke.
The SNA is the internationally agreed standard set of recommendations on how to compile measures of economic activity in accordance with strict accounting conventions based on economic principles. Other macroeconomic data sets also follow the SNA as their respective underlying framework: government finance, external sector, and monetary statistics. The latest edition is the 2008 SNA.
The MPS was developed in the Soviet Union and used by most countries with centrally planned economies. The main difference between the MPS and SNA is that the former excluded “non-material services” from the production boundary. The MPS statistical system was oriented to monitoring central plans and therefore put little emphasis on time-series data.
The effect could be significant and would tend to mask fluctuations in GDP. In a simulation with data from one developing country, Dippelsman, Josyula, and Métreau (2016) found the distortion in GDP growth rates caused by single deflation peaked at about 1.5 percent in 2009, a period of lower commodity prices.
Countries that adhere to the SDDS Plus are required to disseminate a minimum set of internationally comparable sectoral financial balance sheets.
See China’s National Summary Data Page at http://www.stats.gov.cn/english/Statisticaldata/nsdp/201508/t20150819_1232260.html.
Research and development expenditure was included in capital formation in revised national accounts data released in July 2016, better covering this growing aspect of the economy and bringing the data more closely into line with international statistical standards.
BPM6 is the internationally agreed standard set of recommendations on how to compile measures of international transactions and positions based on economic principles. It uses concepts harmonized with the SNA and other statistical manuals. It is supported by a compilation guide and specialized guides on other aspects such as reserve assets and remittances.
The GFSM is the internationally agreed standard set of recommendations on how to compile measures of transactions and stock positions for government finance statistics based on economic principles. It uses concepts harmonized with the SNA and other statistical manuals. The latest edition is the GFSM 2014.
The Monetary and Financial Statistics Manual is the internationally agreed standard set of recommendations on how to compile measures of transactions and stock positions for monetary and financial statistics based on economic principles. It uses concepts harmonized with the SNA and other statistical manuals. The latest edition is the Monetary and Financial Statistics Manual and Compilation Guide.
The financial access survey is carried out every year and managed by the IMF’s Statistics Department. The survey collects and disseminates comparable time-series data on the geographical outreach and use of basic financial services provided by resident financial corporations to resident customers within a country. The survey identifies separately the following users of financial services: households and small and medium enterprises. As of November 2016, it contains data and metadata for 189 jurisdictions from 2004 onward in 152 underlying series and 47 indicators. The data can be accessed at http://data.imf.org/?sk=E5DCAB7E-A5CA-4892-A6EA-598B5463A34C.
As an SDDS subscriber, China uses flexibility options for periodicity of labor market data, which are annual instead of the quarterly data that are the norm for SDDS; and timeliness for general government operations data, which are available with a lag of seven months, instead of the two quarters the SDDS normally requires. The authorities plan to make improvements in these areas.
The link to these data under the SDDS is http://dsbb.imf.org/Pages/SDDS/CtyCtgList.aspx?ctycode=CHN.
