Data
CIP Database 2023
The CIP 4.0 Database
The "East Asian Industrial Productivity" project under the "Raising Industrial and Firm Productivity" program of the Research Institute of Economy, Trade and Industry (RIETI), in cooperation with the Growth Lab of Peking University and the Institute of Economic Research of Hitotsubashi University, has been revising and updating the China Industrial Productivity Database (hereinafter referred to as CIP), a basic resource for analyzing economic growth and structural change in China. The CIP Database 2023 (CIP 4.0) is now available on this website. It is a substantial revision of CIP database 2015 (CIP3.0) because of the new data available after CIP 3.0 and the new methods we used in handling the unsolved data problems in CIP 3.0. The features and major revisions of the CIP 4.0 Database are briefly introduced as follows.
First, the CIP 4.0 time series covers the period from 1987 to 2017 rather than a straightforward extension of the CIP 3.0 series from 1980 to 2010 This is to use China’s two SNA-type complete input-output tables, 1987 and 2017, to confine our time series construction to the best available input-output structures. We explain the reason why we do not prolong the series beyond the control of the two structures as we did in CIP 3.0 in Wu et al. (2023 forthcoming).
Second, in the construction of China’s national input-output time series CIP 4.0 no longer uses the so-called reduced input-output tables published between the complete tables that are available every five years since 1987 because of some unreasonable abrupt structural changes over just one or two years (see Wu and Li, 2023 forthcoming).
Third, CIP 4.0 has substantially revised the distribution of labor employment data across service industries through new methods of handling the two unclassified residuals within and outside the formal sector of the economy, hence having solved the problem of the unreasonable rapid decline of the material services (defined as the services with direct connections or extension of the goods production, e.g., transportation) compared to the non-material services (such as financial services). Information on labor by ownership type and related compensation (not included in CIP 4.0) is used in the revision (see Wu and Zhang, 2023 forthcoming).
Fourth, CIP 4.0 has considerably revised the capital data by a new attempt to distribute the data gap between the CIP investment total and the gross fixed capital formation or GFCF, as given by the national input-output tables, to the CIP 37 industries. Information on investment by ownership type (not included in CIP 4.0) and assumptions are used in the revision. This has significantly affected our estimates of capital stock and capital input by industry (see Wu and Liang, 2023 forthcoming).
Fifth, the growth accounting results using the CIP 4.0 data are provided for China’s aggregate growth and productivity performance with their industry origin, but without the contribution of the types of assets and labor to show a general contribution of the primary inputs rather than the contribution of factor types that are decomposed inevitably based on various assumptions (see Wu et al., 2023 forthcoming).
Technical Papers for CIP 4.0
- Wu, Harry X. and Zhan Li. 2021. “Reassessing China’s GDP Growth Performance: An Exploration of the Underestimated Price Effect”, RIETI Discussion Papers, 21-E-018, 2021 (RIETI: Research Institute for Economy, Trade and Industry, Japan)
- Wu, Harry X. and Zhan Li. 2023 (forthcoming). Construction of China’s National Input-Output Tables in Time Series 1978-2018.
- Wu, Harry X., Zhan Li, David T. Liang, Guang Zhang and Huimin Zhu. 2023 (forthcoming). Accounting for China’s Growth and Productivity Performance in 1978-2018: An Introduction to the CIP 4.0 Database.
- Wu, Harry X. and Guang Zhang. 2023 (forthcoming). Measuring Labor Input in the Post-Reform Chinese Economy, 1978-2018.
- Wu, Harry X. and David T. Liang. 2023 (forthcoming). Measuring Capital Input in the Post-Reform Chinese Economy, 1978-2018.
The CIP Project
The CIP Database was initiated by Professor Harry Wu in 2010. It was since then and till 2019 a collaborative effort between the Research Institute of Economy, Trade and Industries (RIETI)’s East Asian Industrial Productivity Project and the Institute of Economic Research (IER) at Hitotsubashi University. After Professor Wu moved to Peking University in late 2019, it has become a collaboration between the Growth Lab of Peking University, the Institute of Economic Research of Hitotsubashi University and RIETI, basically extended from the previous RIETI-IER/Hito-U collaboration.
The CIP Research Team
- Harry X. Wu (Peking University) (The Team Leader)
- Kyoji Fukao (Hitotsubashi University)
- Tomohiko Inui (Gakushuin University)
- Ximing Yue (Renmin University)
- Zhan Li (Anhui Normal University)
- David Tao Liang (IDE, JETRO)
- George G. Zhang (Hong Kong Science and Technology University)
- Huimin Zhu ((until March 19, 2023) RIETI)
Research Assistants
- Reiko Ashizawa (Hitotsubashi University)
- Ziwei Wu (Peking University)
Acknowledgement
The CIP Project, especially for the construction of CIP 4.0, would like to thank the following people for critical comments and constructive suggestions in their reviews of the CIP data work (in alphabetical order):
- Mun Ho (Harvard University)
- Jiemin Guo (BEA, US)
- Bo Meng (IDE, JETRO)
Data Downloadable
1. China Input-Output Tables
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updated December 21, 2023
1.1 Input-output tables 1987–2017 in millions current yuan. [ XLSX:630KB ]
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updated December 21, 2023
1.2 Gross value-added by industry in millions current yuan. [ XLSX:26KB ]
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updated December 21, 2023
1.3 Gross value of output by industry in millions current yuan. [ XLSX:27KB ]
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updated December 21, 2023
1.4 Distribution of gross value-added in millions current yuan: [ XLSX:40KB ]
- 1.4.1 Capital compensation.
- 1.4.2 Labor compensation.
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updated December 21, 2023
1.5 Final demand by industry in millions current yuan: [ XLSX:78KB ]
- 1.5.1 Consumption.
- 1.5.2 Capital formation.
- 1.5.3 Export.
- 1.5.4 Import.
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updated December 21, 2023
1.6 Producer price index by industry, previous year=100. [ XLSX:22KB ]
2. Data on China’s Capital Input Measurement
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updated December 21, 2023
2.1 Investment by industry in millions current yuan. [ XLSX:28KB ]
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updated December 21, 2023
2.2 Capital stock by industry in millions 2000 yuan. [ XLSX:28KB ]
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updated December 21, 2023
2.3 Capital input index by industry, 2000=1. [ XLSX:27KB ]
3. Data on China’s Labor Input Measurement
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updated December 21, 2023
3.1 Numbers employed by industry in 1000s. [ XLSX:25KB ]
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updated December 21, 2023
3.2 Hours worked by industry in millions. [ XLSX:22KB ]
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updated December 21, 2023
3.3 Labor input index by industry, 2000=1. [ XLSX:27KB ]
4. China’s Growth accounts [XLSX:1.1MB]
updated December 21, 2023
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4.1 The measurement of value-added growth:
- 4.1.1 Nominal gross output by industry (current price, million yuan).
- 4.1.2 Nominal intermediate inputs by industry (current price, million yuan).
- 4.1.3 Nominal value added by industry (current price, million yuan).
- 4.1.4 Growth rate of real gross output by industry.
- 4.1.5 Growth rate of real intermediate inputs by industry.
- 4.1.6 Growth rate of real value added by industry.
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4.2 The measurement of capital input growth:
- 4.2.1 Nominal capital compensation by industry (current price, million yuan).
- 4.2.2 Capital input by industry (Divisia index, 2000=1.000).
- 4.2.3 Real net capital stock index by industry (2000=1.000).
- 4.2.4 Capital quality index by industry (2000=1.000).
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4.3 The measurement of labor input growth:
- 4.3.1 Nominal labor compensation by industry (current price, million yuan).
- 4.3.2 Labor input by industry (Divisia index, 2000=1.000).
- 4.3.3 Hours worked index by industry (2000=1.000).
- 4.3.4 Labor quality index by industry (2000=1.000).
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4.4 Sources of China’s output growth, gross output based:
- 4.4.1 Contribution of intermediate inputs to gross output growth.
- 4.4.2 Contribution of real net capital stock to gross output growth.
- 4.4.3 Contribution of capital quality to gross output growth.
- 4.4.4 Contribution of hours worked to gross output growth.
- 4.4.5 Contribution of labor quality to gross output growth.
- 4.4.6 Contribution of TFP growth.
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4.5 Sources of China’s output growth, value-added based:
- 4.5.1 Contribution of real net capital stock to value-added growth.
- 4.5.2 Contribution of capital quality to value-added growth.
- 4.5.3 Contribution of hours worked to value-added growth.
- 4.5.4 Contribution of labor quality to value-added growth.
- 4.5.5 Contribution of TFP growth.
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4.6 Sources of China’s labor productivity growth, value-added based:
- 4.6.1 Growth rate of labor productivity (real value added/hours worked).
- 4.6.2 Contribution of capital input per hours worked (capital deepening).
- 4.6.3 Contribution of labor quality to labor productivity growth.
- 4.6.4 Contribution of TFP growth.
5. Classification
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updated December 21, 2023
CIP classification reconciled to Chinese National Accounts and EU-KLEMS classifications. [ XLSX:12KB ]
Terms of Use of the Data
When using the data, please cite the CIP Database 2023 published by the Research Institute of Economy, Trade and Industry (RIETI) and Hitotsubashi University, Peking University Growth Lab as the data source.
For inquiries, please contact:
JIP Database Office, Institute of Economic Research, Hitotsubashi University
E-mail: jip-info@ier.hit-u.ac.jp