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Is China Fudging Its GDP Figures? Evidence from Trading Partner Data

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  • John G. Fernald
  • Eric Hsu
  • Mark M. Spiegel

Abstract

We propose using imports, measured as reported exports of trading partners, as an alternative benchmark to gauge the accuracy of alternative Chinese indicators (including GDP) of fluctuations in economic activity. Externally-reported imports are likely to be relatively well measured, as well as free from domestic manipulation. Using principal components, we derive activity indices from a wide range of indicators and examine their fit to (trading-partner reported) imports. We choose a preferred index of eight non-GDP indicators (which we call the China Cyclical Activity Tracker, or C-CAT). Comparison with that index and others indicate that Chinese statistics have broadly become more reliable in measuring cyclical fluctuations over time. However, GDP adds little information relative to combinations of other indicators. Moreover, since 2013, Chinese GDP growth has shown little volatility around a gradually slowing trend. Other measures, including the C-CAT and imports, do not show this reduction in volatility. Since 2017, the C-CAT slowed from well above trend to close to trend. As of mid- 2019, it was giving the same cyclical signal as GDP.

Suggested Citation

  • John G. Fernald & Eric Hsu & Mark M. Spiegel, 2019. "Is China Fudging Its GDP Figures? Evidence from Trading Partner Data," Working Paper Series 2019-19, Federal Reserve Bank of San Francisco.
    • Handle: RePEc:fip:fedfwp:2019-19
    DOI: 10.24148/wp2019-19
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    Cited by:

    1. Camila Gutierrez & Javier Turen & Alejandro Vicondoa, 2025. "Global Financial Spillovers of Chinese Macroeconomic Surprises," IMF Working Papers 2025/133, International Monetary Fund.
    2. Corneli, Flavia & Ferriani, Fabrizio & Gazzani, Andrea, 2023. "Macroeconomic news, the financial cycle and the commodity cycle: The Chinese footprint," Economics Letters, Elsevier, vol. 231(C).
    3. Gern, Klaus-Jürgen & Kooths, Stefan & Liu, Wan-Hsin & Reents, Jan, 2025. "Weltwirtschaft im Sommer 2025: Handelspolitischer Gegenwind bremst Expansion [World Economy Summer 2025: Trade policy headwinds - Slower expansion]," Kieler Konjunkturberichte 124, Kiel Institute for the World Economy (IfW Kiel).
    4. Yu Lu & Fanbin Kong & Luchen Huang & Kai Xiong & Caiyao Xu & Ben Wang, 2021. "Evaluation of the Implementation Effect of the Ecological Compensation Policy in the Poyang Lake River Basin Based on Difference-in-Difference Method," Sustainability, MDPI, vol. 13(15), pages 1-14, August.
    5. Chen, Hongyi & Tillmann, Peter, 2021. "Monetary policy uncertainty in China," Journal of International Money and Finance, Elsevier, vol. 110(C).
    6. Tomas Adam & Sona Benecka, 2020. "An alternative, satellite view of China," Occasional Publications - Chapters in Edited Volumes, in: CNB Global Economic Outlook - January 2020, pages 14-17, Czech National Bank, Research and Statistics Department.
    7. Wang, Xi & Liu, Ying & Chen, Zhongfei, 2022. "Monetary policy dysregulation with data distortion," Economic Modelling, Elsevier, vol. 116(C).
    8. Liu, Zixi, 2024. "Chinese monetary policy spillovers on its international portfolio investment flows," Journal of International Money and Finance, Elsevier, vol. 141(C).
    9. Deschamps, Bruno & Fei, Tianlun & Jiang, Ying & Liu, Xiaoquan, 2025. "Uncertainty and cross-sectional stock returns: Evidence from China," Journal of Banking & Finance, Elsevier, vol. 171(C).
    10. Lv, Mengdi & Jiao, Shoukun & Ye, Shiqi & Song, Hongmei & Xu, Jiexin & Ye, Wuyi, 2024. "Assessing time-varying risk in China’s GDP growth," Economics Letters, Elsevier, vol. 242(C).
    11. Eswar Prasad, 2023. "Has China's Growth Gone from Miracle to Malady?," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 54(1 (Spring), pages 243-270.
    12. Chen, Kaiji & Higgins, Patrick & Zha, Tao, 2024. "Constructing quarterly Chinese time series usable for macroeconomic analysis," Journal of International Money and Finance, Elsevier, vol. 143(C).
    13. Rogoff, Kenneth S. & Yang, Yuanchen, 2024. "A tale of tier 3 cities," Journal of International Economics, Elsevier, vol. 152(C).
    14. Ammer, John & Rogers, John & Wang, Gang & Yu, Yang, 2025. "Visible Hands: Professional Asset Managers’ Expectations and the Stock Market in China," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 60(5), pages 2469-2499, August.
    15. Yujia, Li & Zixiang, Zhu & Ming, Che, 2024. "Exploring the relationship between China's economic policy uncertainty and business cycles: Exogenous impulse or endogenous responses?," Emerging Markets Review, Elsevier, vol. 58(C).
    16. Bruno Deschamps & Tianlun Fei & Ying Jiang & Xiaoquan Liu, 2022. "Procyclical volatility in Chinese stock markets," Review of Quantitative Finance and Accounting, Springer, vol. 58(3), pages 1117-1144, April.
    17. Erdal Yalcin & Gabriel Felbermayr & Heider Kariem & Aleksandra Kirilakha & Ohyun Kwon & Constantinos Syropoulos & Yoto V. Yotov, 2025. "The Global Sanctions Data Base—Release 4: The Heterogeneous Effects of the Sanctions on Russia," The World Economy, Wiley Blackwell, vol. 48(9), pages 2003-2017, September.
    18. Arpita Chatterjee & Richa Saraf, 2024. "Impact of China on commodity exporters," Review of International Economics, Wiley Blackwell, vol. 32(3), pages 1462-1491, August.
    19. Al-Haschimi, Alexander & Apostolou, Apostolos & Azqueta-Gavaldon, Andres & Ricci, Martino, 2023. "Using machine learning to measure financial risk in China," Working Paper Series 2767, European Central Bank.
    20. William Barcelona & Danilo Cascaldi-Garcia & Jasper Hoek & Eva Van Leemput, 2022. "What Happens in China Does Not Stay in China," International Finance Discussion Papers 1360, Board of Governors of the Federal Reserve System (U.S.).
    21. Lai, Pingyao & Zhu, Tian, 2022. "Deflating China's nominal GDP: 2004–2018," China Economic Review, Elsevier, vol. 71(C).
    22. Amaze Lusompa & Jose Mustre-del-Rio, 2025. "KC Fed LMCI Can Help Sift Out Noise in Payroll Data," Economic Bulletin, Federal Reserve Bank of Kansas City, pages 1-3, January.

    More about this item

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access
    • E20 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - General (includes Measurement and Data)
    • F17 - International Economics - - Trade - - - Trade Forecasting and Simulation

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