IDEAS home Printed from https://ideas.repec.org/a/eee/jimfin/v110y2021ics0261560620302187.html
   My bibliography  Save this article

Is China fudging its GDP figures? Evidence from trading partner data

Author

Listed:
  • Fernald, John G.
  • Hsu, Eric
  • Spiegel, Mark M.

Abstract

We use Chinese imports, measured as reported exports of trading partners, as a 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 and free from domestic manipulation. Using principal components, we derive activity indices from a wide range of indicators. We choose a preferred index of eight non-GDP indicators based on their fit to Chinese imports, which we call the China Cyclical Activity Tracker (or C-CAT). We find that Chinese statistics have broadly become more reliable in measuring cyclical fluctuations over time. However, measured GDP has been excessively smooth since 2013, and adds little information relative to combinations of other indicators.

Suggested Citation

  • Fernald, John G. & Hsu, Eric & Spiegel, Mark M., 2021. "Is China fudging its GDP figures? Evidence from trading partner data," Journal of International Money and Finance, Elsevier, vol. 110(C).
    • Handle: RePEc:eee:jimfin:v:110:y:2021:i:c:s0261560620302187
    DOI: 10.1016/j.jimonfin.2020.102262
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0261560620302187
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.jimonfin.2020.102262?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. John W. Dawson & Joseph P. Dejuan & John J. Seater & E. Frank Stephenson, 2001. "Economic information versus quality variation in cross‐country data," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 34(4), pages 988-1009, November.
    2. Peter Reinhard Hansen & Allan Timmermann, 2012. "Choice of Sample Split in Out-of-Sample Forecast Evaluation," CREATES Research Papers 2012-43, Department of Economics and Business Economics, Aarhus University.
    3. Emi Nakamura & Jón Steinsson & Miao Liu, 2016. "Are Chinese Growth and Inflation Too Smooth? Evidence from Engel Curves," American Economic Journal: Macroeconomics, American Economic Association, vol. 8(3), pages 113-144, July.
    4. Fernald, John & Edison, Hali & Loungani, Prakash, 1999. "Was China the first domino? Assessing links between China and other Asian economies," Journal of International Money and Finance, Elsevier, vol. 18(4), pages 515-535, August.
    5. Mark Aguiar & Gita Gopinath, 2007. "Emerging Market Business Cycles: The Cycle Is the Trend," Journal of Political Economy, University of Chicago Press, vol. 115(1), pages 69-102.
    6. Jushan Bai & Pierre Perron, 1998. "Estimating and Testing Linear Models with Multiple Structural Changes," Econometrica, Econometric Society, vol. 66(1), pages 47-78, January.
    7. Sinclair, Tara M., 2019. "Characteristics and implications of Chinese macroeconomic data revisions," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1108-1117.
    8. J. Vernon Henderson & Adam Storeygard & David N. Weil, 2012. "Measuring Economic Growth from Outer Space," American Economic Review, American Economic Association, vol. 102(2), pages 994-1028, April.
    9. Jushan Bai & Pierre Perron, 2003. "Computation and analysis of multiple structural change models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(1), pages 1-22.
    10. Stock, J.H. & Watson, M.W., 2016. "Dynamic Factor Models, Factor-Augmented Vector Autoregressions, and Structural Vector Autoregressions in Macroeconomics," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 415-525, Elsevier.
    11. Clark, Hunter & Pinkovskiy, Maxim & Sala-i-Martin, Xavier, 2020. "China's GDP growth may be understated," China Economic Review, Elsevier, vol. 62(C).
    12. Pesaran, M. Hashem & Pick, Andreas & Pranovich, Mikhail, 2013. "Optimal forecasts in the presence of structural breaks," Journal of Econometrics, Elsevier, vol. 177(2), pages 134-152.
    13. John G. Fernald & Israel Malkin & Mark M. Spiegel, 2013. "On the reliability of Chinese output figures," FRBSF Economic Letter, Federal Reserve Bank of San Francisco, issue mar25.
    14. Maxim Pinkovskiy & Xavier Sala-i-Martin, 2016. "Lights, Camera … Income! Illuminating the National Accounts-Household Surveys Debate," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 131(2), pages 579-631.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.
    2. Chen, Hongyi & Tillmann, Peter, 2021. "Monetary policy uncertainty in China," Journal of International Money and Finance, Elsevier, vol. 110(C).
    3. Wang, Xi & Liu, Ying & Chen, Zhongfei, 2022. "Monetary policy dysregulation with data distortion," Economic Modelling, Elsevier, vol. 116(C).
    4. 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).
    5. John Ammer & John H. Rogers & Gang Wang & Yang Yu, 2022. "Visible Hands: Professional Asset Managers' Expectations and the Stock Market in China," International Finance Discussion Papers 1362, Board of Governors of the Federal Reserve System (U.S.).
    6. 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).
    7. 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).
    8. repec:cnb:ocpubc:geo2020/1 is not listed on IDEAS
    9. 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.
    10. 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.
    11. 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.
    12. 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.).
    13. Lai, Pingyao & Zhu, Tian, 2022. "Deflating China's nominal GDP: 2004–2018," China Economic Review, Elsevier, vol. 71(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Fernald, John G. & Hsu, Eric & Spiegel, Mark M., 2021. "Reprint: Is China fudging its GDP figures? Evidence from trading partner data," Journal of International Money and Finance, Elsevier, vol. 114(C).
    2. repec:zbw:bofitp:2015_029 is not listed on IDEAS
    3. John G. Fernald & Eric Hsu & Mark M. Spiegel, 2015. "Is China fudging its figures? Evidence from trading partner data," Working Paper Series 2015-12, Federal Reserve Bank of San Francisco.
    4. repec:bof:bofitp:urn:nbn:fi:bof-201511031430 is not listed on IDEAS
    5. repec:zbw:bofitp:urn:nbn:fi:bof-201511031430 is not listed on IDEAS
    6. John G. Fernald & Eric Hsu & Mark M. Spiegel, 2015. "Is China fudging its figures? Evidence from trading partner data," Working Paper Series 2015-12, Federal Reserve Bank of San Francisco.
    7. Cross, Jamie & Nguyen, Bao H., 2017. "The relationship between global oil price shocks and China's output: A time-varying analysis," Energy Economics, Elsevier, vol. 62(C), pages 79-91.
    8. Jing Tian & Qing Zhou, 2018. "Improving equity premium forecasts by incorporating structural break uncertainty," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 58(S1), pages 619-656, November.
    9. Liu, Ping & James Hueng, C., 2017. "Measuring real business condition in China," China Economic Review, Elsevier, vol. 46(C), pages 261-274.
    10. Hännikäinen Jari, 2017. "Selection of an Estimation Window in the Presence of Data Revisions and Recent Structural Breaks," Journal of Econometric Methods, De Gruyter, vol. 6(1), pages 1-22, January.
    11. Sam Hak Kan Tang, 2019. "Medium-term macroeconomic volatility and economic development: a new technique," Empirical Economics, Springer, vol. 56(4), pages 1231-1249, April.
    12. Crafts, Nicholas & Mills, Terence, 2017. "Trend TFP Growth in the United States: Forecasts versus Outcomes," CEPR Discussion Papers 12029, C.E.P.R. Discussion Papers.
    13. Crespo-Cuaresma, Jesús & Fernández-Amador, Octavio, 2013. "Business cycle convergence in EMU: A first look at the second moment," Journal of Macroeconomics, Elsevier, vol. 37(C), pages 265-284.
    14. Tae‐Hwy Lee & Shahnaz Parsaeian & Aman Ullah, 2022. "Forecasting Under Structural Breaks Using Improved Weighted Estimation," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 84(6), pages 1485-1501, December.
    15. Davide De Gaetano, 2018. "Forecast Combinations in the Presence of Structural Breaks: Evidence from U.S. Equity Markets," Mathematics, MDPI, vol. 6(3), pages 1-19, March.
    16. Tae‐Hwy Lee & Shahnaz Parsaeian & Aman Ullah, 2022. "Optimal forecast under structural breaks," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(5), pages 965-987, August.
    17. Biolsi, Christopher, 2021. "Labor productivity forecasts based on a Beveridge–Nelson filter: Is there statistical evidence for a slowdown?," Journal of Macroeconomics, Elsevier, vol. 69(C).
    18. Richard Bluhm & Denis de Crombrugghe & Adam Szirmai, 0. "Do Weak Institutions Prolong Crises? On the Identification, Characteristics, and Duration of Declines during Economic Slumps," The World Bank Economic Review, World Bank, vol. 34(3), pages 810-832.
    19. Noriega Antonio E. & Rodríguez-Pérez Cid Alonso, 2011. "Stationarity, structural breaks, and economic growth in Mexico: 1895-2008," Working Papers 2011-11, Banco de México.
    20. Chor, Davin & Li, Bingjing, 2024. "Illuminating the effects of the US-China tariff war on China’s economy," Journal of International Economics, Elsevier, vol. 150(C).
    21. Juan Blyde & Christian Daude & Eduardo Fernández-Arias, 2010. "Output collapses and productivity destruction," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 146(2), pages 359-387, June.
    22. Castle, Jennifer L. & Doornik, Jurgen A. & Hendry, David F., 2024. "Improving models and forecasts after equilibrium-mean shifts," International Journal of Forecasting, Elsevier, vol. 40(3), pages 1085-1100.
    23. Glocker, Christian & Sestieri, Giulia & Towbin, Pascal, 2019. "Time-varying government spending multipliers in the UK," Journal of Macroeconomics, Elsevier, vol. 60(C), pages 180-197.

    More about this item

    Keywords

    China; GDP; Principal components; Structural break; Forecasting;
    All these keywords.

    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

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:jimfin:v:110:y:2021:i:c:s0261560620302187. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/30443 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.