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Characteristics and implications of Chinese macroeconomic data revisions

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  • Sinclair, Tara M.
Abstract
The research examining macroeconomic data for developed economies suggests that an understanding of the nature of data revisions is important both for the production of accurate macroeconomic forecasts and for forecast evaluation. This paper focuses on Chinese data, for which there has been substantial debate about data quality for some time. The key finding in this paper is that, while it is true that the Chinese macroeconomic data revisions are not well-behaved, they are not very different from similarly-timed U.S. macroeconomic data revisions. The positive bias in Chinese real GDP revisions is a result of the fast-growing service sector, which is notably hard to measure in real time. A better understanding of the revisions process is particularly helpful for studies of the forecast errors from surveys of forecasters, where the choice of the vintage for outcomes may have an impact on the estimated forecast errors.

Suggested Citation

  • Sinclair, Tara M., 2019. "Characteristics and implications of Chinese macroeconomic data revisions," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1108-1117.
    • Handle: RePEc:eee:intfor:v:35:y:2019:i:3:p:1108-1117
    DOI: 10.1016/j.ijforecast.2019.04.010
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    1. Evan F. Koenig & Sheila Dolmas & Jeremy Piger, 2003. "The Use and Abuse of Real-Time Data in Economic Forecasting," The Review of Economics and Statistics, MIT Press, vol. 85(3), pages 618-628, August.
    2. Clements, Michael P., 2019. "Do forecasters target first or later releases of national accounts data?," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1240-1249.
    3. S. Borağan Aruoba, 2008. "Data Revisions Are Not Well Behaved," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 40(2‐3), pages 319-340, March.
    4. Sinclair, Tara M. & Joutz, Fred & Stekler, H.O., 2010. "Can the Fed predict the state of the economy?," Economics Letters, Elsevier, vol. 108(1), pages 28-32, July.
    5. Shirley Hsuan Hsieh, 2013. "Chinese Provincial Macroeconomic Data Revisions," Working Papers 2013-9, The George Washington University, Institute for International Economic Policy.
    6. Croushore, Dean & Stark, Tom, 2001. "A real-time data set for macroeconomists," Journal of Econometrics, Elsevier, vol. 105(1), pages 111-130, November.
    7. Clark, Hunter & Pinkovskiy, Maxim & Sala-i-Martin, Xavier, 2020. "China's GDP growth may be understated," China Economic Review, Elsevier, vol. 62(C).
    8. Sinclair, Tara M. & Stekler, H.O., 2013. "Examining the quality of early GDP component estimates," International Journal of Forecasting, Elsevier, vol. 29(4), pages 736-750.
    9. Gultekin Isiklar & Kajal Lahiri & Prakash Loungani, 2006. "How quickly do forecasters incorporate news? Evidence from cross‐country surveys," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(6), pages 703-725, September.
    10. 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.
    11. repec:bla:revinw:v:48:y:2002:i:2:p:205-15 is not listed on IDEAS
    12. Harry X. Wu, 2000. "China'S Gdp Level And Growth Performance: Alternative Estimates And The Implications," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 46(4), pages 475-499, December.
    13. Loungani, Prakash, 2001. "How accurate are private sector forecasts? Cross-country evidence from consensus forecasts of output growth," International Journal of Forecasting, Elsevier, vol. 17(3), pages 419-432.
    14. Karen E. Dynan & Douglas W. Elmendorf, 2001. "Do provisional estimates of output miss economic turning points?," Finance and Economics Discussion Series 2001-52, Board of Governors of the Federal Reserve System (U.S.).
    15. Swanson, Norman R. & van Dijk, Dick, 2006. "Are Statistical Reporting Agencies Getting It Right? Data Rationality and Business Cycle Asymmetry," Journal of Business & Economic Statistics, American Statistical Association, vol. 24, pages 24-42, January.
    16. Carsten A. Holz, 2006. "China'S Reform Period Economic Growth: How Reliable Are Angus Maddison'S Estimates? Response To Angus Maddison'S Reply," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 52(3), pages 471-475, September.
    17. Stark, Tom & Croushore, Dean, 2002. "Forecasting with a real-time data set for macroeconomists," Journal of Macroeconomics, Elsevier, vol. 24(4), pages 507-531, December.
    18. Croushore, Dean, 2006. "Forecasting with Real-Time Macroeconomic Data," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 17, pages 961-982, Elsevier.
    19. Faust, Jon & Rogers, John H & Wright, Jonathan H, 2005. "News and Noise in G-7 GDP Announcements," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 37(3), pages 403-419, June.
    20. Carsten A. Holz, 2006. "CHINA's REFORM PERIOD ECONOMIC GROWTH: HOW RELIABLE ARE ANGUS MADDISON's ESTIMATES?," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 52(1), pages 85-119, March.
    21. Chen, Qiwei & Costantini, Mauro & Deschamps, Bruno, 2016. "How accurate are professional forecasts in Asia? Evidence from ten countries," International Journal of Forecasting, Elsevier, vol. 32(1), pages 154-167.
    22. Rawski, Thomas G., 2001. "What is happening to China's GDP statistics?," China Economic Review, Elsevier, vol. 12(4), pages 347-354.
    23. Dean Croushore, 2019. "Revisions to PCE Inflation Measures: Implications for Monetary Policy," International Journal of Central Banking, International Journal of Central Banking, vol. 15(4), pages 241-265, October.
    24. Isiklar, Gultekin & Lahiri, Kajal, 2007. "How far ahead can we forecast? Evidence from cross-country surveys," International Journal of Forecasting, Elsevier, vol. 23(2), pages 167-187.
    25. Michael P. Clements & Ana Beatriz Galvão, 2013. "Real‐Time Forecasting Of Inflation And Output Growth With Autoregressive Models In The Presence Of Data Revisions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(3), pages 458-477, April.
    26. Holden, K & Peel, D A, 1990. "On Testing for Unbiasedness and Efficiency of Forecasts," The Manchester School of Economic & Social Studies, University of Manchester, vol. 58(2), pages 120-127, June.
    27. Stark, Tom & Croushore, Dean, 2002. "Reply to the comments on 'Forecasting with a real-time data set for macroeconomists'," Journal of Macroeconomics, Elsevier, vol. 24(4), pages 563-567, December.
    28. Frederick Joutz & H. O. Stekler, 1998. "Data revisions and forecasting," Applied Economics, Taylor & Francis Journals, vol. 30(8), pages 1011-1016.
    29. Holz, Carsten A., 2014. "The quality of China's GDP statistics," China Economic Review, Elsevier, vol. 30(C), pages 309-338.
    30. Chadwick C. Curtis & Nelson Mark, 2010. "Business Cycles, Consumption and Risk-Sharing: How Different Is China?," NBER Working Papers 16154, National Bureau of Economic Research, Inc.
    31. Jorg Scheibe, 2003. "The Chinese Output Gap During the Reform Period 1978-2002," Economics Series Working Papers 179, University of Oxford, Department of Economics.
    32. Dean Croushore, 2011. "Frontiers of Real-Time Data Analysis," Journal of Economic Literature, American Economic Association, vol. 49(1), pages 72-100, March.
    33. Gregory Chow, 2006. "Are Chinese Official Statistics Reliable?," CESifo Economic Studies, CESifo Group, vol. 52(2), pages 396-414, June.
    34. Berger, Allen N & Krane, Spencer D, 1985. "The Information Efficiency of Econometric Model Forecasts," The Review of Economics and Statistics, MIT Press, vol. 67(1), pages 128-134, February.
    35. Rawski, Thomas G. & Xiao, Wei, 2001. "Roundtable on Chinese Economic Statistics Introduction," China Economic Review, Elsevier, vol. 12(4), pages 298-302.
    36. repec:bla:revinw:v:46:y:2000:i:4:p:475-99 is not listed on IDEAS
    37. Lixiong Yang, 2017. "An assessment on the quality of China’s preliminary data of quarterly GDP announcements," Applied Economics, Taylor & Francis Journals, vol. 49(54), pages 5558-5569, November.
    38. Dovern, Jonas & Fritsche, Ulrich & Loungani, Prakash & Tamirisa, Natalia, 2015. "Information rigidities: Comparing average and individual forecasts for a large international panel," International Journal of Forecasting, Elsevier, vol. 31(1), pages 144-154.
    39. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 33(1), pages 125-132.
    40. Harry X. Wu, 2007. "The Chinese GDP Growth Rate Puzzle: How Fast Has the Chinese Economy Grown?," Asian Economic Papers, MIT Press, vol. 6(1), pages 1-23, Winter.
    41. Clements, Michael P. & Galvão, Ana Beatriz, 2013. "Forecasting with vector autoregressive models of data vintages: US output growth and inflation," International Journal of Forecasting, Elsevier, vol. 29(4), pages 698-714.
    42. James E. Kennedy, 1990. "An analysis of revisions to the industrial production index," Working Paper Series / Economic Activity Section 109, Board of Governors of the Federal Reserve System (U.S.).
    43. Michael T. Owyang & Hannah Shell, 2017. "China's Economic Data: An Accurate Reflection, or Just Smoke and Mirrors?," The Regional Economist, Federal Reserve Bank of St. Louis, vol. 25(2).
    44. Yueqing Jia, 2011. "A New Look at China’s Output Fluctuations: Quarterly GDP Estimation with an Unobserved Components Approach," Working Papers 2011-006, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    45. Angus Maddison, 2006. "DO OFFICIAL STATISTICS EXAGGERATE CHINA's GDP GROWTH? A REPLY TO CARSTEN HOLZ," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 52(1), pages 121-126, March.
    46. Keidel, Albert, 2001. "China's GDP expenditure accounts," China Economic Review, Elsevier, vol. 12(4), pages 355-367.
    47. Alwyn Young, 2003. "Gold into Base Metals: Productivity Growth in the People's Republic of China during the Reform Period," Journal of Political Economy, University of Chicago Press, vol. 111(6), pages 1220-1261, December.
    48. Masahiro Ashiya, 2006. "Testing the rationality of forecast revisions made by the IMF and the OECD," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 25(1), pages 25-36.
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    Cited by:

    1. repec:bof:bofitp:urn:nbn:fi:bof-201511031430 is not listed on IDEAS
    2. 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.
    3. 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).
    4. repec:zbw:bofitp:2015_002 is not listed on IDEAS
    5. repec:zbw:bofitp:urn:nbn:fi:bof-201511031430 is not listed on IDEAS
    6. Holz, Carsten A., 2014. "The quality of China's GDP statistics," China Economic Review, Elsevier, vol. 30(C), pages 309-338.
    7. repec:zbw:bofitp:2015_029 is not listed on IDEAS
    8. Baum, Christopher F. & Kurov, Alexander & Wolfe, Marketa Halova, 2015. "What do Chinese macro announcements tell us about the world economy?," Journal of International Money and Finance, Elsevier, vol. 59(C), pages 100-122.
    9. Pang, Ke & Siklos, Pierre L., 2016. "Macroeconomic consequences of the real-financial nexus: Imbalances and spillovers between China and the U.S," Journal of International Money and Finance, Elsevier, vol. 65(C), pages 195-212.
    10. 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.
    11. Pang, Ke & Siklos, Pierre L., 2016. "Macroeconomic consequences of the real-financial nexus: Imbalances and spillovers between China and the U.S," Journal of International Money and Finance, Elsevier, vol. 65(C), pages 195-212.
    12. Harry X. Wu & Eric Girardin, 2016. "The ‘new’ normal is ‘old’ in China: Very late catching up and return to the (pre-WTO) old normal," EcoMod2016 9721, EcoMod.
    13. 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).

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    More about this item

    Keywords

    China; Real-time data; Data revisions; Forecasting; Real GDP; Real GNP;
    All these keywords.

    JEL classification:

    • C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access
    • E01 - Macroeconomics and Monetary Economics - - General - - - Measurement and Data on National Income and Product Accounts and Wealth; Environmental Accounts
    • E30 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - General (includes Measurement and Data)

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