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An evaluation of Chinese macroeconomic forecasts

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  • Bruno Deschamps
  • Paolo Bianchi

Abstract

This article evaluates the quality of professional macroeconomic forecasts in China for the years 1995--2009. Using a large panel of forecasts on four macroeconomic variables (GDP, inflation, consumption and investment), we reject the hypothesis of unbiasedness, and find that forecasters have been, on average, overly pessimistic. The source of the bias lies primarily in forecasters' slow adjustment to structural shocks to the level of economic growth. We also reject the hypothesis that forecasters use information efficiently, and find that a large number of forecasters overreact to economic news. Finally, we document large differences of forecast accuracy across both forecasters and variables.

Suggested Citation

  • Bruno Deschamps & Paolo Bianchi, 2012. "An evaluation of Chinese macroeconomic forecasts," Journal of Chinese Economic and Business Studies, Taylor & Francis Journals, vol. 10(3), pages 229-246, December.
  • Handle: RePEc:taf:jocebs:v:10:y:2012:i:3:p:229-246
    DOI: 10.1080/14765284.2012.699704
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    References listed on IDEAS

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    1. Harry X. Wu, 2006. "The Chinese GDP Growth Rate Puzzle: How Fast Has the Chinese Economy Grown?," Hi-Stat Discussion Paper Series d06-176, Institute of Economic Research, Hitotsubashi University.
    2. Curran, Declan & Funke, Michael, 2006. "Taking the temperature : forecasting GDP growth for mainland in China," BOFIT Discussion Papers 6/2006, Bank of Finland, Institute for Economies in Transition.
    3. Declan Curran & Michael Funke, 2006. "Taking the Temperature - Forecasting GDP Growth for Mainland China," Quantitative Macroeconomics Working Papers 20606, Hamburg University, Department of Economics.
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    Cited by:

    1. Mihaela Simionescu, 2014. "What Type Of Social Capital Is Engaged By The French Dairy Stockbreeders? A Characterization Through Their Professional Identities," Romanian Journal of Regional Science, Romanian Regional Science Association, vol. 8(1), pages 87-102, JUNE.
    2. Mihaela Simionescu (Bratu), 2014. "The Performance of Predictions Based on the Dobrescu Macromodel for the Romanian Economy," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 179-195, October.
    3. Mihaela BRATU (SIMIONESCU), 2012. "A Strategy To Improve The Gdp Index Forcasts In Romania Using Moving Average Models Of Historical Errors Of The Dobrescu Macromodel," Romanian Journal of Economics, Institute of National Economy, vol. 35(2(44)), pages 128-138, December.
    4. Mihaela Bratu, 2012. "A Strategy to Improve the Survey of Professional Forecasters (SPF) Predictions Using Bias-Corrected-Accelerated (BCA) Bootstrap Forecast Intervals," International Journal of Synergy and Research, ToKnowPress, vol. 1(2), pages 45-59.
    5. Bratu Mihaela, 2013. "An Evaluation Of Usa Unemployment Rate Forecasts In Terms Of Accuracy And Bias. Empirical Methods To Improve The Forecasts Accuracy," Annals - Economy Series, Constantin Brancusi University, Faculty of Economics, vol. 1, pages 170-180, February.
    6. 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.
    7. repec:ath:journl:tome:34:v:2:y:2014:i:34:p:197-209 is not listed on IDEAS
    8. Mihaela Bratu, 2013. "New Methods of Evaluating the Forecasts Accuracy: A Case Study for USA Inflation," Business and Economic Research, Macrothink Institute, vol. 3(1), pages 21-37, June.

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