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Tracking Chinese CPI inflation in real time

Listed author(s):
  • Michael Funke
  • Aaron Mehrotra

    ()

  • Hao Yu

With recovery from the global financial crisis in 2009 and 2010, inflation emerged as a concern for many central banks in emerging Asia. We use data observed at mixed frequencies to estimate the movement of Chinese headline inflation within the framework of a state-space model, and then take the estimated indicator to nowcast Chinese CPI inflation. The importance of forward-looking and high-frequency variables in tracking inflation dynamics is highlighted and the policy implications discussed. Copyright Springer-Verlag Berlin Heidelberg 2015

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File URL: http://hdl.handle.net/10.1007/s00181-014-0837-3
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Article provided by Springer in its journal Empirical Economics.

Volume (Year): 48 (2015)
Issue (Month): 4 (June)
Pages: 1619-1641

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Handle: RePEc:spr:empeco:v:48:y:2015:i:4:p:1619-1641
DOI: 10.1007/s00181-014-0837-3
Contact details of provider: Web page: http://www.springer.com

Order Information: Web: http://www.springer.com/economics/econometrics/journal/181/PS2

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  1. Eric Ghysels & Arthur Sinko & Rossen Valkanov, 2007. "MIDAS Regressions: Further Results and New Directions," Econometric Reviews, Taylor & Francis Journals, vol. 26(1), pages 53-90.
  2. S. Boragan Aruoba & Francis X. Diebold, 2010. "Real-Time Macroeconomic Monitoring: Real Activity, Inflation, and Interactions," American Economic Review, American Economic Association, vol. 100(2), pages 20-24, May.
  3. Aksoy, Yunus & Piskorski, Tomasz, 2006. "U.S. domestic money, inflation and output," Journal of Monetary Economics, Elsevier, vol. 53(2), pages 183-197, March.
  4. Claudio Borio, 2011. "Central banking post-crisis: What compass for uncharted waters?," BIS Working Papers 353, Bank for International Settlements.
  5. Svensson, Lars E. O., 1997. "Inflation forecast targeting: Implementing and monitoring inflation targets," European Economic Review, Elsevier, vol. 41(6), pages 1111-1146, June.
  6. Clark, Todd E. & McCracken, Michael W., 2001. "Tests of equal forecast accuracy and encompassing for nested models," Journal of Econometrics, Elsevier, vol. 105(1), pages 85-110, November.
  7. Kuzin, Vladimir & Marcellino, Massimiliano & Schumacher, Christian, 2011. "MIDAS vs. mixed-frequency VAR: Nowcasting GDP in the euro area," International Journal of Forecasting, Elsevier, vol. 27(2), pages 529-542.
  8. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
  9. Andrew Filardo & Hans Genberg, 2010. "Targeting inflation in Asia and the Pacific: lessons from the recent past," BIS Papers chapters,in: Bank for International Settlements (ed.), The international financial crisis and policy challenges in Asia and the Pacific, volume 52, pages 251-273 Bank for International Settlements.
  10. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 33(1), pages 125-132.
  11. Durbin, James & Koopman, Siem Jan, 2012. "Time Series Analysis by State Space Methods," OUP Catalogue, Oxford University Press, edition 2, number 9780199641178.
  12. Stock, James H & Watson, Mark W, 2002. "Macroeconomic Forecasting Using Diffusion Indexes," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(2), pages 147-162, April.
  13. Guonan Ma & Yan Xiandong & Liu Xi, 2013. "China’s evolving reserve requirements," Journal of Chinese Economic and Business Studies, Taylor & Francis Journals, vol. 11(2), pages 117-137, May.
  14. Libero Monteforte & Gianluca Moretti, 2013. "Real‐Time Forecasts of Inflation: The Role of Financial Variables," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 32(1), pages 51-61, January.
  15. Simeon Vosen & Torsten Schmidt, 2011. "Forecasting private consumption: survey‐based indicators vs. Google trends," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 30(6), pages 565-578, September.
  16. Estrella, Arturo & Mishkin, Frederic S., 1997. "Is there a role for monetary aggregates in the conduct of monetary policy?," Journal of Monetary Economics, Elsevier, vol. 40(2), pages 279-304, October.
  17. Modugno, Michele, 2013. "Now-casting inflation using high frequency data," International Journal of Forecasting, Elsevier, vol. 29(4), pages 664-675.
  18. Aruoba, S. BoraÄŸan & Diebold, Francis X. & Scotti, Chiara, 2009. "Real-Time Measurement of Business Conditions," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(4), pages 417-427.
  19. Warmedinger, Thomas & Paredes, Joan & Asimakopoulos, Stylianos, 2013. "Forecasting fiscal time series using mixed frequency data," Working Paper Series 1550, European Central Bank.
  20. Pierre Guérin & Massimiliano Marcellino, 2013. "Markov-Switching MIDAS Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 31(1), pages 45-56, January.
  21. Harvey, David & Leybourne, Stephen & Newbold, Paul, 1997. "Testing the equality of prediction mean squared errors," International Journal of Forecasting, Elsevier, vol. 13(2), pages 281-291, June.
  22. Marta Bańbura & Michele Modugno, 2014. "Maximum Likelihood Estimation Of Factor Models On Datasets With Arbitrary Pattern Of Missing Data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(1), pages 133-160, January.
  23. Croushore, Dean, 2006. "Forecasting with Real-Time Macroeconomic Data," Handbook of Economic Forecasting, Elsevier.
  24. International Monetary Fund, 2009. "What Drives China’s Interbank Market?," IMF Working Papers 09/189, International Monetary Fund.
  25. Faust, Jon & Wright, Jonathan H., 2009. "Comparing Greenbook and Reduced Form Forecasts Using a Large Realtime Dataset," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(4), pages 468-479.
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