Forecasting China's Economic Growth and Inflation

Patrick Higgins, Tao Zha and Karen Zhong

No 22402, NBER Working Papers from National Bureau of Economic Research, Inc

Abstract: Although macroeconomic forecasting forms an integral part of the policymaking process, there has been a serious lack of rigorous and systematic research in the evaluation of out-of-sample model-based forecasts of China's real GDP growth and CPI inflation. This paper fills this research gap by providing a replicable forecasting model that beats a host of other competing models when measured by root mean square errors, especially over long-run forecast horizons. The model is shown to be capable of predicting turning points and to be usable for policy analysis under different scenarios. It predicts that China's future GDP growth will be of L-shape rather than U-shape.

JEL-codes: C53 E1 E17 (search for similar items in EconPapers)
Date: 2016-07
New Economics Papers: this item is included in nep-cna, nep-for, nep-ger, nep-mac and nep-tra
Note: EFG ME
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

Published as Patrick Higgins & Tao Zha & Wenna Zhong, 2016. "Forecasting China's economic growth and inflation," China Economic Review, .

Downloads: (external link)
http://www.nber.org/papers/w22402.pdf (application/pdf)

Related works:
Journal Article: Forecasting China's economic growth and inflation (2016)
Working Paper: Forecasting China's Economic Growth and Inflation (2016)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nbr:nberwo:22402

Ordering information: This working paper can be ordered from
http://www.nber.org/papers/w22402

Access Statistics for this paper

More papers in NBER Working Papers from National Bureau of Economic Research, Inc National Bureau of Economic Research, 1050 Massachusetts Avenue Cambridge, MA 02138, U.S.A.. Contact information at EDIRC.
Bibliographic data for series maintained by ().