Forecasting China's economic growth and inflation

Patrick Higgins, Tao Zha and Wenna Zhong

China Economic Review, 2016, vol. 41, issue C, 46-61

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. We find that M2 supply, rather than interest rates, is a key variable for forecasting macroeconomic variables. Annual GDP growth for the next five years is predicted to be close to the 6.5% official target and a future GDP growth path is predicted to be of L-shape rather than U-shape.

Keywords: Out of sample; Density forecasts; Policy projections; Scenario analysis; Probability bands; Random walk; Bayesian priors (search for similar items in EconPapers)
JEL-codes: C53 E10 E40 (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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Related works:
Working Paper: Forecasting China's Economic Growth and Inflation (2016)
Working Paper: Forecasting China's Economic Growth and Inflation (2016)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:chieco:v:41:y:2016:i:c:p:46-61

DOI: 10.1016/j.chieco.2016.07.011

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