An adaptive approach to forecasting three key macroeconomic variables for transitional China

Linlin Niu, Xiu Xu and Ying Chen

No 2015-023, SFB 649 Discussion Papers from Humboldt University Berlin, Collaborative Research Center 649: Economic Risk

Abstract: We propose the use of a local autoregressive (LAR) model for adaptive estimation and forecasting of three of China's key macroeconomic variables: GDP growth, inflation and the 7-day interbank lending rate. The approach takes into account possible structural changes in the data-generating process to select a local homogeneous interval for model estimation, and is particularly well-suited to a transition economy experiencing ongoing shifts in policy and structural adjustment. Our results indicate that the proposed method outperforms alternative models and forecast methods, especially for forecast horizons of 3 to 12 months. Our 1-quarter ahead adaptive forecasts even match the performance of the well-known CMRC Langrun survey forecast. The selected homogeneous intervals indicate gradual changes in growth of industrial production driven by constant evolution of the real economy in China, as well as abrupt changes in interestrate and inflation dynamics that capture monetary policy shifts.

Keywords: Chinese economy; local parametric models; forecasting (search for similar items in EconPapers)
JEL-codes: E43 E47 (search for similar items in EconPapers)
Date: 2015
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Journal Article: An adaptive approach to forecasting three key macroeconomic variables for transitional China (2017)
Working Paper: An adaptive approach to forecasting three key macroeconomic variables for transitional China (2015)
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