An adaptive approach to forecasting three key macroeconomic variables for transitional ChinaLinlin Niu, Xiu Xu and Ying Chen Economic Modelling, 2017, vol. 66, issue C, 201-213 Abstract: The macroeconomic forecasts for emerging economies often suffer from the constraints of instability and limited data. In light of these constraints, we propose the use of a local autoregressive (LAR) model with a data-driven estimation window, i.e., a local homogenous interval, that is adaptively identified to strike a balance between information efficiency and stability. When applied to three key macroeconomic variables of China, the LAR model substantially outperforms the alternative models for various forecast horizons of 3 to 12 months, with forecast error reductions of between 4% and 64% for the IP growth, and between 1% and 68% for the inflation rate. The one-quarter ahead performance of the LAR model matches that of a well-known survey forecast. The patterns of the identified local intervals also coincide with the characteristic evolution of the gradual reforms and monetary policy shifts in China. In short, the LAR model is suitable for not only forecasting, but also the real-time monitoring of the effects of regime and policy changes in emerging economies. Keywords: Emerging economy; China; Local parametric model; Out-of-sample forecasting; Instability; Data limitation (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:ecmode:v:66:y:2017:i:c:p:201-213 DOI: 10.1016/j.econmod.2017.07.001 Access Statistics for this article Economic Modelling is currently edited by S. Hall and P. Pauly More articles in Economic Modelling from Elsevier |
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