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	Improving inflation prediction with the quantity theory
	Wang, Ying ; Tu, Yundong ; Chen, Song Xi
	2016
关键词	Cointegrations Inflation forecasting Quantity theory of money Phillips Curve TIME-SERIES MODELS MONEY CHINA
英文摘要	This paper focuses on the role of the quantity theory in improving inflation forecasts. We find that the cointegration-based quantity theory does not hold for the period after 1995 for the U.S. data. However, that period is well explained by an adaptive quantity theory based on a functional-coefficient cointegration that adapts to the unemployment rate. The forecasting exercises show that the adaptive quantity theory has superior predictive power for targeting future inflation. (C) 2016 Elsevier B.V. All rights reserved.; National Statistics Burea; LMEQF at Peking University; National Natural Science Foundation of China [11131002, G0113, 71301004, 71472007, 71532001, 71671002]; SSCI; ARTICLE; yundong.tu@gsm.pku.edu.cn; 112-115; 149
语种	英语
出处	SCI
出版者	ECONOMICS LETTERS
内容类型	其他
源URL	[http://hdl.handle.net/20.500.11897/459315]
专题	数学科学学院
推荐引用方式 GB/T 7714	Wang, Ying,Tu, Yundong,Chen, Song Xi. Improving inflation prediction with the quantity theory. 2016-01-01.

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