Analysis of the Impact of China’s GDP Data Revision on Monetary Policy from the Perspective of Uncertainty

ABSTRACT

Based on the uncertainty brought about by the revision of GDP data, this article calculates the revision effect of GDP data uncertainty from 2000 to 2017 in China, analyzes the implications of GDP revision on output gap estimation, and estimates the effect of this uncertainty on monetary policy. The main results show the following: (1) GDP data revision indeed leads to noticeable uncertainty in the measured GDP and its growth rate in China. (2) The effect of data revision on the output gap shows a downward trend, and the results of the QT filter are most robust among the methods. (3) Controlling the uncertainty of the output gap model to a certain extent, the synchronism and forward-looking Taylor rules can describe China’s monetary policy behavior, while considering the uncertainty of data, the synchronism Taylor rules perform best. The above conclusions have practical reference and policy implications.

KEYWORDS:

• Data uncertainty
• model uncertainty
• quarterly GDP data revision
• optimal monetary policy rules

JEL CLASSIFICATION:

• C32
• E32
• E52

Notes

1. An early expression of this argument may be found in Tinbergen (1952).

2. In 2017, the NBS carried out a simplified reform of China’s GDP accounting and data release system, which was adjusted from three steps (preliminary accounting, preliminary verification, and final verification) to two steps (preliminary accounting and final verification).

3. See http://data.stats.gov.cn/.