 Monetary policy dysregulation with data distortionXi Wang, Ying Liu and Zhongfei Chen Economic Modelling, 2022, vol. 116, issue C Abstract: There is widespread skepticism about the veracity of China’s economic data; however, its implications for making monetary policy decisions and evaluating macroeconomic models remain unclear. We show that economic data distortion introduces undesirable movements in policy interest rates and provides a seriously distorted picture of macroeconomic outcomes using a variant New Keynesian model with forward-looking variables in the sense of endogenous monetary policy. Overstated (understated) output gap data cause monetary policy more restrictive (expansionary), and may incur pro-cyclical regulating mistakes of monetary policy in a limiting case. The data distortion can increase rather than decrease actual economic instability. Actual economic fluctuations become stronger as the persistence and uncertainty of data distortion increase. The theoretical propositions are validated by the calibration and simulation work. This study contributes to a better understanding of the mechanism and effects of data distortion, and it suggests that the central bank can make policy adjustments to improve regulatory efficiency. Keywords: Data distortion; Monetary policy; Dysregulation; China’s macroeconomy (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:116:y:2022:i:c:s0264999322002516 DOI: 10.1016/j.econmod.2022.106012 Access Statistics for this article Economic Modelling is currently edited by S. Hall and P. Pauly More articles in Economic Modelling from Elsevier |
Is your work missing from RePEc? Here is how to contribute.
Questions or problems? Check the EconPapers FAQ or send mail to .
EconPapers is hosted by the
School of Business at Örebro University.