The Predictive Power of the User Cost Spread for Economic Recession in China and the US
Dongfeng Chang (),
Ryan Mattson () and
Biyan Tang ()
Additional contact information
Dongfeng Chang: School of Economics, Shandong University, Jinan 250100, Shandong, China
Biyan Tang: University of Massachusetts Dartmouth, Economics Department, North Dartmouth, MA 02747-2300, USA
International Journal of Financial Studies, 2019, vol. 7, issue 2, 1-12
The predictive power of the yield curve slope, or the yield spread is well established in the United States (US) and European Union (EU) countries since 1998. However, there exists a gap in the literature on the predictive power of the yield spread on the Chinese economy. This paper provides a different leading recession indicator using the Chinese and US economy as comparative examples: the user cost spread, being the difference of the opportunity costs of holding government securities of different maturities. We argue that the user cost spread, based on the Divisia monetary aggregate data like the ones produced by the Center for Financial Stability, provides improved predictive ability and a better intuitive explanation based on changes in the user cost price of holding bonds.
Keywords: Divisia monetary aggregates; user cost spread; recession; China; yield spread (search for similar items in EconPapers)
JEL-codes: G1 G2 G3 F2 F3 F41 F42 (search for similar items in EconPapers)
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed
Downloads: (external link)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:gam:jijfss:v:7:y:2019:i:2:p:34-:d:240702
Access Statistics for this article
International Journal of Financial Studies is currently edited by Prof. Dr. Nicholas Apergis
More articles in International Journal of Financial Studies from MDPI, Open Access Journal
Bibliographic data for series maintained by XML Conversion Team ().