Fiscal space and government debt sustainability: empirical analysis based on Chinese  national debt
Articles
Huiyu Zhang
Jiangxi University of Finance and Economics image/svg+xml
https://orcid.org/0009-0005-6757-7642
Jolita Vveinhardt
Vytautas Magnus University image/svg+xml
Jianhua Xiao
School of Public Finance and Tax, Jiangxi University of Finance and Economics, Nanchang, China
Jiangxi University of Finance and Economics image/svg+xml
Domicián Máté
University of Debrecen image/svg+xml
Published 2026-07-01
https://doi.org/10.15388/Tibe.2026.25.2.18
PDF

Keywords

fiscal space
government debt sustainability
VAR
VECM
China

How to Cite

Zhang, H., Vveinhardt, J., Xiao, J., & Máté, D. (2026). Fiscal space and government debt sustainability: empirical analysis based on Chinese  national debt. Transformations In Business & Economics, 25(2 (68), 415-439. https://doi.org/10.15388/Tibe.2026.25.2.18

Abstract

Grounded  in the  intertemporal  budget  constraint  theory , this  paper  defines  'fiscal space' as a core indicator of debt sustainability  and employs a VECM  model to analyze China's national debt data from 1994 to 2023. The findings reveal that economic growth is the most critical factor for expanding fiscal space, exerting a rapid and sustained positive effect in both the short and long term. The tax burden and population aging have a limited positive impact on fiscal space but may exert long-term pressure on its growth. The effect of inflation on fiscal space is minor and inconsistent. A mismatch between the fiscal revenue and expenditure significantly hinders the expansion of fiscal space. Fostering the high-quality economic growth , enhancing fiscal revenues , and optimizing the management of fiscal revenues and expenditures are crucial for safeguarding China's government debt sustainability.

PDF

References

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Downloads

Download data is not yet available.

Most read articles by the same author(s)