Constructing quarterly Chinese time series usable for macroeconomic analysis

Kaiji Chen, Patrick Higgins and Tao Zha

Journal of International Money and Finance, 2024, vol. 143, issue C

Abstract: During episodes such as the global financial crisis and the Covid-19 pandemic, China experienced notable fluctuations in its GDP growth and key expenditure components. To explore the primary sources of these fluctuations, we construct a comprehensive dataset of GDP and its components in both nominal and real terms at a quarterly frequency. Applying two SVAR models to this dataset, we uncover the principal drivers of China's economic fluctuations across different episodes. In particular, our findings reveal the stark and enduring impacts of consumption-constrained shocks on GDP and all of its components, especially household consumption, both during and in the aftermath of the COVID-19 pandemic.

Keywords: Quarterly data; GDP components; Consumption subcomponents; Volatility; SVAR; Distinct regimes; Shock heteroskedasticity (search for similar items in EconPapers)
JEL-codes: C82 E02 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0261560624000391
Full text for ScienceDirect subscribers only

Related works:
Working Paper: Constructing Quarterly Chinese Time Series Usable for Macroeconomic Analysis (2024)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:jimfin:v:143:y:2024:i:c:s0261560624000391

DOI: 10.1016/j.jimonfin.2024.103052

Access Statistics for this article

Journal of International Money and Finance is currently edited by J. R. Lothian

More articles in Journal of International Money and Finance from Elsevier
Bibliographic data for series maintained by Catherine Liu ().