Constructing quarterly Chinese time series usable for macroeconomic analysis

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. •The paper constructs a detailed dataset of major expenditure components of GDP in nominal and real terms at a quarterly frequency.•The dataset provides a valuable resource for macroeconomic analysis.•An SVAR model is used to identify primary drivers of Chinese macroeconomic fluctuations.•Consumption-constrained shocks exerted enduring impacts on GDP and household consumption during and post the Covid-19 pandemic.•The findings shed light on how crises can permanently alter the nature of economic shocks in China.