This study provides a comprehensive empirical examination of the drivers and dynamics of Juglar cycles in China from 1981 to 2024. We develop a unified framework that integrates investment, institutional, productivity, and structural factors, and employ a Vector Error Correction Model to analyze the long-run equilibrium and short-run adjustment mechanisms linking fixed asset investment (FAI), government fiscal expenditure (GFE), total factor productivity (TFP), industrial structure upgrading (ISU), and gross domestic product (GDP). Our results confirm a stable cointegration relationship and identify FAI as the most influential long-run driver of output, with a 1% increase in FAI leading to a 0.88% rise in GDP. Industrial upgrading also exerts a positive long-run influence on growth, whereas government spending exhibits a significant negative effect, potentially indicating crowding-out or efficiency losses. In the short run, we find unidirectional Granger causality from FAI to GDP, suggesting that changes in investment contain meaningful predictive power for future output fluctuations. Furthermore, impulse response and variance decomposition analyses illustrate the temporal evolution of these effects, highlighting that the contribution of TFP gains importance over the medium term. Overall, this study deepens our understanding of business cycle transmission mechanisms in emerging economies and offers valuable insights for policymakers seeking to balance investment-driven growth with structural reforms for sustainable and robust economic development.
Gao et al. (Sun,) studied this question.