In recent decades, developing countries have faced an increase in natural disasters, resulting in substantial economic loss. This study investigates the effects of natural disasters on two key macroeconomic indicators: external debt and foreign direct investment (FDI). Using a balanced panel dataset of 75 developing countries from 2000 to 2022, we apply a two-stage system generalized method of moments (Sys-GMM) approach alongside three static models to account for potential heterogeneity. Our findings show that natural disasters significantly increase external debt, while adversely affecting FDI. Moreover, the interaction between natural disasters and trade has a dual impact, exerting a negative effect on external debt, but a positive influence on FDI inflows. To address temporal dynamics, we analyzed five lags of natural disasters and found external debt increases persist for 5 years. These findings suggest policymakers should strengthen sovereign risk financing and climate-resilient infrastructure to protect macroeconomic stability.
Using data from September 2011 to November 2023, this paper examines how shocks to economic policy uncertainty (EPU) and the China Iron Ore Price Index (CIOPI) propagate along China’s iron ore–steel chain. TVP-VAR estimates show the clearest adverse short-run EPU response in the steel-sector index; the direct CIOPI response is not distinguishable from zero, while downstream responses are heterogeneous. An unexpected CIOPI increase raises steel and selected downstream stock indices only briefly, and forward–reverse asymmetry is not established. Local projections show that higher EPU is followed by declines in steel-industry new orders, greater order-adjustment intensity, and short-run changes in steel and port inventories, consistent with an order–inventory adjustment channel. The spillover index is 68.77%, with machinery as the principal net transmitter. Removing the CSI 300 component reduces connectedness to 21.83%, but machinery retains this role. The findings are robust to BVAR estimation, alternative lag orders, and variance-decomposition horizons.
This paper examines the degree of persistence in new firm formation across six major European economies (Belgium, Denmark, France, Germany, Poland, and Spain) during the 2015–2023 period. Specifically, it evaluates whether the effects of shocks on entrepreneurship exert a permanent impact or, conversely, tend to be reversed over time. To this end, the study applies fractional integration techniques, combining parametric and semiparametric estimators to ensure robust persistence parameters. Furthermore, the study incorporates an analysis of structural breaks identifying how disruptive macroeconomic events have altered the long-term trend of new firm formation. Finally, it explores the implications of European integration for entrepreneurial dynamics among the selected countries. The empirical results show heterogeneous degrees of persistence, suggesting mean reversion in all cases but with different speeds of adjustment. The findings highlight substantial cross-country heterogeneity and imply that entrepreneurship policies in the EU should be tailored to country-specific persistence patterns.
U.S. monetary policy exerts pronounced international spillovers and constitutes a key source of disturbances to global financial stability. Based on quarterly data for 50 economies over 2002–2023, we employ a fixed-effects panel model to examine the link between U.S. monetary policy uncertainty and systemic financial risk. We find that increases in U.S. monetary policy uncertainty materially raise systemic financial risk across economies. Asset price movements and volatility in cross-border capital flows emerge as potential channels underlying this relationship. Further analysis shows that financial openness amplifies these spillovers, whereas higher levels of economic development and stronger institutional quality help mitigate the rise in systemic financial risk induced by external monetary policy uncertainty. These findings suggest that, to safeguard macroeconomic and financial stability, economies should tailor financial opening strategies to domestic conditions, prudently manage liberalization, and promote high-quality development with institutional improvements, thereby enhancing resilience to external uncertainty shocks.
While AI profoundly reshapes the labor market, its spatial impact remains under-researched. Addressing this, this paper uses data from the China Migrant Population Dynamic Monitoring Survey and the China Patent Database across 250 prefecture-level cities during 2014–2018 to examine AI's effect on labor out-migration intention. Findings reveal AI significantly increases out-migration intention, especially among women and in non-digital hubs or central/western regions. Mechanistically, the results are consistent with a displacement channel involving routine jobs and a restructuring channel involving industrial shifts. These channels can be understood through a “skill-spatial mismatch” resulting from the changing spatial distribution of tasks. Furthermore, regional aging and fiscal support amplify the positive relationship between AI and out-migration intention. The study concludes by emphasizing the need for a spatially inclusive employment policy framework as AI reshapes employment geography. The findings concern workers' stated propensity to leave, which may precede future mobility, rather than observed migration flows.
