Recent studies document the disparity between short- and long-run trade elasticities. In this paper, we propose a dynamic multi-country general equilibrium model with market-specific marketing capital and convex capital adjustment costs to account for the persistence in bilateral trade flow responses. Our model predicts that the dynamic effects of the Trump tariff shocks can take around two decades to die out. We connect the model to a reduced-form dynamic gravity equation with multiple horizons to decompose the long-run trade elasticity into the "static trade elasticity" and the "dynamic trade elasticity". Incorporating the dynamic effects, our estimate of long-run trade elasticity is two times as large as the short-run elasticity.

The paper looks into the puzzle of low household savings in three Southern European (SE3) countries – Cyprus, Greece, and Portugal. Building on the household saving drivers literature, we employ cross-country micro-level data and investigate the key saving patterns, examining their heterogeneity across households in SE3 countries relative to the EA average. The results confirm the prominent role of income, along with interest rate, inflation, fiscal balance, and debt in shaping household savings in SE3 countries. Quantile regressions employed to analyze saving behavior across the distribution of households suggest that households with lower savings tend to see their savings dip (or dissavings rise) more-than-proportionately with shocks to income, interest rate, inflation, and government balance. Our policy simulations across the distribution of households suggest that targeted rather than universal policy intervention could improve household savings, especially of the most vulnerable ones.

The high-speed railway (HSR) network in China has developed rapidly over the past ten years, offering a new means of travel and also regenerating and redistributing economic activities by encouraging population mobility. Using the Yangtze River Delta urban agglomeration as a case study, this paper investigates the redistribution of economic activities resulting from HSRs by developing a locally weighted regression model, geographically network weighted regression (GNWR). This GNWR is formulated in light of the current account identity in economics and incorporates the changes in network-based travel time from HSRs and the degrees of cities, thereby offering a more appropriate method of capturing the movement of economic activities. Importantly, the coefficients in GNWR can reflect the net inflow or outflow of different cities in terms of their residents' investment and/or consumption. The results of the analysis show that HSRs have significantly changed the spatial redistribution of economic activities due to more frequent and rapid mobility. For investment activities, HSR drew the inflow to the second-tier cities alongside HSR and strengthened the status of core cities; for consumption activities, HSR motivated the inflow to non-HSR cities located in the peripheral areas.