Using a new database on global multinational production (MP), I document that world multinational enterprise (MNE) sales declined as sharply as trade during the Great Recession (2008–2009). This collapse was driven by MNEs from a few key headquarters countries and associated with steeper GDP declines in MP-intensive countries. MNEs amplified the trade collapse because their overall sales fell while they maintained higher trade intensity than domestic firms. In a calibrated quantitative model with flexible vertical and horizontal MNE structures, international trade, and input–output linkages, I show that productivity shocks, which disproportionately affected trade-intensive MNEs, contributed more to the trade collapse than demand shocks. MNEs’ productivity shocks accounted for over half of the global GDP decline during the Great Recession. MP linkages significantly amplified the transmission of headquarters-country productivity shocks to global GDP, MP, and trade.
Are landlocked countries at risk from sea-level rise? We identify a new mechanism where natural disaster shocks influence countries’ macroeconomic performance through cross-border trade spillovers. Analyzing global data on climate disasters, infrastructure, trade, and the macroeconomy from 1970 to 2019, we find that climate disasters impacting ports, critical infrastructure for international trade, reduce imports, exports, and economic output in both the affected country and its major trade partner (both upstream and downstream) countries. The GDP effects on main upstream and downstream countries are as large as those in directly impacted countries: While directly affected countries offset climate disaster damages with increased government spending and investment, trade partners do not. Effective adaptation efforts, including building climate-resilient infrastructure and implementing disaster relief measures, must account for the cross-border spillover effects of climate disasters.
What is the most cost-efficient way to impose trade sanctions against Russia? We build a quantitative model of international trade with input–output connections. Sanctioning countries choose import tariffs to simultaneously maximize their income and minimize Russia’s income, with different weights placed on these objectives. We find, first, that for countries with low willingness to pay for sanctions against Russia, the most cost-efficient sanction is an approximately 20% tariff on all Russian products. Second, if countries are willing to pay at least US$0.70 for each US$1 drop in Russian welfare, an embargo on Russia’s mining and energy products is the most cost-efficient policy.