TDPE | Trade Day 2026

About

On November 6, the Moynihan Institute and Trade, Development and Political Economy series will host its second annual “Trade Day.”

Trade Day is a full-day workshop focusing on how trade policies influence global development, economic resilience and political institutions.

Trade Day presenters:

Dave Donaldson (Massachusetts Institute of Technology), “Quantifying the Sensitivity of Quantitative Trade Models”Woan Foong Wong (University of Oregon), “Geopolitical Risk and Foreign Dependence in Global Shipping”Luca Opromolla (North Carolina State University), “Production Cost, Export Prices, and Ambiguity” Dave Donaldson (MIT)

“Quantifying the Sensitivity of Quantitative Trade Models”

Modern quantitative trade models emphasize cross-country heterogeneity in productivity across goods as the source of trade and its benefits. In workhorse versions, this heterogeneity is assumed to follow specific functional forms, such as i.i.d. Frechet or Pareto. We pro-vide a systematic exploration of how sensitive the gains from trade estimated from these models are to relaxing this assumption—first, with a new formula for sharp bounds on gains from trade across all possible distributions, and then with a numerical characterization for the case where distributions must be close to the workhorse form. Importantly, for each candidate distribution we ensure that its implied trade model is consistent with standard estimation methods such as the ability to match all bilateral trade data points and an exogeneity assumption. Our estimated bounds are wide, even for small departures from the canonical model: the maximal gain is about four times larger and the minimal gain is zero. Imposing high-level re-strictions on the distributions considered—for example, maintaining Frechet or Pareto marginals while relaxing independence, or vice versa—does little to shrink these bounds.

(Co-authors: Habib Chenguiti Ansari (Birkbeck) and Edward Wiles (Harvard))

Woan Foong Wong (University of Oregon)

"Geopolitical Risk and Foreign Dependence in Global Shipping"

We study how dependence on maritime routes and foreign vessel capacity shapes countries' vulnerability to disruptions. We develop an analytical framework that links trade exposure, shipping-cost changes, and producer-price adjustment to welfare losses and to the incentives to initiate a disruption. These incentives depend on the loss imposed on the target relative to the economic cost the disruptor bears. Using vessel registries, port rotations, bilateral trade, and least-cost rerouting, we measure how exposed each country's trade is to ship-ping lanes, how easily it can reroute around disruptions, and how much it relies on foreign-operated and foreign-built vessels. We then quantify the welfare effects using global shipping and trade data and a spatial equilibrium model with endogenous routing and vessel deployment. We show that exposure need not imply vulnerability or large losses. Heavily used routes may be easy to bypass, and vessel reallocation and price adjustment redistribute costs across countries. Conditional on the observed withdrawal from Suez, our model reproduces key features of vessel reallocation and freight charges during the Red Sea disruptions. We then map geographic vulnerability across the global network and find the ocean locations that are most vulnerable for each country, including the United States and China. Relative to these two, losing access to ocean routes is more costly for smaller economies. Around Taiwan, a blockade of Taiwan's non-Chinese trade imposes much larger losses on Taiwan and Hong Kong than on China.