Conference Agenda

Globally, a large fraction of solid waste is disposed in open dumps, generating a range of harmful externalities. Research on this topic is limited by a lack of data, however. We address this gap by developing methods to construct a globally representative time- series of open dumps, starting with a small, unrepresentative sample of crowdsourced observations. We use these observations to train a potentially biased machine learning model that can predict dumps using satellite imagery. We then employ active learning techniques to select and verify an approximately optimal representative subset of verified points to debias our machine learning predictions. This method gives unbiased estimates of dump prevalence and results in significant efficiency gains relative to standard methods, even in the presence of model miscalibration. We use our data to quantify how international trade in waste generates open dumps. Our results show a dramatic increase in open-air landfills globally after China banned imports of plastic waste in 2018. The increase is concentrated in low-income countries that saw increased imports, suggesting that trade plays a role in overwhelming local waste management systems and the subsequent leakage of waste into the environment.

Managed trade policies, which refer to government interventions that utilize quantitative trade restrictions to achieve specific, measurable outcomes, have garnered significant recent attention. While such policies have long been used in agricultural and food markets to support commodity prices and shield domestic producers from international competition, the empirical evidence on their environmental consequences is notably limited, especially within the context of agricultural commodities in developed economies. \\

Using the 2014 U.S.–Mexico Suspension Agreement as a quasi-experiment, this paper presents the first empirical study to quantify the causal environmental consequences of shifting from free trade to a managed trade agreement. Employing a spatial difference-in-differences design with high-resolution remote sensing data, we document a 15\% increase in agricultural fires in fields most exposed to the trade shock. This surge, primarily driven by land-use conversion from wetlands and diverse crops to sugarcane, underscores how trade-induced agricultural intensification can adversely affect regional air quality and rural public health.

This paper investigates the impact of plastic waste trade on marine plastic pollution and its economic and ecological costs. Using a novel satellite-based marine plastic pollution dataset and a natural experiment in the global waste trade, our results show a significant increase by 5.7% in coastal plastic pollution for every $1,000 increase in grid-level plastic waste imports. This increase in marine plastic debris causes an efficiency decline of around 10.86% in coastal capture fisheries and a 0.25% reduction in marine biodiversity in the short-term. A simple cost-benefit calculation shows that each additional dollar of waste imports increases cost related to marine plastic pollution by $12.94, roughly twice the previously documented $6.28 cost of air pollution. We provide strong evidence for the ecological externalities of the plastic waste trade, which outweigh its other externalities.

We examine how waste material imports affect firm-level pollution and productivity

in China during 2000–2013. Using a shift-share instrumental variable strategy exploit-

ing tariff differentials between virgin and waste materials (plastic, paper, metal), we

find that a one percentage point increase in waste import share raises pollution inten-

sity, defined as emissions per unit of real output, by 1.45% for SO2, 1.16% for NOx,

and 0.75% for soot, while simultaneously increasing real output per employee by 2.12%. Motivated by these findings, we then develop a general equilibrium model incorporating emission and disposal externalities, demonstrating that optimal policy requires both environmental taxes and waste tariffs: environmental taxes reduce both aggregate emissions and waste disposal, while tariffs shift sourcing from imported to domestic waste, reducing disposal externalities while preserving local production. The counterfactual analysis shows that aggregate welfare would increase by approximately 0.06% if the tariff on waste paper were adjusted to its optimal level.