Coasts contain a disproportionate share of the world's population, reflecting historical advantages, but environmental change threatens a reversal of coastal fortune in the coming decades as natural disasters intensify and sea levels rise. This paper considers whether large infrastructure investments should continue to favor coastal areas. I estimate a dynamic spatial equilibrium framework using detailed geo-referenced data on road investments in Vietnam from 2000 to 2010 and find evidence that coastal favoritism has significant costs. The results highlight the importance of accounting for the dynamic effects of environmental change in deciding where to allocate infrastructure today.

Environmental externalities—uncompensated damages imposed on others—lie at the root of climate change, pollution, deforestation and biodiversity loss. Empirical evidence is limited, however, as to how externalities drive private decision making. We study one such behaviour, illegal tropical forest fires, using 15 years of daily satellite data covering over 107,000 fires across Indonesia. Weather-induced variation in fire spread risk and variation in who owns surrounding land allow us to identify how far externalities influence the decision to use fire. Relative to when all spread risks are internalized, we find that firms overuse fire when surrounded by unleased government lands where property rights are weak. In contrast, and consistent with the Coase Theorem, firms treat risks to nearby private concessions similarly to risks to their own land. Government sanctions, concentrated on fires spreading to populated areas, also deter fires, consistent with Pigouvian deterrence.

There are two broad views as to why people stay poor. One emphasizes differences in fundamentals, such as ability, talent, or motivation. The poverty traps view emphasizes differences in opportunities that stem from access to wealth. To test these views, we exploit a large-scale, randomized asset transfer and an 11-year panel of 6,000 households who begin in extreme poverty. The setting is rural Bangladesh, and the assets are cows. The data support the poverty traps view—we identify a threshold level of initial assets above which households accumulate assets, take on better occupations (from casual labor in agriculture or domestic services to running small livestock businesses), and grow out of poverty. The reverse happens for those below the threshold. Structural estimation of an occupational choice model reveals that almost all beneficiaries are misallocated in the work they do at baseline and that the gains arising from eliminating misallocation would far exceed the program costs. Our findings imply that large transfers, which create better jobs for the poor, are an effective means of getting people out of poverty traps and reducing global poverty.