This paper investigates the link between housing supply restrictions and increased exposure to natural hazard risks in the United States, considering a wide range of extreme climate threats. It shows that urban growth has heightened exposure to these risks, driven both by the growth of the riskiest cities and the growth in the riskiest areas within cities. Across cities, it finds no evidence that strict housing supply regulations are keeping people away from the riskiest cities. However, within cities, less elastic housing supply in safe areas leads to higher growth in at-risk areas.

Abstract In the past two decades, about half of the new homes in the United States were built in areas at risk of natural hazards. Why is new residential development being exposed to such risk? I posit that land-use regulations restricting development in safer areas, along with frictions in property insurance markets, contribute to this pattern. I study this question in the context of exposure to wildfire risk in the metropolitan area of San Diego, California, where areas unexposed to risk are highly regulated and built out, and insurance regulations prevent premiums from accurately pricing the risk of property damage. I estimate a quantitative urban model using detailed spatial data on zoning, density limits, lot size restrictions, wildfire risk, and insurance. In the model, the regulations reallocate the population to unregulated at-risk areas. Through simulations, I demonstrate how these effects depend on the estimated disamenities from wildfire risk, insurance access, and the spatial correlations between regulations, wildfire risk, and location amenities.

Countries are increasingly turning to non-tariff barriers that are hard to measure and often illegal under WTO rules. What are the impacts of these policies, and what do they reveal about market power in international trade? We study a comprehensive system of discretionary import licenses imposed by Argentina, where we observe the universe of transaction-level requests and approval decisions between 2013 and 2015. Approvals varied across firms and products in a manner consistent with the government’s trade and investment objectives, and over time to safeguard the current account. Interacting these sources of variation to construct an instrument, we estimate that stricter restrictions increased the prices paid by importers, a result that runs counter to competitive price-setting behavior. Informed by a model and a classifier-Lasso, the price and quantity responses identify—for each combination of importer, narrow product, and origin—which side (importer or exporter) holds market power. We find that larger importers are more likely to hold market power, and those trading with richer countries are less likely to. The market-power distribution strongly shapes the effects of quantitative restrictions and the magnitude of optimal tariffs. Import prices rose by 4% as a result of Argentina’s import restrictions, but would have risen by 13% (fallen by 8%) had all foreign firms (Argentinian firms) held market power.