This paper studies the barriers to water trade in California's surface water market. Despite significant price disparities between users, less than 5% of surface water is traded annually. Commonly cited frictions include incomplete property rights, costly management of externalities, and infrastructural constraints. I build and estimate a model of California's water market to decompose these frictions and simulate counterfactuals. My model features agricultural production, urban demand, hydrological externalities, and bilateral transaction costs. I find that incomplete property rights and constraints on an important bottleneck in the system represent significant sources of friction. Despite qualitative concern about the regulatory burden of managing externalities, this friction is relatively modest. I estimate that constructing new infrastructure coupled with streamlining water rights management would quadruple trade volume, increase agricultural profits by 10%, and increase environmental water supply. While these interventions reduce misallocation amongst farmers, they do not significantly benefit urban buyers.

Many proposed surface water transfers undergo a series of regulatory reviews designed to mitigate hydrological and economic externalities. While these reviews help limit externalities, they impose substantial transaction costs that also limit trade. To promote a well-functioning market for surface water in California, we describe how a new kind of water right and related regulatory practices can balance the trade-off between externalities and transaction costs, and how a Water Incentive Auction can incentivize a sufficient number of current rights holders to swap their old rights for the new ones. The Water Incentive Auction adapts lessons learned from the US government’s successful Broadcast Incentive Auction.

Media: [KJZZ Radio] [SIEPR] [Quartz]

We provide new evidence on the drivers of the early US coronavirus pandemic. We combine an epidemiological model of disease transmission with quasi-random variation arising from the timing of stay-at-home-orders to estimate the causal roles of policy interventions and vol- untary social distancing. We then relate the residual variation in disease transmission rates to observable features of cities. We estimate significant impacts of policy and social distancing responses, but we show that the magnitude of policy effects is modest, and most social distancing is driven by voluntary responses. Moreover, we show that neither policy nor rates of voluntary social distancing explain a meaningful share of geographic variation. The most important predictors of which cities were hardest hit by the pandemic are exogenous characteristics such as population and density.

Media: [Vox] [Forbes]

We introduce a novel measure of segregation, experienced isolation, that captures individuals’ exposure to diverse others in the places they visit over the course of their days. Using Global Positioning System (GPS) data collected from smartphones, we measure experienced isolation by race. We find that the isolation individuals experience is substantially lower than standard residential isolation measures would suggest, but that experienced andresidential isolation are highly correlated across cities. Experienced isolation is lower relative to residential isolation in denser, wealthier, more educated cities with high levels of public transit use, and is also negatively correlated with income mobility. Individuals are more isolated close to home and at locations like churches and schools, and less isolated at entertainment, retail, and eating establishments.

We propose a sensitivity analysis for Synthetic Control (SC) treatment effect estimates to interrogate the assumption that the SC method is wellspecified, namely that choosing weights to minimize pre-treatment prediction error yields accurate predictions of counterfactual post-treatment outcomes. Our data-driven procedure recovers the set of treatment effects consistent with the assumption that the misspecification error incurred by the SC method is at most the observable misspecification error incurred when using the SC estimator to predict the outcomes of some control unit. We show that under one definition of misspecification error, our procedure provides a simple, geometric motivation for comparing the estimated treatment effect to the distribution of placebo residuals to assess estimate credibility. When we apply our procedure to several canonical studies that report SC estimates, we broadly confirm the conclusions drawn by the source papers.

How do permanent changes in the amount of water available for productive uses affect local communities? Concerns about negative impacts on local economies that sell water have driven repugnance toward water market liberalization and curtailed efforts to promote market re-allocation—a powerful policy tool to adapt to increasing water scarcity. This paper uses the liberalization of water markets in Australia’s Murray-Darling Basin in 2007 to investigate the effects of the re-allocation of water on local economies and residents’ welfare. We exploit differences in endowments of soil productivity to instrument for post-reform changes in water usage to measure their effect on wages, home prices, and populations. Losing water is associated with lower wages, lower rents, and lower populations 14 years on. To quantify the welfare implications, we develop and estimate a residential choice model. The model-implied average willingness to pay to avoid a nearby farmer selling an acre-foot of water is around $50, which is around a quarter of the average market price. We consider different market designs that ensure Pareto improvements for all local communities while achieving the productive efficiency gains of an unfettered market.

Agents experience externalities through each other's actions and allocations. In that sense, all resources can be considered the commons . Standard property right design that only specifies each agent's own allocation, and not what actions can be taken, is no longer the appropriate framework in the presence of externalities. We extend property rights to rights over any change in action and allocation that create externalities. Each agent's right is represented by a probability that the agent's preferred change is enforced in the outside option. Agents have private information about their externalities. The designer wants to implement the efficient change but is subject to incentive compatibility and individual rationality constraints. Rights must resolve the trade-off between allowing for productive changes in use and protecting impacted third-parties. Using tools from mechanism design we compute the expected transaction cost of implementing efficient resource management for any choice of rights. We characterize robust rights to the commons that guarantee implementation of efficient outcomes at the lowest cost.