Resilience, Uncertainty, and the Role of Economics in Ecosystem Management

Many natural systems have the potential to switch between alternative dynamic behaviors. We consider a system with two distinct equations of motion that are separated by a threshold value of the state variable. We show that utility maximization will give a decision making rule that is consistent with ecosystem-based management objectives that aim to reduce the probability that the system crosses the threshold. Moreover, we find that increasing uncertainty (both uncertainty embedded in the natural system and uncertainty of the decision maker about the location of the threshold) can lead to nonmonotonic changes in precaution. Although small increases in uncertainty may at first increase precaution, large enough increases in uncertainty will lead to a decrease in precaution.Resource /Energy Economics and Policy,

Airports, Air Pollution, and Contemporaneous Health

Airports are some of the largest sources of air pollution in the United States. We demonstrate that daily airport runway congestion contributes significantly to local pollution levels and contemporaneous health of residents living nearby and downwind from airports. Our research design exploits the fact that network delays originating from large airports on the East Coast increase runway congestion in California, which in turn increases daily pollution levels around California airports. Using the component of California air pollution driven by airport congestion, we find that carbon monoxide (CO) leads to significant increases in hospitalization rates for asthma, respiratory, and heart related emergency room admissions that are an order of magnitude larger than conventional estimates: A one standard deviation increase in daily pollution levels leads to an additional $1 million in hospitalization costs for respiratory and heart related admissions for the 6 million individuals living within 10km (6.2 miles) of the 12 largest airports in California. While infants and the elderly are more sensitive to air pollution, we also find significant relationships for the adult population. The health impacts are driven by CO, not NO2 or O3, and occur at levels far below existing EPA mandates. Our results suggest there may be sizable morbidity benefits from lowering the existing CO standard.

Climate Change, Crop Yields, and Internal Migration in the United States

We investigate the link between agricultural productivity and net migration in the United States using a county-level panel for the most recent period of 1970-2009. In rural counties of the Corn Belt, we find a statistically significant relationship between changes in net outmigration and climate-driven changes in crop yields, with an estimated semi-elasticity of about -0.17, i.e., a 1% decrease in yields leads to a 0.17% net reduction of the population through migration. This effect is primarily driven by young adults. We do not detect a response for senior citizens, nor for the general population in eastern counties outside the Corn Belt. Applying this semi-elasticity to predicted yield changes under the B2 scenario of the Hadley III model, we project that, holding other factors constant, climate change would on average induce 3.7% of the adult population (ages 15-59) to leave rural counties of the Corn Belt in the medium term (2020-2049) compared to the 1960-1989 baseline, with the possibility of a much larger migration response in the long term (2077-2099). Since there is uncertainty about future warming, we also present projections for a range of uniform climate change scenarios in temperature or precipitation.

Estimating the impact of climate change on crop yields: The importance of non-linear temperature effects

There has been an active debate whether global warming will result in a net gain or net loss for United States agriculture. With mounting evidence that climate is warming, we show that such warming will have substantial impacts on agricultural yields by the end of the century: yields of three major crops in the United States are predicted to decrease by 60 to 79% under the most rapid warming scenario. We use a 55-year panel of crop yields in the United States and pair it with a unique fine-scale weather data set that incorporates the whole distribution of temperatures between the minimum and maximum within each day and across all days in the growing season. The key contribution of our study is in identifying a highly non-linear and asymmetric relationship between temperature and yields. Yields increase in temperature until about 29° C for corn and soybeans and 33° C for cotton, but temperatures above these thresholds quickly become very harmful, and the slope of the decline above the optimum is significantly steeper than the incline below it. Previous studies average temperatures over a season, month, or day and thereby dilute this highly non-linear relationship. We use encompassing tests to compare our model with others in the literature and find its out-of-sample forecasts are significantly better. The stability of the estimated relationship across regions, crops, and time suggests it may be transferable to other crops and countries

Identifying Supply and Demand Elasticities of Agricultural Commodities: Implications for the US Ethanol Mandate

We present a new framework to identify demand and supply elasticities of agricultural commodities using yield shocks - deviations from a time trend of output per area, which are predominantly caused by weather fluctuations. Demand is identified using current-period shocks that give rise to exogenous shifts in supply. Supply is identified using past shocks, which affect expected future prices through inventory accretion or depletion. We use our estimated elasticities to evaluate the impact of ethanol subsidies and mandates on world food commodity prices, quantities, and food consumers' surplus. The current US ethanol mandate requires that about 5 percent of world caloric production from corn, wheat, rice, and soybeans be used for ethanol generation. As a result, world food prices are predicted to increase by about 30 percent and global consumer surplus from food consumption is predicted to decrease by 155 billion dollars annually. If a third of the biofuel calories are recycled as feed stock for livestock, the predicted price increase scales back to 20 percent. While commodity demand is extremely inelastic, price response is muted by a significant supply response that is obscured if futures prices are not instrumented. The resulting expansion of agricultural growing area potentially offsets the CO2 emission benefits from biofuels.

Estimating the Impact of Climate Change on Crop Yields: The Importance of Nonlinear Temperature Effects

The United States produces 41% of the world's corn and 38% of the world's soybeans, so any impact on US crop yields will have implications for world food supply. We pair a panel of county-level crop yields in the US with a fine-scale weather data set that incorporates the whole distribution of temperatures between the minimum and maximum within each day and across all days in the growing season. Yields increase in temperature until about 29C for corn, 30C for soybeans, and 32C for cotton, but temperatures above these thresholds become very harmful. The slope of the decline above the optimum is significantly steeper than the incline below it. The same nonlinear and asymmetric relationship is found whether we consider time series or cross-sectional variation in weather and yields. This suggests limited potential for adaptation within crop species because the latter includes farmers' adaptations to warmer climates and the former does not. Area-weighted average yields given current growing regions are predicted to decrease by 31-43% under the slowest warming scenario and 67-79% under the most rapid warming scenario by the end of the century.

Water Quality Violations and Avoidance Behavior: Evidence from Bottled Water Consumption

In this paper, we examine the impact of poor water quality on avoidance behavior by estimating the change in bottled water purchases in response to drinking water violations. Using data from a national grocery chain matched with water quality violations, we find an increase in bottled water sales of 22 percent from violations due to microorganisms and 17 percent from violations due to elements and chemicals. Back-of-the envelope calculations yield costs of avoidance behavior at roughly $60 million for all nationwide violations in 2005, which likely reflects a significant understatement of the total willingness to pay to eliminate violations.

Cointegration: A tool for Ecosystem-Based Conservation and Management of Fisheries

Species within marine ecosystems are known to be interconnected. This is a result of many factors including predation and competition for resources. Despite this, many fisheries are still managed using a single species framework. This paper uses cointegration analysis to quantify the relationship between different fish species. Cointegration is a method for examining how time series variables that are integrated (e.g., I(0) or long memory fractional) and move together. Using data from Northern Anchovy, Pacific Sardines, and Albacore Tuna off the California coast, a vector error correction model is estimated which shows a statistically significant relationship between anchovy and tuna harvests. Results suggest financial gains from accounting for external effects between these two fisheries and provide an economic justification for ecosystem based management.Keywords: Environmental, Ecological and Economic Considerations in the Conservation and Management of Forage Fish, Fisheries Economics, Fishery Managemen

Comparing and combining process-based crop models and statistical models with some implications for climate change

We compare predictions of a simple process-based crop model (Soltani and Sinclair 2012), a simple statistical model (Schlenker and Roberts 2009), and a combination of both models to actual maize yields on a large, representative sample of farmer-managed fields in the Corn Belt region of the United States. After statistical post-model calibration, the process model (Simple Simulation Model, or SSM) predicts actual outcomes slightly better than the statistical model, but the combined model performs significantly better than either model. The SSM, statistical model and combined model all show similar relationships with precipitation, while the SSM better accounts for temporal patterns of precipitation, vapor pressure deficit and solar radiation. The statistical and combined models show a more negative impact associated with extreme heat for which the process model does not account. Due to the extreme heat effect, predicted impacts under uniform climate change scenarios are considerably more severe for the statistical and combined models than for the process-based model