Valuing Options in Water Markets: A Laboratory Investigation

Risk and reliability dominate water supply discussions in the arid western United States in light of increasing demand and finite, weather-dependant supply. Thus water agencies increasingly turn to contractual mechanisms such as dry-year options to manage supply risk in advance of need. Although a few water agencies across the West have implemented dry-year options, sufficient data for conventional econometric analysis do not yet exist. We thus utilize experimental economics to analyze the effect of annual dry-year options on water markets. We consider how market structure (competitive versus monopsony power) and option contract availability affect water price and allocation within a market and find that realized gains from trade are on average higher when options can be traded, by 46% in competitive markets and by 63% in dominant buyer markets. Important for the political feasibility of such markets, we also find that gains from trade, once an options market is available, are much more evenly distributed between the single buyer and the many sellers in the case of monopsony.Resource /Energy Economics and Policy, D23, L22, Q25,

Implementing Options Markets in California To Manage Water Supply Uncertainty

In California, the tremendous spatial and temporal variation in precipitation suggests that flexible contractual arrangements, such as option contracts, would increase allocative efficiency of water over time and space. Under such arrangements, a water agency pays an option premium for the right to purchase water at some point in the future, if water conditions turn out to be dry. The premium represents the value of the flexibility gained by the buyer from postponing its decision whether to purchase water. In California, the seller of existing option arrangements is often an agricultural producer who can fallow land, in the event that a water option is exercised. In this simulation-optimization approach, we seek to determine the value of transferring water uncertainty from one party to another at several locations in California, given current water prices and the spatial and temporal distribution of water year types in the state. (Preliminary analysis covers northern California; future analysis will incorporate southern California.) We analyze within a mathematical programming framework whether increased trading among water agencies across time as well as space would result in significant gains from trade. We use output from CALVIN, an economic-engineering optimization model of the California water system which runs the current configuration of the California water system over historical hydrological conditions, to generate water's imputed price at different locations during different seasons. We also explore reasons why previous theoretical calculations of option value in the western United States have far exceeded option premia on existing bilateral contracts.Risk and Uncertainty,

Valuing Options in California Water Markets: A Laboratory Investigation

Risk and reliability dominate water supply discussions in the arid western United States. In the past, water managers built additional storage to mitigate supply risk. The optimal, least expensive storage sites have now been taken, and there are strong, environmental objections to new facilities. Reliability of existing supplies is further diminished due to concerns about endangered species and global climate change. Thus water agencies increasingly turn to contractual mechanisms such as dry-year options to manage supply risk in advance of need. However, although a few water agencies across the West have implemented dry-year options, sufficient data for conventional econometric analysis do not yet exist. We thus utilize experimental economics to analyze the effect of annual dry-year options on water markets. How do market structure (competitive versus market power) and option contract availability affect water price and allocation within a market? Experiment participants trade stochastic realizations of water in a non-uniform double auction parameterized to resemble the California water market. We find that realized gains from trade are on average higher when options can be traded, by 11% in competitive markets and by 21% in dominant buyer markets. Findings in this analysis may assist policymakers in preparing for the next multi-year drought in California.Resource /Energy Economics and Policy,

An Econometric Test of Water Market Structure in the Western United States

Water markets form differently across the western United States, depending on the relative importance of water supply uncertainty and impediments to water transfers. In many locations, trades take the form of short-term leases of water, allowing the underlying property rights to remain unaffected. In other regions, water right transfers predominate. We quantify the relative effects of economic, hydrologic, and state-level institutional variables on a water agency’s decision whether to lease or purchase water rights. Econometric analysis of 3,806 transactions reported in the Water Strategist over 1990 supports the conclusion that market structure varies across states in accordance with local hydrologic and economic conditions. These conditions call for alternative forms of economic organization to achieve efficiency

Estimating an Ex Ante Cost Function for Belgian Arable Crop Farms

We estimate a farm-level cost function for Belgian crop farms using FADN data over the study period 1996-2006. We rely on an estimation of farmers' expected yields at the time cropping decisions are made rather than actual yields observed in the FADN data. The use of an ex ante cost function improves the cost function estimation. We subsequently suggest how our cost function can be used in simulations to analyze farmer response to changes in output price risk.cost function estimation, panel data, risk, Agricultural and Food Policy, Crop Production/Industries, Production Economics, Q12, Q18,

Cholesterol Homeostasis in Two Commonly Used Human Prostate Cancer Cell-Lines, LNCaP and PC-3

BACKGROUND:Recently, there has been renewed interest in the link between cholesterol and prostate cancer. It has been previously reported that in vitro, prostate cancer cells lack sterol-mediated feedback regulation of the major transcription factor in cholesterol homeostasis, sterol-regulatory element binding protein 2 (SREBP-2). This could explain the accumulation of cholesterol observed in clinical prostate cancers. Consequently, perturbed feedback regulation to increased sterol levels has become a pervasive concept in the prostate cancer setting. Here, we aimed to explore this in greater depth. METHODOLOGY/PRINCIPAL FINDINGS:After altering the cellular cholesterol status in LNCaP and PC-3 prostate cancer cells, we examined SREBP-2 processing, downstream effects on promoter activity and expression of SREBP-2 target genes, and functional activity (low-density lipoprotein uptake, cholesterol synthesis). In doing so, we observed that LNCaP and PC-3 cells were sensitive to increased sterol levels. In contrast, lowering cholesterol levels via statin treatment generated a greater response in LNCaP cells than PC-3 cells. This highlighted an important difference between these cell-lines: basal SREBP-2 activity appeared to be higher in PC-3 cells, reducing sensitivity to decreased cholesterol levels. CONCLUSION/SIGNIFICANCE:Thus, prostate cancer cells are sensitive to changing sterol levels in vitro, but the extent of this regulation differs between prostate cancer cell-lines. These results shed new light on the regulation of cholesterol metabolism in two commonly used prostate cancer cell-lines, and emphasize the importance of establishing whether or not cholesterol homeostasis is perturbed in prostate cancer in vivo

AI is a viable alternative to high throughput screening: a 318-target study

: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery