The willingness to pay-willingness to accept gap, the "endowment effect," subject misconceptions, and experimental procedures for eliciting valuations

We conduct experiments to explore the possibility that subject misconceptions, as opposed to a particular theory of preferences referred to as the “endowment effect,” account for reported gaps between willingness to pay (“WTP”) and willingness to accept (“WTA”). The literature reveals two important facts. First, there is no consensus regarding the nature or robustness of WTP-WTA gaps. Second, while experimenters are careful to control for subject misconceptions, there is no consensus about the fundamental properties of misconceptions or how to avoid them. Instead, by implementing different types of experimental controls, experimenters have revealed notions of how misconceptions arise. Experimenters have applied these controls separately or in different combinations. Such controls include ensuring subject anonymity, using incentive-compatible elicitation mechanisms, and providing subjects with practice and training on the elicitation mechanism before employing it to measure valuations. The pattern of results reported in the literature suggests that the widely differing reports of WTP-WTA gaps could be due to an incomplete science regarding subject misconceptions. We implement a “revealed theory” methodology to compensate for the lack of a theory of misconceptions. Theories implicit in experimental procedures found in the literature are at the heart of our experimental design. Thus, our approach to addressing subject misconceptions reflects an attempt to control simultaneously for all dimensions of concern over possible subject misconceptions found in the literature. To this end, our procedures modify the Becker-DeGroot-Marschak mechanism used in previous studies to elicit values. In addition, our procedures supplement commonly used procedures by providing extensive training on the elicitation mechanism before subjects provide WTP and WTA responses. Experiments were conducted using both lotteries and mugs, goods frequently used in endowment effect experiments. Using the modified procedures, we observe no gap between WTA and WTP. Therefore, our results call into question the interpretation of observed gaps as evidence of loss aversion or prospect theory. Further evidence is required before convincing interpretations of observed gaps can be advanced

Models of Financial Markets with Extensive Participation Incentives

We consider models of financial markets in which all parties involved find incentives to participate. Strategies are evaluated directly by their virtual wealths. By tuning the price sensitivity and market impact, a phase diagram with several attractor behaviors resembling those of real markets emerge, reflecting the roles played by the arbitrageurs and trendsetters, and including a phase with irregular price trends and positive sums. The positive-sumness of the players' wealths provides participation incentives for them. Evolution and the bid-ask spread provide mechanisms for the gain in wealth of both the players and market-makers. New players survive in the market if the evolutionary rate is sufficiently slow. We test the applicability of the model on real Hang Seng Index data over 20 years. Comparisons with other models show that our model has a superior average performance when applied to real financial data.Comment: 17 pages, 16 figure

An Experimental Test of Precautionary Bidding

Auctions often involve goods exhibiting a common knowledge ex-post risk that is independent of buyers’ private values or their signals regarding common value components. Esö and White (2004) showed theoretically that ex-post risk leads to precautionary bidding for DARA bidders: Agents reduce their bids by more than their appropriate risk premium. Testing precautionary bidding with data from the field seems almost impossible. We conduct experimental first-price auctions that allow us to directly identify the precautionary premium and find clear evidence for precautionary bidding. Bidders are significantly better off when a risky object rather than an equally valued sure object is auctioned. Our results are robust if we control for potentially confounding decision biases

On the Economic Value and Price-Responsiveness of Ramp-Constrained Storage

The primary concerns of this paper are twofold: to understand the economic value of storage in the presence of ramp constraints and exogenous electricity prices, and to understand the implications of the associated optimal storage management policy on qualitative and quantitative characteristics of storage response to real-time prices. We present an analytic characterization of the optimal policy, along with the associated finite-horizon time-averaged value of storage. We also derive an analytical upperbound on the infinite-horizon time-averaged value of storage. This bound is valid for any achievable realization of prices when the support of the distribution is fixed, and highlights the dependence of the value of storage on ramp constraints and storage capacity. While the value of storage is a non-decreasing function of price volatility, due to the finite ramp rate, the value of storage saturates quickly as the capacity increases, regardless of volatility. To study the implications of the optimal policy, we first present computational experiments that suggest that optimal utilization of storage can, in expectation, induce a considerable amount of price elasticity near the average price, but little or no elasticity far from it. We then present a computational framework for understanding the behavior of storage as a function of price and the amount of stored energy, and for characterization of the buy/sell phase transition region in the price-state plane. Finally, we study the impact of market-based operation of storage on the required reserves, and show that the reserves may need to be expanded to accommodate market-based storage

Distributed Stochastic Market Clearing with High-Penetration Wind Power

Integrating renewable energy into the modern power grid requires risk-cognizant dispatch of resources to account for the stochastic availability of renewables. Toward this goal, day-ahead stochastic market clearing with high-penetration wind energy is pursued in this paper based on the DC optimal power flow (OPF). The objective is to minimize the social cost which consists of conventional generation costs, end-user disutility, as well as a risk measure of the system re-dispatching cost. Capitalizing on the conditional value-at-risk (CVaR), the novel model is able to mitigate the potentially high risk of the recourse actions to compensate wind forecast errors. The resulting convex optimization task is tackled via a distribution-free sample average based approximation to bypass the prohibitively complex high-dimensional integration. Furthermore, to cope with possibly large-scale dispatchable loads, a fast distributed solver is developed with guaranteed convergence using the alternating direction method of multipliers (ADMM). Numerical results tested on a modified benchmark system are reported to corroborate the merits of the novel framework and proposed approaches.Comment: To appear in IEEE Transactions on Power Systems; 12 pages and 9 figure