Simple Bidding Research Articles

An auction story: How simple bids struggle with uncertainty

Abstract Short-term electricity markets are key to an efficient production by generation units. We develop a two-period model to assess different bidding formats to determine for each bidding format the optimal bidding strategy of competitive generators facing price-uncertainty. We compare the results for simple bidding, block bidding and multi-part bidding. We find that even under optimal simple and block bidding, generators face the risk of ex-post suboptimal solutions, whereas in multi-part bidding these do not occur. This points to efficiency gains of multi-part bidding in the presence of uncertainty in electricity markets.

An Auction Story: How Simple Bids Struggle with Uncertainty

Short-term electricity markets are key to an efficient production by generation units. We develop a two-period model to assess different bidding formats to determine for each bidding format the optimal bidding strategy of competitive generators facing price-uncertainty. We compare the results for simple bidding, block bidding and multi-part bidding and find that even under optimal simple and block bidding generators face the risk of ex-post suboptimal solutions, whereas in multi-part bidding these do not occur. This points to efficiency gains of multi-part bidding in the presence of uncertainty in electricity markets.

One man, one bid

We compare two mechanisms to implement a simple binary choice, e.g. adopt one of two proposals. We show that when neither alternative is ex ante preferred, simple majority voting cannot implement the first best outcome. We introduce a simple bidding mechanism where votes can be bought at a quadratic cost and voters receive rebates equal to the average of others' payments. This mechanism is budget-balanced, individually rational, and fully efficient in the limit. Moreover, the mechanism redistributes from those that gain from the outcome to those that lose and everyone is better off under bidding compared to voting. We test the two mechanisms in the lab using an environment with “moderate” and “extremist” voters. The observed efficiency losses under voting are close to theoretical predictions and significantly larger than under bidding. Because of redistribution, the efficiency gain from bidding benefits mostly the moderate voters.

Frictions in Internet Auctions with Many Traders: A Counterexample

Peters and Severinov (2006) (PS henceforth) characterize a perfect Bayesian equilibrium (PBE) in a competing auctions environment, where all buyers are linked to all the sellers. PS characterize a PBE using a simple bidding rule, whereby buyers select in which auction to bid. In this note we show that when buyers are linked with a subset of the sellers (i.e. when there are search frictions), the PS bidding rule is no longer guaranteed to be efficient nor a PBE of the competing auctions game of PS. Our results indicate that researchers should be cautious when using the PS bidding rule to make inference about the behavior of buyers and sellers in a market where frictions are present such as eBay.

Bidding with limited statistical knowledge in online auctions

We consider online auctions from the point of view of a single bidder who has an average budget constraint. By modeling the rest of the bidders through a probability distribution (often referred to as the mean-field approximation), we develop a simple bidding strategy which can be implemented without any statistical knowledge of bids, valuations, and query arrival processes. The key idea is to use stochastic approximation techniques to automatically track long-term averages.

The Advanced Bidding Strategy for Power Generators Based on Reinforcement Learning

Facing the competition in the maturing electricity markets, the power producers have to devise innovative bidding strategies to maximize profits while balancing the costs. In this article a new method for supply bid design based on reinforcement learning of agents is proposed for a thermal power producer. Through their bidding strategies, the producers are following the composite objective function of maximizing profits while maintaining the utilization factor. The performance indicators, which include profit of each unit and its utilization factor, are presented in learning and non-learning scenarios for the Slovenian power system. The results show that the agents that use the reinforcement learning bidding strategy consistently outperform those that use simple non-learning bidding on the electricity market.

Connection establishment protocol based on mutual selection by users and network providers

This paper proposes a new connection establishment protocol involving several competing network providers in a multimedia telecommunications environment. This connection establishment protocol, which is based on the concept of open competitive bidding, enables mutual selection by users and network providers. By employing this proposed protocol, both network providers and users can pursue their own objectives according to their own bidding and awarding strategies. In this paper, a simple bidding strategy for network providers is presented, and the effectiveness of this strategy is evaluated by means of computer simulation. It is shown that each network provider can improve its profit by adopting this strategy. In this paper, an example of utility functions for users is presented, and the effectiveness of the mechanism to select a network provider is also evaluated by means of computer simulation. Each user can improve his/her utility by selecting an appropriate network provider based on this utility function.

Willingness to pay: a valid and reliable measure of health state preference?

The development of methods to measure willingness to pay (WTP) has renewed interest in cost-benefit analysis (CBA) for the economic evaluation of health care programs. The authors studied the construct validity and test-retest reliability of WTP as a measure of health state preferences in a survey of 102 persons (mean age 62 years; 54% male) who had chronic lung disease (forced expiratory volume < 70%). Interview measurements included self-reported symptoms, the oxygen-cost diagram for dyspnea, Short-Form 36 for general health status, rating scale and standard gamble for value and utility of current health state relative to death and healthy lung functioning, and WTP for a hypothetical intervention offering a 99% chance of healthy lung functioning and a 1% chance of death. WTP was elicited by a simple bidding game. To test for starting-point bias, the respondents were randomly assigned to one of five starting bids. All health status and preference measurements except WTP (controlling for income) showed significant (p < 0.05) difference between disease-severity groups (mild/moderate/severe). WTP was significantly (p = 0.01) associated with household income, but other health status and preference measure were not. The measure most highly correlated with WTP was standard gamble (r = -0.46). There was no association between starting bid and mean WTP adjusted for income and health status. The test-retest reliability of WTP was acceptable (r = 0.66) but lower than that for the standard gamble (r = 0.82).(ABSTRACT TRUNCATED AT 250 WORDS)

The Possibility of Efficient Mechanisms for Trading an Indivisible Object

We study a trading problem in which the seller of an indivisible object races at least two potential buyers. Each trader′s valuation is privately known and regarded by the others as an independent random variable. We assume that the highest possible buyers′ valuation is greater, by an arbitrarily small amount, than the seller′s highest possible valuation. We show that for a family of distributions forming an open set in the space of probability distributions, there exist individually rational, ex post efficient, Bayesian mechanisms for trading the object. In addition, we show that any such mechanism is equivalent to a simple bidding game. Journal of Economic Literature Classification Numbers: D82, C72.

A Bidding Simulation for Training Estimators

A simulation for training estimators and managers is described. The game simulates a bidding situation in the construction industry, with the participants split into teams which bid against each other for government contracts. The contracts are differentiated in terms of workload implications and location, and the teams are encouraged to use discriminating bidding strategies. The cost estimates provided include substantial uncertainty, and the teams can purchase more accurate estimates as well as buying competitive information. As a result of playing the game, participants appreciated the importance of expenditure on estimates, keeping good records, and using simple bidding models.

A Bidding Simulation for Training Estimators

A simulation for training estimators and managers is described. The game simulates a bidding situation in the construction industry, with the participants split into teams which bid against each other for government contracts. The contracts are differentiated in terms of workload implications and location, and the teams are encouraged to use discriminating bidding strategies. The cost estimates provided include substantial uncertainty, and the teams can purchase more accurate estimates as well as buying competitive information. As a result of playing the game, participants appreciated the importance of expenditure on estimates, keeping good records, and using simple bidding models.