The thesis investigates a number of auction formats both theoretically and empirically. The effect of different auction rules on the final price and on bidder valuations is analyzed. Results from an experimental sale of real goods, testing revenue equivalence of the open and sealed-bid second-price auction do not conform to theoretical predictions: the open auction leading to significantly lower prices than the sealed-bid auction. It turns out that the open auction format allows bidders to satisfy a tendency to "stick together" with their valuations. The empirical results motivate a dynamic bidding model of interdependent valuations, bidders being uncertain about their valuations and learning from the exit-prices of their rivals. Furthermore, bidding behavior on the Internet is investigated in the hard close and the automatically extended auction. Late bidding is shown to be a rational strategy in the hard close auction, but not in the automatically extended auction. Theoretical results show that the expected final price and seller revenue is lower in the hard close auction than in the automatically extended auction, where prestige-concerns can lead to an explosive final price. Moreover, Yahoo auction data confirms the strong presence of late bidding in the hard-close auction and the seller's preference for the automatically extended auction. (author´s abstract)

We experimentally study the effects of allotment - the division of an item into homogeneous units - in independent private value auctions. We compare a single-item, first-price auction with two equivalent treatments with allotment: a two-unit discriminatory auction and two simultaneous single-unit first-price auctions. We find that allotment mitigates overbidding, with this effect being stronger in the discriminatory auction. In the allotment treatments, we observe large and persistent bid spreading. Across treatments, the discriminatory auction is the least efficient and generates the lowest revenue.

This Master’s thesis deals about strategy for Improving Auction of Properties in RS Gavlas Company. The theoretical part is concerned with an auction theory and a contemporary legislation. The practical part examines Czech auction market, an auction process, customer relationship management implementation and legislative problems with the aim to find new possibilities of use for company RS Gavlas.

In a deregulated electricity market, auction serves as a primary pricing tool in various segments of the market including day-ahead, real time, ancillary services markets, and Financial Transmission Rights (FTRs) market. Deregulated power markets around the world use different auction strategies that exist in the literature, since very little comparative guidelines exist as to the relative merits of these strategies. In this thesis, a computational methodology and its solution framework are developed to evaluate the impact of an auction strategy on the equilibrium prices in a constrained network with multiple generators at nodes, and where transactions are settled using the optimal power flow (OPF) program. The methodology is tested on a power market represented by a sample 12-bus IEEE network available in the MATPOWER software, which is reconfigured to allow multiple generators to supply power at a bus. The network is used as a platform to comprehensively assess the performance of uniform price auction, discriminatory auction, and second-price uniform auction. Auction rules are used to update generator costs, which are then introduced into the OPF program for obtaining optimal price and quantity allocations. This Auction-OPF procedure is embedded within a game theoretic model that obtains the equilibrium bidding strategies and the corresponding prices and quantities for the network. A detailed comparison of the auction mechanisms is carried out using different measures of performance such as revenue, average prices, and quantity weighted average prices. The comparison shows that there is, perhaps, an appreciable difference among the auction mechanisms. However, to statistically confirm the impact of auction choices, a mixed level factorial experiment is designed with auction strategy, network load, and congestion as three different factors and a closeness measure (defined as the difference between average total revenue and the average total cost of generators in the network per hour) as the responsible variable. An analysis of variance conducted on the experimental outcomes indicates that the load level and the auction strategy significantly affect the network performance. The presence market power under the auction strategies is examined through two well known indices, Herfindahl-Hirschmann Index (HHI) and Lerners Index. It is concluded from the HHI values that all three auction strategies allow the market to be moderately competitive. The Lerners index values show that, while discriminatory auction results in highest bid markup, second price uniform auction induces bidding at or close to the marginal cost.

No description available.

Doctor of Philosophy / Department of Electrical and Computer Engineering / Sanjoy Das / The future energy grid is expected to operate in a decentralized fashion as a network of autonomous microgrids that are coordinated by a Distribution System Operator (DSO), which should allocate energy to them in an efficient manner. Each microgrid operating in either islanded or grid-connected mode may be considered to manage its own resources. This can take place through auctions with individual units of the microgrid as the agents. This research proposes efficient auction mechanisms for the energy grid, with is-landed and connected microgrids. The microgrid level auction is carried out by means of an intermediate agent called an aggregator. The individual consumer and producer units are modeled as selfish agents. With the microgrid in islanded mode, two aggregator-level auction classes are analyzed: (i) price-heterogeneous, and (ii) price homogeneous. Under the price heterogeneity paradigm, this research extends earlier work on the well-known, single-sided Kelly mechanism to double auctions. As in Kelly auctions, the proposed algorithm implements the bidding without using any agent level private infor-mation (i.e. generation capacity and utility functions). The proposed auction is shown to be an efficient mechanism that maximizes the social welfare, i.e. the sum of the utilities of all the agents. Furthermore, the research considers the situation where a subset of agents act as a coalition to redistribute the allocated energy and price using any other specific fairness criterion. The price homogeneous double auction algorithm proposed in this research ad-dresses the problem of price-anticipation, where each agent tries to influence the equilibri-um price of energy by placing strategic bids. As a result of this behavior, the auction’s efficiency is lowered. This research proposes a novel approach that is implemented by the aggregator, called virtual bidding, where the efficiency can be asymptotically maximized, even in the presence of price anticipatory bidders. Next, an auction mechanism for the energy grid, with multiple connected mi-crogrids is considered. A globally efficient bi-level auction algorithm is proposed. At the upper-level, the algorithm takes into account physical grid constraints in allocating energy to the microgrids. It is implemented by the DSO as a linear objective quadratic constraint problem that allows price heterogeneity across the aggregators. In parallel, each aggrega-tor implements its own lower-level price homogeneous auction with virtual bidding. The research concludes with a preliminary study on extending the DSO level auc-tion to multi-period day-ahead scheduling. It takes into account storage units and conven-tional generators that are present in the grid by formulating the auction as a mixed inte-ger linear programming problem.

Master of Agribusiness / Department of Agricultural Economics / Kevin Gwinner / Purple Wave, Inc. has five major auction categories: Real Estate; Business Liquidation; Heavy Equipment (Agricultural and Construction); State Surplus; and Personal Property). Although Purple Wave is rapidly expanding in all categories its current focus is on increasing its real estate sales category. Selling real estate via the auction method is the fastest growing sector of the auction industry. The auction process provides a time-defined result, usually 60 to 90 days from contract signing to closing. The process also establishes a true market value established by the public. I have been tasked with evaluating our current real estate marketing methods. I am to determine the best way to allocate marketing funds to attract the most viable, competitive, well funded, and aggressive real estate bidders. The economic rationale of this issue is the ability to market real estate for higher sale prices. The cost of this issue cannot be measured in terms of a direct expense. The issue is how the company could best spend the marketing funds they receive to ensure the auction will reach the maximum price for the property. Purple Wave is paid on a percent of the sale price. The customer and company have everything to gain from a higher sale price since both will receive a larger profit. Purple Wave would like this issue to be solved with the development of a marketing menu. The real estate teams can use this new menu to show a potential customer how their marketing funds will be used to gain them the maximum amount of advertising exposure. The format can also show sellers how we plan to invest the marketing funds in specific promotional areas.

The purpose of this thesis is to analyze the international tea trade. The first part of this thesis covers the major producers and consumers of tea trade. The second part of the thesis covers different methods on how to trade such as trades done through auctions and new ways of trading such as forward prices as well as direct prices also known as direct sales. The third part of the thesis covers perspectives and new trends of tea trading.

In this dissertation, I develop a framework to investigate the implications of Affirmative Action in college admissions on both study effort choice and college placement outcomes for high school students. I model the college admissions process as a Bayesian game where heterogeneous students compete for seats at colleges and universities of varying prestige. There is an allocation mechanism which maps each student's achieved test score into a seat at some college. A colorblind mechanism ignores race, while Affirmative Action mechanisms may give preferential treatment to minorities in a variety of ways. The particular form of the mechanism determines how students' study effort is linked with their payoff, playing a key roll in shaping behavior. I use the model to evaluate the ability of a given college admission policy to promote academic achievement and to minimize racial academic gaps--namely, the achievement gap and the college enrollment gap. On the basis of these criteria, I derive a qualitative comparison of three canonical classes of college admissions policies: color-blind admissions, quotas, and admission preferences. I also perform an empirical policy analysis of Affirmative Action (AA) in US college admissions, using data from 1996 on American colleges, freshman admissions, and entrance test scores to measure actual AA practices in the American college market. Minority college applicants in the United States effectively benefit from a 9% inflation of their SAT scores, as well as a small fixed bonus of approximately 34 SAT points. I also estimate distributions over student heterogeneity and perform a series of counterfactual policy experiments. This procedure shows that AA practices in the US significantly improve college placement outcomes for minorities, at the cost of discouraging achievement by the most and least talented students. The analysis also indicates ways in which AA could be re-designed in order to better achieve its objectives. As it turns out, a quota system produces a substantial improvement relative to either the current system or a color-blind system. However, quotas are illegal in the US and cannot be implemented as such. Nevertheless, I propose a variation on the AA policy already in place that is outcome-equivalent to a quota.

Increasingly used in online auctions, buyout prices allow bidders to instantly purchase the item listed. We distinguish two types: a temporary buyout option disappears if a bid above the reserve price is made; a permanent one remains throughout the auction or until it is exercised. In a model featuring time-sensitive bidders with uniform valuations and Poisson arrivals but endogenous bidding times, we focus on finding temporary and permanent buyout prices maximizing the seller's discounted revenue, and examine the relative benefit of using each type of option in various environments. We characterize equilibrium bidder strategies in both cases and then solve the problem of maximizing seller's utility by simulation. Our numerical experiments suggest that buyout options may significantly increase a seller’s revenue. Additionally, while a temporary buyout option promotes early bidding, a permanent option gives an incentive to the bidders to bid late, thus leading to concentrated bids near the end of the auction. / Singapore-MIT Alliance (SMA)