51 research outputs found

    Bidding Markets

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    The existence of a ‘bidding market’ is commonly cited as a reason to tolerate the creation or maintenance of highly concentrated markets. We discuss three erroneous arguments to that effect: the ‘consultants’ fallacy’ that ‘market power is impossible’, the ‘academics’ fallacy’ that (often) ‘market power does not matter’, and the ‘regulators’ fallacy’ that ‘intervention against pernicious market power is unnecessary’, in markets characterized by auctions or bidding processes. Furthermore we argue that the term ‘bidding market’ as it is widely used in antitrust is unhelpful or misleading. Auctions and bidding processes do have some special features—including their price formation processes, common-values behaviour, and bid-taker power—but the significance of these features has been overemphasized, and they often imply a need for stricter rather than more lenient competition policy.Bidding Markets, Auctions, Antitrust, Competition Policy, Bidding, Market Power, Private Values, Common Values, Anti-trust

    Introduction to Economic Analysis

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    This book presents introductory economics ("principles") material using standard mathematical tools, including calculus. It is designed for a relatively sophisticated undergraduate who has not taken a basic university course in economics. It also contains the standard intermediate microeconomics material and some material that ought to be standard but is not. The book can easily serve as an intermediate microeconomics text. The focus of this book is on the conceptual tools and not on fluff. Most microeconomics texts are mostly fluff and the fluff market is exceedingly over-served by $100+ texts. In contrast, this book reflects the approach actually adopted by the majority of economists for understanding economic activity. There are lots of models and equations and no pictures of economists

    Blockchain-Coordinated Frameworks for Scalable and Secure Supply Chain Networks

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    Supply chains have progressed through time from being limited to a few regional traders to becoming complicated business networks. As a result, supply chain management systems now rely significantly on the digital revolution for the privacy and security of data. Due to key qualities of blockchain, such as transparency, immutability and decentralization, it has recently gained a lot of interest as a way to solve security, privacy and scalability problems in supply chains. However conventional blockchains are not appropriate for supply chain ecosystems because they are computationally costly, have a limited potential to scale and fail to provide trust. Consequently, due to limitations with a lack of trust and coordination, supply chains tend to fail to foster trust among the network’s participants. Assuring data privacy in a supply chain ecosystem is another challenge. If information is being shared with a large number of participants without establishing data privacy, access control risks arise in the network. Protecting data privacy is a concern when sending corporate data, including locations, manufacturing supplies and demand information. The third challenge in supply chain management is scalability, which continues to be a significant barrier to adoption. As the amount of transactions in a supply chain tends to increase along with the number of nodes in a network. So scalability is essential for blockchain adoption in supply chain networks. This thesis seeks to address the challenges of privacy, scalability and trust by providing frameworks for how to effectively combine blockchains with supply chains. This thesis makes four novel contributions. It first develops a blockchain-based framework with Attribute-Based Access Control (ABAC) model to assure data privacy by adopting a distributed framework to enable fine grained, dynamic access control management for supply chain management. To solve the data privacy challenge, AccessChain is developed. This proposed AccessChain model has two types of ledgers in the system: local and global. Local ledgers are used to store business contracts between stakeholders and the ABAC model management, whereas the global ledger is used to record transaction data. AccessChain can enable decentralized, fine-grained and dynamic access control management in SCM when combined with the ABAC model and blockchain technology (BCT). The framework enables a systematic approach that advantages the supply chain, and the experiments yield convincing results. Furthermore, the results of performance monitoring shows that AccessChain’s response time with four local ledgers is acceptable, and therefore it provides significantly greater scalability. Next, a framework for reducing the bullwhip effect (BWE) in SCM is proposed. The framework also focuses on combining data visibility with trust. BWE is first observed in SC and then a blockchain architecture design is used to minimize it. Full sharing of demand data has been shown to help improve the robustness of overall performance in a multiechelon SC environment, especially for BWE mitigation and cumulative cost reduction. It is observed that when it comes to providing access to data, information sharing using a blockchain has some obvious benefits in a supply chain. Furthermore, when data sharing is distributed, parties in the supply chain will have fair access to other parties’ data, even though they are farther downstream. Sharing customer demand is important in a supply chain to enhance decision-making, reduce costs and promote the final end product. This work also explores the ability of BCT as a solution in a distributed ledger approach to create a trust-enhanced environment where trust is established so that stakeholders can share their information effectively. To provide visibility and coordination along with a blockchain consensus process, a new consensus algorithm, namely Reputation-based proof-of cooperation (RPoC), is proposed for blockchain-based SCM, which does not involve validators to solve any mathematical puzzle before storing a new block. The RPoC algorithm is an efficient and scalable consensus algorithm that selects the consensus node dynamically and permits a large number of nodes to participate in the consensus process. The algorithm decreases the workload on individual nodes while increasing consensus performance by allocating the transaction verification process to specific nodes. Through extensive theoretical analyses and experimentation, the suitability of the proposed algorithm is well grounded in terms of scalability and efficiency. The thesis concludes with a blockchain-enabled framework that addresses the issue of preserving privacy and security for an open-bid auction system. This work implements a bid management system in a private BC environment to provide a secure bidding scheme. The novelty of this framework derives from an enhanced approach for integrating BC structures by replacing the original chain structure with a tree structure. Throughout the online world, user privacy is a primary concern, because the electronic environment enables the collection of personal data. Hence a suitable cryptographic protocol for an open-bid auction atop BC is proposed. Here the primary aim is to achieve security and privacy with greater efficiency, which largely depends on the effectiveness of the encryption algorithms used by BC. Essentially this work considers Elliptic Curve Cryptography (ECC) and a dynamic cryptographic accumulator encryption algorithm to enhance security between auctioneer and bidder. The proposed e-bidding scheme and the findings from this study should foster the further growth of BC strategies

    Essays in Natural Resource Economics

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    Allocation decisions in many natural resource markets are governed by mechanisms designed to alleviate information asymmetries and other types of market imperfections. For example, the crew in most commercial fisheries is remunerated via a lay system of payments designed to alleviate a potential team agency problem. The four essays in this dissertation explore the use of mechanisms in natural resource and environmental economics. The first essay examines the lay system of payments in commercial fisheries. Under the lay system, the harvesting crew is remunerated via a share of total vessel revenues less a portion of trip expenditures. The essay has two goals. First, the essay provides an explanation for the lay system as an incentive mechanism to alleviate a potential team agency problem. This explanation of the lay system explains anomalies that are at odds with the theory of pure risk sharing. Second, the essay shows the implications of the lay system for econometric modeling of fisheries and for understanding firm behavior. The second and third essay, examine bidder behavior in auctions for cutting rights of standing timber in British Columbia. The second essay provides an empirical framework for estimating treatment assignment of observations given data on outcomes. The framework is used to explore whether bidder collusion was evident in a data set of nearly 3,000 auctions (over 10,000 individual bids) for cutting rights of standing timber in British Columbia from 1996-2000. The third essay examines the role of ex ante uncertainty over private values and ex post resale opportunities on bidder behavior. The essay extends the theoretical work of Haile (2003) by allowing for risk-averse bidders. The theoretical model is tested by examining both field data and experimental data from the lab. The fourth essay provides a formal model of individual contribution decisions under a tontine mechanism. The essay analyzes the performance of tontines and compares them to another popular fundraising scheme: lotteries. Individual contribution decisions under the optimal tontine, an equivalent valued single-prize lottery, and the voluntary contribution mechanism are compared using a controlled laboratory experiment

    Three Essays on Managing Competitive Bid Procurement.

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    Procurement has emerged as a critical function, yet a challenging topic, since in many firms procurement operations are complex, and laced with misaligned incentives and information asymmetry between buyers and suppliers. This dissertation explores three different contexts that arise from a buyer’s lack of information. The first essay explores the value of cost modeling in competitive bid procurement, to understand if, how and when cost modeling should be deployed. I show that although bid competition sometimes duplicates the information gleaned by cost modeling, the latter can still be beneficial when it helps the buyer set an effective reserve price. Then I analyze how the buyer can gain the most benefit through cost modeling. Specifically, I characterize which supplier(s) to learn about, which portion(s) of the costs to learn, and how deeply and broadly the buyer should learn for general supply base topologies. The second essay studies the problem that a buyer's request for quotes (RFQ) contains an error that triggers re-design and associated supplier windfall profit. Surprisingly, I find that RFQ error encourages suppliers to submit lower bids with anticipation of future windfall profit. I also find that supplier disparity in error-detecting expertise generally hurts the buyer. Furthermore, I propose a "pre-pay" and “error-bounty” approach to stem supplier windfall profit and induce knowledgeable suppliers to divulge the existence of RFQ error. The third essay considers whether a buyer should exclude or include an incumbent supplier in the auction. Excluding the incumbent allows the buyer to set an aggressive reserve price while including the incumbent in the auction drums up competition with one more bidder. I find that the buyer’s decision depends on the incumbent’s and entrants’ cost distributions: When the incumbent’s cost is expected to be substantially different from the entrants’ (either much lower or much higher) and has low uncertainty, excluding the incumbent is the better option; Conversely, when the incumbent’s cost is comparable to the entrants’ and has similar amount of uncertainty, the buyer prefers inviting the incumbent to the auction.PhDBusiness AdministrationUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/102447/1/yinyan_1.pd

    Resource management for virtualized networks

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    Network Virtualization has emerged as a promising approach that can be employed to efficiently enhance the resource management technologies. In this work, the goal is to study how to automate the bandwidth resource management, while deploying a virtual partitioning scheme for the network bandwidth resources. Works that addressed the resource management in Virtual Networks are many, however, each has some limitations. Resource overwhelming, poor bandwidth utilization, low profits, exaggeration, and collusion are types of such sort of limitations. Indeed, the lack of adequate bandwidth allocation schemes encourages resource overwhelming, where one customer may overwhelm the resources that supposed to serve others. Static resource partitioning can resist overwhelming but at the same time it may result in poor bandwidth utilization, which means less profit rates for the Internet Service Providers (ISPs). However, deploying the technology of autonomic management can enhance the resource utilization, and maximize the customers’ satisfaction rates. It also provides the customers with a kind of privilege that should be somehow controlled as customers, always eager to maximize their payoffs, can use such a privilege to cheat. Hence, cheating actions like exaggeration and collusion can be expected. Solving the aforementioned limitations is addressed in this work. In the first part, the work deals with overcoming the problems of low profits, poor utilization, and high blocking ratios of the traditional First Ask First Allocate (FAFA) algorithm. The proposed solution is based on an Autonomic Resource Management Mechanism (ARMM). This solution deploys a smarter allocation algorithm based on the auction mechanism. At this level, to reduce the tendency of exaggeration, the Vickrey-Clarke-Groves (VCG) is proposed to provide a threat model that penalizes the exaggerating customers, based on the inconvenience they cause to others in the system. To resist the collusion, the state-dependent shadow price is calculated, based on the Markov decision theory, to represent a selling price threshold for the bandwidth units at a given state. Part two of the work solves an expanded version of the bandwidth allocation problem, but through a different methodology. In this part, the bandwidth allocation problem is expanded to a bandwidth partitioning problem. Such expansion allows dividing the link’s bandwidth resources based on the provided Quality of Service (QoS) classes, which provides better bandwidth utilization. In order to find the optimal management metrics, the problem is solved through Linear Programming (LP). A dynamic bandwidth partitioning scheme is also proposed to overcome the problems related to the static partitioning schemes, such as the poor bandwidth utilization, which can result in having under-utilized partitions. This dynamic partitioning model is deployed in a periodic manner. Periodic partitioning provides a new way to reduce the reasoning of exaggeration, when compared to the threat model, and eliminates the need of the further computational overhead. The third part of this work proposes a decentralized management scheme to solve aforementioned problems in the context of networks that are managed by Virtual Network Operators (VNOs). Such decentralization allows deploying a higher level of autonomic management, through which, the management responsibilities are distributed over the network nodes, each responsible for managing its outgoing links. Compared to the centralized schemes, such distribution provides higher reliability and easier bandwidth dimensioning. Moreover, it creates a form of two-sided competition framework that allows a double-auction environment among the network players, both customers and node controllers. Such competing environment provides a new way to reduce the exaggeration beside the periodic and threat models mentioned before. More important, it can deliver better utilization rates, lower blocking, and consequently higher profits. Finally, numerical experiments and empirical results are presented to support the proposed solutions, and to provide a comparison with other works from the literature

    Benefits from Private Antitrust Enforcement: Forty Individual Case Studies

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    This Paper presents information about forty of the largest recent successful private antitrust cases. To do this, the paper gathers information about each case, including, inter alia, (1) the amount of money each action recovered for the victims of each alleged antitrust violation, (2) what proportion of the money was recovered from foreign entities, (3) whether government action preceded the private litigation, (4) the attorney\u27s fees awarded to plaintiffs\u27 counsel, (5) on whose behalf money was recovered (direct purchasers, indirect purchasers, or a competitor), and (6) the kind of claim the plaintiffs asserted (rule of reason, per se, or a combination of the two). A separate Study, forthcoming in the University of San Francisco Law Review (available at: Benefits from Private Antitrust Enforcement: An Analysis of Forty Cases), aggregates and analyzes this information. That Study also compares the total monetary amounts paid in all forty cases, as well as from the subset of the forty cases that also resulted in criminal penalties, to the total criminal antitrust fines imposed during the same period by the United States Department of Justice ( DOJ ), and also to the deterrence effects of the prison sentences that resulted from DOJ prosecutions during this period. The overall goal of the project is to take a first step toward providing an empirical basis for assessing whether private enforcement of the antitrust laws serves its intended purposes and is in the public interest. The results of the Study show that private antitrust enforcement helps the economy in many ways. It very significantly compensates victims of illegal corporate behavior, and is almost always the only way they can receive redress. Private enforcement often prevents foreign corporations from keeping the many billions of dollars they illegally obtain from individual and corporate purchasers in the United States. The Study also shows that almost half of the underlying violations were first uncovered by private attorneys, not government enforcers, and that litigation in many other cases had a mixed public/private origin. The evidence also shows that private litigation probably does more to deter antitrust violations than all the fines and incarceration imposed as a result of criminal enforcement by the U.S. Department of Justice. This is one of the most surprising results from our Study. We do not know of any past study that has documented that private enforcement has such a significant deterrence effect as compared to DOJ criminal enforcement

    Counter-IP Conspiracies: Patent Alienability and the Sherman Antitrust Act

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    Anticompetitive collusion by intellectual property owners frequently triggered antitrust enforcement during the twentieth century. An emerging area of litigation and scholarship, however, involves conspiracies by potential licensees of intellectual property to reduce or eliminate opportunities by a property’s holders to profit from it, or even to recoup their investments in creating and protecting it. The danger is that potential licensees will collude with one another to suppress royalties or sale prices. This Article traces the history of such litigation, provides an overview of the scholarly and theoretical arguments against monopsonistic or oligopsonistic collusion against licensors of intellectual property, and summarizes empirical evidence that the prime economic and business-related justification for such collusion, namely the need to reduce patent holdup, is relatively weak. It argues that some decisions not to license intellectual-property rights, or to license them at suppressed rates, may be anticompetitive, particularly if they are the result of a collusive process or serve to maintain or expand market power. Finally, it urges greater attention from a macroeconomic perspective to the plight of inventors and workers in the high-technology and patent-intensive industries. As a preliminary attempt to heighten awareness of the issue, it describes recent allegations that market power on the part of consumers of high-technology patent licenses, and reduced bargaining clout on the part of individual employees and inventors, may be contributing to unemployment and inequality
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