Sequential pivotal mechanisms for public project problems

It is well-known that for several natural decision problems no budget balanced Groves mechanisms exist. This has motivated recent research on designing variants of feasible Groves mechanisms (termed as `redistribution of VCG (Vickrey-Clarke-Groves) payments') that generate reduced deficit. With this in mind, we study sequential mechanisms and consider optimal strategies that could reduce the deficit resulting under the simultaneous mechanism. We show that such strategies exist for the sequential pivotal mechanism of the well-known public project problem. We also exhibit an optimal strategy with the property that a maximal social welfare is generated when each player follows it. Finally, we show that these strategies can be achieved by an implementation in Nash equilibrium.Comment: 19 pages. The version without the appendix will appear in the Proc. 2nd International Symposium on Algorithmic Game Theory, 200

A System for Distributed Mechanisms: Design, Implementation and Applications

We describe here a structured system for distributed mechanism design appropriate for both Intranet and Internet applications. In our approach the players dynamically form a network in which they know neither their neighbours nor the size of the network and interact to jointly take decisions. The only assumption concerning the underlying communication layer is that for each pair of processes there is a path of neighbours connecting them. This allows us to deal with arbitrary network topologies. We also discuss the implementation of this system which consists of a sequence of layers. The lower layers deal with the operations that implement the basic primitives of distributed computing, namely low level communication and distributed termination, while the upper layers use these primitives to implement high level communication among players, including broadcasting and multicasting, and distributed decision making. This yields a highly flexible distributed system whose specific applications are realized as instances of its top layer. This design is implemented in Java. The system supports at various levels fault-tolerance and includes a provision for distributed policing the purpose of which is to exclude `dishonest' players. Also, it can be used for repeated creation of dynamically formed networks of players interested in a joint decision making implemented by means of a tax-based mechanism. We illustrate its flexibility by discussing a number of implemented examples.Comment: 36 pages; revised and expanded versio

Supply Side Optimisation in Online Display Advertising

On the Internet there are publishers (the supply side) who provide free contents (e.g., news) and services (e.g., email) to attract users. Publishers get paid by selling ad displaying opportunities (i.e., impressions) to advertisers. Advertisers then sell products to users who are converted by ads. Better supply side revenue allows more free content and services to be created, thus, benefiting the entire online advertising ecosystem. This thesis addresses several optimisation problems for the supply side. When a publisher creates an ad-supported website, he needs to decide the percentage of ads first. The thesis reports a large-scale empirical study of Internet ad density over past seven years, then presents a model that includes many factors, especially the competition among similar publishers, and gives an optimal dynamic ad density that generates the maximum revenue over time. This study also unveils the tragedy of the commons in online advertising where users' attention has been overgrazed which results in a global sub-optimum. After deciding the ad density, the publisher retrieves ads from various sources, including contracts, ad networks, and ad exchanges. This forms an exploration-exploitation problem when ad sources are typically unknown before trail. This problem is modelled using Partially Observable Markov Decision Process (POMDP), and the exploration efficiency is increased by utilising the correlation of ads. The proposed method reports 23.4% better than the best performing baseline in the real-world data based experiments. Since some ad networks allow (or expect) an input of keywords, the thesis also presents an adaptive keyword extraction system using BM25F algorithm and the multi-armed bandits model. This system has been tested by a domain service provider in crowdsourcing based experiments. If the publisher selects a Real-Time Bidding (RTB) ad source, he can use reserve price to manipulate auctions for better payoff. This thesis proposes a simplified game model that considers the competition between seller and buyer to be one-shot instead of repeated and gives heuristics that can be easily implemented. The model has been evaluated in a production environment and reported 12.3% average increase of revenue. The documentation of a prototype system for reserve price optimisation is also presented in the appendix of the thesis

Stochastic Mechanisms for Truthfulness and Budget Balance in Computational Social Choice

In this thesis, we examine stochastic techniques for overcoming game theoretic and computational issues in the collective decision making process of self-interested individuals. In particular, we examine truthful, stochastic mechanisms, for settings with a strong budget balance constraint (i.e. there is no net flow of money into or away from the agents). Building on past results in AI and computational social choice, we characterise affine-maximising social choice functions that are implementable in truthful mechanisms for the setting of heterogeneous item allocation with unit demand agents. We further provide a characterisation of affine maximisers with the strong budget balance constraint. These mechanisms reveal impossibility results and poor worst-case performance that motivates us to examine stochastic solutions. To adequately compare stochastic mechanisms, we introduce and discuss measures that capture the behaviour of stochastic mechanisms, based on techniques used in stochastic algorithm design. When applied to deterministic mechanisms, these measures correspond directly to existing deterministic measures. While these approaches have more general applicability, in this work we assess mechanisms based on overall agent utility (efficiency and social surplus ratio) as well as fairness (envy and envy-freeness). We observe that mechanisms can (and typically must) achieve truthfulness and strong budget balance using one of two techniques: labelling a subset of agents as ``auctioneers'' who cannot affect the outcome, but collect any surplus; and partitioning agents into disjoint groups, such that each partition solves a subproblem of the overall decision making process. Worst-case analysis of random-auctioneer and random-partition stochastic mechanisms show large improvements over deterministic mechanisms for heterogeneous item allocation. In addition to this allocation problem, we apply our techniques to envy-freeness in the room assignment-rent division problem, for which no truthful deterministic mechanism is possible. We show how stochastic mechanisms give an improved probability of envy-freeness and low expected level of envy for a truthful mechanism. The random-auctioneer technique also improves the worst-case performance of the public good (or public project) problem. Communication and computational complexity are two other important concerns of computational social choice. Both the random-auctioneer and random-partition approaches offer a flexible trade-off between low complexity of the mechanism, and high overall outcome quality measured, for example, by total agent utility. They enable truthful and feasible solutions to be incrementally improved on as the mechanism receives more information and is allowed more processing time. The majority of our results are based on optimising worst-case performance, since this provides guarantees on how a mechanism will perform, regardless of the agents that use it. To complement these results, we perform empirical, average-case analyses on our mechanisms. Finally, while strong budget balance is a fixed constraint in our particular social choice problems, we show empirically that this can improve the overall utility of agents compared to a utility-maximising assignment that requires a budget imbalanced mechanism

Insolvency risk determinants and capital regulation effect on conventional and Islamic banks of Pakistan

In the wake of several recent bank collapses following the 2008 global financial crisis, insolvency risk, previously understudied, emerges as one of the key risks in the banking sector. Hence, this study aims to fulfill this gap by investigating insolvency risk ( measured by Z-SCORE) and its dependency on asset quality (nonperforming loans (NPL), provision for nonperforming loans (PNPL)), income structure (IATA, IITA, FBTA), macroeconomic factors (GDP growth, inflation (INF), Interest (INT) and Corruption (CUR). Capital regulation (CAR) is incorporated in the research model to assess its moderating effect on the relationships between those independent variables and insolvency risk. 161 conventional banks and 35 observations from Islamic banks of Pakistan were analyzed from 2007 to 2015 period. The data were collected from the several sources such as Annual report of banks, Economic Surveys of Pakistan, World Bank database and Transparency International reports. Random Effect, Common Effect model and Hierarchical Regression were performed to identify the determinants of insolvency risk and the moderating effect of CAR on the banks. The results show that NPL, IITA, FBTA, GDP, INF and CUR were found significant with insolvency risk in conventional banks, while CAR moderated NPL, PNPL and INF with insolvency risk. For Islamic banks, GDP was negatively whilst CUR was positively related to insolvency risk. Both were significant. In contrast to conventional banks, CAR strengthened NPL, PNPL, IATA, IITA and FBTA relationship with the Z-SCORE. The findings of CAR effect on the relationship between asset quality, income structure and macroeconomic factors with insolvency risk were mixed in conventional and Islamic banks of Pakistan. The mixed results imply that policy makers and practitioners should develop different prudential regulations and risk management strategies to conventional and Islamic banks in order to mitigate insolvency risk, hence increase the sustainable growth of Pakistani banks

A CONJOINT ANALYSIS STUDY OF PREFERENCES AND PURCHASING BEHAVIOR OF POTENTIAL ADOPTERS OF THE BUREAU OF LAND MANAGEMENT WILD HORSES

This study uses conjoint analysis to examine the preferences of buyers for Bureau of Land Management (BLM) wild horses based on physical attributes of wild horses and individual characteristics of the buyers. Generalized ordered logit models and multinomial logit models are used to study the impact of the buyers’ demographic characteristics such as age, gender, knowledge about wild horse care, and number of wild horses previously adopted on physical attributes of the horses such as color, age, height, training status, temperament, conformation, and unique markings. Using a choice experiment, taken together, these attributes determine buyer’s preferences for a wild horse. This study reveals that characteristics of buyers have significant effects on their preferences for wild horses. Their gender, age, knowledge about wild horse care, and the number of horses previously adopted influence the importance that buyers place on physical attributes of a wild horse in their decision to purchase a wild horse