Aggregate Utility Function Research Articles

Asymmetric Horizontal Differentiation under Advertising in a Cournot Duopoly

Horizontal differentiation is generally derived from the aggregate utility function and is assumed to be symmetric. However, empirical work suggests that asymmetric horizontal differentiation can exist in practice. This paper examines the topic of asymmetric horizontal differentiation by allowing a firm’s costly advertising to have a different impact on its own demand function than it does on that of its rival. This leads to the interesting analytical result that advertising that increases the cross-price effect of its rival can lead to an increase in firm profits. This introduces the possibility of a ‘couple’ effect where firm advertising can tilt its own and its rival’s demand functions in different directions. Several competitive advertising ‘couple’ scenarios are explored using numerical simulation.

On the Microfoundation of Linear Oligopoly Demand

Abstract We critically assess the representative consumer with quadratic aggregate utility function which forms the foundation of a well-known class of linear oligopoly demand structures. It is argued that this approach is problematic and redundant. Regarding the latter, we show how the same demand system can be derived directly from a population of heterogeneous buyers for any number of products. Welfare analyses based on aggregate demand is shown to be sensitive to the underlying microfoundation.

Network utility maximisation through particle swarm optimisation

Given a network system with several nodes that are linked together in a certain topology, the network utility maximisation (NUM) problem is concerned with searching for the maximum aggregate utility function of all nodes under the constraint of limited link capacities. This paper proposes the use of a gradient-free, stochastic optimisation approach based on particle swarm optimisation (PSO) method for solving the NUM problem. In contrast to much of the prior solution methods which often assume the concavity of the network's utility function, the proposed PSO approach is capable of solving NUM problems with either concave or nonconcave utility functions. We show through simulation results of solving NUM problems in medium size networks that the optimal solutions obtained by the proposed PSO method indeed correspond to the exact global optima.

CAT Bond Spreads via HARA Utility and Nonparametric Tests

After deriving a new utility-based model for pricing catastrophe (CAT) bonds under hyperbolic absolute risk aversion (HARA), we propose two specification tests that use nonparametric estimation techniques to test simultaneously for all possible misspecifications. Existing pricing models, including our new one, are then estimated and tested using CAT bonds primary market data. The utility-based model we propose not only is well-suited for explaining the risk-return relation observed in the CAT bond market but also delivers the best performance among the tested models. We also provide new empirical evidence that the aggregate utility function of CAT bond investors exhibits decreasing absolute risk aversion.

Aggregation with a mix of indivisible and continuous labor supply decisions

Purpose The purpose of this paper is to explore the problem of non-convex labor supply decision in an economy with both discrete and continuous labor decisions. In contrast to the setup in McGrattan et al. (1997), here each household faces an indivisible labor supply choice in the market sector, while it can choose to work any number of hours in the non-market sector. Design/methodology/approach The authors show how lotteries as in Rogerson (1988) can again be used to convexify consumption sets, and aggregation over individual preferences. Findings With a mix of discrete and continuous labor supply decisions, disutility of non-market work becomes separable from market work, and the elasticity of the latter increases from unity to infinity. Research limitations/implications As a possible venue for future research, the authors plan to feed the derived aggregate utility function above in a sophisticated real-business-cycle model to investigate the effect of those preferences for the transmission of technology and fiscal shocks. Originality/value This is a novel and interesting result in the aggregation literature.

Cat Bond Spreads: A New Model with an Empirical Validation Using Nonparametric Tests

Previous empirical studies on catastrophe (CAT) bond premium calculations rely almost exclusively on actuarial models, and usually compare their accuracy strictly in terms of in-sample t and predictive power. We contribute to this literature by deriving a utility-based specification for pricing CAT bonds under Hyperbolic Absolute Risk Aversion (HARA), and by proposing two specification tests that use nonparametric estimation techniques to test simultaneously for all possible mis-specifications. Various pricing models are then estimated and tested with data from the primary market for CAT bonds. Our results suggest that the utility-based model we propose not only is well-suited for explaining the risk-return relationship observed in the CAT bond market but also delivers the best performance among the tested models. We also provide new empirical evidence that the aggregate utility function of CAT investors exhibits decreasing absolute risk aversion.

Floor and Upside Investing in Retirement without Annuities

I investigate optimal stock/bond asset allocation and consumption decisions using a utility function that is intended to be representative of a retired individual's need for an income floor and desire for upside potential. I do this without using annuities. Breaking with a common assumption that you should become more conservative if you have reached “your number,” the asset allocation to stocks increases if floor consumption is largely satisfied. I discover a bond heavy region that absorbs the impact of downside stock market shocks and protect the income floor. I also discover declining absolute bond holdings when downside risks are small. Careful tuning of the parameters of the aggregate utility function makes it possible to engineer the asset allocation/consumption strategy to meet the retired individual's specific income goals while keeping the consumption floor covered.

Optimized Network Selection Using Aggregate Utility Function in Heterogeneous Wireless Networks

To provide global connectivity with high speed and high quality at any place and any time is now becoming a reality due to the integration and co-ordination of different Radio Access Technologies(RAT) such as Worldwide Interoperability for Microwave Access (WiMAX), Universal mobile Telecommunication Systems (UMTS), Wireless Local Area network (WLAN) and Long Term Evolution (LTE).Such a diversity of networks offers different choices in terms of bandwidth, security, cost, latency and the coverage area for the mobile user. For such a heterogeneous wireless environment, it is important to design an intelligent handover algorithm which selects the optimal target network. The existing works do not consider the interdependence between the criteria and the use of application QoS in weight calculation during network evaluation process. To address this issue, an appropriate multicriteria network selection algorithm based on multiplicative weighted utility function is proposed to provide complete solution for seamless connectivity in heterogeneous environment based on network conditions, application QoS, Mobile Terminal (MT) battery level and user preferences. MATLAB based simulations are conducted to highlight the effectiveness of proposed scheme and simulation results confirm that the proposed scheme selects the best suitable network for both Real-Time (RT) and Non- Real Time (NRT) applications while achieving optimization between QoS, cost and energy consumption. The Cobb-Douglas based user satisfaction degree is also estimated to verify whether the selected network maximizes the end user satisfaction for the offered service.

A Service Broker Model for Cloud based Render Farm Selection

Cloud computing is gaining popularity in the 3D Animation industry for rendering the 3D images. Rendering is an inevitable task in creating the 3d animated scenes. It is a process where the scene files to be animated is read and converted into 3D photorealistic images automatically. Since it is a computationally intensive task, this process consumes the majority of the time taken for 3D images production. As the scene files could be processed in parallel, clusters of computers called render farms can be used to speed up the rendering process. The advantage of using Cloud based render farms is that it is scalable and can be availed on demand. One of the important challenges faced by the 3D studios is the comparison and selection of the cloud based render farm service provider who could satisfy their functional and the non functional Quality of Service (QoS) requirements. In this paper we propose, a frame work for Cloud Service Broker (CSB) responsible for the selection and provision of the cloud based render farm. The Cloud Service Broker matches the functional and the non functional Quality of Service requirements (QoS) of the user with the service offerings of the render farm service providers and helps the user in selecting the right service provider using an aggregate utility function. The CSB also facilitates the process of Service Level Agreement (SLA) negotiation and monitoring by the third party monitoring services.

Exploiting Knowledge Management for Supporting Multi-Band Spectrum Selection in Non-Stationary Environments

This paper proposes a new knowledge management framework for spectrum selection under non-stationary conditions supporting a set of applications with heterogeneous requirements. In this respect, an optimization problem is formulated to maximize an aggregate utility function that captures the suitability of spectrum portions with respect to the various application requirements and a set of preferences for using the different spectrum bands. Motivated by the practical limitations when solving the considered problem directly, an alternative solution is proposed. It exploits a statistical characterization of the environment retained in the knowledge database of the proposed framework. To cope with the non-stationarity of the environment, a reliability tester is proposed to detect relevant changes in radio conditions, and update database statistics accordingly. Then, a knowledge manager exploiting these statistics is developed to monitor the time-varying suitability of spectrum resources. Based on this, a novel spectrum management is proposed to approximate the optimal solution of the considered problem. The results obtained in a realistic digital home reveal that, under stationary conditions, the proposed strategy performs very close to the optimal solution with much less requirements in terms of spectrum reconfiguration and measurement reporting. Furthermore, thanks to the reliability tester support, substantial robustness is shown when interference conditions become non-stationary, thus proving the practicality of the proposed solution.

A Framework for SOFTWARE-AS-A-SERVICE Selection and Provisioning

As cloud computing is increasingly transforming the information technology landscape, organizations and businesses are exhibiting strong interest in Software-as-a-Service (SaaS) offerings that can help them increase business agility and reduce their operational costs. They increasingly demand services that can meet their functional and non-functional requirements. Given the plethora and the variety of SaaS offerings, we propose, in this paper, a framework for SaaS provisioning, which relies on brokered Service Level agreements (SLAs), between service consumers and SaaS providers. The Cloud Service Broker (CSB) helps service consumers find the right SaaS providers that can fulfil their functional and non-functional requirements. The proposed selection algorithm ranks potential SaaS providers by matching their offerings against the requirements of the service consumer using an aggregate utility function. Furthermore, the CSB is in charge of conducting SLA negotiation with selected SaaS providers, on behalf of service consumers, and performing SLA compliance monitoring.

RobP2P: A Robust Architecture for Resource Sharing in Mobile Peer-to-Peer Networks

Peer-to-peer (P2P) systems are constructed to provide resource sharing among interested participants (peers) in a dis- tributed and self-organized fashion. The way P2P networks are formed is critical to the overall system performance due to communications and network maintenance overhead. Mobile environments pose additional challenges on P2P networks due to heterogeneity of nodes, inherent limited resources, dynamic context and wireless network characteris- tics. This paper presents RobP2P, a robust architecture to construct mobile P2P networks and efficiently maintain the network state. RobP2P introduces a novel super-peer selection protocol based on an aggregate utility function that takes into account peers’ capability and context. It also presents an agile scheme through which super-peers can delegate their responsibilities to more powerful and stable joining or existing peers. Our simulation results show that the RobP2P is efficient, less prone to failure, and generates lower overhead traffic, while reliably maintaining the consistency of network state.

Proportionally Quasi-Fair Scheduling for End-to-End Rates in Multi-Hop Wireless Networks

Known an a criterion that solves the trade-off between fairness and efficiency, proportional fairness is well-studied in cellular networks in the Qualcomm High Data Rate System. In multi-hop wireless networks, proportional fairness is solved by maximizing the logarithmic aggregate utility function. However, this approach can deal with instantaneous rates only where long term fairness is to be targeted. In this case, cumulative rates are more suitable. This paper proposes a framework for multi-hop wireless networks to guarantee fairness of cumulative data rates. The framework can be extended to other kinds of fairness such as max-min fairness, and to more complex networks, multi-channel multi-radio wireless networks.

Aggregate Labor Supply

Macroeconomics has made tremendous advances following the introduction of labor supply into the field. Today, it is widely acknowledged that labor supply matters for many key economic issues, particularly for business cycles and tax policy analysis. However, the extent to which labor supply matters for such questions depends on the aggregate labor supply elasticity—that is, the sensitivity of the time allocation between market and nonmarket activities. For several decades, the magnitude of the aggregate labor supply elasticity has been the subject of much debate. In this article, we review the debate and conclude that the elasticity of labor supply of the aggregate household is much higher than the elasticity of the identical households being aggregated. The aggregate household utility function differs from the individuals’ utility functions for the same reason that the aggregate production function differs from the individual firms’ production functions being aggregated. The differences in individual and aggregate supply elasticities are what aggregation theory predicts.

Advanced Demand Side Management for the Future Smart Grid Using Mechanism Design

In the future smart grid, both users and power companies can potentially benefit from the economical and environmental advantages of smart pricing methods to more effectively reflect the fluctuations of the wholesale price into the customer side. In addition, smart pricing can be used to seek social benefits and to implement social objectives. To achieve social objectives, the utility company may need to collect various information about users and their energy consumption behavior, which can be challenging. In this paper, we propose an efficient pricing method to tackle this problem. We assume that each user is equipped with an energy consumption controller (ECC) as part of its smart meter. All smart meters are connected to not only the power grid but also a communication infrastructure. This allows two-way communication among smart meters and the utility company. We analytically model each user's preferences and energy consumption patterns in form of a utility function. Based on this model, we propose a Vickrey-Clarke-Groves (VCG) mechanism which aims to maximize the social welfare, i.e., the aggregate utility functions of all users minus the total energy cost. Our design requires that each user provides some information about its energy demand. In return, the energy provider will determine each user's electricity bill payment. Finally, we verify some important properties of our proposed VCG mechanism for demand side management such as efficiency, user truthfulness, and nonnegative transfer. Simulation results confirm that the proposed pricing method can benefit both users and utility companies.

International Law and Domestic Political Coalitions: The Grand Theory of Compliance with International Law

Abstract Compliance with international law is always dependent upon a contemporaneous domestic political decision to comply. This Article articulates the importance of the interdependence between home-state domestic politics and foreign-state domestic politics in determining compliance. International legal commitments allow the formation of domestic coalitions between those who will benefit from their own state's compliance with the international legal rule, and those who will benefit from other states' compliance with the international legal This Article extends the rationalist approach to compliance with international law to the domestic politics of the target state. The theory developed in this Article builds on established approaches to international relations in the political science literature, in particular the liberal theory of international relations associated with Andrew Moravcsik, the two-level game theory approach associated with Robert Putnam, and the second image reversed approach associated with Peter Gourevitch. This Article extends these approaches (i) from broader international relations to international law and (ii) from adherence to compliance. The model advanced in this Article allows the formalization and contextualization of a variety of factors that up to now have been viewed in isolation as explanatory variables in the decision to comply. Policymakers can use this model as an analytical template by which to assess whether their counterparties would comply with any undertakings they may make. [A] prudent ruler cannot keep his word, nor should he, where such fidelity would damage him, and when the reasons that made him promise are no longer relevant. Niccolo Machiavelli1 Applied to relations between nations, [the] bureaucratic politics model directs attention to intra-national games, the overlap of which constitutes international relations. Graham Allison2 I. INTRODUCTION If international law is to be a useful tool of international cooperation, we must know more about its social effects: its ability to cause states to take action that they would not have taken, or to refrain from taking action that they would have taken but for the existence of the international law Greater understanding of the effects of international law will allow more efficient allocation of diplomatic and analytical resources toward international law that will resolve international problems and will reduce uncertainty that may result in under-use of international law as a tool of cooperation. However, greater understanding will require greater particularity of analysis. This Article proposes a social scientific theory of compliance with international law that focuses attention on the domestic politics underlying a state's decision to comply with a particular international legal It develops further a preference -based model that describes the internal mechanisms of state compliance with international law, building on work in political science by Dai, Gourevitch, Moravcsik, Iida, Milner, Mo, Putnam, and others who have been instrumental in developing a two-level game-based theory of international cooperation. That political science literature focuses on cooperation in the form of adherence to a rule. Except for the work by Dai, however, the literature does not examine the subsequent issue of compliance with the The two extensions of this work made in this Article - from broader international relations to international law, and from adherence to compliance - help to illuminate the problem of compliance, and provide a social scientific, positive approach to compliance. Most prior social scientific theories of compliance with international law take the structure of the state's aggregate utility function as a given and evaluate the circumstances under which the threat of retaliation, or perhaps the fear of reduced reputation or reduced opportunities for future cooperation, would provide incentives for compliance. …

Max-utility subcarrier allocation for heterogeneous services in wireless OFDM system

In future wireless network, one user will require multiple homogeneous or heterogeneous services simultaneously. Then, the scheduling algorithm is not only responsible for assigning a resource block to different users but also sharing the assigned resource block among multiple services for one user. Most of the traditional scheduling algorithms are designed to serve one service per user, and cannot be applied directly to this scenario because of the fairness criterion. This article focuses on adaptive resource allocation for multiple services per user at the downlink of orthogonal frequency division multiplexing (OFDM) based system. This article addresses this integrative resource scheduling problem based on utility function. First, the optimal algorithm for dynamic subcarrier allocation and share is deduced for homogeneous best-effort service system. Then the algorithm is extended to heterogeneous services system by classifying the delay sensitive service according to the head-of-line packet delay. The design goal is to maximize aggregate utility function to exploit multiuser diversity gain to the greatest extent even as guaranteeing quality of service (QoS) for delay sensitive service.

The Kullback-Leibler Divergence and Nonnegative Matrices

This correspondence establishes an interesting connection between the Kullback-Leibler divergence and the Perron root of nonnegative irreducible matrices. In the second part of the correspondence, we apply these results to the power control problem in wireless communications networks to show a fundamental tradeoff between fairness and efficiency. A power vector is said to be efficient if it maximizes the overall network efficiency expressed in terms of an aggregate network utility function parameterized by some weight vector. For two widely used examples of utility functions, the correspondence identifies the unique weight vector for which a power vector is both efficient and max-min fair in the sense that each communication link has the same quality-of-service. These results also give rise to new saddle point characterizations of the Perron root

Multi‐Criteria Analysis of Input Use in Agriculture

In this paper we present a methodology for the analysis of input use in the agricultural sector. The novelty of the theoretical model described here is that it has been developed considering a multi‐criteria environment. Thus, the optimal input use condition is determined by evaluating “multi‐attribute utility” and “multi‐attribute marginal utility”. We show how the approach adopted in this paper is a generalisation of the single‐attribute expected utility theory. The theoretical model developed is thereafter implemented in an empirical application that studies water for irrigation use as a particular case. The results show how multi‐attribute utility functions elicited for a sample of 52 irrigators explain differences in irrigation water use in relatively homogeneous agricultural systems, albeit exhibiting dissimilar partial utility functions for water use. We conclude that these differences come from the dissimilar weights that farmers attach to each attribute in the aggregate utility function.

Pricing and Congestion Management in a Network With Heterogeneous Users

This note presents an economic model for a communication network with utility-maximizing elastic users who adapt to congestion by adjusting their flows. Users are heterogeneous with respect to both the utility they attach to different levels of flow and their sensitivity to delay. Following Kelly et al. (1998), we introduce dynamic rate-control algorithms, based on the users' utility functions and delay sensitivities, as well as tolls charged by the system, and examine the behavior of these algorithms. We show that allowing heterogeneity with respect to delay sensitivity introduces a fundamental nonconvexity into the congestion-cost functions. As a result, there are often multiple stationary points of the aggregate net utility function. Hence, marginal-cost pricing-equating users' marginal utilities to their marginal costs-may identify a local maximum or even a saddle point, rather than a global maximum. Moreover, the dynamic rate-control algorithm may converge to a local rather than global maximum, depending on the starting point. We present examples with different user utility functions, including some in which the only interior stationary point is a saddlepoint which is dominated by all the single-user optimal allocations. We also consider variants of the dynamic algorithm and their performance in a network with heterogeneous users. Our results suggest that applying a rate-control algorithm such as TCP (Transmission Control Protocol), even when augmented by some form of implicit or explicit pricing, may have unexpected and perhaps undesirable effects on the allocation of flows among heterogeneous delay-sensitive users.