Pareto optimal redistribution, utility interdependence and social optimum

1973 ◽  
Vol 109 (2) ◽  
pp. 337-344
Author(s):  
Karl W. Roskamp
1973 ◽  
Vol 1 (4) ◽  
pp. 359-371 ◽  
Author(s):  
Harold M. Hochman ◽  
James D. Rodgers

Geoffrey Brennan and Cliff Walsh contrast the different transfer patterns of Pareto-optimal redistribution of income resulting from our model (American Economic Review, 1969) and from the model used by von Furstenberg and Mueller (FM). They attempt to show that our model is inconsistent and that, when corrected, would produce a similar transfer pattern to that of FM. We argue that our paper was more general than they allege and that the differences between the transfer patterns in our model and that of FM reflect differences in the concept of horizontal equity and assumptions about utility interdependence, and not any inconsistency on our part.


2011 ◽  
pp. 65-87 ◽  
Author(s):  
A. Rubinstein

The article considers some aspects of the patronized goods theory with respect to efficient and inefficient equilibria. The author analyzes specific features of patronized goods as well as their connection with market failures, and conjectures that they are related to the emergence of Pareto-inefficient Nash equilibria. The key problem is the analysis of the opportunities for transforming inefficient Nash equilibrium into Pareto-optimal Nash equilibrium for patronized goods by modifying the institutional environment. The paper analyzes social motivation for institutional modernization and equilibrium conditions in the generalized Wicksell-Lindahl model for patronized goods. The author also considers some applications of patronized goods theory to social policy issues.


2019 ◽  
pp. 100-107
Author(s):  
A. M. Batkovsky ◽  
A. V. Leonov ◽  
A. Yu. Pronin ◽  
A. V. Fomina

In conditions of limited financial resources of the state, the task of assessing the appropriateness and choosing rational options for the joint use of traditional and new types of high-tech products is topical. The paper proposes a method for substantiating rational options for the joint use of traditional and new products of high-tech products, based on the criteria of their comparative technical and economic assessment, namely, comparing the achieved efficiency and the required cost of performing a fixed set of tasks. The dialectical foundations of the method are presented, in particular, it is established that the law of development of high-tech products fully corresponds to the well-known classical law of «denial of denial». The structure of the method, the order of formation of the set of Pareto-optimal options for the joint use of traditional and new products, as well as the algorithm for choosing a rational option are considered.


2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Maya Diamant ◽  
Shoham Baruch ◽  
Eias Kassem ◽  
Khitam Muhsen ◽  
Dov Samet ◽  
...  

AbstractThe overuse of antibiotics is exacerbating the antibiotic resistance crisis. Since this problem is a classic common-goods dilemma, it naturally lends itself to a game-theoretic analysis. Hence, we designed a model wherein physicians weigh whether antibiotics should be prescribed, given that antibiotic usage depletes its future effectiveness. The physicians’ decisions rely on the probability of a bacterial infection before definitive laboratory results are available. We show that the physicians’ equilibrium decision rule of antibiotic prescription is not socially optimal. However, we prove that discretizing the information provided to physicians can mitigate the gap between their equilibrium decisions and the social optimum of antibiotic prescription. Despite this problem’s complexity, the effectiveness of the discretization solely depends on the type of information available to the physician to determine the nature of infection. This is demonstrated on theoretic distributions and a clinical dataset. Our results provide a game-theory based guide for optimal output of current and future decision support systems of antibiotic prescription.


Author(s):  
Yiguang Gong ◽  
Yunping Liu ◽  
Chuanyang Yin

AbstractEdge computing extends traditional cloud services to the edge of the network, closer to users, and is suitable for network services with low latency requirements. With the rise of edge computing, its security issues have also received increasing attention. In this paper, a novel two-phase cycle algorithm is proposed for effective cyber intrusion detection in edge computing based on a multi-objective genetic algorithm (MOGA) and modified back-propagation neural network (MBPNN), namely TPC-MOGA-MBPNN. In the first phase, the MOGA is employed to build a multi-objective optimization model that tries to find the Pareto optimal parameter set for MBPNN. The Pareto optimal parameter set is applied for simultaneous minimization of the average false positive rate (Avg FPR), mean squared error (MSE) and negative average true positive rate (Avg TPR) in the dataset. In the second phase, some MBPNNs are created based on the parameter set obtained by MOGA and are trained to search for a more optimal parameter set locally. The parameter set obtained in the second phase is used as the input of the first phase, and the training process is repeated until the termination criteria are reached. A benchmark dataset, KDD cup 1999, is used to demonstrate and validate the performance of the proposed approach for intrusion detection. The proposed approach can discover a pool of MBPNN-based solutions. Combining these MBPNN solutions can significantly improve detection performance, and a GA is used to find the optimal MBPNN combination. The results show that the proposed approach achieves an accuracy of 98.81% and a detection rate of 98.23% and outperform most systems of previous works found in the literature. In addition, the proposed approach is a generalized classification approach that is applicable to the problem of any field having multiple conflicting objectives.


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