optimal policy
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Author(s):  
Eren Gürer

AbstractThis study explores the implications of rising markups for optimal Mirrleesian income and profit taxation. Using a stylized model with two individuals, the main forces shaping welfare-optimal policies are analytically characterized. Although a higher profit tax has redistributive benefits, it adversely affects market competition, leading to a greater equilibrium cost-of-living. Rising markups directly contribute to a decline in optimal marginal taxes on labor income. The optimal policy response to higher markups includes increasingly relying on the profit tax to fund redistribution. Declining optimal marginal income taxes assists the redistributive function of the profit tax by contributing to the expansion of the profit tax base. This response alone considerably increases the equilibrium cost-of-living. Nevertheless, a majority of the individuals become better off with the optimal policy. If it is not possible to tax profits optimally, due, for example, to profit shifting, increasing redistribution via income taxes is not optimal; every individual is worse off relative to the scenario with optimal profit taxation.


Sensors ◽  
2021 ◽  
Vol 21 (24) ◽  
pp. 8306
Author(s):  
Sima Barzegar ◽  
Marc Ruiz ◽  
Luis Velasco

As the dynamicity of the traffic increases, the need for self-network operation becomes more evident. One of the solutions that might bring cost savings to network operators is the dynamic capacity management of large packet flows, especially in the context of packet over optical networks. Machine Learning, particularly Reinforcement Learning, seems to be an enabler for autonomicity as a result of its inherent capacity to learn from experience. However, precisely because of that, RL methods might not be able to provide the required performance (e.g., delay, packet loss, and capacity overprovisioning) when managing the capacity of packet flows, until they learn the optimal policy. In view of that, we propose a management lifecycle with three phases: (i) a self-tuned threshold-based approach operating just after the packet flow is set up and until enough data on the traffic characteristics are available; (ii) an RL operation based on models pre-trained with a generic traffic profile; and (iii) an RL operation with models trained for real traffic. Exhaustive simulation results confirm the poor performance of RL algorithms until the optimal policy is learnt and when traffic characteristics change over time, which prevents deploying such methods in operators’ networks. In contrast, the proposed lifecycle outperforms benchmarking approaches, achieving noticeable performance from the beginning of operation while showing robustness against traffic changes.


Author(s):  
K. Swetha

Abstract: In the Proposed work we are going to assimilate two important process called TEF and imperfect debugging in software systems for analyzing FDP and FCP. Byapplying the tools called debuggers we are going to identify the failures and going to correct them in order to attain the high quality reliability. As we know, testingeffort function is predicted during this time by allocating the resources which influences considerably only for the fault identification rate and also for the correction of such faults. Additionally, new faults may be included for evaluating as the feedback. In this technique, first it is proposed to demonstrate for the inclusion of TEF and fault introduction into FDP and later develop FCP as delayedFDP with a proper effort for correction. The FCP as well FCP as paired specific models which are extracted based on the basis of types of assumptions of introducing fault introduction as well as correction effort. In addition, the optimal policy of software releasefor different criteria with examples was also presentedin this work. Keywords: FDP, FCP, TEF, Fault


Entropy ◽  
2021 ◽  
Vol 23 (12) ◽  
pp. 1572
Author(s):  
Yutao Chen ◽  
Anthony Ephremides

In this paper, we study a slotted-time system where a base station needs to update multiple users at the same time. Due to the limited resources, only part of the users can be updated in each time slot. We consider the problem of minimizing the Age of Incorrect Information (AoII) when imperfect Channel State Information (CSI) is available. Leveraging the notion of the Markov Decision Process (MDP), we obtain the structural properties of the optimal policy. By introducing a relaxed version of the original problem, we develop the Whittle’s index policy under a simple condition. However, indexability is required to ensure the existence of Whittle’s index. To avoid indexability, we develop Indexed priority policy based on the optimal policy for the relaxed problem. Finally, numerical results are laid out to showcase the application of the derived structural properties and highlight the performance of the developed scheduling policies.


2021 ◽  
Author(s):  
Xiaodong Li ◽  
Ruixin Su ◽  
Yilin Chen ◽  
Tianming Yang

We often postpone or even avoid making decisions when we feel uncertain. Uncertainty estimation is not an afterthought of decision making but a dynamic process that accompanies decision making in parallel and affects decision making. To study concurrent uncertainty estimation during decision making, we adapted the classic random-dots motion direction discrimination task to allow a reaction-time measure of uncertainty responses. Subjects were asked to judge whether a patch of random dots was moving left or right. In addition, they could seek assistance by choosing to look at a second stimulus that had the same direction but high coherence any time during the task. The task allows us to measure the reaction time of both the perceptual decisions and the uncertainty responses. The subjects were more likely to choose the uncertainty response when the motion coherence was low, while their reaction times of the uncertainty responses showed individual variations. To account for the subjects' behavior, we created an optimal policy decision model in which decisions are based on the value functions computed from the accumulated evidence using a drift-diffusion process. Model simulations captured key features of the subjects' choices, reaction times, and proportions of uncertainty responses. Varying model parameters explained individual variations in the subjects and the correlations between decision accuracy, proportions of uncertainty responses, and reaction times at the individual level. Our model links perceptual decisions and value-based decisions and indicates that concurrent uncertainty estimation may be based on comparisons between values of uncertainty responses and perceptual decisions, both of which may be derived from the same evidence accumulation process during decision making. It provides a theoretical framework for future investigations, including the ones that aim at the underlying neural mechanism.


Ekonomika ◽  
2021 ◽  
Vol 100 (2) ◽  
pp. 101-132
Author(s):  
Metin Tetik ◽  
Reşat Ceylan

The problem of coordination between policymakers seems to have created fundamental problems related to economic and social costs, targeted inflation, potential growth, and a high budget deficit. To resolve these problems in this framework, it is important to see the results of the interaction between policymakers and to propose an optimal policy strategy. In this study, the interactions between monetary and fiscal policymakers are examined game theoretically within the framework of the New Keynesian model. The strategic interaction between these policymakers is assessed using the DSGE (Dynamic Stochastic General Equilibrium) model for a small open economy. From this point of view, the interaction between policymakers is assessed within the framework of hypothetical scenarios. The optimal monetary and fiscal policies for a small open economy are derived from the leader-follower mechanism solution known as the Stackelberg solution. Optimal Stackelberg policy rules derived for a small open economy contribute to the literature of economics. The performance of the game theoretically derived optimal policy rules is evaluated through dynamic simulation within the framework of counterfactual experiments. The parameters developed for the model are calibrated for the Turkish economy. Dynamic simulation of the models, the impulse response functions, and the social loss analysis shows that the optimal policy mix for the Turkish economy is when the monetary policymaker is the leader, and the fiscal policymaker is the follower.


2021 ◽  
pp. 69-85
Author(s):  
Robin Becker ◽  
Barry Dwolatzky ◽  
Elias Karakitsos ◽  
Berc Rustem

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