Characterization Of Optimal Policy Research Articles

The Role of Multiple Pollutants and Pollution Intensities in the Policy Reform of Taxes and Standards

Abstract Countries with varying degrees of pollution intensities, facing increasing global competition and addressing emissions from multiple pollutants may undertake policy reforms inconsistent with cooperative outcomes, where global welfare is higher. Among others, this is because of the incentives to set laxer policy to be more cost competitive. A number of welfare-enhancing and emissions-reducing policy reforms consistent with the cooperative equilibrium, but also consistent with addressing concerns about global competitiveness are derived. The analysis indicates that the nature of multiple pollutants and asymmetries in pollution intensities are key in the design of policy reform and characterization of optimal policy. With complementarity and asymmetry in pollution intensities, laxer taxation and stricter standards are consistent with welfare gains. Laxer taxation arises with large asymmetry in pollution intensities regardless of whether pollutants are complements/substitutes. The policy reform of standards requires both complementarity and asymmetry in pollution intensities. Results are reversed if pollutants are substitutes.

Emission Taxes and Product Differentiation in the Presence of Foreign Firms

Industries characterized by differentiated products are important contributors of greenhouse gases and currently subject to market-based policies such as emission taxes. In the context of developing countries, fears about foreign investment leaving the country are often used as an argument not to address industry emissions through emission taxes. This paper develops a Cournot model with product differentiation in the presence of abatement efforts where host and foreign firms are subject to an emission tax. The analysis indicates that abatement efforts and differences in pollution intensity coefficients across firms may play a significant role in the characterization of optimal policy. The analysis also suggests that the government may opt to encourage foreign, less pollution-intensive firms via higher taxation. Additionally, this paper examines how an optimal emission tax may be adjusted as products become more differentiated; industry emissions may fall/rise as a result of more differentiated products. One important contribution of this paper is that it emphasizes the role of abatement efforts, product differentiation, and differences in pollution intensity coefficients across firms in the characterization of the optimal emission tax.

Discrete-Time Hybrid Decision Processes: The Discounted Case

This paper is a sequel to Kageyama et al. [1], in which a Markov-type hybrid process has been constructed and the corresponding discounted total reward has been characterized by the recursive equation. The objective of this paper is to formulate a hybrid decision process and to give the existence and characterization of optimal policies.

Good news and bad news in two-armed bandits

This note provides a characterization of optimal policies in a class of two-armed bandits that allows for correlated arms. This characterization extends previously known results in the literature. In particular, it implies, under a mild continuity assumption, the optimality of cutoff belief strategies for this class of bandits. Cutoff beliefs are not unique, though.

Characterization of optimal policy for capital replacement models

In this paper we describe the behaviour of a number of replacement models that are used in practice to model replacement decision problems. For clarity of outcome in our analysis, we focus on the following problem: an existing equipment of a certain age and performance performs a necessary function; should we replace this equipment with a new equipment (which performs the same function), and, if so, when? The reasons for replacement of the existing equipment may be numerous, but we focus solely on the economic aspect. In practice, the outcome of an economic replacement modelling exercise, for which the models we describe would be useful, would be expected to influence the actual replacement decision and not necessarily drive it. The decision-maker would bring other technological, social and political factors to bear on the decision. The replacement problem above may be generalized as the consideration of the release of a capital project at some time in the future. The purpose of our analysis is to consider whether the models behave sensibly in general, and are therefore useful in practice, and also to compare and contrast alternative model choices. We essentially look at two replacement decision models: a fixed planning horizon model with a variable number of replacement cycles; and a variable planning horizon model with a fixed number of replacement cycles. These models are also related to the classic ‘economic life’ model. We use R to denote the capital cost of the new equipment, and τ to denote the age of the existing equipment at the start of the planning horizon. The planning horizon is that interval over which we consider the economic consequences of operation and replacement. The current and new equipment perform identical functions. We model age-related costs (operating costs, revenue, resale values) using a function f (t) that models the rate of change of age-related costs with respect to the age of the plant. We call f the cost rate for

H/sup ∞/-0ptimal Control and Related Minimax Design Problems: A Dynamic Game Approach

One of the major concentrated activities of the past decade in control theory has been the development of the so-called control theory, which addresses the issue of worst-case controller design for linear plants subject to unknown disturbances and plant uncertainties. Among the different time-domain approaches to this class of worst-case design problems, the one that uses the framework of dynamic, differential game theory stands out to be the most natural. This is so because the original H-infinity control problem (in its equivalent time-domain formulation) is in fact a minimax optimization problem, and hence a zero-sum game, where the controller can be viewed as the minimizing player and disturbance as the maximizing player. Using this framework, the authors present in this book a complete theory that encompasses continuous-time as well as discrete-time systems, finite as well as infinite horizons, and several different measurement schemes, including closed loop perfect state, delayed perfect state, samples state, closed-loop imperfect state, delayed imperfect state and sampled imperfect state information patterns. They also discuss extensions of the linear theory to nonlinear systems, and derivation of the lower dimensional controller for systems with regularly and singularly perturbed dynamics. This is the second edition of a 1991 book with the same title, which, besides featuring a more streamlined presentation of the results included in the first edition, and at places under more refined conditions, also contains substantial new material, reflecting new developments in the field since 1991. Among these are the nonlinear theory; connections between H-infinity-optimal control and risk sensitive stochastic control problems; H-infinity filtering for linear and nonlinear systems; and robustness considerations in the presence of regular and singular perturbations. Also included are a rather detailed description of the relationship between frequency-and time-domain approaches to robust controller design, and a complete set of results on the existence of value and characterization of optimal policies in finite- and infinite-horizon LQ differential games. The authors believe that the theory is now at a stage where it can easily be incorporated into a second-level graduate course in a control curriculum, that would follow a basic course in linear control theory covering LQ and LQG designs. The framework adopted in this book makes such an ambitious plan possible. For the most part, the only prerequisite for the book is a basic knowledge of linear control theory. No background in differential games, or game theory in general, is required, as the requisite concepts and results have been developed in the book at the appropriate level. The book is written in such a way that makes it possible to follow the theory for the continuous- and discrete-time systems independently (and also in parallel).

A Dynamic Nash Game Model of Oil Market Disruption and Strategic Stockpiling

In this paper we present and analyze a Nash dynamic game model for investigating public and private sector oil inventory policies in unstable world oil markets. Conceptual results about the model include simple, verifiable conditions for uniqueness and stability of solutions, along with characterizations of optimal policies. We also present results and discuss computational issues that arise in determining subgame perfect infinite-horizon equilibria, using a steady-state policy iteration approach.

Convexity and characterization of optimal policies in a dynamic routing problem

An infinite horizon, expected average cost, dynamic routing problem is formulated for a simple failure-prone queueing system, modelled as a continuous time, continuous state controlled stochastic process. We prove that the optimal average cost is independent of the initial state and that the cost-to-go functions of dynamic programming are convex. These results, together with a set of optimality conditions, lead to the conclusion that optimal policies are switching policies, characterized by a set of switching curves (or regions), each curve corresponding to a particular state of the nodes (servers).

Optimal assignments in a markovian queueing system

A generalization of the Hypercube queueing model for exponential queueing systems is presented which allows for distinguishable servers and multiple types of customers. Given costs associated with each server-customer pair, the determination of the assignment policy which minimizes time-averaged costs is formulated as a Markov decision problem. A characterization of optimal policies is obtained and used in an efficient algorithm for determining the optimum. The algorithm combines the method of successive approximations and “Howard's method” in a manner which is particularly applicable to Markov decision problems having large, sparse transition matrices.

Characterization of Optimal Policies in Vector-Valued Markovian Decision Processes

Infinite horizon Markovian decision processes with Rp-valued additive utilities are considered. The optimization criterion, here, is a pseudo-order preference relation induced by a convex cone in Rp. The state space is a countable set, and the action space is a compact metric space. Certain assumptions on the continuity of the reward vector and the transition probability are made. In this setting, an algorithm improving policies with respect to the chosen preference relation is given. A point-to-set mapping is defined, and optimal policies are characterized by fixed points of the mapping which are maximal in the set of all fixed points.

On the Characterization of Optimal Policies in Non‐Stationary Dynamic Programs

On the Characterization of Optimal Policies in Non‐Stationary Dynamic Programs