Optimal index rules for single resource allocation to stochastic dynamic competitors

In this paper we present a generic Markov decision process model of optimal single resource allocation to a collection of stochastic dynamic competitors. The main goal is to identify sufficient conditions under which this problem is optimally solved by an index rule. The main focus is on the frozen-if-not-allocated assumption, which is notoriously found in problems including the multi-armed bandit problem, tax problem, Klimov network, job sequencing, object search and detection. The problem is approached by a Lagrangian relaxation and decomposed into a collection of normalized parametric single-competitor subproblems, which are then optimally solved by the well-known Gittins index. We show that the problem is equivalent to solving a time sequence of its Lagrangian relaxations. We further show that our approach gives insights on sufficient conditions for optimality of index rules in restless problems (in which the frozen-if-not-allocated assumption is dropped) with single resource; this paper is the first to prove such conditions

Evidence from surveys of price-setting managers: Policy lessons and directions for ongoing research

Understanding the determinants of individual price setting behaviour is crucial for the formulation of monetary policy, especially in an economy experiencing ongoing structural change. These behavioural mechanisms play a fundamental role in influencing the characteristics of aggregate inflation and in determining how monetary policy affects inflation and real economic activity. Thus, this line of research can strengthen the conceptual foundations of general equilibrium models with sticky prices, enabling these models to provide monetary policymakers with an increasingly useful framework for interpreting and forecasting the evolution of the macroeconomy. In this paper, we introduce the Walrasian model as a benchmark for comparison, and we discuss the extent to which recent micro evidence on firms’ price setting behavior provides significant support for some basic elements of the New Keynesian perspective. We then proceed to analyze the implications of the micro evidence in distinguishing between competing theories of price stickiness. Finally, the paper concludes with some brief reflections about the lessons for monetary policy.

Consumer-Directed Health Care: Can Consumers Look After Themselves?

In health care systems today, including those of Switzerland and the United States, participants do not necessarily see the big picture of lifetime health costs and quality of life, and in many systems consumers and providers lack the incentives to manage preventative and chronic care to minimize lifetime private and social health costs. Resource allocation problems induced by asymmetric information and misaligned incentives are exacerbated if consumers fail to have the acuity or perspective needed to make choices consistent with their self-interest when faced with complex health care choices with ambiguous future consequences. This paper examines rationality of consumers’ health perceptions and choices using as a natural experiment the recent introduction in the United States of a highly subsidized market for prescription drug insurance, and draws lessons from this experiment on the practicality of “Consumer Directed Health Care” as an approach to achieving efficient allocation of health care resources by confronting consumers with the full marginal costs of the services they use

Foraging under conditions of short-term exploitative competition: The case of stock traders

Theory purports that animal foraging choices evolve to maximize returns, such as net energy intake. Empirical research in both human and nonhuman animals reveals that individuals often attend to the foraging choices of their competitors while making their own foraging choices. Due to the complications of gathering field data or constructing experiments, however, broad facts relating theoretically optimal and empirically realized foraging choices are only now emerging. Here, we analyze foraging choices of a cohort of professional day traders who must choose between trading the same stock multiple times in a row---patch exploitation---or switching to a different stock---patch exploration---with potentially higher returns. We measure the difference between a trader's resource intake and the competitors' expected intake within a short period of time---a difference we call short-term comparative returns. We find that traders' choices can be explained by foraging heuristics that maximize their daily short-term comparative returns. However, we find no one-best relationship between different trading choices and net income intake. This suggests that traders' choices can be short-term win oriented and, paradoxically, maybe maladaptive for absolute market returns

Dynamic order acceptance and capacity planning within a multi-project environment.

We present a tactical decision model for order acceptance and capacity planning that maximizes the expected profits from accepted orders, allowing for regular as well as nonregular capacity.We apply stochastic dynamic programming to determine a profit threshold for the accept/reject decision as well as an optimal capacity allocation for accepted projects, both with an eye on maximizing the expected revenues within the problem horizon.We derive a number of managerial insights based on an analysis of the influence of project and environmental characteristics on optimal project selectionand capacity usage.Capacity planning; multi-project; Order acceptance; Stochastic dynamic programming;

A genetic algorithm for the design of a fuzzy controller for active queue management

Active queue management (AQM) policies are those policies of router queue management that allow for the detection of network congestion, the notification of such occurrences to the hosts on the network borders, and the adoption of a suitable control policy. This paper proposes the adoption of a fuzzy proportional integral (FPI) controller as an active queue manager for Internet routers. The analytical design of the proposed FPI controller is carried out in analogy with a proportional integral (PI) controller, which recently has been proposed for AQM. A genetic algorithm is proposed for tuning of the FPI controller parameters with respect to optimal disturbance rejection. In the paper the FPI controller design metodology is described and the results of the comparison with random early detection (RED), tail drop, and PI controller are presented

Abstracts of Invited and Selected Papers and Organized Symposia, WAEA Annual Meetings, San Francisco, California, July 6-8, 2005

Teaching/Communication/Extension/Profession,