A criticism of mechanism design theory is that the optimal mechanism designed for one environment can produce drastically different actions, outcomes, and payoffs in a second, even slightly different, environment. In this sense, the theoretically optimal mechanisms usually studied are not “robust.” To study robust mechanisms while maintaining an expected utility maximization approach, we study a multiagent model in which the mechanism must be designed before the environment is as well understood as is usually assumed. The particular model is of an auction setting with binary private values. Our main result is that if the prior belief about the correlation in the agents' values is diffuse enough, the optimal Bayesian-Nash auction must also satisfy dominant strategy incentive constraints. Furthermore, when the optimal auction does provide dominant strategy incentives, it takes one of two forms: (i) if perfect correlation and negative correlation are excluded as possibilities, the auction incorporates all information about the prior belief over the possible correlations, and (ii) if either perfect correlation or negative correlation is a possibility, the auction does not incorporate any correlation information and can be described as a modified Vickrey auction.

ABSTRACT: Performance evaluation with multiple tasks and multiple measures is a favorite indoor sport, replete with coaches, clinics, and Monday morning quarterbacks. Here we tweak the familiar LEN setting to exhibit a modest reluctance to feed it an ever increasing supply of measures.

Our previous attempt resulted in a paper by the same five authors, “Quantum information and accounting information: their salient features and conceptual applications,” published in the July–August 2006 issue of the Journal of Accounting and Public Policy. We now extend the previous paper to examine topological quantum computation, a remarkably innovative approach to decoherence and imprecise quantum computation. In this approach, exotic topological states are created for a natural medium to store and manipulate quantum information globally throughout the entire system. The process is intrinsically protected against imprecision and decoherence. We also explore conceptual, if not technical, applications of topological quantum computation to accounting. This is done by introducing topology’s inherent emphasis of qualitative characteristics to traditional accounting which has been dominated by quantitative characteristics. Here, financial statements’ monetary amounts may be contrasted to internal controls’ error frequencies. Part I of the paper deals with applications of topology to quantum information, after a brief introduction to basic tools. In particular the use of Fibonacci anyon and its powerful results are explained. Part II deals with applications of topology to accounting information. Part III deals with applications of topology to other potential fields.

GAAP mandates a variety of departures from historical cost valuation. We consider a simple model that produces corresponding variety, depending on prevailing regulatory objectives and economic conditions. The model entails entrepreneurial investment in an asset followed by private information about asset value that cannot be communicated. A lemons problem arises in the asset resale market, creating a role for mandated disclosure in the form of audited asset revaluation.

Accounting provides an important source of economic measures, yet consistently falls short of the economist’s conceptual ideal. This shortfall is fodder for economic research, is the result of economic forces, and is the key to making the best possible use of these measures.

ABSTRACT: Performance evaluation with multiple tasks and multiple measures has been explored in a variety of settings. Yet, the efficient design of a portfolio of performance measures remains opaque, largely because of the multidimensional nature of the exercise. Here we focus on the value of adding measures to an existing portfolio of measures in a multi-task LEN style agency model. We offer an algebraic decomposition that projects the gain from a set of additional performance measures into “distance” and “risk” components. The distance component comports with task balance and intensity issues and the risk component with the inevitable risk sharing or compensating wage differential issue.

This article discusses contributions made by different systems of measurement that are used to assess employee productivity on performance. The use of quantum probabilities as a model for the design of measurements sensitive to the relationship between individual employee performance and team performance is considered. Connections between group interaction and differences in the cost of control in the establishment of performance measures are considered. Statistical analysis is used to demonstrate that group monitoring systems can be more effective than individual monitoring systems for teams in the workplace.

INTRODUCTION Measurement often appears far from benign. Close to home we have the systemwide, at times corrosive effects of student evaluations and popular press rankings. Modern medicine exhibits cycles of advances in measurement, e.g., blood chemistry, followed by development of pharmaceuticals designed to improve those measures. Many are the stories of the athlete more interested in personal than team glory. And then there is the unfolding case of earnings, where we encounter developments in financial engineering and organizational arrangements that seem to have no purpose beyond improving the earnings measure. Economically, we are accustomed to measures being simply a source of information, where Bayesian revision in decision making or valuation and optimal contracting in trading arrangements determine the information’s effect on organizational and individual behavior. Although subtleties surface in a multitask setting, and we know ‘‘bad’’ information can drive out ‘‘good’’ information (e.g., Holmstrom and Milgrom 1991), it seems the story is deeper. A commitment to produce a particular set of measures has the potential to affect the organization’s behavior, to affect productivity, in ways that go beyond traditional information effects. Here we put forward and analyze one such setting. Exactly how the act of measurement produces effects beyond mere information effects is an open question. Our approach is to look to the physical sciences, where measurement is far from benign, and to import the natural effect of measurement in that setting to a human organization. We do not claim this

ABSTRACT: We examine the design of asset revaluation policies in settings where a regulator can mandate fair value disclosure in order to mitigate a lemons problem in the asset resale market. The welfare-maximizing policy generally prescribes fair value certification for the lower asset values and (less costly) historical cost reporting for the higher asset values. The potential for voluntary certification can reduce welfare by increasing equilibrium certification costs and promoting underinvestment in socially valuable projects. Thus, a single regulated source of information (mandated disclosure) can be preferable to two sources of information (mandated and voluntary disclosure).