To Preference via Entrenchment

We introduce a simple generalization of Gardenfors and Makinson's epistemic entrenchment called partial entrenchment. We show that preferential inference can be generated as the sceptical counterpart of an inference mechanism defined directly on partial entrenchment.Comment: 16 page

Who's minding the store? motivating and monitoring hired managers at small, closely held firms: the case of commercial banks

We test whether the gains from hiring an outside manager exceed the principal-agent costs of owner-manager separation at 266 small, closely held U.S. commercial banks. Our results suggest that hiring an outside manager can improve a bank's profit efficiency, but that these gains depend on aligning the hired managers with owners via managerial shareholdings. We find that over-utilizing this control mechanism results in entrenchment, while under-utilization is costly in terms of foregone profits. This study provides a relatively unfettered test of mitigating principal-agent costs, because these small banks cannot rely on market forces or blocks of outside investors to monitor managers.Small business ; Banks and banking - Costs ; Bank management

Variability, negative evidence, and the acquisition of verb argument constructions

We present a hierarchical Bayesian framework for modeling the acquisition of verb argument constructions. It embodies a domain-general approach to learning higher-level knowledge in the form of inductive constraints (or overhypotheses), and has been used to explain other aspects of language development such as the shape bias in learning object names. Here, we demonstrate that the same model captures several phenomena in the acquisition of verb constructions. Our model, like adults in a series of artificial language learning experiments, makes inferences about the distributional statistics of verbs on several levels of abstraction simultaneously. It also produces the qualitative learning patterns displayed by children over the time course of acquisition. These results suggest that the patterns of generalization observed in both children and adults could emerge from basic assumptions about the nature of learning. They also provide an example of a broad class of computational approaches that can resolve Baker's Paradox

The Role of Self-Regulation in Corporate Governance

This paper assesses the effectiveness of self-regulation to promote investor interests. TheNetherlands provides an excellent opportunity to gather such evidence for two reasons. First,characteristics of the Dutch corporate governance structure have made it the recent focus ofattention by the European Union, the International Monetary Fund and countries (e.g., Korea)when deliberating issues of corporate governance. Second, during the period 1996-1998, aprivate sector initiative was undertaken to promote change in the balance of power betweenmanagement and investors. Not surprisingly, the United States Securities and ExchangeCommission has closely followed the Dutch "experiment" in self-regulation. We begin byidentifying corporate governance characteristics that are linked to firm value. We thencompare corporate governance characteristics and the relation between firm value and thesecharacteristics before and after the private sector initiative. We find that therecommendations of the private sector initiative had no substantive effect on corporategovernance characteristics or their relationship with firm value. Using event study techniqueswe document the market's skepticism about the successful evolution of corporate governancepractices in the Netherlands through self-regulation. The one exception to this generalconclusion is the market for new listings. Overall, our results confirm the importance ofshareholder voting rights, and who controls these rights, when considering the design of asuccessful self-regulation process.corporate governance;law and economics;financial economics;International economics

Acquiring and processing verb argument structure : distributional learning in a miniature language

Adult knowledge of a language involves correctly balancing lexically-based and more language-general patterns. For example, verb argument structures may sometimes readily generalize to new verbs, yet with particular verbs may resist generalization. From the perspective of acquisition, this creates significant learnability problems, with some researchers claiming a crucial role for verb semantics in the determination of when generalization may and may not occur. Similarly, there has been debate regarding how verb-specific and more generalized constraints interact in sentence processing and on the role of semantics in this process. The current work explores these issues using artificial language learning. In three experiments using languages without semantic cues to verb distribution, we demonstrate that learners can acquire both verb-specific and verb-general patterns, based on distributional information in the linguistic input regarding each of the verbs as well as across the language as a whole. As with natural languages, these factors are shown to affect production, judgments and real-time processing. We demonstrate that learners apply a rational procedure in determining their usage of these different input statistics and conclude by suggesting that a Bayesian perspective on statistical learning may be an appropriate framework for capturing our findings