199 resultados para Maury


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Mode of access: Internet.

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This paper examines the impact of a regime shift on the valuation of politically powerful oligarch firms. Focusing on the Yeltsin-Putin regime shift in Russia, we find that the valuations of outside shareholders claims are significantly higher under the Putin regime than under the Yeltsin regime after controlling for industry and time effects. The findings suggest that the increasing cost of extracting private benefits outweigh the reduction in the value of political connections following the political regime change. The results are also consistent with changes in the risk of state expropriation. Our results show that effects driven by the political regime change complement the traditional view stating that increased ownership concentration improved the performance of Russian oligarch firms.

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“Corporate governance deals with the ways in which suppliers of finance to firms assure themselves of getting a return on their investment” (Shleifer and Vishny (1997, p. 737). According to La Porta et al. (1999), research in corporate finance relevant for most countries should focus on the incentives and capabilities of controlling shareholders to treat themselves preferentially at the expense of minority shareholders. Accordingly, this thesis sets out to answer a number of research questions regarding the role of large shareholders in public firms that have received little attention in the literature so far. A common theme in the essays stems from the costs and benefits of individual large-block owners and the role of control contestability from the perspective of outside minority shareholders. The first essay empirically examines whether there are systematic performance differences between family controlled and nonfamily controlled firms in Western Europe. In contrast to the widely held view that family control penalizes firm value, the essay shows that publicly traded family firms have higher performance than comparable firms. In the second essay, we present both theoretical and empirical analysis on the effects of control contestability on firm valuation. Consistent with the theoretical model, the empirical results show that minority shareholders benefit from a more contestable control structure. The third essay explores the effects of individual large-block owners on top management turnover and board appointments in Finnish listed firms. The results indicate that firm performance is an important determinant for management and board restructurings. For certain types of turnover decisions the corporate governance structure influences the performance / turnover sensitivity. In the fourth essay, we investigate the relation between the governance structure and dividend policy in Finnish listed firms. We find evidence in support of the outcome agency model of dividends stating that lower agency conflicts should be associated with higher dividend payouts.

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Computing has recently reached an inflection point with the introduction of multicore processors. On-chip thread-level parallelism is doubling approximately every other year. Concurrency lends itself naturally to allowing a program to trade performance for power savings by regulating the number of active cores; however, in several domains, users are unwilling to sacrifice performance to save power. We present a prediction model for identifying energy-efficient operating points of concurrency in well-tuned multithreaded scientific applications and a runtime system that uses live program analysis to optimize applications dynamically. We describe a dynamic phase-aware performance prediction model that combines multivariate regression techniques with runtime analysis of data collected from hardware event counters to locate optimal operating points of concurrency. Using our model, we develop a prediction-driven phase-aware runtime optimization scheme that throttles concurrency so that power consumption can be reduced and performance can be set at the knee of the scalability curve of each program phase. The use of prediction reduces the overhead of searching the optimization space while achieving near-optimal performance and power savings. A thorough evaluation of our approach shows a reduction in power consumption of 10.8 percent, simultaneous with an improvement in performance of 17.9 percent, resulting in energy savings of 26.7 percent.