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OECD Principles (oecd + principle)

Distribution by Scientific Domains

Business, Economics, Finance and Accounting	80%

Selected Abstracts

Corporate Governance in the Russian Federation: the relevance of the OECD Principles on shareholder rights and equitable treatment

CORPORATE GOVERNANCE, Issue 2 2001
Fianna Jesover
Despite progress in developing extensive legislation and regulations, there is still a long way to go before the standards of corporate governance in Russia will instil widespread confidence in investors. The emphasis is now on their implementation and enforcement by the state and private sector institutions. Transparent, equitable rules and predictable enforcement mechanisms are necessary to make the Russian economy attractive to both domestic and foreign investors, and enhance public confidence in the overall reform process. This paper uses the first two chapters of the OECD Principles of Corporate Governance on shareholder rights and their equitable treatment and looks through their prism at the Russian corporate governance condition. [source]

Do Investors Really Value Corporate Governance?

JOURNAL OF INTERNATIONAL FINANCIAL MANAGEMENT & ACCOUNTING, Issue 2 2007
Evidence from the Hong Kong Market
To examine the relation between corporate governance and firm value, we develop an instrument to assess the corporate governance practices of listed companies in Hong Kong. Based on the Revised OECD Principles of Corporate Governance (OECD) and the Code of Best Practices (HKEx), we construct a corporate governance index (CGI) for Hong Kong listed companies. Unlike measures used in other studies, the CGI score reflects the presence of good corporate governance practices as well as variation in the quality of corporate governance practices. Empirical evidence shows that a company's market valuation is positively related to its overall CGI score, a composite measure of a firm's corporate governance practices. We also find that the transparency component of the CGI score drives the relation with market valuation. In summary, this study provides supporting evidence for the notion that, in Hong Kong, good corporate governance practices are consistent with value maximization. [source]

GIQAR position paper on ,Archiving and Good Laboratory Practice',

QUALITY ASSURANCE JOURNAL, Issue 4 2005
M. M. Brunetti
Abstract Archiving of documents and specimens generated during a non-clinical laboratory study is a basic Good Laboratory Practice (GLP) requirement. The records and materials that should be archived as well as the characteristics and the organisation of archive facilities are addressed in the OECD Series on Principles of Good Laboratory Practice No. 1 (OECD Principles of Good Laboratory Practice (as revised in 1997) [1]. However, in recent years, questions concerning archiving have been raised and the need for a more detailed guidance on this matter has become evident The aim of the Society for Applied Pharmacological Sciences/Italian Group of Quality Assurance in Research (SSFA/GIQAR) working group on ,Archiving according to GLP' was to issue a position paper, present it for discussion in an ad hoc round table with representatives of the Italian GLP monitoring authority to promote common standards and to provide additional recommendations on storage and retention of records. Copyright © 2005 John Wiley & Sons, Ltd. [source]

Principles of QSAR models validation: internal and external

MOLECULAR INFORMATICS, Issue 5 2007
Paola Gramatica
Abstract The recent REACH Policy of the European Union has led to scientists and regulators to focus their attention on establishing general validation principles for QSAR models in the context of chemical regulation (previously known as the Setubal, nowadays, the OECD principles). This paper gives a brief analysis of some principles: unambiguous algorithm, Applicability Domain (AD), and statistical validation. Some concerns related to QSAR algorithm reproducibility and an example of a fast check of the applicability domain for MLR models are presented. Common myths and misconceptions related to popular techniques for verifying internal predictivity, particularly for MLR models (for instance cross-validation, bootstrap), are commented on and compared with commonly used statistical techniques for external validation. The differences in the two validating approaches are highlighted, and evidence is presented that only models that have been validated externally, after their internal validation, can be considered reliable and applicable for both external prediction and regulatory purposes. [source]