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A multivariate measurement error model AXB is considered. The errors in [A,B] are rowwise independent, but within each row the errors may be correlated. Some of the columns are observed without errors, and in addition the error covariance matrices may differ from row to row. The total covariance structure of the errors is supposed to be known up to a scalar factor. The fully weighted total least squares estimator of X is studied, which in the case of normal errors coincides with the maximum likelihood estimator. We give mild conditions for weak and strong consistency of the estimator, when the number of rows in A increases. The results generalize the conditions of Gallo given for a univariate homoscedastic model (where B is a vector), and extend the conditions of Gleser given for the multivariate homoscedastic model. We derive the objective function for the estimator and propose an iteratively reweighted numerical procedure.Acknowledgements.A. Kukush is supported by a postdoctoral research fellowship of the Belgian office for Scientific, Technical and Cultural Affairs, promoting Scientific and Technical Collaboration with Central and Eastern Europe. S. Van Huffel is a full professor with the Katholieke Universiteit Leuven. This paper presents research results of the Belgian Programme on Interuniversity Poles of Attraction (IUAP Phase V-22), initiated by the Belgian State, Prime Ministers Office-Federal Office for Scientific, Technical and Cultural Affairs, of the Concerted Research Action (GOA) projects of the Flemish Government MEFISTO-666 (Mathematical Engineering for Information and Communication Systems Technology), of the IDO/99/03 project (K.U. Leuven) Predictive computer models for medical classification problems using patient data and expert knowledge, of the FWO projects G.0200.00, G.0078.01 and G.0270.02. The scientific responsibility is assumed by its authors. The authors would like to thank Maria Luisa Rastello and Amedeo Premoli for bringing the EW-TLS problem to their attention. The authors are grateful to two anonymous referees for the valuable comments. 相似文献
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In this study we explore attribute differences between U.S. GAAP and IFRS earnings. Our study is motivated by the ongoing harmonization process in accounting standard setting as well as by recent convergence projects by the FASB and the IASB. We test two market-based earnings attributes, i.e., value relevance and timeliness, as well as two accounting-based earnings attributes, i.e., predictability and accrual quality. These attributes are tested for German New Market firms as they are allowed to choose between IFRS and U.S. GAAP for financial reporting purposes. Overall, we find that U.S. GAAP and IFRS only differ with regard to predictive ability. The fact that U.S. GAAP accounting information outperforms IFRS also holds after controlling for differences in firm characteristics, such as size, leverage and the audit firm. However, our results also seem to suggest that these differences are not fully valued by investors, as we do not observe significant and consistent differences for the value-relevance attribute. 相似文献
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We test whether the amount and/or quality of financial statement information affects the financial structure of small and medium-sized enterprises (SMEs). Belgian SMEs are used, because there are important differences in disclosure and audit requirements among them. Consistent with the traditional view that asymmetric or incomplete information restricts access to external funds, our results indicate that both the amount and quality of financial statement information are positively related to SME leverage. In addition, we find that leverage is positively related to asset structure, growth (prospects) and median industry leverage, and negatively related to firm age and profitability. 相似文献
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