Tax evasion, information reporting, and the regressive bias hypothesis

A robust prediction from the tax evasion literature is that optimal auditing induces a regressive bias in e¤ective tax rates compared to statutory rates. If correct, this will have important distributional consequences. Nevertheless, the regressive bias hypothesis has never been tested empirically. Using a unique data set, we provide evidence in favor of the regressive bias prediction but only when controlling for the tax agency�s use of third-party information in predicting true incomes. In aggregate data, the regressive bias vanishes because of the systematic use of third-party information. These results are obtained both in simple reduced-form regressions and in a data-calibrated state-of-the-art model

Damage Detection of Structural Systems with Noisy Incomplete Input and Response Measurements

A probabilistic approach for damage detection is presented using noisy incomplete input and response measurements that is an extension of a Bayesian system identification approach developed by the authors. This situation may be encountered, for example, during low-level ambient vibrations when a structure is instrumented with accelerometers that measure the input ground motion and structural response at a few locations but the wind excitation is not measured. A substructuring approach is used for the parameterization of the mass and stiffness distributions. Damage is defined to be a reduction of the substructure stiffness parameters compared with those of the undamaged structure. By using the proposed probabilistic methodology, the probability of various damage levels in each substructure can be calculated based on the available data. A four-story benchmark building subjected to wind and ground shaking is considered in order to demonstrate the proposed approach

Activity Specific Knowledge Characteristics in the Internationalization Process

PurposeThe purpose of this paper is to investigate differences in the characteristics of knowledge, which is very important for the internationalization of different business activities. In particular, the focus is on internationalization in emerging markets such as China and India.Design/methodology/approachThe paper presents a framework primarily based on knowledge management theory, which is illustrated in relation to interesting cases of four companies that are global leaders.FindingsAn R&amp;D knowledge gap still exists in China and India. Differences across business activities exist in terms of the characteristics of the knowledge, which is most important for the internationalization in emerging markets within multinational corporations (MNCs). The most important knowledge for the internationalization of R&amp;D activities is more tacit than it is for manufacturing activities and international purchasing activities. The source of the most important knowledge for the internationalization of R&amp;D activities, as well as manufacturing activities, is more likely to be the MNC itself, than when marketing activities or purchasing activities are internationalized to emerging markets.Originality/valueA model is developed that illustrates differences between the most important knowledge for the internationalization of key business activities within MNCs. It is proposed that the technical dimension of tacit knowledge is more easily codified than the cognitive dimension of tacit knowledge. The cognitive dimension of local tacit knowledge is crucial for the internationalization of marketing activities, whereas the technical dimension of tacit R&amp;D knowledge from the home base is crucial for the internationalization of R&amp;D activities.</jats:sec

Transnationalism and Multi-dimensional Flow of Remittance in Cambodia

This journal has been published at different time periods under the following titles: Explorations: A Graduate Student Journal of Southeast Asian Studies, Explorations in Southeast Asian Studies, and The Journal of the Southeast Asian Studies Association