The taxation of multinationals: Firm level evidence for Belgium.

This paper provides empirical evidence of a more favorable tax treatment for foreign multinationals compared to similar domestic firms in a small open economy. Using treatment effects to control for self-selection of foreign firms into low tax firms, we find that foreign multinationals have substantially lower effective tax rates compared to domestic firms. In our estimations we also control for firm size, sector membership and business-cycle effects. A simple theoretical framework is used to explain our empirical findings and rests on the notion that multinational firms are in a better position to bargain for lower taxes with governments as a result of their 'footloose' nature and outside location options.Belgium; Corporate taxation; Domestic; Economy; Effective tax rates; Effects; Firm level data; Firm size; Firms; Framework; Multinational firms; Multinationals; Open; Options; Sector; Self-selection; Size; Tax rates;

EPR spectrum via entangled states for an Exchange-Coupled Dimer of Single-Molecule Magnets

Multi-high-frequency electron paramagnetic resonance(EPR) spectrum for a supermolecular dimer $[ Mn_4]_2$ of single-molecule magnets recently reported [S. Hill, R. S. Edwards, N. Aliaga-Alcalde and G. Christou(HEAC), Science 302, 1015 (2003)] is studied in terms of the perturbation method in which the high-order corrections to the level splittings of degenerate states are included. It is shown that the corresponding eigenvectors are composed of entangled states of two molecules. The EPR-peak positions are calculated in terms of the eigenstates at various frequencies. From the best fit of theoretical level splittings with the measured values we obtain the anisotropy constant and exchange coupling which are in agreement with the corresponding values of experimental observation. Our study confirms the prediction of HEAC that the two $Mn_4$ units within the dimer are coupled quantum mechanically by the antiferromagnetic exchange interaction and the supermolecular dimer behaviors in analogy with artificially fabricated quantum dots.Comment: 16 pages,2 figures, 2 table

Modelling spatial weight matrices and lags in spatial panel models

Although each variable in a spatial econometric model can have its own spatial weight matrix, practitioners generally adopt one common pre-specified spatial weight matrix for all of them. This thesis breaks this practice for commonly used spatial econometric models with controls for fixed effects in space and time and different panel data settings, using both pre-specified and parameterized spatial weight matrices. The proposed quasi-maximum likelihood estimators of the parameters of these models are proven to be identified, consistent, and asymptotically normal. Three results in this thesis stand out. First, spatial autoregressive errors tend to go together with a sparse matrix and spatial moving average errors with a dense matrix. Second, indirect spillover effects, the focus of many empirical studies, can be severely biased when one common pre-specified spatial weight matrix is used. Third, identification problems that plagued the empirical literature trying to estimate general nesting spatial models are diminished if the spatial weight matrices are parameterized

Playing cards with Cézanne : how the contemporary artists of China copy and recreate

textMy dissertation investigates the concepts and techniques of “copying” and appropriation in contemporary Chinese art, which, despite its phenomenal growth, has seldom been credited as original. Critics either condemn the Chinese artists’ willingness to appropriate from others as a lack of individuality, or declare it as a peculiarly “Chinese” quality. This paper, instead, argues that the Chinese artists deliberately adopt such “copying” as a visual strategy, in order to reexamine the traditions they “borrowed”, to reflect on their own cultural status in the modern world, and to challenge the conventional concept of originality--namely, to show that originality is not created by irreducible individuality or mystified inspiration, but by the author’s choice as well as manipulation of contexts. This strategy, I argue, is essential to the proper evaluation and interpretation of contemporary Chinese artworks. The first two chapters of my dissertation focus on laying out the context from which this art grows. I review how the ideas, styles and institutional structures of western modern art were imitated, questioned and redefined by the Chinese artists, from 1978 to the present; I then examine the conceptual complexity of originality and “copying” in the theories of modernism, postmodernism, postcolonialism and in traditional Chinese art. The next two chapters focus on, respectively, calligraphy and photography in contemporary Chinese art, both of which contain the paradox between originality and “copying” in their very nature. The works of four artists, Xu Bing, Qiu Zhijie, Hong Hao and Zhao Bandi, are discussed in details. Xu's site-specific reproduction of “pseudo characters” manage to engage its targeted audiences, psychologically and physically; Qiu's obsessive yet futile copying of a canon of calligraphy returns the act of writing to its essence--a physical pursuit of one's spiritual state of being; Hong's photographic emulation of an ancient masterpiece suggests that painting may excel photography in its ability to portray a grand cityscape; Zhao’s simulacrum of pop culture paradigms enables him to evade political censorship, and to have an substantial yet ironic impact in a broader public sphere. Each of these works has made a unique contribution to the redefinition of artistic originality.Comparative Literatur

A multi-task learning CNN for image steganalysis

Convolutional neural network (CNN) based image steganalysis are increasingly popular because of their superiority in accuracy. The most straightforward way to employ CNN for image steganalysis is to learn a CNN-based classifier to distinguish whether secret messages have been embedded into an image. However, it is difficult to learn such a classifier because of the weak stego signals and the limited useful information. To address this issue, in this paper, a multi-task learning CNN is proposed. In addition to the typical use of CNN, learning a CNN-based classifier for the whole image, our multi-task CNN is learned with an auxiliary task of the pixel binary classification, estimating whether each pixel in an image has been modified due to steganography. To the best of our knowledge, we are the first to employ CNN to perform the pixel-level classification of such type. Experimental results have justified the effectiveness and efficiency of the proposed multi-task learning CNN

An ecosystem approach to knowledge management: Case studies of two Australian SMEs

This study is centred on the premise that knowledge is personalised information which can be enriched through the process of learning, then shared and applied to practical situations to attain value. To highlight the complex nature of knowledge management (KM) as a set of practices and aimed to enhance collaboration, the concept of a Collaborative Leaning Ecosystem (CLES) is presented as holistic approach toward improving practical learning environments. In view of the pressing need for better KM in small-to-medium (SME) enterprises, the CLES framework is used to examine the KM positions of two Australian SMEs. Viewing each case as an 'organisational ecosystem', the holistic assessment of each SME exposes certain KM inefficiencies unique to the firm, which are addressed through a set of actionable KM strategies for improving the relationships among the components interacting within each organisational ecosystem