Symmetric cash flow-taxation and cross-border investments

The discussion about income versus consumption as the ideal tax base looks back on a long history. In recent years, the debate about income versus consumption as the better tax base reemerged in the United States (2002) and in Germany (2006). In view of the long history of the debate, it is surprising that still relatively little research has been done on crossborder-investments in a cash flow-tax system. The presented article tries to fill this gap. For the case of a harmonized introduction of symmetric cash flow-tax systems in several countries, rules are developed that could guarantee a systematic and feasible treatment of crossborder investments. Preference is given to the RF-base-cash flow-tax on the personal level without a separate company tax. As a result the presented article states, that a coordinated introduction of symmetric cash flow-tax systems in several neighboring countries could be possible. To guarantee the success of the reform, each country must be willing to commit to intensive cooperation in tax matters. A unilateral introduction of a cash flow-tax and the resulting clash of a consumption-based tax system with an income-based tax system - the socalled collision-case - will be addressed in a following paper. -- Die Frage, ob das Einkommen oder der Konsum die vorziehenswürdige Bemessungsgrundlage bildet, weist eine lange Tradition auf. In der jüngeren Vergangenheit erlebte die Frage angesichts neuer Reformvorschläge in den USA (2002) und in Deutschland (2006) eine Renaissance. Angesichts der langen Historie der Diskussion überrascht es, dass die steuerliche Behandlung grenzüberschreitender Investitionen in einem Cash-flow-Steuer-System bisher kaum untersucht wurde. Der vorliegende Artikel versucht diese Lücke zu schließen. Für den Fall der Einführung gleicher Cash-flow-Steuer-Systeme in allen Ländern (Harmoniefall) werden Regelungen entwickelt, die eine systematische und durchführbare Besteuerung grenzüberschreitender Investitionen sicherstellen. Als betrachtetes Cash-flow-Steuer-System wird eine RF-base-Cash-flow-Steuer auf persönlicher Ebene ohne eigenständige Besteuerung auf Unternehmungsebene herangezogen. Der vorliegenden Artikel kommt zum Ergebnis, dass eine koordinierte Einführung gleicher Cash-flow-Steuer-Systeme möglich ist. Voraussetzung dafür ist allerdings eine enge Kooperation der Länder in Steuerfragen. Die unilaterale Einführung eines Konsumsteuersystems in einem einzelnen Land und das daraus resultierende Zusammentreffen von Konsumsteuersystem und Einkommensteuersystem - der sog. Kollisionsfall - werden in einem folgenden Beitrag untersucht.Cash flow-tax,consumption tax,international taxation,cross-border investments

Alternating model trees

Model tree induction is a popular method for tackling regression problems requiring interpretable models. Model trees are decision trees with multiple linear regression models at the leaf nodes. In this paper, we propose a method for growing alternating model trees, a form of option tree for regression problems. The motivation is that alternating decision trees achieve high accuracy in classification problems because they represent an ensemble classifier as a single tree structure. As in alternating decision trees for classifi-cation, our alternating model trees for regression contain splitter and prediction nodes, but we use simple linear regression functions as opposed to constant predictors at the prediction nodes. Moreover, additive regression using forward stagewise modeling is applied to grow the tree rather than a boosting algorithm. The size of the tree is determined using cross-validation. Our empirical results show that alternating model trees achieve significantly lower squared error than standard model trees on several regression datasets

Online estimation of discrete densities using classifier chains

We propose an approach to estimate a discrete joint density online, that is, the algorithm is only provided the current example, its current estimate, and a limited amount of memory. To design an online estimator for discrete densities, we use classifier chains to model dependencies among features. Each classifier in the chain estimates the probability of one particular feature. Because a single chain may not provide a reliable estimate, we also consider ensembles of classifier chains. Our experiments on synthetic data show that the approach is feasible and the estimated densities approach the true, known distribution with increasing amounts of data

Fast conditional density estimation for quantitative structure-activity relationships

Many methods for quantitative structure-activity relationships (QSARs) deliver point estimates only, without quantifying the uncertainty inherent in the prediction. One way to quantify the uncertainy of a QSAR prediction is to predict the conditional density of the activity given the structure instead of a point estimate. If a conditional density estimate is available, it is easy to derive prediction intervals of activities. In this paper, we experimentally evaluate and compare three methods for conditional density estimation for their suitability in QSAR modeling. In contrast to traditional methods for conditional density estimation, they are based on generic machine learning schemes, more specifically, class probability estimators. Our experiments show that a kernel estimator based on class probability estimates from a random forest classifier is highly competitive with Gaussian process regression, while taking only a fraction of the time for training. Therefore, generic machine-learning based methods for conditional density estimation may be a good and fast option for quantifying uncertainty in QSAR modeling.http://www.aaai.org/ocs/index.php/AAAI/AAAI10/paper/view/181

Upper Bound on the Capacity of a Cascade of Nonlinear and Noisy Channels

An upper bound on the capacity of a cascade of nonlinear and noisy channels is presented. The cascade mimics the split-step Fourier method for computing waveform propagation governed by the stochastic generalized nonlinear Schroedinger equation. It is shown that the spectral efficiency of the cascade is at most log(1+SNR), where SNR is the receiver signal-to-noise ratio. The results may be applied to optical fiber channels. However, the definition of bandwidth is subtle and leaves open interpretations of the bound. Some of these interpretations are discussed.Comment: The main change is to define the noise as bandlimited already in (8) rather than before (15). This serves to clarify subsequent step

A study of hierarchical and flat classification of proteins

Automatic classification of proteins using machine learning is an important problem that has received significant attention in the literature. One feature of this problem is that expert-defined hierarchies of protein classes exist and can potentially be exploited to improve classification performance. In this article we investigate empirically whether this is the case for two such hierarchies. We compare multi-class classification techniques that exploit the information in those class hierarchies and those that do not, using logistic regression, decision trees, bagged decision trees, and support vector machines as the underlying base learners. In particular, we compare hierarchical and flat variants of ensembles of nested dichotomies. The latter have been shown to deliver strong classification performance in multi-class settings. We present experimental results for synthetic, fold recognition, enzyme classification, and remote homology detection data. Our results show that exploiting the class hierarchy improves performance on the synthetic data, but not in the case of the protein classification problems. Based on this we recommend that strong flat multi-class methods be used as a baseline to establish the benefit of exploiting class hierarchies in this area

A Two-Dimensional Signal Space for Intensity-Modulated Channels

A two-dimensional signal space for intensity- modulated channels is presented. Modulation formats using this signal space are designed to maximize the minimum distance between signal points while satisfying average and peak power constraints. The uncoded, high-signal-to-noise ratio, power and spectral efficiencies are compared to those of the best known formats. The new formats are simpler than existing subcarrier formats, and are superior if the bandwidth is measured as 90% in-band power. Existing subcarrier formats are better if the bandwidth is measured as 99% in-band power.Comment: Submitted to IEEE Communications Letters, Feb. 201