Was kostet eine finanzierungsneutrale Besteuerung von Kapitalgesellschaften?

Die Besteuerung von Kapitaleinkommen im deutschen Ertragsteuerrecht erfolgt nicht finanzierungsneutral. Der Sachverständigenrat zur Begutachtung der gesamtwirtschaftlichen Entwicklung hatte im Vorfeld der Unternehmensteuerreform 2008/09 ein finanzierungsneutrales Körperschaftsteuersystem vorgeschlagen, das jedoch nicht umgesetzt wurde, da befürchtet wurde, dass die politische Zielvorgabe geringer Steuerausfälle nicht eingehalten worden wäre. Wir untersuchen in diesem Beitrag dieZinsbereinigung des Grundkapitals, eine Reformalternative, die ebenso Finanzierungsneutralität sichert, im Hinblick auf die zu erwartenden Steuerausfälle. Hierfür verwenden wir die Körperschaftsteuerstatistik des Statistischen Bundesamtes. Wir stellen fest, dass die Steuerausfälle verhältnismäßig gering sind. -- Capital income taxation in Germany distorts financing decisions of corporations as the after-tax cost of capital for equity is considerably higher than for debt. Since 2006 the German Council of Economic Experts has been proposing a neutral tax system similar to the Norwegian shareholder ACE tax. In the last German corporate and personal income tax reform in 2008/09 this proposal has not been realized because revenue losses were expected to be unacceptably high. In this paper we estimate the expected tax revenue losses of an alternative concept which also ensures neutrality with respect to financing decisions: a notional interest deduction on nominal capital and capital reserve. Data from the official German corporate income tax statistics are used. We show that revenue losses are relatively small.

Modellierung von Aktienanlagen bei laufenden Umschichtungen und einer Besteuerung von Veräußerungsgewinnen

Dieser Beitrag entwickelt ein Verfahren, das die Komplexität der Endvermögensberechnung von Aktienanlagen unter Berücksichtigung der Besteuerung und regelmäßiger Portfolioumschichtung erheblich reduziert. Bisher ist eine vergleichbar präzise Berechnung wegen rekursiver Abhängigkeiten sehr aufwändig. Die Belastungswirkungen verschiedener Besteuerungsverfahren von Aktienanlagen sind unter der Verwendung des hergeleiteten Verfahrens nun einfacher bestimmbar, sogar dann, wenn sie sich im Zeitpunkt des Steuerzugriffs unterscheiden (Aktienfonds, Zertifikate, Riester-Rente). Diese Vereinfachung wird erreicht, indem ein bestimmtes Umschichtungsverhalten angenommen wird. Dieses Umschichtungsverhalten stimmt mit dem Verhaltensmuster überein, dass der Investor zwar vor der steuerwirksamen Aufdeckung von Kurssteigerungen zurückschreckt, jedoch auch einen Anreiz hat, laufend Umschichtungen im Portfolio vorzunehmen, obwohl dies negative steuerliche Konsequenzen hervorruft. -- This paper develops a technique, which simplifies the calculation of terminal values of share investments when portfolio turnovers repeatedly trigger capital gains taxation. So far the calculations of these values are difficult, due to recursive dependencies, which cannot be expressed by geometric series. Using our technique, tax burdens of differently taxed forms of share investments can be determined in an easy way even if those methods imply different elements of deferred taxation (equity funds, certificates, preferred taxed pension plans). The simplification is reached by assuming a specific trading strategy. This strategy is in line with empirically observed investor behavior which is characterized by periodical portfolio turnovers and reluctance to realize taxable capital gains.Veräußerungsgewinnbesteuerung,Aktienanlage,laufende Umschichtungen,capital gains tax,portfolio investments,periodical portfolio turnovers

TRY plant trait database – enhanced coverage and open access

Plant traits - the morphological, anatomical, physiological, biochemical and phenological characteristics of plants - determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits - almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Delirium Screening in Neurocritical Care and Stroke Unit Patients: A Pilot Study on the Influence of Neurological Deficits on CAM-ICU and ICDSC Outcome

Background/objective!#!Delirium is a common complication in critically ill patients with a negative impact on hospital length of stay, morbidity, and mortality. Little is known on how neurological deficits affect the outcome of commonly used delirium screening tools such as the Confusion Assessment Method for the Intensive Care Unit (CAM-ICU) and the Intensive Care Delirium Screening Checklist (ICDSC) in neurocritical care patients.!##!Methods!#!Over a period of 1 month, all patients admitted to a neurocritical care and stroke unit at a single academic center were prospectively screened for delirium using both CAM-ICU and ICDSC. Tool-based delirium screening was compared with delirium evaluation by the treating clinical team. Additionally, ICD-10 delirium criteria were assessed.!##!Results!#!One hundred twenty-three patients with a total of 644 daily screenings were included. Twenty-three patients (18.7%) were diagnosed with delirium according to the clinical evaluation. Delirium incidence amounted to 23.6% (CAM-ICU) and 26.8% (ICDSC). Sensitivity and specificity of both screening tools were 66.9% and 93.3% for CAM-ICU and 69.9% and 93.9% for ICDSC, respectively. Patients identified with delirium by either CAM-ICU or ICDSC presented a higher proportion of neurological deficits such as impaired consciousness, expressive aphasia, impaired language comprehension, and hemineglect. Subsequently, generalized estimating equations identified a significant association between impaired consciousness (as indexed by Richmond Agitation and Sedation Scale) and a positive delirium assessment with both CAM-ICU and ICDSC, while impaired language comprehension and hemineglect were only associated with a positive CAM-ICU result.!##!Conclusions!#!A positive delirium screening with both CAM-ICU and ICDSC in neurocritical care and stroke unit patients was found to be significantly associated with the presence of neurological deficits. These findings underline the need for a more specific delirium screening tool in neurocritical care patients

A New Decision Process for Choosing the Wind Resource Assessment Workflow with the Best Compromise between Accuracy and Costs for a Given Project in Complex Terrain

In wind energy, the accuracy of the estimation of the wind resource has an enormous effect on the expected rate of return of a project. For a given project, the wind resource assessor is faced with a difficult choice of a wide range of simulation tools and workflows with varying accuracies (or “skill”) and costs. There is currently no guideline or process available in the industry for helping with the decision of the most “optimal” choice—and this is particularly challenging in mountainous (or “complex”) terrain. In this work, a new decision process for selecting the Wind Resource Assessment (WRA) workflow that would expect to deliver the best compromise between skill and costs for a given wind energy project is developed, with a focus on complex terrain. This involves estimating the expected skill and cost scores using a set of pre-defined weighted parameters. The new process is designed and tested by applying seven different WRA workflows to five different complex terrain sites. The quality of the decision process is then assessed for all the sites by comparing the decision made (i.e., choice of optimal workflow) using the expected skill and cost scores with the decision made using the actual skill and cost scores (obtained by comparing measurements and simulations at a validation location). The results show that the decision process works well, but the accuracy decreases as the site complexity increases. It is therefore concluded that some of the parameter weightings should be dependent on site complexity. On-going work involves collecting more data from a large range of sites, implementing measures to reduce the subjectivity of the process and developing a reliable and robust automated decision tool for the industry

A New Decision Process for Choosing the Wind Resource Assessment Workflow with the Best Compromise between Accuracy and Costs for a Given Project in Complex Terrain

In wind energy, the accuracy of the estimation of the wind resource has an enormous effect on the expected rate of return of a project. For a given project, the wind resource assessor is faced with a difficult choice of a wide range of simulation tools and workflows with varying accuracies (or “skill”) and costs. There is currently no guideline or process available in the industry for helping with the decision of the most “optimal” choice—and this is particularly challenging in mountainous (or “complex”) terrain. In this work, a new decision process for selecting the Wind Resource Assessment (WRA) workflow that would expect to deliver the best compromise between skill and costs for a given wind energy project is developed, with a focus on complex terrain. This involves estimating the expected skill and cost scores using a set of pre-defined weighted parameters. The new process is designed and tested by applying seven different WRA workflows to five different complex terrain sites. The quality of the decision process is then assessed for all the sites by comparing the decision made (i.e., choice of optimal workflow) using the expected skill and cost scores with the decision made using the actual skill and cost scores (obtained by comparing measurements and simulations at a validation location). The results show that the decision process works well, but the accuracy decreases as the site complexity increases. It is therefore concluded that some of the parameter weightings should be dependent on site complexity. On-going work involves collecting more data from a large range of sites, implementing measures to reduce the subjectivity of the process and developing a reliable and robust automated decision tool for the industry