The Impact of Environmental Risk Exposure on the Determinants of Sustainable Entrepreneurship

Does the increasing awareness of environmental risk exposure also affect intentions to create enterprises which address these social and environmental failures? Besides economic explanations that social and environmental needs and market failure create opportunities for sustainable entrepreneurship, it is less clear how cognitive processes and motivations related to sustainable entrepreneurship are shaped by its context. This research integrates environmental risk exposure as a contextual variable into the theory of planned behavior and uses data gathered in the course of the Global Entrepreneurship Monitor. We provide empirical evidence for the impact of environmental risk exposure on the determinants of sustainable entrepreneurial intention and contribute to a deeper understanding of the formation of sustainable entrepreneurial intention.DFG, 414044773, Open Access Publizieren 2019 - 2020 / Technische Universität Berli

Corrective Ad Valorem and Unit Taxes: A Welfare Comparison

The ad valorem versus unit taxes debate has traditionally emphasized tax yield. For this criterion, ad valorem taxes outperform unit taxes in terms of welfare for a wide range of imperfect competition settings, including Dixit-Stiglitz monopolistic competition. Yet, in a number of policy fields, such as environmental, health or trade economics, policy makers apply taxes to target the production/consumption volume in an industry, i.e. aim at a certain corrective effect rather than tax yield. This paper compares the two tax instruments with respect to equal corrective-effect in a Dixit-Stiglitz setting with love of variety, entry, exit, and redistribution of tax revenues. We find that unit taxes lead to more firms in the industry, less output per firm, less tax revenue, but higher welfare compared to ad valorem taxes.Externalities; Monopolistic competition; Taxes; Specific taxes; Welfare

Description and molecular diagnosis of a new species of Brunfelsia (Solanaceae) from the Bolivian and Argentinean Andes

Brunfelsia plowmaniana N.Filipowicz & M.Nee sp. nov., a species from humid and cloud forests of the Bolivian and Argentinean Andes, is described and provided with a molecular diagnosis, using provisions available in the recently approved International Code of Nomenclature for algae, fungi and plants. Specimens belonging to the new species were previously placed in the polymorphic B. uniflora (Pohl) D.Don, which a molecular phylogeny revealed as polyphyletic. Revision of numerous collections revealed clear morphological differences between the new species and B. uniflora, the type locality of which is in the state of São Paulo, Brazil

How to Turn an Industry Green: Taxes versus Subsidies

Environmental policies frequently target the ratio of dirty to green output within the same industry. To achieve such targets the green sector may be subsidised or the dirty sector be taxed. This paper shows that in a monopolistic competition setting the two policy instruments have different welfare effects. For a strong green policy (a severe reduction of the dirty sector) a tax is the dominant instrument. For moderate policy targets, a subsidy will be superior (inferior) if the initial situation features a large (small) share of dirty output. These findings have implications for policies such as the Californian Zero Emission Bill or the EU Action Plan for Renewable Energy Sources.Environmental policy; Monopolistic competition; Taxes; Subsidies; Welfare; Zero Emission Bill

Varying Coefficient Tensor Models for Brain Imaging

We revisit a multidimensional varying-coefficient model (VCM), by allowing regressor coefficients to vary smoothly in more than one dimension, thereby extending the VCM of Hastie and Tibshirani. The motivating example is 3-dimensional, involving a special type of nuclear magnetic resonance measurement technique that is being used to estimate the diffusion tensor at each point in the human brain. We aim to improve the current state of the art, which is to apply a multiple regression model for each voxel separately using information from six or more volume images. We present a model, based on P-spline tensor products, to introduce spatial smoothness of the estimated diffusion tensor. Since the regression design matrix is space-invariant, a 4-dimensional tensor product model results, allowing more efficient computation with penalized array regression