Corporate Social Responsibility and the Environment: A Theoretical Perspective

We survey the growing theoretical literature on the motives for and welfare effects of corporate greening. We show how both market and political forces are making environmental CSR profitable, and we also discuss morally-motivated or altruistic CSR. Welfare effects of CSR are subtle and situation-contingent, and there is no guarantee that CSR enhances social welfare. We identify numerous areas in which additional theoretical work is needed.corporate social responsibility, environment, self-regulation, preemption, private politics

Astroturf: Interest Group Lobbying and Corporate Strategy

We study three corporate nonmarket strategies designed to influence the lobbying behavior of other special interest groups: (1) astroturf, in which the firm covertly subsidizes a group with similiar views to lobby when it normally would not; (2) the bear hug, in which the firm overtly pays a group to alter its lobbying activitives; and (3) self-regulation, in which the firm voluntarily limits the potential social harm from its activities. All three strategies reduce the informativeness of lobbying, and all reduce the payoff of the public decision-maker. We show that the decision-maker would benefit by requiring the public disclosure of funds but that the availability of alternative strategies limits the impact of such a policy.

Exploratory Climate Data Visualization and Analysis Using DV3D and UVCDAT

Earth system scientists are being inundated by an explosion of data generated by ever-increasing resolution in both global models and remote sensors. Advanced tools for accessing, analyzing, and visualizing very large and complex climate data are required to maintain rapid progress in Earth system research. To meet this need, NASA, in collaboration with the Ultra-scale Visualization Climate Data Analysis Tools (UVCOAT) consortium, is developing exploratory climate data analysis and visualization tools which provide data analysis capabilities for the Earth System Grid (ESG). This paper describes DV3D, a UV-COAT package that enables exploratory analysis of climate simulation and observation datasets. OV3D provides user-friendly interfaces for visualization and analysis of climate data at a level appropriate for scientists. It features workflow inte rfaces, interactive 40 data exploration, hyperwall and stereo visualization, automated provenance generation, and parallel task execution. DV30's integration with CDAT's climate data management system (COMS) and other climate data analysis tools provides a wide range of high performance climate data analysis operations. DV3D expands the scientists' toolbox by incorporating a suite of rich new exploratory visualization and analysis methods for addressing the complexity of climate datasets

Predicting Post-Fire Change in West Virginia, USA from Remotely-Sensed Data

Prescribed burning is used in West Virginia, USA to return the important disturbance process of fire to oak and oak-pine forests. Species composition and structure are often the main goals for re-establishing fire with less emphasis on fuel reduction or reducing catastrophic wildfire. In planning prescribed fires land managers could benefit from the ability to predict mortality to overstory trees. In this study, wildfires and prescribed fires in West Virginia were examined to determine if specific landscape and terrain characteristics were associated with patches of high/moderate post-fire change. Using the ensemble machine learning approach of Random Forest, we determined that linear aspect was the most important variable associated with high/moderate post-fire change patches, followed by hillshade, aspect as class, heat load index, slope/aspect ratio (sine transformed), average roughness, and slope in degrees. These findings were then applied to a statewide spatial model for predicting post-fire change. Our results will help land managers contemplating the use of prescribed fire to spatially target landscape planning and restoration sites and better estimate potential post-fire effects

Locally Advanced Spiroadenocarcinoma in the Regional Axilla of a Breast Cancer Patient: Hallmarks of Definitive Diagnosis and Management.

Eccrine spiroadenocarcinoma is an extremely rare malignant eccrine gland tumor which may masquerade as other more common malignancies such as poorly differentiated squamous carcinoma or metastatic breast cancer. We report a case of an ulcerated axillary skin lesion with bulky adenopathy in a 77 year-old female with a prior history of ipsilateral triple negative breast carcinoma. The clear transition of benign spiradenoma to malignant carcinoma was essential to establishing a definitive diagnosis and treatment plan

Interactive Communication with Unknown Noise Rate

Alice and Bob want to run a protocol over a noisy channel, where a certain number of bits are flipped adversarially. Several results take a protocol requiring $L$ bits of noise-free communication and make it robust over such a channel. In a recent breakthrough result, Haeupler described an algorithm that sends a number of bits that is conjectured to be near optimal in such a model. However, his algorithm critically requires $a \ priori$ knowledge of the number of bits that will be flipped by the adversary. We describe an algorithm requiring no such knowledge. If an adversary flips $T$ bits, our algorithm sends $L + O\left(\sqrt{L(T+1)\log L} + T\right)$ bits in expectation and succeeds with high probability in $L$. It does so without any $a \ priori$ knowledge of $T$. Assuming a conjectured lower bound by Haeupler, our result is optimal up to logarithmic factors. Our algorithm critically relies on the assumption of a private channel. We show that privacy is necessary when the amount of noise is unknown.Comment: Made substantial improvements to the algorithm and analysis. Previous version had a subtle error involving the adversary's ability to attack fingerprint

Self-regulation, taxation and public voluntary environmental agreements

An increasingly popular instrument for solving environmental problems is the "public voluntary agreement (VA)", in which government offers modest technical assistance and positive publicity to firms that reach certain environmental goals. Prior papers treat such agreements as a superior, low-cost instrument that can be used to pre-empt a threat of traditional, inefficient, regulation. We present a more general model in which public Vas may instead be weak tools used when political opposition makes environmental taxes infeasible. We explore the conditions under which taxes, public VAs, and unilateral industry actions are to be expected, the implications for industry size, as well as the welfare implications of the various instruments