Environmentalism in the EU-28 context: the impact of governance quality on environmental energy efficiency

Environmental policies are a significant cornerstone of a developed economy, but the question that arises is whether such policies lead to a sustainable growth path. It is clear that the energy sector plays a pivotal role in environmental policies, and although the current literature has focused on examining the link between energy consumption and economic growth through an abundance of studies, it does not explicitly consider the role of institutional or governance quality variables in the process. Both globalization and democracy are important drivers of sustainability, while environmentalism is essential for the objective of gaining a “better world.” Governance quality is expected to be the key, not only for economic purposes but also for the efficiency of environmental policies. To that end, the analysis in this paper explores the link between governance quality and energy efficiency for the EU-28 countries, spanning the period 1995 to 2014. The findings document that there is a nexus between energy efficiency and income they move together: the most efficient countries are in the group with higher GDP per capita. Furthermore, the results show that governance quality is an important driver of energy efficiency and, hence, of environmental policies.University of Granad

Conditional spatial policy dependence: theory and model specification

The authors discuss how scholars can bring theories of spatial policy dependence and empirical model specifications closer in line so that the empirical analysis actually tests the theoretical predictions. Comprehensive theories of spatial policy dependence typically suggest that the jurisdictions receiving spatial stimuli systematically differ in their exposure to such signals as a function of the intensity of their interaction with other jurisdictions. Similarly, theories often predict that governments also differ in their responsiveness to any given spatial stimulus as a function of the institutional, political, economic, or social context in which they operate. In other words, theories typically postulate that spatial dependence is conditional on exposure and responsiveness, neither of which is accounted for in the standard empirical practice of estimating one single common coefficient for a row-standardized spatial lag variable. The authors show how scholars can adequately model both forms of heterogeneity with properly specified interaction effects models

Predicting risky choices from brain activity patterns

Previous research has implicated a large network of brain regions in the processing of risk during decision making. However, it has not yet been determined if activity in these regions is predictive of choices on future risky decisions. Here, we examined functional MRI data from a large sample of healthy subjects performing a naturalistic risk-taking task and used a classification analysis approach to predict whether individuals would choose risky or safe options on upcoming trials. We were able to predict choice category successfully in 71.8% of cases. Searchlight analysis revealed a network of brain regions where activity patterns were reliably predictive of subsequent risk-taking behavior, including a number of regions known to play a role in control processes. Searchlights with significant predictive accuracy were primarily located in regions more active when preparing to avoid a risk than when preparing to engage in one, suggesting that risk taking may be due, in part, to a failure of the control systems necessary to initiate a safe choice. Additional analyses revealed that subject choice can be successfully predicted with minimal decrements in accuracy using highly condensed data, suggesting that information relevant for risky choice behavior is encoded in coarse global patterns of activation as well as within highly local activation within searchlights

How to communicate the scientific consensus on climate change: plain facts, pie charts or metaphors?

Previous research has identified public perceptions of the scientific consensus on climate change as an important gateway belief. Yet, little research to date has examined how to effectively communicate the scientific consensus on climate change. In this study, we conducted an online experiment using a national quota sample to compare three approaches to communicating the scientific consensus, namely: (a) descriptive text, (b) a pie chart and (c) metaphorical representations. Results indicate that while all three approaches can significantly increase public understanding of the degree of scientific consensus, the pie chart and simple text have superior recall and are most effective across political party lines. We conclude that the scientific consensus on climate change is most effectively communicated as a short, simple message that is easy to comprehend and remember. Representing the consensus visually in the form of a pie chart appears to be particularly useful