Climate

Buildings have a major impact on the environment through excessive use of resources, such as energy and water, and large carbon dioxide emissions. In this paper we revisit the study of Eichholtz et al. (2010) about the economics of environmentally sustainable buildings and estimate the effect of green building practices on market rents. For this, we use new matching methods that take advantage of the clustered structure of the buildings data.

Until fairly recently, the main approach to getting business to respond to climate change has been top-down efforts to regulate emissions and enact various forms of "carbon pricing." The aim of such efforts has been to make businesses "internalize" the costs associated with greenhouse gas (GHG) emissions. Governments are expected to set the environmental protection rules for companies in their respective countries, and markets are expected to adjust to the new regulations and carbon prices.

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I was thrilled to see thousands of activists and celebrities marching through Manhattan Sunday calling on the United Nations and government leaders to do more on climate change. Inaction by U.S. politicians is always at the epicenter of these calls, given Washington's lack of consensus on the issue. But this overlooks the track record of this country when it comes to reducing greenhouse gas emissions.

We develop a simple dynamic investment strategy that allows long‐term passive investors to hedge climate risk without sacrificing financial returns. Our proposed hedging strategy goes beyond a simple divestment of high carbon footprint or stranded assets stocks. This is just the first step. The second step is to optimize the composition of the low carbon portfolio so as to minimize the tracking error with the reference benchmark index. We show that tracking error can be almost eliminated even for a low carbon index that has 50% less carbon footprint.

A recent surge of research has investigated the potential of pro-environmental behavior interventions to affect other pro-environmental behaviors not initially targeted by the intervention. The evidence evaluating these spillover effects has been mixed, with some studies finding evidence for positive spillover (i.e., one pro-environmental behavior increases the likelihood of performing additional pro-environmental behaviors) and others finding negative spillover (i.e., one pro-environmental behavior decreases the likelihood of additional pro-environmental behaviors).

Utilizing theory and empirical insights from psychology and behavioural economics, this paper examines individuals' cognitive and motivational barriers to adopting climate change adaptation and mitigation measures that increase consumer welfare. We explore various strategies that take into account the simplified decision-making processes used by individuals and resulting biases. We make these points by working through two examples: (1) investments in energy efficiency products and new technology and (2) adaptation measures to reduce property damage from future floods and hurricanes.

Public opinion polls reveal that the perception of climate change as an uncertain phenomenon is increasing, even as consensus has increased within the scientific community of its reality and its attribution to human causes. At the same time, the scientific community has sought to improve its communication practices, in order to present a more accurate picture to the public and policy makers of the state of scientific knowledge about climate change. In this review article, we examine two sets of insights that could influence the success of such communication efforts.

There are obvious economic predictors of ability and willingness to invest in environmental sustainability. Yet, given that environmental decisions represent trade-offs between present sacrifices and uncertain future benefits, psychological factors may also play a role in country-level environmental behavior. Gott's principle suggests that citizens may use perceptions of their country's age to predict its future continuation, with longer pasts predicting longer futures.