Conference Agenda

Global society needs to reduce carbon emissions quickly to limit the damages caused by climate change. Most economists agree that a carbon price is an effective and cost-efficient policy to mitigate emissions, yet low public acceptance and limited political support remain major barriers to its widespread implementation. This crowd-sourced many-designs project reports results from 55 behavioral interventions on real-world support for carbon pricing, independently developed by international research teams randomly selected from an initial pool of 135 applications. By implementing all interventions simultaneously with almost 20,000 U.S. residents, this pre-registered study ensures comparability of results, accelerates scientific knowledge generation, and reduces risks of scientific malpractices such as p-hacking, selective reporting, and HARKing. Results show very small (Cohen’s d from 0.04 to 0.07) and statistically significant positive effects of behavioral interventions on real-world support, stated support, and willingness to endorse a carbon price that internalizes social costs of $120 per ton of CO2 emissions. This entails an increase in support for carbon pricing across measures of around two percentage points. We find low between-study heterogeneity (τ from 0.07 to 0.12), indicating that behavioral interventions in this domain are similarly effective. Lastly, we identify strong overconfidence among research teams regarding the expected effects of their interventions and those of others, highlighting the need to recalibrate expectations.

We quantify differences between the stated and revealed support for wind and solar energy in a controlled and pre-registered lab experiment. We implemented a 2 x 2 between-subject design and varied energy type (wind or solar) as well as preference type (stated or revealed). We find strong evidence for an intention-behavior gap for both energy types: The stated support was significantly higher than the revealed support for wind and solar energy, even after controlling for potential confounding factors. Our results provide evidence that a lower-than-expected level of revealed support for the energy transition is driven in part by skepticism, which remains undetected in stated preferences methods.

This paper studies how the organisational structure of markets influences moral consumption behavior in the presence of environmental externalities. Motivated by pressing environmental challenges such as climate change, biodiversity loss, and pollution, the study focuses on markets where purchasing a “moral” product generates a real positive impact through the planting of trees to offset carbon emissions. The experimental markets incorporate network externalities, whereby a consumer’s valuation increases with the number of other consumers purchasing the same product, as in technology markets and environmentally motivated consumption such as electric vehicle adoption. Under these conditions, multiple competitive equilibria exist. The market experiment examines equilibrium convergence and price discovery by varying trading institutions and informational richness, comparing a continuous double auction with a posted offer institution. Results show higher prices under posted offer trading for both moral and standard products, although standard products consistently trade at lower prices. While the share of moral product transactions varies widely across markets and does not differ significantly by institution, overall efficiency is higher under posted offer trading because fewer transactions occur in the double auction markets.

Scope sensitivity is a key validity criterion of stated preference (SP) studies. However, little is known about its underlying determinants, especially in the context of low-carbon energy technologies (LCET). In particular, the role of spatial characteristics in shaping willingness to pay (WTP) sensitivity to scope remains largely unexplored. This is the first valuation study to investigate how spatial factors interact with external scope effects on WTP for emerging LCETs, i.e., Carbon Capture and Storage (CCS). The study proposes a new behavioral model, conceptualizing the interplay between spatial factors and technology-scope in preference formation. The framework is empirically tested using Danish representative survey data on WTP for CCS with varying CO2 reduction potentials. The SP data is combined with high-resolution spatial information on respondents’ proximity to energy infrastructure and environmental features. We find significant interaction effects between CCS scope and spatial variables. Increased local forest coverage is associated with higher WTP for larger-scope CCS, whereas solar farm exposure significantly reduces WTP for CCS with smaller emissions reduction potential. The observed patterns indicate that spatial responsiveness is a function of technology-scope, leading to variations in spatial-dependent WTP scope elasticities. The findings highlight the importance of accounting for spatial-scope interactions in SP research.