Research

An important driver of climate change inaction is the belief that individuals cannot have any tangible impact on climate change through their own actions. Currently available statistics are not suited to systematically assess or challenge this belief. In this paper, I derive the marginal impact of emission reductions—the effect of reducing emissions by 1 tonne of CO₂ (tCO₂)—on physical climate change outcomes, document important misperceptions, show how they affect behavior, and derive policy implications. Using climate models, I find that the impact of reducing emissions by 1 tCO₂ is thousands of liters less glacier ice melting, several additional hours of aggregate life expectancy, and multiple m² less vegetation undergoing ecosystem change. Subjects underestimate these figures by orders of magnitude. Moreover, their mental model is inconsistent with climate models. First, they misperceive climate change as a threshold public goods game. Second, they incorrectly assume that the marginal impact increases when others also reduce their emissions (strategic complementarity). Providing subjects with the climate-scientific findings causally increases perceived self-efficacy, intentions to reduce own emissions, and real donations to reduce global emissions. Providing information about the marginal impact is a cost-effective demand-side mitigation strategy. The information can also serve as a catalyst for other climate policies by reframing their benefits and challenging arguments against unilateral action that are based on threshold thinking.

We lay out a simple framework for optimal green retailing and use it to evaluate a heavily publicized “true cost” campaign, in which a large German grocer added the estimated uninternalized externality costs to selected products and donated the proceeds to climate change mitigation projects. When the campaign increased prices, demand decreased less than would be predicted by responses to standard short-term price changes, suggesting that warm glow from the donations increased demand. Surveys show that the campaign did not substantially affect beliefs about externality magnitudes, but consumers expressed concerns about greenwashing and viewed true cost pricing more skeptically after the campaign. To quantify the effects of alternative policies, we build a structural model of retailer and grocery choice, in which we allow for rich substitution patterns across product categories, and estimate it using home scanner data. The model predicts that a cross-subsidy from high- to low-externality foods can generate even larger welfare gains per dollar of forgone profits than the pricing campaign. However, the welfare gains of such unilateral green retailing campaigns remain orders of magnitude below a first-best Pigouvian tax.

Mitigating climate change to reach international targets requires action by public and private actors on all scales. Yet, the effectiveness of emission reductions by individual people, organizations, regions, and countries is often perceived to be small, limiting both private and public mitigation efforts. Currently, there is no comprehensive quantification of the consequences of individual-scale emission reductions on relatable climate change outcomes. Here, we introduce and quantify the “one-tonne effect,” which measures the effect of each tonne of CO₂ emission reductions based on climate impact projections using a flexible statistical estimation framework. We apply this framework to 16 climate impacts across hydrology, cryosphere, ecosystems, food, and well-being. We show that the one-tonne effect is on human scales—comparable to everyday human dimensions and perceptions—for most impacts, given current expected warming. For systems at risk of complete loss, such as coral reefs, marginal emission reductions delay complete loss, with rapidly increasing effects under more ambitious climate policies. By demonstrating that each tonne of emission savings contributes meaningfully to reducing climate damages, our findings show that individual climate actions matter. Our estimates can be used to quantify the benefits of private and public mitigation efforts, and motivate individuals to reduce their emissions.

Note: This paper extends the estimation methodology first developed in the appendix of The Marginal Impact of Emission Reductions: Estimates, Beliefs and Behavior, and applies it to a much broader set of climate impacts. The latter paper motivates this study, by documenting the importance of a measure like the “one-tonne effect” for individual and collective decision-making.

This paper reviews the growing field of behavioral environmental economics: the study of how cognition, beliefs, and social preferences shape sustainable behavior and the effectiveness and political feasibility of environmental policy. We synthesize recent theoretical, experimental, and empirical contributions, with emphasis on sustainable consumption, green investment, firm behavior, and political economy. We highlight design lessons and open questions for policy and research.

Addressing climate change depends on large-scale system changes, which require public advocacy. Here, we identified and tested 17 expert-crowdsourced theory-informed behavioral interventions designed to promote public, political, and financial advocacy in a large quota-matched sample of US residents (n = 31,324). The most consistently effective intervention emphasized both the collective efficacy and emotional benefits of climate action, increasing advocacy by up to 10 percentage points. This was also the top intervention among participants identifying as Democrats. Appealing to binding moral foundations, such as purity and sanctity, was also among the most effective interventions, showing positive effects even among participants identifying as Republicans. These findings provide critical insights to policymakers and practitioners aiming to galvanize the public behind collective action and advocacy on climate change with affordable and scalable interventions.

A key issue in science is assessing robustness to data analysis choices, while avoiding selective reporting and providing valid inference. Specification Curve Analysis is a tool intended to prevent selective reporting. Alas, when used for inference it can create severe biases and false positives, due to wrongly adjusting for covariates, and mask important treatment effect heterogeneity. As our motivating application, it led an influential study to conclude there is no relevant association between technology use and teenager mental well-being. We discuss these issues and propose a strategy for valid inference. Bayesian Specification Curve Analysis (BSCA) uses Bayesian Model Averaging to incorporate covariates and heterogeneous effects across treatments, outcomes and sub-populations. BSCA gives significantly different insights into teenager well-being. It provides strong evidence that technology has relevant associations with teenager well-being: (1) well-being is negatively associated with electronic device usage, (2) social media use is negatively associated with self-assessed well-being but positively associated with parent-assessed well-being, and (3) has a stronger negative association with self-assessed well-being for girls compared to boys.

HM Treasury’s estimation of the economic consequences of Brexit – using standard macroeconomic models – during the EU referendum campaign represents a remarkable intervention in a highly politicized public debate. It raises a series of questions about the use of economic expertise. Through a detailed theoretical and empirical critique of the Treasury’s methodology – and a reassessment of the likely effects of Brexit in light of this – we cast doubt on the utility of their approach, highlighting methodological issues, unrealistic assumptions, and misrepresentations of established facts. In the process we seek to identify some of the wider implications for the use and potential abuse of economic expertise in highly charged political contexts, such as the EU referendum debate.

A basic but as yet unachieved goal for UN missions is to know the exact locations of their peacekeepers at any given time. Such tracking would help field missions plan operations, avoid and respond to ambushes, kidnappings and friendly fire incidents, rapidly send reinforcements and retrieve wounded peacekeepers, ultimately saving lives. Improved effectiveness could be obtained from ‘precision peacekeeping’, where soldiers, police and civilians are deployed to precise locations and events, while operational leaders follow their movements. Fortunately, tracking technology has improved considerably so that commercial solutions for real-time tracking of personnel and vehicles are now available at lower cost and increased accuracy and sophistication, while being more user-friendly. The advances in phone and vehicle tracking systems are reviewed here to identify the benefits, drawbacks and challenges, especially any political ones, for the United Nations. The world organization can benefit from modern blue mission tracking, without having to develop costly, customized solutions. Such initiatives have few technological or financial hurdles but the politics and institutionalization of continuous positional surveillance needs policy modernization, guided by a nuanced understanding of technological empowerment.