The annual International Behavioural Public Policy Conference 2025 at Cambridge University [June 25-26]

Behavioural Transformations 2025 at London School of Economics [June 27-28]

Annual European Association of Environmental and Resource Economists Conference in Leuven [July 1-4]

The annual Advances in Field Experiments 2025 Conference at London School of Economics [September 5-6]

9th Workshop on Experimental Economics for the Environment [September 10-11] 

Sustainable Food Systems Symposium [September 16-17]. Keynote Lecture.

FINBEPOL Keynote Lecture. Finnish PMO BI Day [September 20]

BSRIA Briefing 2024 - Sustainable Futures: Redefining Retrofit for Net Zero Living. Keynote Lecture [November 22]

Warwick Economics Department Seminar Series [November 27-28]

Norway Tax Administration and Oslo RCT Brown Bag Seminar [December 4] (online)

WHO Athens Keynote Lecture in Quality of Care Conference [December 10] (online)

Imperial College Business School CEPHI Seminar [January 13, 2025]

UCL Behavioural Economics for the Environment Lecture [27 January, 2025]

OECD Policy Brief  Launch “Green Lift, Mind Shift" Academic Keynote [29 January, 2025]

Pakistan Climate Policy Dialogue: BPP Keynote [19 February, 2025]

Oxford Behavioral Insights Group (BIG) Lecture [20 February 2025]

UK Ofcom Lecture [3 March 2025] 

Brighton College - Masterclass on Nudging [11 March 2025]

OECD- Cambridge Workshop on Trust in Institutions [20 March 2025]

MSH Alps, University Grenoble Alpes Workshop on Behavioural Influence and Resistance to Influence [14 April 2025]

CERAG Conference on Behavioural Science and Public Policy [20 April 2025]

NoBeC Keynote Lecture, University of Penn [8 May 2025]

Council of Europe, Behavioural Science Seminar [12 May 2025]

Pellervo Economic Research PTT in Helsinki  Invited Lecture [16 May 2025]

Abstract: Behavioural public policy (BPP) applies behavioural insights to aid policy-making and implementation. Emerging from the burgeoning interest in nudges in the late 2000s, BPP has matured over the last decade. It has produced novel concepts and rich empirical data, helping researchers and policy-makers understand and explain human behaviour with a multidisciplinary lens. Even though BPP is an established field of endeavour, it is at a crucial juncture when it is important to assess how it is likely to grow as a field. To help understand the dynamics of knowledge innovation and utilisation, this article discusses the past, present, and future of behavioural public policy. We draw on the substantive achievements of nudge and BPP, the engagement of policy-makers in nudge units and commissioned BPP policies, the growth of empiricism via experiments, and an emergent ethical dimension illustrated by new tools, such as boost and nudge+. We highlight the increasingly prominent role of agency and reasonableness in future initiatives, and we outline benefits that newer methods, such as computational social sciences, can have on the field in making sense of heterogeneity. BPP shows a sustained attention over time, with growing richness in its academic and policy agenda, and is not a cyclical or temporary phenomenon.

Abstract: People differ in their underlying economic preferences and needs for energy retrofits. Accelerating the energy transition, therefore, requires tailoring personalised solutions for distinct groups of individuals. In this paper, we create behavioural phenotypes of green energy investors in the residential sector of the Netherlands. Using a latent class analysis on a representative sample of 2,245 respondents, we identify four distinct classes of investors: Comfort-driven Rationalists, Financially Driven Rationalists, Policy-driven Environmentalists, and Erratic Choosers. We innovate upon the literature by linking class profiling to economic preferences and behavioural biases, alongside socio-demographic and household characteristics. Our findings can help practitioners design bottom-up tailored behavioural interventions to accelerate the uptake of green energy investments.

Abstract: Transitioning to clean energy is necessary to meet the climate targets of the Paris Agreement. Accelerating decarbonisation requires improving energy efficiency and making large-scale green energy investments, inter alia in residential homes. Household energy behaviours and investment decisions are mostly suboptimal as individuals often face significant psychological barriers and are subjected to various cognitive biases. Consequently, one-size-fits-all interventions, that are aimed at fostering green energy behaviours, lead to information overload and rebound effects, thereby being inefficient. A growing proposition in behavioural sciences is to personalise the delivery of behavioural interventions (BIs) to facilitate the uptake of energy-efficient behaviours. This is typically done, for example, by tailoring different BIs to individuals to overcome individual biases in the adoption of green appliances and renovations. Nonetheless, there is no clear know-how to use different statistical methods to tailor BIs. While researchers rely on various techniques to customise BIs for specific groups, this segmentation process lacks coherence overall. In this paper, we systematically review and sort the literature on statistical clustering models, including machine learning methods, that have been used to optimize behavioural interventions for improving residential energy efficiency. Our review provides a holistic overview of these different methods, along with clear recommendations for practitioners to use them. It further highlights the role that machine learning algorithms can play in automating BIs, for example, by using sophisticated data analysis and pattern recognition to identify intricate relationships between decision-making factors, leading to highly optimised personalised strategies for increased energy efficiency.

Abstract: Meat consumption and willingness to reduce it may be linked to political ideology, with a common assumption that left-leaning individuals favour meat reduction policies more than right-leaning ones. However, rigorous evidence is lacking on this point. This study examines whether support for meat reduction policies varies by self-reported political ideology. Using a conjoint experiment with nationally representative samples from Denmark, Germany, the Netherlands, and the UK (N=2,008), we randomly vary four attributes of a hypothetical meat tax: cost, revenue redistribution, motivation, and outreach. We find that right-wing voters support a baseline meat tax more than left-wing voters, but their support decreases when policies involve revenue redistribution, incorporate environmental costs, or emphasize environmental over health concerns. These patterns are partly explained by differences in Schwartz values across ideological groups. Our findings highlight the role of narratives in shaping political debates on meat taxation.

Abstract: Are stringent vaccine promotion policies associated with higher uptake, even when people are hesitant about the vaccine? In a survey of G-7 countries, 22% of respondents (n=42,217) say they do not trust the COVID-19 vaccine, but half of them nonetheless take up at least one vaccination. We investigate a range of factors associated with vaccination, focusing on the stringency of vaccine promotion policies, which change the costs and benefits of immunization choices. We show that living in a country with more stringent vaccination policies is positively associated with uptake of the initial vaccination protocol, including among people who are skeptical about the vaccine. The association between policy stringency and uptake of the booster vaccine is also positive among those who are skeptical about the vaccine. However, this association is not differentially stronger compared to the group who trust the vaccine. Our findings suggest that policy stringency can play a key role in vaccine uptake. Our findings raise questions for policymakers, in finding the appropriate balance between persuasive and coercive policies to promote policy goals.

Abstract: The mission of the Principles for Responsible Management Education by the UN is to transform management education and to engage students with the Sustainable Development Goals (SDGs). However, it seems that relevant SDGs are not being met, especially on important goals such as zero hunger. What is needed are pedagogical tools and interventions that help future leaders to feel empowered to act positively to contribute to SDGs. An effective way of doing this is by writing a letter to the future. In this paper we develop a novel format of this letter to the future challenge (LTC), an online scalable written learning intervention where participants (a) reflect on and write about the imagined ideal world contrasting this with the idea of the world that will come to pass if nothing changes, and (b) reflect on and write about concrete goals and actions that contribute to certain SDGs. LFC is a promising new toolkit for management education. Based on insights from positive psychology, we propose that LFC offers ways to increase a self-transcendent action repertoire, and potentially kickstart societal change. LFC can be part of a pedagogical toolkit to enhance human agency and foster building good intentions for sustained behaviour change.

Abstract: Understanding the mechanisms through which behavioural interventions work remains a critical challenge in behavioural science. While randomized controlled trials (RCTs) provide reliable evidence for intervention efficacy, they are seldom designed to reveal the underlying causal pathways that drive observed outcomes. We introduce a comprehensive data-driven methodological protocol -- BriDGE -- that combines advanced causal inference techniques, such as Directed Acyclic Graphs (DAGs), causal discovery algorithms, and Generalized Additive Models (GAMs), to enhance mechanistic insights in behavioural applications. BriDGE modifies conventional experimental analysis with a stepwise approach including DAG-based hypothesis formulation, modelling of nonlinear relationships with GAMs, and detailed mediation analysis. Using bootstrapping and sensitivity checks, BriDGE ensures robust and reliable detection of both direct and indirect effects. We use a simulation study to validate BriDGE's ability to identify complex causal mechanisms, offering researchers with a robust framework for deepening understanding of causal mechanisms and optimizing intervention design. There are natural limitations of BriDGE -- we discuss their implications when applied to public policy. We call for a greater integration of these methods in the toolkit of applied policy analysis to bridge the gap from “what works" to “why and how it works".

Abstract: Vegetarian diets can reduce global ecological costs. Yet meat continues to be culturally dominant, especially in the West. Does culture hamper the adoption of vegetarian diets? In an online experiment, we observed the intentions of 2,775 English participants to choose vegetarian food. We causally test if framing food options with culturally familiar names alters the effectiveness of a nudge promoting vegetarianism. Facing culturally familiar food does not change the effect of the nudge. However, exploratory analyses reveal that participants ask for lower monetary compensation for being forced to choose vegetarian food when it is culturally framed. Thus, welfare losses of hard policies, like bans, may be lower when alternative options look familiar.

Abstract: Behavioural nudges, such as defaults, improve human welfare by reducing choice overload. But how far should policy-makers go in reducing available choices?  Using a preregistered, online survey experiment, we randomly assign 1,518 UK citizens to two versions of the same opt-out default nudge aimed at encouraging charitable donations. In one version, the default was embedded in a list of multiple options, whereas in the other it was presented as a single choice. In both versions, participants could opt-out and choose any preferred donation amount. We find that when the default is embedded in a multiple-choice list, opting out rates and average individual donations are significantly higher compared to the standard single-choice default. Our findings suggest that encouraging active choosing alongside a default can improve agency without necessarily deteriorating behavioural outcomes.

Abstract: Respondents from around the world are financially incentivized to complete surveys in higher paying markets, and some respondents are even willing to falsify their credentials to do so. We propose a new cost-free method for identifying and excluding non-target respondents who see blank JavaScript-programmed experiments due to VPN usage. Using a dataset of 72,200 respondents in the G-7 countries, we show that 94 respondents (0.13\%) in our entire G-7 sample and 49 respondents (0.49\%) who report being from the United States are likely using virtual private networks (VPNs) to disguise their locations to qualify for surveys outside of their country. These non-target respondents provide low-quality responses, affecting external validity. Simple JavaScript programming can reject this rare type of non-target respondent from surveys administered using Qualtrics. 

Nudge+, a nudge for good thinkers.  Joint with Peter John. (Under consideration in Cambridge University Press)