The challenges of behavioural insights for effective policy design

ABSTRACT

Behavioural insights are becoming increasingly popular with policy practitioners. Findings and methods originally provided by cognitive psychology and later behavioural economics have found use in the formulation of public policies. Their most popularised application has emerged under the auspices of libertarian paternalism in the form of ‘nudging’. Its proponents claim to provide a new instrument to facilitate the formulation of effective and evidence-based policy, taking people’s actual behaviour into account from the outset, while preserving their liberty to choose. This article reviews the origins of libertarian paternalism and the behavioural insights it builds on and takes a critical look at the foundations nudging relies on as a policy tool. It also discusses the ongoing efforts to build policy capacity to integrate behavioural insights and experimental methods in the creation of public policy. Behavioural insights offer a powerful tool to reshape and design new evidence-based policy. However, designers ought to be aware of the underlying assumptions on individual behaviour, the broadness of the mandate the nudging approach claims and the challenges they pose for design effectiveness.

KEYWORDS:

• Libertarian paternalism
• nudging
• behavioural economics
• heuristics and biases
• policy effectiveness

Acknowledgments

I wish to thank two anonymous reviewers, Luigi Bobbio, Gilberto Capano, Bruno Heyndels, Michael Howlett, Benny Geys, Jona Linde, M Ramesh, Rasmus Wiese and the participants of the following meetings for their comments and suggestions on earlier drafts: the GDN II Workshop on Effective Policy Design (Florence, November 2016), the Annual Meeting of the European Public Choice Society (Budapest, April 2017) and the 3^rd International Conference on Public Policy (Singapore, June 2017).

Disclosure statement

No potential conflict of interest was reported by the author.

Notes

¹ See Page (2006) for a more differentiating discussion of the term ‘policy’ and its different levels of meaning.

² Of course, not all policies are the result of conscious design. Many are simply the outcome of ad hoc decision-making, bargaining or other ‘non-design’ processes (Capano & Howlett, 2015; Howlett, 2014). This article abstracts from these instances to the benefit of a deliberate design process.

³ Views on the emergence of rational choice theory and its implications for the development of economics and political science differ between the disciplines. For a political science focused summary of common rational choice theories see Jones (2001). See Amadae and Bueno de Mesquita (1999) for a review of their development and use.

⁴ The concept of the self-interested agent obviously predates EUT and is often traced back to Adam Smith’s self-interested butcher, brewer and farmer (Smith, 1776/2010, p. 9-10) and to the works of John Stuart Mill on political economy. The term ‘economic man’ and its Latin form Homo oeconomicus arose in the early nineteenth century as criticism of such an understanding of human interests, see Oxford English Dictionary and Pareto (1906/2014).

⁵ The anchoring bias describes people’s tendency of overweighting initial (and potentially irrelevant) pieces of information regardless of their probability of occurrence in making (numeric) judgements. Such behaviour has been shown to influence housing prices (Northcraft & Neale, 1987), consumer’s willingness to pay for products (Ariely, Loewenstein, & Prelec, 2003) and salary negotiations (Thorsteinson, 2011). Overconfidence is mostly related with the overestimation of the accuracy of one’s own estimates or of one’s own performance. It is rooted in a bias in the estimation of subjective probabilities. The availability bias describes people’s tendency to overestimate the probability of events for which they can easily recall an example. For instance, the rate of airplane crashes.

⁶ Note that some authors categorise the described and other biases in terms of ‘bounded rationality’, ‘bounded willpower’ and ‘bounded self-interest’ (Jolls et al., 1998). The first two categories roughly mirror the distinctions made above, whereas ‘bounded self-interest’ captures aspects of altruism, fairness and reciprocity considerations (see below). Given that particularly the term ‘bounded rationality’ has been used differently across literatures, I will abstain from its use.

⁷ In general, advances in clinical methods have provided new avenues for research on decision-making, moving from analysing the expressed choices of people to the underlying cognitive functions of the brain (Camerer, Loewenstein, & Prelec, 2005; De Martino, Kumaran, Seymour, & Dolan, 2006; Sanfey & Chang, 2008; Sanfey et al., 2006). See Felsen and Reiner (2015) for a specific discussion on the potential role of neuroscience in the debate on nudging.

⁸ In a turn of tables, some economists argue that behavioural economics is simply a return to the origins of economic theory after venturing off into the neoclassical world of axiomatic rationality. As Camerer, Loewenstein and Rabin (2004, p. 5) put it:

'When economics first became identified as a distinct field of study, psychology did not exist as a discipline. Many economists moonlighted as the psychologists of their time. […] For example, Adam Smith commented (1790/2005, p. 192) that "we suffer more ... when we fall from a better to a worse situation, than we ever enjoy when we rise from a worse to a better". Loss aversion!'

⁹ Source: https://en.oxforddictionaries.com/definition/behavioural_economics, accesses 27 February 2018.

¹⁰ In the same vein, and not surprisingly given the origin of the research agenda, Daniel Kahneman (2013) has argued for the use of the term applied behavioural science.

¹¹ In the case of an unhealthy diet, for example, the costs of increased health care spendings to treat obesity and related health issues.

¹² See Sugden (2013) for a discussion of this point of view in welfare economics and of a contractarian alternative in which welfare maximisation results from mutually beneficial agreements between individuals without a central planner.

¹³ Whether ex-ante preferences exist or preferences are elicited during the decision-making process is a separate point of debate (see, for instance, Fischhoff & Manski, 2000; Tversky & Thaler, 1990).

¹⁴ See also the discussion by Qizilbash (2012) of the applicability of the informed desire account to the welfare considerations of Thaler and Sunstein (2008).

¹⁵ Another objection lies in the understanding of preference ordering and individual-level maximising. Even if a policy designer wants to act benevolently, the two-system approach of Thaler and Sunstein (2003, 2008) aims at maximising the target’s individual welfare (however defined), not at increasing the utility a rational target would maximise given the chance. The preferences a person holds, whether coherent or biased, are subjectively ordered and the utility a person gets from their fulfilment are impossible for a third party to judge or even presuppose. Without the instrument of revealed preferences, interventions are necessarily based on the interpretations of the planner which preferences are ‘real’ or meaningful and the chosen definition of welfare (Mitchell, 2005; Sugden, 2008).

¹⁶ There is an ongoing debate on debiasing as a preferable approach to nudging to maintain freedom of choice and limit paternalistic intervention in response to cognitive biases, see, for instance, Gigerenzer (2015) and Mitchell (2005).

¹⁷ This is an interesting proposition in a world Thaler and Sunstein (2008) construct to show that the intervention itself would be highly effective and argue that governmental choice designers ought to be trusted.

¹⁸ Note that leaving the arrangement as it currently is does not feature as an option. Thaler and Sunstein (2008) argue that any arrangement is taken to have a large effect, and therefore, the current display cannot be neutral either.

¹⁹ This starting point for an argument for paternalistic policies is interesting also for discussing an intervention on, of all possible target groups, children’s choices. They are probably the least contentious group to argue for paternalistic intervention (as the origin of the word may suggest) and the least appropriate to be steered towards choices that make them ‘better off, as judged by themselves’ (Thaler & Sunstein, 2008, p. 5). For completeness, it should be mentioned that an earlier version of the example features adults as customers (Sunstein & Thaler, 2003). See Rebonato (2012) for a more detailed discussion of this and other examples.

²⁰ Note that this is one example where a nudge would not qualify as being paternalistic, given that it by definition will not benefit the interfered with individual.

²¹ See also Kuehnhanss (2018) for a discussion of nudging relative to information-based tools. The distinctions between different ‘kinds’ of nudges will not be discussed in this article. See, however, Baldwin (2014) and Hansen and Jespersen (2013) for categorisations and discussions of nudges according to their impact on the autonomy of the target and their transparency, respectively.

²² See Klick and Mitchell (2006) for a discussion of the effect of paternalistic policies on, among other factors, the learning capabilities of its targets.

²³ Note that the previous New Labour government had already taken first steps towards using behavioural insights in some of its strategy papers and specific policies concerning the environment, finance and health (Halpern, Bates, Beales, & Heathfield, 2004; Whitehead, Jones, & Pykett, 2011). The Behavioural Insights Team was privatised in the form of a social purpose company in 2014. It is part owned by the Cabinet Office.

²⁴ Note that information provision is not necessarily a nudge and the mentioned examples have been argued to reflect classic persuasion and signalling of authority (Mols et al., 2015).

²⁵ See http://blogs.ec.europa.eu/eupolicylab/portfolios/biap-country_overviews/ for an actively maintained overview.

Additional information

Funding

This work was financially supported by the Research Foundation Flanders (FWO) in the form of a PhD fellowship [Grant No. 11V2117N].

Notes on contributors

Colin R. Kuehnhanss

Colin R. Kuehnhanss is a postdoctoral researcher at the Department of Applied Economics of the Vrije Universiteit Brussel, Belgium. His research interests include political economy, behavioural economics, and political decision-making. Previous work was published in the European Journal of Political Economy, JCMS: Journal of Common Market Studies, Journal of Economic Psychology, and Public Administration.