A critical behavioural economics and behavioural science reading list

This reading list is a balance to the one-dimensional view in many popular books, TED talks, conferences, academic press releases and consultancy sales pitches. For those who feel they have a good understanding of the literature after reading Thinking Fast and Slow, Predictably Irrational and Nudge, this is for you. [In the time since I drafted the first version of this list in 2017, it’s fair to say that the balance has swung a bit.]

The purpose of this reading list is not to imply that all behavioural economics or behavioural science is bunk (it’s not). That said, I did not design the list to be balanced; you can combine this list with plenty of reading lists from elsewhere for that.

Please let me know if there are any other books or articles I should add, or if there are any particularly good replies to what I have listed. I am sure I have missed some good ones. I have set a mild quality bar on what I have included. I don’t agree with all the arguments, but everything on the list has at least one interesting idea.

1. Books

Gerd Gigerenzer, Peter Todd and the ABC Research Group, Simple Heuristics That Make Us Smart: Simple heuristics can be both fast and accurate, particularly when we assess real-life performance rather than conformity with the principles of rationality.

Doug Kenrick and Vlad Griskevicius, The Rational Animal: How Evolution Made Us Smarter Than We Think: A good introduction to the idea that evolutionary psychology could add a lot of value to behavioural economics, but has the occasional straw man discussion of economics and a heavy reliance on priming research (and you will see below how that is panning out).

David Levine, Is Behavioural Economics Doomed?: A good but slightly frustrating read. I agree with Levine’s central argument that rationality is underweighted, but the book is littered with straw man arguments.

Lionel Page, Optimally irrational: The Good Reasons We Behave the Way We Do: We should invest more in understanding why people behave the way they do.

Mario J. Rizzo and Glen Whitman, Escaping Paternalism: Rationality, Behavioral Economics, and Public Policy: An excellent critique of the traditional behavioural economists’ arguments for paternalism.

Phil Rosenzweig, Left Brain, Right Stuff: How Leaders Make Winning Decisions: An entertaining examination of how behavioural economics findings hold up for real world decision-making.

Gilles Saint-Paul, The Tyranny of Utility: Behavioral Social Science and the Rise of Paternalism: Sometimes hard to share Saint-Paul’s anger, but some important underlying points.

Hugo Mercier, Not Born Yesterday: The Science of Who We Trust and What We Believe: A strong argument that we are not gullible and easily manipulated, but rather skeptical and rational in the way we filter information.

Robert Sugden’s The Community of Advantage: A Behavioural Economist’s Defence of the Market: A well balanced critique from someone who has worked in the field for decades.

2. General and methodological critiques

Applied behavioural economics: In The death of behavioral economics, Jason Hreha argues that applied behavioural economics is on the way out. Scott Alexander responds.

Are we biased?: Gerd Gigerenzer debates Daniel Kahneman and Amos Tversky. Gigerenzer tees off (pdf). Kahneman and Tversky respond (pdf - this pdf also includes a rejoinder to Gigerenzer’s later piece). Gigerenzer returns (pdf). I’m a fan of a lot of Gigerenzer’s work, but his strength has never been the direct attack. Kahneman and Tversky get the better of this exchange. My post here.

As-if models: Nathan Berg and Gerd Gigerenzer note that behavioral economics is neoclassical economics in disguise (pdf of working paper). They write that “‘As-if’ arguments are frequently put forward in behavioral economics to justify ‘psychological’ models that add new parameters to fit decision outcome data rather than specifying more realistic or empirically supported psychological processes that genuinely explain these data.” Includes a critique of prospect theory’s lack of realism as a decision-making process.

Critiquing economics I: Ken Binmore argues (pdf) that the claim “economic man” is a failure can be both attacking a position not held by economics and ignoring the experimental evidence of people behaving like “economic man”.

Critiquing economics II: Pete Lunn and Tim Harford debate whether “the idea that the very foundations of economics are being undermined is absurd.”

The effectiveness of nudging: Mertens et al “found” that choice architecture interventions promote behavior change with a small to medium effect size. Andrew Gelman responds. Three articles in reply argue that most of the pooled effects in Mertens et al. are overestimated and hence unrepresentative, there is no evidence for nudging after correcting for publication bias, and there is no reason to expect large and consistent effects of nudge interventions. Some of the garbage in the meta-analysis led to a correction, although the papers from Brian Wansink remained (more on Wansink below).

Evolutionary theory I: Owen Jones proposes that “… Behavioral Economics, and those who rely on it, are falling behind with respect to new developments in other disciplines that also bear directly on the very same mysteries of human decision-making.”

Evolutionary theory II: Douglas Kenrick and colleagues argue that many of our biases are in fact deeply rational. (My post).

Ergodicity: Ole Peters proposes The ergodicity problem in economics. “[B]y carefully addressing the question of ergodicity, many puzzles besetting the current economic formalism are resolved in a natural and empirically testable way.” See also David Meder and friends’ Ergodicity-breaking reveals time optimal economic behavior in humans. My posts here, here and here.

Humility: In Aren’t we smart, fellow behavioural scientists, I suggest that “As applied behavioural scientists, we need to inject some humility into our assessment of other people’s decisions. … We need to stop making glib assumptions about what other people want and how they can best achieve their objectives.”

Lab experiments 1: Ken Binmore and Avner Shaked urge experimentalists to “join the rest of the scientific community in adopting a more skeptical attitude when far-reaching claims about human behavior are extrapolated from very slender data”. Fehr and Schmidt respond, as do Eckel and Gintis. Binmore and Shaked wrote a rejoinder.

Lab experiments 2: Steven Levitt and John List note that, while economic models can benefit from incorporating insights from psychology, “behavior in the lab might be a poor guide to real-world behavior.” (pdf).

Lab experiments 3: Steven Levitt and John List suggest that caution is required when attempting to generalise lab results out of sample.

Many co-authors: Emerging from the Francesca Gino frauds (see below) was the Many Co-authors project. For all studies in which Gino was involved, was Gino involved in data collection? The truly underwhelming element of this project is how rarely data has been made publicly available. Further, it once again highlights that shenanigans by people like Gino are only the tip of the iceberg. Here’s one outcome, a retraction of Don’t stop believing: Rituals improve performance by decreasing anxiety for which Gino was a co-author but not involved in data collection for most of the studies. Missing data and questionable data management all round. It’s best to retain the default of disbelief.

Megastudies: Do megastudies improve the impact of applied behavioural science? Katherine Milkman and friends argue so. My initial take and a later reflection suggest there are trade-offs and problems in execution.

Preferences: Gerardo Infante, Guilhem Lecouteux and Robert Sugden argue that Behavioural welfare economics does not model human psychology as it really is, but rather as “faulty Econs” (pdf). Daniel Hausman responds. Infante and friends provide a rejoinder (working paper pdf).

Pre-registration: Protzko and friends argue that rigour-enhancing practices such as confirmatory tests, large sample sizes, preregistration and methodological transparency increase replication rates. The problem: they didn’t preregister their own analysis. Jessica Hullman discusses here and here. My two cents. Andrew Gelman provides a nice summary following the retraction.

The need for theory I: David Levine and Jie Zheng propose that (pdf) Economic theory makes strong predictions about many situations and is generally quite accurate in predicting behavior in the laboratory. “In situations where the theory is thought to fail, the failure is in the application of theory rather than the theory failing to explain the evidence.”

The need for theory II: Michael Muthukrishna and Joseph Henrich argue that the replication crisis in the psychological sciences is a problem of lack of theory.

Replication: The Open Science Collaboration found that Thirty-six percent of psychology replications had significant results (pdf). Effect sizes were halved in magnitude. Social psychology fares particularly poorly.

Self criticism: Ariel Rubinstein notes that “[f]or Behavioral Economics to be a revolutionary program of research rather than a passing episode, it must become more open-minded and much more critical of itself.”

Too many biases: I argue that instead of building a messier and messier picture of human behavior, we need a new model.

WEIRD people: Joseph Henrich, Steven Heine and Ara Norenzayan propose that “we need to be less cavalier in addressing questions of human nature on the basis of data drawn from this particularly thin, and rather unusual, slice of humanity.” But see Cremieux on weirdness and two papers in response (1, 2).

3. Counterpoints to famous biases, effects and stories

The backfire effect: Daniel Engber reviews the evidence. I first saw doubts about the effect on WNYC.

Choice overload: Mark Lepper and Sheena Iyengar’s famous jam study (pdf). A meta-analysis by Benjamin Scheibehenne and friends (pdf) - the mean effect size of changing the number of choices across the studies was virtually zero (although note the Brian Wansink studies in the meta-analysis!). Other studies point to conditions where it might occur, such as Chernev and friends who identify some factors that facilitate choice overload.

Depletion of willpower: Daniel Engber summarises the state of affairs. The meta-analysis referred to by Engber. And the failed replication that triggered the article.

Disfluency: The original N=40 paper (pdf). The N=7000 replication (pdf). Terry Burnham tells the story. (And interestingly, Adam Alter, author of the first paper, suggests that the law of small numbers should be more widely known).

Dishonest bankers: Cohn and colleagues argue that “When their professional identity as bank employees is rendered salient, a significant proportion of them become dishonest”. But look at the data more closely, and primed bankers cheat no more than the student controls. See also Rahwan and friends for a failed replication.

The Florida effect: The poster child for the replication crisis. Ed Yong catalogues the story nicely.

Grit: Daniel Engber reviews Angela Duckworth’s book. I review. (I like the way Angela Duckworth deals with criticism. Also listen to this Econtalk episode.)

Growth mindset: The Wikipedia summary. Scott Alexander’s initial exploration and clarification. A pre-registered study and meta-analysis both showing a tiny but apparently real effect. A more recent meta-analysis concludes that “Across all studies, we observed a small overall effect … which was nonsignificant after correcting for potential publication bias. … We conclude that apparent effects of growth mindset interventions on academic achievement are likely attributable to inadequate study design, reporting flaws, and bias.”

The hot hand illusion: The original Thomas Gilovich, Robert Vallone and Amos Tversky paper arguing people are seeing a hot hand in basketball when none exists. Work by Joshua Miller and Adam Sanjurjo (working paper pdf) shows the original argument was based on a statistical mistake. The hot hand does exist in basketball. (Although I will say that there is plenty of evidence of people seeing patterns where they don’t exist.) ESPN explores. My post here.

Hungry judges: Shai Danziger and friends find that favourable rulings by Israeli parole boards plunge in the lead up to meal breaks (from 65% to near 0). Andreas Glockner suggests this might be a statistical artefact. Keren Weinshall-Margela and John Shapard point out that the hearing order is not random (Danziger and friends respond). And Daniel Lakens suggests we should dismiss the finding as simply being impossible. My post here. A similar analysis of judges during Ramadan (working paper pdf) finds the opposite effect - they are more lenient when hungry.

Hyperbolic discounting: Ariel Rubinstein points out that (pdf) “the same type of evidence, which rejects the standard constant discount utility functions, can just as easily reject hyperbolic discounting as well.”

Illusion of control: Francesca Gino, Zachariah Sharek and Don Moore note that illusion of control experimental results can be statistical artefacts (pdf). “[B]y focusing on situations marked by low control, prior research has created the illusion that people systematically overestimate their level of control.” My post here.

Loss aversion I: David Gal and Derek Rucker claim that (working paper) “current evidence does not support that losses, on balance, tend to be any more impactful than gains.” E. Tory Higgins and Nira Liberman respond, as do Itamar Simonson and Ran Kivetz. Gal and Rucker rejoinder (working paper pdf). My post here. Mrkva and friends also add to the debate.

Loss aversion II: Eldad Yechiam makes a related argument in Acceptable losses: the debatable origins of loss aversion (pdf). My post here. Also see Scott Alexander.

Money priming: Doug Rohrer, Harold Pashler and Christine Harris find that subtle reminders of money don’t change people’s political views (pdf). Kathleen Vohs fights back (pdf). Miguel Vadillo, Tom Hardwicke and David R. Shanks respond. Analysis of the broader literature on money priming suggests, among other things, massive publication bias.

Moral reminders: The original (N = 229) paper co-authored by Nina Mazar, On Amir and Dan Ariely (pdf). The (N=5,786) multi-lab replication by Verschuere and friends: “This small effect was numerically in the opposite direction of the original study.” More recently, an investigation into the data provenance has led to an Expression of Concern. Relatedly, here and here are posts analysing the “shredders” used in some of Ariely’s honesty experiments.

Organ donation: Does Austria have a 99.94% organ donation rate because of the design of their driver’s licence application? No.

Overconfidence: Don Moore and Paul Healy address the many concepts tangled up in the word “overconfidence”” (pdf). [My post]/overconfident-about-overconfidence/).

Power pose: Jesse Singal on Dana Carney’s shift from author of the classic power pose paper (pdf) to skeptic. Carney’s posted a document about her shift on her website.

Priming mating motives: Shanks and friends on Romance, risk, and replication: Can consumer choices and risk-taking be primed by mating motives? (pdf): A failed replication, plus “a meta-analysis of this literature reveals strong evidence of either publication bias or p-hacking.” (I have cited some of these studies approvingly in published work - a mistake.)

Prospect theory: The prospect theory model, the centrepiece of behavioural economics, has us as loss averse and risk seeking when facing losses, and risk averse when considering gains. Ryan Oprea proposes that most of the evidence underlying theories of risk, such as prospect theory, actually reflect mistakes under complexity.

Safety signs kill motorists: Hall and Madsen proposed that dynamic signs that reported Texas road fatalities - “1669 deaths this year on Texas roads” - caused more accidents and fatalities. I argue that we shouldn’t take too much from this single paper.

Scarcity: My review of the book. Reanalysis of the original scarcity paper (pdf) without dichotomising income eliminated the effect. The original authors managed to resurrect the effect (pdf) by combining the data from three experiments, but once you are at this point, you have well and truly entered the garden of forking paths. Leandro Carvalho and friends found that “participants surveyed before and after payday performed similarly on a number of cognitive function tasks.” Then, in a replication of scarcity papers by O’Donnell and friends: “Of the 20 studies that were significant in the original, four of our replication efforts yielded significant results.”

Signing at the top, part I: Lisa Shu and friends report in PNAS that “signing before—rather than after—the opportunity to cheat makes ethics salient when they are needed most and significantly reduces dishonesty.” Ariella Kristal, Ashley Whillans and the authors of the original paper report a failed replication. A discussion of what this means in Scientific American. That, of course, is only the beginning of the story (see the fraud story below).

4. Fraud and misconduct

The Cornell Food and Brand Lab’s catalogue of eating biases (led by Brian Wansink): Jesse Singal catalogues the events. Stephanie Lee’s reviews emails from the lab. Corrections and retractions are flowing. It’s fair to say that we shouldn’t place any weight on results out of that lab. (Although somewhat amazingly, Wansink’s experiment with a bottomless soup bowl replicated! I didn’t believe the original experiment ever existed - and am still doubtful that it did.)

Diederik Stapel: For a long-time, the most salient fraud in social science. The NYT tells the story. My favourite (now retracted) study of his was on how trash-filled environments make people racist. For a long time I thought of Stapel as an extreme but rare case of fraud. I now believe fraud is common, but most people don’t leave such a trail.

Francesca Gino: In a series of four posts (1, 2, 3, 4), the Data Colada team document a series of frauds in Francesca Gino’s work. Failing to recall Barbara Streisand’s experience, Gino sued the Data Colada team. The lawsuit was later dismissed (although as at the time of writing, Gino’s claim against Harvard remains ongoing). Fortunately, the Harvard investigation was made public as a result of the court proceedings, allowing even more analysis by the Data Colada team into how the fraud was perpetrated.

Signing at the top, part II: The field trial data from the signing at the top study (noted above) was completely made up. This led to the paper being retracted and an investigation into Ariely (that ultimately reached no adverse findings). That, of course, was only one of two frauds in this paper. The other, also uncovered by the Data Colada team, was that the data in experiment 1 had been manipulated. Absent the manipulation, there was no effect.

5. Applications of behavioural economics (and nudging)

Government failure I: In Homo economicus or homo paleas?, John Cochrane states that “The case for the free market is not that each individual’s choices are perfect. The case for the free market is long and sorry experience that government bureaucracies are pretty awful at making choices for people.” Noah Smith responds.

Government failure II: Ted Gayer writes that “the main failure of rationality is not with the energy-using consumers and firms, but instead the main failure of rationality is with the regulators themselves.” Two related papers by Gayer and W. Kip Viscusi are Overriding Consumer Preferences With Energy Regulations (pdf) and Behavioral Public Choice: The Behavioral Paradox of Government Policy (pdf)

Implementation: DellaVigna, Kim and Linos find that a nudge trial with a negative result is almost as likely to be implemented as a positive result.

A manifesto for applying behavioural science: Michael Hallsworth writes a manifesto for applying behavioural science (longer and ungated BIT version here). A few observations from me.

More than nudging I: Reuben Finighan looks beyond nudging (pdf), stating that “Policymakers often mistakenly see behavioural policy as synonymous with”nudging”. Yet nudges are only one part of the value of the behavioural revolution—and not even the lion’s share”

More than nudging II: George Loewenstein and Nick Chater put nudges in perspective, writing that “This paper aims to remind policy-makers that behavioural economics can influence policy in a variety of ways, of which nudges are the most prominent but not necessarily the most powerful.” Richard Thaler responds. Chater and Loewenstein later took this critique further, arguing that the belief that society’s problems can be addressed cheaply and effectively at the level of the individual, without modifying the system in which the individual operates, is a mistake.

Paternalism: Robert Sugden writes that (pdf) “The claim that the paternalist is merely implementing what the individual would have chosen for herself under ideal conditions is a common theme in paternalistic arguments, but should always be viewed with scepticism.” Also see Sugden’s Do people really want to be nudged towards healthy lifestyles?, Sunstein’s response (pdf) and Sugden’s rejoinder.

Policy failure I: Philip Booth notes that “We seem to have gone … to a situation where we have regulators who use economics 101 supplemented with behavioural economics to try to bring perfection to markets that simply cannot be perfected and perhaps cannot be improved.”

Policy failure II: Tim Harford writes that “The appeal of a behavioural approach is not that it is more effective but that it is less unpopular.” (Google the article and go through that link if you hit the paywall.)

Policy failure III: George Loewenstein and Peter Ubel argue that “behavioral economics is being used as a political expedient, allowing policymakers to avoid painful but more effective solutions rooted in traditional economics.”

Policy failure IV: In a Behavioural and Brain Sciences target article, George Loewenstein and Nick Chater argue that focussing on interventions at the individual level is inadvertently preventing systemic change. There are many responses, but I’ll highlight those by Michael Hallsworth, David Gal and Derek Rucker, Cass Sunstein, Richard Thaler and Ralph Hertwig.

6. If you want some background

I know this list is of critiques, but here are a few books I would recommend if you want a basic background.

Daniel Kahneman’s Thinking, Fast and Slow is still the best popular overview of behavioural science. However, it is not standing the test of time particularly well. Here is a fantastic analysis of the priming chapter, and Kahneman’s response to that review in the comments. A review of the estimated replicability of all the chapters is similarly damming. It’s unfortunate that something better hasn’t yet emerged. Just pair it with this reading list!

Erik Angner’s A Course in Behavioral Economics is a good and readable academic presentation of the core principles of behavioural economics.

Cass Sunstein and Richard Thaler’s Nudge: The Final Edition is not my favourite book, but it’s a useful to understand the mindset of many nudge proponents.

Richard Thaler’s Misbehaving is a pretty good (although very US-centric) history of behavioural economics.

Michael Lewis’s The Undoing Project is an accessible overview of Kahneman and Tversky’s work.

Michael Hallsworth and Elspeth Kirkman’s Behavioral Insights is a solid book on translating behavioural science into applied public policy.