Thomas Graeber

Photo Thomas Graeber Assistant Professor, Harvard Business School
Associate Editor, Journal of the European Economic Association

My research is in behavioral and experimental economics.
I teach Negotiation in the MBA curriculum.

[cv]     [Harvard faculty page]     [contact: tgraeber@hbs.edu]

Office location: Baker Library | Bloomberg Center 440



Current Research

Behavioral Attenuation
with Benjamin Enke, Ryan Oprea and Jeffrey Yang
[abstract]   [pdf]   [latest version: September 6, 2024]

We report a large-scale examination of behavioral attenuation: due to information-processing constraints, the elasticity of people’s decisions with respect to economic fundamentals is generally too small. We implement more than 30 experiments, 20 of which were crowd-sourced from leading experts. These experiments cover a broad range of economic decisions, from choice and valuation to belief formation, from strategic games to generic optimization problems, involving investment, savings, effort supply, product demand, taxes, environmental externalities, fairness, cooperation, beauty contests, information disclosure, search, policy evaluation, memory, forecasting and inference. In 93% of our experiments, the elasticity of decisions to fundamentals decreases in participants’ cognitive uncertainty, our measure of the severity of information-processing constraints. Moreover, in decision problems with objective solutions, we observe elasticities that are universally smaller than is optimal. Many widely-studied decision anomalies represent special cases of behavioral attenuation. We discuss both its limits and why it often gives rise to the classic phenomenon of diminishing sensitivity.

Lost in Transmission
with Shakked Noy and Chris Roth
[abstract]   [pdf]   [latest version: November 17, 2024]

How does word-of-mouth transmission distort economic information? We pay participants to listen to audio recordings containing economic forecasts and accurately transmit the information through voice messages. Other participants listen to an original or a transmitted recording before stating incentivized beliefs. Across various transmitter incentive schemes, a forecast's reliability is lost in transmission at a far higher rate than the forecast’s level. Reliable and unreliable information, once filtered through transmission, impact listener beliefs similarly. Mechanism experiments show that information about reliability is not perceived as less relevant or harder to transmit, but is less likely to come to mind during transmission.

Explanations
with Chris Roth and Constantin Schesch
[abstract]   [pdf]   [latest version: June 25, 2024]

When people exchange knowledge, both truths and falsehoods can proliferate. We study the role of explanations for the spread of truths and falsehoods in 15 financial decision tasks. Participants record the reasoning behind each of their answers with incentives for accuracy of their listeners’ responses, providing over 6,900 unique verbal explanations in total. A separate group of participants either only observe one orator’s choice or additionally listen to the corresponding explanation before making their own choice. Listening to explanations strongly improves aggregate accuracy. This effect is asymmetric: explanations enable the spread of truths, but do not curb the contagion of falsehoods in knowledge exchange. To study mechanisms, we extract every single argument provided in the explanations, alongside a large collection of speech features, revealing the nature of financial reasoning on each topic. Explanations for truths exhibit a significantly richer message space and higher argument quality than explanations for falsehoods. These content differences in the supply of explanations for truths versus falsehoods account for 60% of their asymmetric benefit, whereas orator and receiver characteristics play a minor role.

Stories, Statistics, and Memory
Forthcoming at The Quarterly Journal of Economics
with Chris Roth and Florian Zimmermann
[abstract]   [pdf]  

For many decisions, we encounter relevant information over the course of days, months or years. We consume such information in various forms, including stories – qualitative content about individual instances – and statistics – quantitative data about collections of observations. This paper proposes that information type – story versus statistic – shapes selective memory. In controlled experiments, we document a pronounced story-statistic gap in memory: the average impact of statistics on beliefs fades by 73% over the course of a day, but the impact of a story fades by only 32%. Guided by a model of selective memory, we disentangle different mechanisms and document that similarity relationships drive this gap. Recall of a story increases when its qualitative content is more similar to a memory prompt. Irrelevant information in memory that is similar to the prompt, on the other hand, competes for retrieval with relevant information, impeding successful recall.

Complexity and Time
Conditionally Accepted at The Journal of the European Economic Association
with Benjamin Enke and Ryan Oprea
[abstract]   [pdf]   [latest version: Aug 5, 2024]

A large literature shows that people’s valuation of delayed financial rewards violates exponential discounting, exhibiting a hyperbolic pattern: high short-run impatience that strongly decreases in the length of the delay. We test the hypothesis that the hyperbolic pattern in measured discount rates reflects mistakes driven by the complexity of evaluating delayed payoffs. We document that hyperbolicity (i) is strongly associated with choice inconsistency and cognitive uncertainty, (ii) increases in overt complexity manipulations and (iii) arises nearly identically in computationally similar tasks that involve no actual payoff delays. Our results suggest that even if people had exponential discount functions, complexity-driven mistakes would cause them to make hyperbolic choices. We examine which experimental techniques to estimate present bias are (not) confounded by information-processing constraints.

Translating Information Into Action
Revised for The American Economic Review
with Reshmaan Hussam, Kailash Pandey, Abu Shonchoy and Chikako Yamauchi
[abstract]   [pdf]   [latest version: July 3, 2024]

While models of technology adoption posit learning as the basis of behavior change, information campaigns in public health frequently fail to change behavior. We design an information campaign embedding hand-hygiene edutainment within popular dramas using mobile phones, randomly distributed to households in Bangladesh. We document substantial improvements in handwashing and health, yet no change in hygiene knowledge. Guided by a framework of learning with frictions, we find evidence that recent edutainment exposure - as reminders - and cumulative exposure - by forming cue-action associations - generate behavior change, but not learning strategies that rely on assessing the actual returns to handwashing.

"De Gustibus" and Disputes about Reference Dependence
Revised for The Review of Economic Studies
with Pol Campos-Mercade, Lorenz Goette, Alex Kellogg and Charles Sprenger
[abstract]   [pdf]   [latest version: November 10, 2023]

Existing tests of reference-dependent preferences assume universal loss aversion. This paper examines the implications of heterogeneity in gain-loss attitudes for such tests. In experiments on labor supply and exchange behavior we measure gain-loss attitudes and then study a canonical treatment effect that distinguishes different models of reference dependence. We document substantial heterogeneity in gain-loss attitudes and evidence against universal loss aversion. We then document heterogeneous treatment effects over gain-loss attitudes consistent with formulations of expectations-based reference points. Assuming homogeneous preferences would lead to different and possibly incorrect conclusions in these tests. Our findings provide foundational support for reference points derived from expectations, and reconcile inconsistencies across prior exercises.

The Complexity of Economic Decisions
with Xavier Gabaix
[abstract]   [pdf]   [latest version: August 24, 2024]

We propose a theory of the complexity of economic decisions. Leveraging a macroeconomic framework of production functions, we conceptualize the mind as a cognitive economy, where a task’s complexity is determined by its composition of cognitive operations. Complexity emerges as the inverse of the total factor productivity of thinking about a task. It increases in the number of importance-weighted components and decreases in the degree to which the effect of one or few components on the optimal action dominates. Higher complexity generates larger decision errors and behavioral attenuation to variation in problem parameters. The model applies both to continuous and discrete choice. We develop a theory-guided experimental methodology for measuring subjective perceptions of complexity that is simple and portable. A series of experiments test and confirm the central predictions of our model for perceptions of complexity, behavioral attenuation, and decision errors. We provide a template for applying the framework to core economic decision domains, and then develop several applications including the complexity of static consumption choice with one or several interacting goods, consumption over time, the tax system, forecasting, and discrete choice between goods.


Publications

Intertemporal Altruism
with Felix Chopra and Armin Falk
(American Economic Journal: Microeconomics, 2024, vol 16 (1), pp. 329–357
[abstract]   [pdf]  

Most prosocial decisions involve intertemporal trade-offs. Yet, the timing of prosocial utility flows is ambiguous and bypassed by most models of other-regarding preferences. We study the behavioral implications of the time structure of prosocial utility, leveraging a conceptual distinction between consequence-dated and choice-dated utility flows. We conduct a high-stakes donation experiment that comprehensively characterizes discounting behavior in self–other trade-offs and allows us to identify different prosocial motives from their distinct time profiles. Our data can only be explained by a combination of choice- and consequence-dated prosocial utility. Both motives are pervasive and negatively correlated at the individual level.

Cognitive Uncertainty  
with Benjamin Enke
(The Quarterly Journal of Economics, 2023, vol 138 (4), pp. 2021–2067
[abstract]   [pdf]  

This article documents the economic relevance of measuring cognitive uncertainty: people’s subjective uncertainty over their ex ante utility-maximizing decision. In a series of experiments on choice under risk, the formation of beliefs, and forecasts of economic variables, we show that cognitive uncertainty predicts various systematic biases in economic decisions. When people are cognitively uncertain—either endogenously or because the problem is designed to be complex—their decisions are heavily attenuated functions of objective probabilities, which gives rise to average behavior that is regressive to an intermediate option. This insight ties together a wide range of empirical regularities in behavioral economics that are typically viewed as distinct phenomena or even as reflecting preferences, including the probability weighting function in choice under risk; base rate insensitivity, conservatism, and sample size effects in belief updating; and predictable overoptimism and -pessimism in forecasts of economic variables. Our results offer a blueprint for how a simple measurement of cognitive uncertainty generates novel insights about what people find complex and how they respond to it.

Confidence, Self-Selection and Bias in the Aggregate  
with Benjamin Enke and Ryan Oprea
(The American Economic Review, 2023, vol. 113 (7), pp. 1933-1966)
[abstract]   [pdf]

The influence of behavioral biases on aggregate outcomes depends in part on self-selection: whether rational people opt more strongly into aggregate interactions than biased individuals. In betting market, auction and committee experiments, we document that some errors are strongly reduced through self-selection, while others are not affected at all or even amplified. A large part of this variation is explained by differences in the relationship between confidence and performance. In some tasks, they are positively correlated, such that self-selection attenuates errors. In other tasks, rational and biased people are equally confident, such that self-selection has no effects on aggregate quantities.

Inattentive Inference  
(Journal of the European Economic Association, 2023, vol. 21 (2), pp. 560–592)
[abstract]   [pdf]

This paper studies how people infer a state of the world from information structures that include additional, payoff-irrelevant states. For example, learning from a customer review about a product’s quality requires accounting for the reviewer’s otherwise-irrelevant taste. This creates an attribution problem common to all information structures with multiple causes. We report controlled experimental evidence for pervasive overinference about states that affect utility – a form of “omitted variable bias” in belief updating –, providing an explanation for various misattribution patterns. In studying why systematic misattribution arises, we consistently find that errors are not due to deliberate effort avoidance or a lack of cognitive capacity. Instead, people behave as if they form incomplete mental models of the information structure and fail to notice the need to account for alternative causes. These mental models are not stable but context-dependent: misattribution responds to a variety of attentional manipulations, but not to changes in the costs of inattention.

Measuring the Scientific Effectiveness of Contact Tracing: Evidence from a Natural Experiment
with Thiemo Fetzer
(Proceedings of the National Academy of Sciences, 2021, vol. 118 (33))
[abstract]   [pdf]

Contact tracing has for decades been a cornerstone of the public health approach to epidemics, including Ebola, severe acute respiratory syndrome, and now COVID-19. It has not yet been possible, however, to causally assess the method’s effectiveness using a randomized controlled trial of the sort familiar throughout other areas of science. This study provides evidence that comes close to that ideal. It exploits a large-scale natural experiment that occurred by accident in England in late September 2020. Because of a coding error involving spreadsheet data used by the health authorities, a total of 15,841 COVID-19 cases (around 20% of all cases) failed to have timely contact tracing. By chance, some areas of England were much more severely affected than others. This study finds that the random breakdown of contact tracing led to more illness and death. Conservative causal estimates imply that, relative to cases that were initially missed by the contact tracing system, cases subject to proper contact tracing were associated with a reduction in subsequent new infections of 63% and a reduction insubsequent COVID-19–related deaths of 66% across the 6 wk following the data glitch.

Bayesian signatures of confidence and central tendency in perceptual judgment  
with Yang Xiang, Benjamin Enke and Samuel Gershman  
(Attention, Perception & Psychophysics, 2021)
[abstract]   [pdf]

This paper theoretically and empirically investigates the role of Bayesian noisy cognition in perceptual judgment, focusing on the central tendency effect: the well-known empirical regularity that perceptual judgments are biased towards the center of the stimulus distribution. Based on a formal Bayesian framework, we show that measures of subjective confidence can be used to explain the central tendency effects and response variability through a Bayesian lens. Specifically, our model clarifies that lower subjective confidence as a measure of posterior uncertainty about a judgment should predict (i) a lower sensitivity of magnitude estimates to objective stimuli; (ii) a higher sensitivity to the mean of the stimulus distribution; (iii) a stronger central tendency effect at higher stimulus magnitudes; and (iv) higher response variability. To test these predictions, we collect a tailored large-scale experimental data set and additionally re-analyze perceptual judgment data from several previous experiments. Across data sets, subjective confidence is strongly predictive of the central tendency effect and response variability, both correlationally and when we exogenously manipulate the magnitude of sensory noise. Our results lend support to Bayesian explanations of both confidence and the central tendency effect.

Delayed Negative Effects of Prosocial Spending on Happiness
with Armin Falk
(Proceedings of the National Academy of Sciences, 2020, vol. 117 (12), pp. 6463-6468)
[abstract]   [pdf]  

Does prosocial behavior promote happiness? We test this longstanding hypothesis in a behavioral experiment that extends the scope of previous research. In our Saving a Life paradigm, every participant either saved one human life in expectation by triggering a targeted donation of 350 euros or received an amount of 100 euros. Using a choice paradigm between two binary lotteries with different chances of saving a life, we observed subjects’ intentions at the same time as creating random variation in prosocial outcomes. We repeatedly measured happiness at various delays. Our data weakly replicate the positive effect identified in previous research but only for the very short run. One month later, the sign of the effect reversed, and prosocial behavior led to significantly lower happiness than obtaining the money. Notably, even those subjects who chose prosocially were ultimately happier if they ended up getting the money for themselves. Our findings revealed a more nuanced causal relationship than previously suggested, providing an explanation for the apparent absence of universal prosocial behavior.