Joshua R. Schwartzstein

Joshua R. Schwartzstein

Cahners-Rabb Professor of Business Administration

Cahners-Rabb Professor of Business Administration

Negotiation, Organizations & Markets
+1 (617) 496-5910
 
Joshua R. Schwartzstein
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(617) 496-5910
Featured Work Publications Research Summary Awards & Honors
Overview
Professor Schwartzstein uses the lens of behavioral economics to build more psychologically accurate assumptions into economic models, and he applies these models to create a more realistic understanding of market outcomes and optimal public policy.
Behavioral Hazard and Public Policy

It is well recognized that people overuse low-value medical care due to moral hazard—because copays are lower than costs. Now Professor Schwartzstein has introduced the concept of “behavioral hazard” to explain the opposite: people underuse high-value care because they underweight the benefits of, for example, taking medications for chronic diseases like diabetes or hypertension. He has derived optimal copay formulas that incorporate both moral and behavioral hazard. When both are taken into account, health insurance can do more than provide financial protection: it can also improve health care efficiency. Professor Schwartzstein’s findings and methods can be applied to other forms of social insurance and public policy problems.

Relative Thinking and Consumer Choice

Fixed differences appear smaller when compared to large differences. Professor Schwartzstein has proposed a model of relative thinking, in which a person weighs a given change by less when he compares it to a larger range. Relative thinking implies that a person is less likely to exert effort in a money-earning activity if he had expected to earn higher returns or if there is greater income uncertainty. Relative thinking also induces a tendency to overspend, and for a person to spend more freely if she is infrequently allotted large amounts to consume rather than frequently allotted small amounts. The model clarifies issues ranging from why insurance can encourage investment to the optimal scheduling of entitlements distributions.

Selective Attention and Learning

What do we notice, and how does this affect what we learn? Standard economic models of learning ignore memory by assuming that we remember everything. But there is growing recognition that memory is imperfect. Further, memory imperfections do not stem from limited recall alone; rather, not all information will be encoded into memory. Professor Schwartzstein has developed a model of belief formation that recognizes that attention is selective, and that we narrow our attention to what we currently believe is worthwhile. This model makes predictions about when people will attend to the right variables, when they will not, and what biased ideas may result. The key insight is that such inattention may compound itself—a person may persistently fail to learn what is worth attending to. In experimental research, Professor Schwartzstein has shown that seaweed farmers in Indonesia consistently failed to recognize a key variable in optimizing production—and that they did respond based on seeing summaries of the researchers’ data.

Joshua Schwartzstein is a Professor of Business Administration in the Negotiation, Organizations & Markets Unit. 

Professor Schwartzstein is a behavioral economist who focuses on incorporating psychologically realistic assumptions about (in)attention, memory, mental models, and perception into rigorous formal economic frameworks, with the aim of generating novel and practical insights with broad managerial relevance. His research has appeared in the Quarterly Journal of Economics, the American Economic Review, the Review of Economic Studies, the Journal of Economic Perspectives, the Journal of the European Economic Association, the Annual Review of Economics, and the Journal of Law and Economics. It has also been referenced in The New York Times, Science, and Health Affairs.

Professor Schwartzstein holds a PhD in economics from Harvard University and a BA in behavioral economics, economics, and mathematics from Cornell University.

Featured Work
"Using Models to Persuade"
American Economic Review 111, no.1 (January 2021): 276-323.
We present a framework where "model persuaders" influence receivers’ beliefs by proposing models that organize past data to make predictions. Receivers are assumed to find models more compelling when they better explain the data, fixing receivers’ prior beliefs. Model persuaders face a tradeoff: better-fitting models induce less movement in receivers’ beliefs. Consequently, a receiver exposed to the true model can be most misled by persuasion when that model fits poorly, competition between persuaders tends to neutralize the data by pushing towards better-fitting models, and a persuader facing multiple receivers is more effective when he can send tailored, private messages.
"Learning Through Noticing: Theory and Evidence from a Field Experiment"
Quarterly Journal of Economics 129, no.3 (August 2014): 1311-1315.
We consider a model of technological learning under which people "learn through noticing": they choose which input dimensions to attend to and subsequently learn about from available data. Using this model, we show how people with a great deal of experience may persistently be off the production frontier because they fail to notice important features of the data they possess. We also develop predictions on when these learning failures are likely to occur, as well as on the types of interventions that can help people learn. We test the model's predictions in a field experiment with seaweed farmers. The survey data reveal that these farmers do not attend to pod size, a particular input dimension. Experimental trials suggest that farmers are particularly far from optimizing this dimension. Furthermore, consistent with the model, we find that simply having access to the experimental data does not induce learning. Instead, behavioral changes occur only after the farmers are presented with summaries that highlight previously unattended-to relationships in the data.
"Behavioral Hazard in Health Insurance"
Quarterly Journal of Economics 130, no.4 (November 2015): 1623-1667.
A fundamental implication of standard moral hazard models is overuse of low-value medical care because copays are lower than costs. In these models, the demand curve alone can be used to make welfare statements, a fact relied on by much empirical work. There is ample evidence, though, that people misuse care for a different reason: mistakes or "behavioral hazard." Much high-value care is underused even when patient costs are low, and some useless care is bought even when patients face the full cost. In the presence of behavioral hazard, welfare calculations using only the demand curve can be off by orders of magnitude or even be the wrong sign. We derive optimal copay formulas that incorporate both moral and behavioral hazard, providing a theoretical foundation for value-based insurance design and a way to interpret behavioral "nudges." Once behavioral hazard is taken into account, health insurance can do more than just provide financial protection—it can also improve health care efficiency.
"Selective Attention and Learning"
Journal of the European Economic Association 12, no. 6 (December 2014): 1423-1452)
What do we notice and how does this affect what we learn and come to believe? I present a model of an agent who learns to make forecasts on the basis of readily available information, but is selective as to which information he attends to: he chooses whether to attend as a function of current beliefs about whether such information is predictive. If the agent does not attend to some piece of information, it cannot be recalled at a later date. He uses Bayes’ rule to update his beliefs given attended-to information, but does not attempt to fill in missing information. The model demonstrates how selective attention may lead the agent to persistently fail to recognize important empirical regularities, make systematically biased forecasts, and hold incorrect beliefs about the statistical relationship between variables. In addition, it identifies factors that make such errors more likely or persistent. The model is applied to shed light on stereotyping and discrimination, persistent learning failures and disagreement, and the process of discovery.
Journal Articles
Book Chapters
Working Papers
Cases and Teaching Materials
Research Summary
Overview
Professor Schwartzstein uses the lens of behavioral economics to build more psychologically accurate assumptions into economic models, and he applies these models to create a more realistic understanding of market outcomes and optimal public policy.
Behavioral Hazard and Public Policy

It is well recognized that people overuse low-value medical care due to moral hazard—because copays are lower than costs. Now Professor Schwartzstein has introduced the concept of “behavioral hazard” to explain the opposite: people underuse high-value care because they underweight the benefits of, for example, taking medications for chronic diseases like diabetes or hypertension. He has derived optimal copay formulas that incorporate both moral and behavioral hazard. When both are taken into account, health insurance can do more than provide financial protection: it can also improve health care efficiency. Professor Schwartzstein’s findings and methods can be applied to other forms of social insurance and public policy problems.

Relative Thinking and Consumer Choice

Fixed differences appear smaller when compared to large differences. Professor Schwartzstein has proposed a model of relative thinking, in which a person weighs a given change by less when he compares it to a larger range. Relative thinking implies that a person is less likely to exert effort in a money-earning activity if he had expected to earn higher returns or if there is greater income uncertainty. Relative thinking also induces a tendency to overspend, and for a person to spend more freely if she is infrequently allotted large amounts to consume rather than frequently allotted small amounts. The model clarifies issues ranging from why insurance can encourage investment to the optimal scheduling of entitlements distributions.

Selective Attention and Learning

What do we notice, and how does this affect what we learn? Standard economic models of learning ignore memory by assuming that we remember everything. But there is growing recognition that memory is imperfect. Further, memory imperfections do not stem from limited recall alone; rather, not all information will be encoded into memory. Professor Schwartzstein has developed a model of belief formation that recognizes that attention is selective, and that we narrow our attention to what we currently believe is worthwhile. This model makes predictions about when people will attend to the right variables, when they will not, and what biased ideas may result. The key insight is that such inattention may compound itself—a person may persistently fail to learn what is worth attending to. In experimental research, Professor Schwartzstein has shown that seaweed farmers in Indonesia consistently failed to recognize a key variable in optimizing production—and that they did respond based on seeing summaries of the researchers’ data.

Awards & Honors
Received Honorable Mention in 2016 for the Arrow Award for Best Paper in Health Economics from the International Health Economics Association for “Behavioral Hazard in Health Insurance” (Quarterly Journal of Economics, November 2015) with K. Baicker and S. Mullainathan.
Additional Information
Additional Information