Alain Enthoven on fragmented American health care

 Writing in Health Affairs, Alain Enthoven notes that most American workers insured through their jobs work for self-insured employers, i.e. employers who themselves pay for the health care of their covered lives. This means that many of them are relatively small buyers of health insurance, which leads them to deal with fee for service providers, rather than big health maintenance organizations, which might be a better model for a national health care system.

Employer Self-Funded Health Insurance Is Taking Us In The Wrong Direction by Alain C. Enthoven

"The 2020 Kaiser Family Foundation Survey of Employer Health Benefits reports that 67 percent of employed, insured workers are covered under self-insured, or self-funded, arrangements. Under these arrangements, the employer, not an external insurer, directly bears the financial risk for the cost of employee health care.

Self-funded arrangements have grown steadily as a share of the insurance market over the past 15 years and now include many employers with less than 200 employees. While this may be the most cost-effective decision for individual employers under the current regulatory framework, it has the effect of locking in uncoordinated, open-ended fee-for-service (FFS) and locking out comparatively economical Integrated Delivery Systems (IDS)."

Fair algorithms for selecting citizen assemblies, in Nature

 Here's a paper that grapples with the problem that not every group in society is equally likely to accept an appointment for which they have been selected, which complicates the problem of selecting representative committees while also giving each potential member approximately the same chance of being selected.

Fair algorithms for selecting citizens’ assemblies. by Bailey Flanigan, Paul Gölz, Anupam Gupta, Brett Hennig & Ariel D. Procaccia, Nature (2021). https://doi.org/10.1038/s41586-021-03788-6

Abstract: Globally, there has been a recent surge in ‘citizens’ assemblies’1, which are a form of civic participation in which a panel of randomly selected constituents contributes to questions of policy. The random process for selecting this panel should satisfy two properties. First, it must produce a panel that is representative of the population. Second, in the spirit of democratic equality, individuals would ideally be selected to serve on this panel with equal probability2,3. However, in practice these desiderata are in tension owing to differential participation rates across subpopulations4,5. Here we apply ideas from fair division to develop selection algorithms that satisfy the two desiderata simultaneously to the greatest possible extent: our selection algorithms choose representative panels while selecting individuals with probabilities as close to equal as mathematically possible, for many metrics of ‘closeness to equality’. Our implementation of one such algorithm has already been used to select more than 40 citizens’ assemblies around the world. As we demonstrate using data from ten citizens’ assemblies, adopting our algorithm over a benchmark representing the previous state of the art leads to substantially fairer selection probabilities. By contributing a fairer, more principled and deployable algorithm, our work puts the practice of sortition on firmer foundations. Moreover, our work establishes citizens’ assemblies as a domain in which insights from the field of fair division can lead to high-impact applications.

...

"To our knowledge, all of the selection algorithms previously used in practice (Supplementary Information section 12) aim to satisfy one particular property, known as ‘descriptive representation’ (that the panel should reflect the composition of the population)16. Unfortunately, the pool from which the panel is chosen tends to be far from representative. Specifically, the pool tends to overrepresent groups with members who are on average more likely to accept an invitation to participate, such as the group ‘college graduates’.  

...

"Selection algorithms that pre-date this work focused only on satisfying quotas, leaving unaddressed a second property that is also central to sortition: that all individuals should have an equal chance of being chosen for the panel.

...

"Although it is generally impossible to achieve perfectly equal probabilities, the reasons to strive for equality also motivate a more gradual version of this goal: making probabilities as equal as possible, subject to the quotas. We refer to this goal as ‘maximal fairness’. 

...

"the algorithms in our framework (1) explicitly compute a maximally fair output distribution and then (2) sample from that distribution to select the final panel (Fig. 1). Crucially, the maximal fairness of the output distribution found in the first step makes our algorithms optimal. To see why, note that the behaviour of any selection algorithm on a given instance is described by some output distribution; thus, as our algorithm finds the fairest possible output distribution, it is always at least as fair as any other algorithm."

A lottery for antibody treatment, with slots reserved for vulnerable patients

 It's always good to see a collaboration between physicians and economists on allocating scarce resources, and here's a case report of allocating monoclonal antibodies in Boston (with some resemblance to school choice), forthcoming in the journal CHEST.

A novel approach to equitable distribution of scarce therapeutics: institutional experience implementing a reserve system for allocation of Covid-19 monoclonal antibodies  Emily Rubin, MD JD MSHP, Scott L. Dryden-Peterson, MD, Sarah P. Hammond, MD, Inga Lennes, MD MBA MPH, Alyssa R. Letourneau, MD MPH, Parag Pathak, PhD, Tayfun Sonmez, PhD, M. Utku Ünver, PhD.

DOI: https://doi.org/10.1016/j.chest.2021.08.003, To appear in: CHEST

"Background. In fall 2020, the Food and Drug Administration issued emergency use authorization for monoclonal antibody therapies (mAbs) for outpatients with Covid-19.  The Commonwealth of Massachusetts issued guidance outlining the use of a reserve system with a lottery for allocation of mAbs in the event of scarcity that would prioritize socially vulnerable patients for 20% of the infusion slots. The Mass General Brigham (“MGB”) health system subsequently implemented such a reserve system.

"Research Question. Can a reserve system be successfully deployed in a large health system in a way that promotes equitable access to mAb therapy among socially vulnerable patients with Covid-19?

...

"Results: Notwithstanding multiple operational challenges, the reserve system for allocation of mAb therapy worked as intended to enhance the number of socially vulnerable patients who were offered and received mAb therapy. A significantly higher proportion of patients offered mAb therapy were socially vulnerable (27.0%) than would have been the case if the infusion appointments had been allocated using a pure lottery system without a vulnerable reserve (19.8%) and a significantly higher proportion of patient who received infusions were socially vulnerable (25.3%) than would have been the case if the infusion appointments had been allocated using a pure lottery system (17.6%)

...

"The reserve for vulnerable patients was a “soft” reserve, meaning that if there were not enough patients in either the high SVI or high incidence town categories to fill the vulnerable slots, those slots were allocated to patients who were next in line by overall lottery number. This was done in order to avoid unused capacity for a therapy that is time sensitive and requires significant infrastructure to provide. Once the lottery had been run, dedicated, primarily multilingual clinicians who had been trained to discuss the therapies with patients called patients to verify eligibility and engage in a shared-decision making conversation to determine whether the patient would like to receive an infusion.

Early experience with running the lottery prior to patient engagement revealed that a large number of patients declined the therapy once offered, were deemed ineligible once contacted, or wished to discuss the therapy with a trusted clinician. The process subsequently was changed to allow clinicians to enter referrals for their own patients once they established patient interest (“manual referrals”). 

...

"All of the 274 patients who were guaranteed slots and 206 of 368 patients on the wait list were called, for a total of 480 patients called. The number of wait list patients called on a given day was a function of both how many of the guaranteed slots were not filled and how much capacity there was in the system to make phone calls on any given day. Of those patients who were called, 132 (27.5%) declined, 33 (6.9%) were deemed ineligible by virtue of being asymptomatic, 19 (4.0%) were deemed ineligible by virtue of having severe symptoms, 11 (2.3%) had been or were planning to be infused elsewhere, 61 (12.7%) could not be reached, and 191 were infused (39.8% of those called and 9.7% of total referred patients).

...

"Had we operated a pure lottery with no reserve for socially vulnerable patients, and all other factors had remained constant, 19.8% of patients offered therapy (88) would have been in the top SVI quartile as opposed to 27.0% (120) in our actual population, and 17.6% of infused patients (32) would have been in the top SVI quartile as opposed to 25.3% (46) in our actual population.

...

"The system we describe is to our knowledge the first instance of a reserve system being used to allocate scarce resources at the individual level during a pandemic.

"A reserve system with lottery for tiebreaking within categories can be straightforward to operate if there are few or no steps between the assignment of lottery spots and the distribution of the good. This could be true, for example, of allocation of antiviral medications to inpatients with Covid-19. In the case of monoclonal antibody therapies, there were multiple factors that could and often did interrupt the trajectory between allocation and distribution. These included the complexity of administering infusion therapy, the time sensitive nature of the therapy, the relative paucity of evidence for the therapy at the time the mAb program started, and the dynamic nature of Covid-19. The conversations with patients about a therapy that held promise but did not yet have strong evidence to support its efficacy and had not been formally FDA approved were often challenging and time consuming. Many patients identified for allocation were difficult or impossible to reach. Others declined therapy once it was offered and discussed, or had become either too well or too sick to be candidates for the therapy once they were reached.

...

"Notwithstanding significant challenges, the reserve system implemented in our health system for allocation of mAb therapy worked as intended to enhance the number of socially vulnerable patients who were offered the therapy. A significantly higher proportion of socially vulnerable patients were offered mAb therapy than would have been if the infusion appointments had been allocated using a pure lottery system without a vulnerable reserve. The intended enhancement of the pool of vulnerable patients who actually received monoclonal antibody therapy was counterbalanced to some extent by the disproportionate number of vulnerable patients who declined therapy, but even fewer socially vulnerable patients would have received the therapy if the lottery system had not included a vulnerable reserve. 

Generalizing deferred acceptance in many to one matching with contracts, by Hatfield, Kominers and Westkamp in RESTUD

 Stability, Strategy-Proofness, and Cumulative Offer Mechanisms, by John William Hatfield, Scott Duke Kominers, Alexander Westkamp, The Review of Economic Studies, Volume 88, Issue 3, May 2021, Pages 1457–1502, https://doi.org/10.1093/restud/rdaa052

Abstract: We characterize when a stable and strategy-proof mechanism is guaranteed to exist in the setting of many-to-one matching with contracts. We introduce three novel conditions—observable substitutability, observable size monotonicity, and non-manipulability via contractual terms—and show that when these conditions are satisfied, the cumulative offer mechanism is the unique mechanism that is stable and strategy-proof (for workers). Moreover, we show that our three conditions are, in a sense, necessary: if the choice function of some firm fails any of our three conditions, we can construct unit-demand choice functions for the other firms such that no stable and strategy-proof mechanism exists. Thus, our results provide a rationale for the ubiquity of cumulative offer mechanisms in practice.

Guns and public health: research funds available again

 Here's the story, from the Journal of the American Medical Association:

Gun Violence Researchers Are Making Up for 20 Years of Lost Time by Alicia Ault, JAMA. Published online August 4, 2021. doi:10.1001/jama.2021.11469

"By late July, the Gun Violence Archive reported 25 370 US firearm deaths in 2021, putting the year on track to surpass last year’s 43 559 deaths. US Centers for Disease Control and Prevention (CDC) data showed that 39 707 people lost their lives to gun violence in 2019. It was the third consecutive year in which US gun violence deaths approached 40 000 and the end of a decade in which the death rate from gun violence increased by 17%, from 10.1 to 11.9 deaths per 100 000 population. The rate has remained above 11 per 100 000 population since 2015.

"Although the CDC gathers firearm mortality data, its gun violence research had largely been dormant since 1996 when the Dickey Amendment prohibited the agency from using its injury prevention funding “to advocate or promote gun control.” The amendment technically didn’t prohibit gun violence research, but the chill was numbing.

"In 2019, however, Congress authorized $25 million in spending on gun violence research, to be split evenly between the CDC and the National Institutes of Health (NIH). Although the amount is nearly 10 times greater than the $2.6 million that the CDC was spending on gun violence prevention studies when the Dickey Amendment took effect, a leading expert said the field is still woefully underfunded.

Stanford SITE seminar: Experimental Economics, August 12-13

 

SITE 2021 PROGRAM

Session 5: Experimental Economics

Date

Thursday, August 12, 2021, 9am - Friday, August 13, 2021, 1pm

Location

Zoom

ORGANIZED BY

• Christine Exley, Harvard Business School
• Muriel Niederle, Stanford University
• Alejandro Martínez Marquina, Stanford University
• Alvin Roth, Stanford University
• Lise Vesterlund, University of Pittsburgh

This workshop will be dedicated to advances in experimental economics combining laboratory and field-experimental methodologies with theoretical and psychological insights on decision-making, strategic interaction and policy. We would invite papers in lab experiments, field experiments and their combination that test theory, demonstrate the importance of psychological phenomena, and explore social and policy issues. In addition to senior faculty members, invited presenters will include junior faculty as well as graduate students.  

In This Session

Thursday, August 12, 2021

AUG 12

9:00 AM - 9:30 AM

Increasing the Demand for Workers with a Criminal Record

Presented by: Dorothea Kübler (WZB Berlin and TU Berlin)

Co-author(s): Hande Erkut (WZB Berlin)

AUG 12

9:30 AM - 10:00 AM

What Money Can Buy: How Market Exchange Promotes Values

Presented by: Roberto Weber (University of Zurich)

Co-author(s): Sili Zhang (University of Zurich)

AUG 12

10:00 AM - 10:30 AM

Your Place in the World - Relative Income and Global Inequality

Presented by: Johanna Mollerstrom (George Mason University)

Co-author(s): Dietmar Fehr (University of Heidelberg) and Ricardo Perez-Truglia (University of California Berkeley)

AUG 12

10:30 AM - 11:00 AM

Break

AUG 12

11:00 AM - 11:30 AM

Increasing the Demand for Workers with a Criminal Record

Presented by: Mitchell Hoffman (University of Toronto)

Co-author(s): Shai Bernstein (Harvard Business School), Emanuele Colonnelli (University of Chicago Booth), and Benjamin Iverson (Brigham Young University)

AUG 12

11:30 AM - 11:45 AM

Why High Incentives Cause Repugnance: A Framed Field Experiment

Presented by: Robert Stüber (WZB Berlin)

AUG 12

11:45 AM - 12:00 PM

Estimating Preferences for Competition from Convex Budget Sets

Presented by: Lina Lozano (Maastricht University)

Co-author(s): Ernesto Reuben (NYU Abu Dhabi)

AUG 12

12:00 PM - 12:15 PM

Corrections and Collaborations in Group Work

Presented by: Yuki Takahashi (University of Bologna)

AUG 12

12:15 PM - 12:30 PM

The Good Wife? Reputation Dynamics Within the Household and Women's Access to Resources

Presented by: Nina Buchmann (Stanford University)

Co-author(s): Pascaline Dupas (Stanford University) and Roberta Ziparo (Aix-Marseille School of Economics)

AUG 12

12:30 PM - 1:00 PM

Break - Discussion

Friday, August 13, 2021

AUG 13

9:00 AM - 9:30 AM

Eliciting Moral Preferences: Theory and Experiment

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Presented by: Roland Benabou (Princeton University)

Co-author(s): Armin Falk (University of Bonn), Henkel Luca (University of Bonn), and Jean Tirole (University of Toulouse)

We examine to what extent a personís moral preferences can be inferred from observing their choices, for instance via experiments, and in particular, how one should interpret certain behaviors that appear deontologically motivated. Comparing the performance of the direct elicitation (DE) and multiple-price list (MPL) mechanisms, we characterize in each case how (social or self) image motives ináate the extent to which agents behave prosocially. More surprisingly, this signaling bias is shown to depend on the elicitation method, both per se and interacted with the level of visibility: it is greater under DE for low reputation concerns, and greater under MPL when they become high enough. We then test the modelís predictions in an experiment in which nearly 700 subjects choose between money for themselves and implementing a 350e donation that will, in expectation, save one human life. Interacting the elicitation method with the decisionís level of visibility and salience, we Önd the key crossing e§ect predicted by the model. We also show theoretically that certain ìKantianî postures, turning down all prices in the o§ered range, easily emerge under MPL when reputation becomes important enough.

AUG 13

9:30 AM - 10:00 AM

Social Identity and Belief Polarization

Presented by: Yan Chen (University of Michigan)

Co-author(s): Kevin Bauer (Goethe University Frankfurt), Florian Hett (Johannes Gutenberg University Mainz), and Michael Kosfeld (Goethe University Frankfurt)

AUG 13

10:00 AM - 10:30 AM

Learning and Initial Play in the Prisoner's Dilemma

Presented by: Drew Fudenberg (MIT)

Co-author(s): Gustav Karreskog (Stockholm School of Economics)

AUG 13

10:30 AM - 11:00 AM

Break

AUG 13

11:00 AM - 11:30 AM

A Robust Test of Prejudice for Discrimination Experiments

Presented by: Daniel Martin (Northwestern University Kellogg School of Management)

Co-author(s): Philip Marx (Louisiana State University)

AUG 13

11:30 AM - 11:45 AM

Customer Discrimination and Quality Signals: A Field Experiment with Healthcare

Presented by: Alex Chan (Stanford University)

AUG 13

11:45 AM - 12:00 PM

Inference from Rareness and Valence of Events

Presented by: David Klinowski Gomez (Stanford University)

Co-author(s): Muriel Niederle (Stanford University) and Collin Raymond (Purdue University)

AUG 13

12:00 PM - 12:15 PM

Near-Miss Deterrence: Incorporating Near-Miss Effects into Deterrence Theory

Presented by: Stephanie Permut (Carnegie Mellon University)

Co-author(s): Silvia Saccardo (Carnegie Mellon University), Julie Downs (Carnegie Mellon University), and George Loewenstein (Carnegie Mellon University)

AUG 13

12:15 PM - 12:30 PM

Inducing Positive Sorting Through Performance Pay: Experimental Evidence from Pakistani Schools

Presented by: Christina Brown (University of Chicago)

Co-author(s): Tahir Andrabi (Pomona College)

AUG 13Break - Discussion

The export market for fighter planes

 Here's an article from a recent issue of Foreign Affairs, about why China's export market for fighter jets is not taking off, even though there jets are now very good. The sub-headline gets right to the point: countries buy weapons from allies, not potential adversaries, and are looking for strategic relationships as well as hardware.

The World Doesn’t Want Beijing’s Fighter Jets. Snazzy weapons mean a lot less if you don’t have friends.  by By Richard Aboulafia,

"Fighter jet exports represent a unique combination of hard and soft power. If a country can sell fighter jets abroad, that means it can attract customers for sophisticated weapons that can sell for upwards of $100 million, which in turn proves that the country has appeal as a strategic partner.

...

Criminalizing the clients of sex work makes the client population riskier to sex workers (study in the UK)

 Here's a  recent study that suggests that criminalizing the clients of prostitutes results in the client population becoming more risky.

Quashing demand or changing clients? Evidence of criminalisation of sex work in the UK, by Marina Della Giusta, Maria Laura Di Tommaso, Sarah Jewell, and Francesca Bettio, July 2021

Abstract: The use of regulation of sex work is undergoing sweeping changes across Europe and client criminalisation is becoming very widespread, with conflicting claims about the intended and actual consequences of this policy. We discuss changes in demand for paid sex accompanying the criminalization of prostitution in the United Kingdom, which moved from a relatively permissive regime under the Wolfenden Report of 1960, to a much harder line of aiming to crack down on prostitution with the Prostitution (Public Places) Scotland Act 2007 and the Policing and Crime Act of 2009 in England and Wales. We make use of two waves of the British National Survey of Sexual Attitudes and Lifestyles (NATSAL2, conducted in 2000-2001 and NATSAL3, conducted in 2010-2012) to document the changes in both the amount of demand for paid sex and in the type of clients that have taken place across the two waves, and their possible implications for policies that frame prostitution as a form of crime.

"The language of ‘prostitute’ and ‘prostitution’ is typically aligned with abolitionist perspectives that see the sale of sex as entailing women’s exploitation and objectification, both by those who manage and create the opportunity for the sexual transaction as well as by those clients who make the purchase and maintain the demand. The language of ‘sex workers’ and ‘sex work’ has typically been preferred by those who emphasize women’s agency in entering into commercial sex transactions (albeit under conditions of constraint) and who call for the regulation of the sale of sex as akin to the sale of non-sexual labor or services. We deliberately use the two terms interchangeably in our work...

...

"Germany, the Netherlands and Greece have moved towards acknowledging prostitution as a regular job on one side, and Sweden, Norway, Finland, France and Ireland have hardened their stance instead aiming to eradicate prostitution as a form of violence on the other side. In the first group of countries, the consideration of sex work as legitimate labor has led to shifting bans on outdoor and indoor prostitution subject to compliance with regulations (Netherlands since 2000, Germany since 2002). Sex workers are entitled to a number of employment related protections under the law and local authorities required to ensure that brothels are suitably licensed and operating in accordance with relevant health and safety requirements. The abolitionist model, conversely, seeks to prohibit prostitution, facilitate exit and punish clients and has applied in varying degrees in the United States and, more recently, Sweden, Norway and Finland. In Sweden it is an offence, punishable by a fine or imprisonment for up to six months, to obtain a casual sexual relationship for payment. Both outdoor and indoor prostitution are prohibited, although only the clients will be criminalized.

...

"The evidence we bring indicates that the increased stigmatization of prostitution that has taken place in the UK over the period 2000-2012, during which prostitution was progressively criminalized, does not support the expectations of a significant reduction in demand as the policy intended and corresponds to a change in the type of clients that are observed through successive waves of the British National Survey of Sexual Attitudes and Lifestyles (NATSAL henceforth). We conclude that this provides further support for the idea that demand for sexual services might be inelastic to both the market price and the implicit price of stigma, whereby criminalization is not likely to be conducive to decreases in demand as is hoped for. Rather, it might jeopardize the working conditions and safety of existing prostitutes thus raising the welfare cost of abolitionism. 

Stanford SITE Seminar: Psychology and Economics, Aug 9-10

 

Session 4: Psychology and Economics

Date

Monday, August 9, 2021, 9am - Tuesday, August 10, 2021, 12:30pm

ORGANIZED BY

• B. Douglas Bernheim, Stanford University
• John Beshears, Harvard Business School
• Vincent Crawford, University of Oxford and University of California, San Diego
• David Laibson, Harvard University
• Ulrike Malmendier, University of California, Berkeley

As we have done for many years, this workshop brings together researchers working on issues at the intersection of psychology and economics. The segment will focus on evidence of and explanations for non-standard choice patterns, as well as the positive and normative implications of those patterns in a wide range of economic decision-making contexts, such as lifecycle consumption and savings, workplace productivity, health, and prosocial behavior. The presentations will frequently build upon insights from other disciplines, including psychology and sociology. Theoretical, empirical, and experimental studies will be included.

In This Session

Monday, August 9, 2021

AUG 9

9:00 AM - 9:30 AM

The Gender Gap in Self-Promotion

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Presented by: Christine Exley (Harvard Business School)

Co-author(s): Judd B. Kessler (The Wharton School, University of Pennsylvania)

In applications, interviews, performance reviews, and many other environments, individuals subjectively describe their ability and performance to others. We run a series of experiments, involving over 4,000 participants from online labor markets and over 10,000 school-aged youth. We find a large gender gap in self-promotion: Women subjectively describe their ability and performance to potential employers less favorably than equally performing men. Even when all incentives to promote are removed, however, the gender gap remains. The gender gap in self-promotion is reflective of an underlying gender gap in how individuals subjectively evaluate their own performance. This underlying gender gap proves persistent and arises as early as the sixth grade.

AUG 9

9:30 AM - 10:00 AM

Partial Equilibrium Thinking in General Equilibrium

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Presented by: Francesca Bastianello (Harvard University)

Co-author(s): Paul Fontanier (Harvard University)

We develop a theory of “Partial Equilibrium Thinking” (PET), whereby agents fail to understand the general equilibrium consequences of their actions when inferring information from endogenous outcomes. PET generates a two-way feedback effect between outcomes and beliefs, which can lead to arbitrarily large deviations from fundamentals. In financial markets, PET equilibrium outcomes exhibit over-reaction, excess volatility, high trading volume, and return predictability. We extend our model to allow for rationality of higher-order beliefs, general forms of model misspecification, and heterogenous agents. We show that more sophisticated agents may contribute to greater departures from rationality. We also draw a distinction between models of misinference and models with biases in Bayesian updating, and study how these two departures from rationality interact. Misinference from mistakenly assuming the world is rational amplifies biases in Bayesian updating.

AUG 9

10:00 AM - 10:15 AM

Break

AUG 9

10:15 AM - 10:45 AM

Belief-Updating: Inference versus Extrapolation

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Presented by: Tony Q. Fan (Stanford University),

Co-author(s): Yucheng Liang (Carnegie Mellon University) and Cameron Peng (London School of Economics and Political Science)

Survey forecasts of macroeconomic and financial variables show widespread overreaction to news, but laboratory experiments on belief updating typically find underinference from signals. We provide new experimental evidence to connect these two seemingly inconsistent phenomena. Building on a classic experimental paradigm, we study how people make inferences and revise forecasts in the same fully-specified information environment. Subjects underreact to signals when inferring about fundamental states (“underinference”), but overreact to signals when revising forecasts about future outcomes (“overextrapolation”). In the latter task, subjects appear to be using a mix of simplifying heuristics, such as focusing on the representative state (the state most consistent with the signal) and anchoring on the signal. Additional treatments link our results to the difficulty of recognizing the conceptual connection between inference and forecast revision problems.

AUG 9

10:45 AM - 11:15 AM

Learning in the Household

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Presented by: Gautam Rao (Harvard University)

Co-author(s): John J. Conlon (Harvard University), Malavika Mani (Columbia University), Matthew Ridley (MIT), and Frank Schilbach (MIT)

This paper studies social learning and information pooling within the household using a lab experiment with 400 married couples in Chennai, India. Participants are asked to guess the fraction of red balls in an urn after each spouse privately receives draws from the urn and then has a chance to learn their spouse’s draws through a face-to-face discussion. Guesses are paid for accuracy and the payoff is split equally between the spouses, aligning their incentives. We find that husbands’ beliefs respond less than half as much to information that was collected by their wives, relative to ‘own’ information. This failure of learning is not due to communication frictions: when we directly share their wife’s information with husbands, they continue to under-weight it relative to their own draws. Wives do not display this behavior, and instead equally weight their own and their spouse’s information. In a follow-up experiment with pairs of strangers, individuals of both genders put more weight on their own information than on their partner’s. We conclude that people have a general tendency to under-weight others’ information relative to their own, and speculate that a norm of wives deferring to their husbands may play a countervailing role in our context.

AUG 9

11:15 AM - 11:30 AM

Break

AUG 9

11:30 AM - 12:00 PM

Does Saving Cause Borrowing?

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Presented by: Michaela Pagel (Columbia GSB)

Co-author(s): Paolina Medina (Mays Business School of Texas A&M University)

We study whether or not nudging individuals to save more has the unintended consequence of additional borrowing in high-interest unsecured consumer credit. We analyze the effects of a large-scale experiment in which 3.1 million bank customers were nudged to save more via (bi-)weekly SMS and ATM messages. Using Machine Learning methods for causal inference, we build a score to sort individuals according to their predicted treatment effect. We then focus on the individuals in the top quartile of the distribution of predicted treatment effects who have a credit card and were paying interest at baseline. Relative to their control, this group increased their savings by 5.7% on average or 61.84 USD per month. At the same time, we can rule out increases in credit card interest larger than 1.25 USD with 95% statistical confidence. We thus estimate that for every additional dollar of savings, individuals incur less than 2 cents in additional borrowing cost. This is a direct test test of the predictions of rational co-holding models, and is an important result to evaluate policy proposals to increase savings via nudges or more forceful measures.

AUG 9

12:00 PM - 12:30 PM

Dynamic Preference "Reversals" and Time Inconsistency

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Presented by: Dmitry Taubinsky (UC Berkeley)

Co-author(s): Philipp Strack (Yale University)

We study identification of time preferences from data sets where an agent at time 0 makes an advance commitment, and later at time 1 can revise their choice. A common intuition, motivating many empirical studies, is that systematic reversals toward certain alternatives imply time inconsistency. We show that this intuition is generally incorrect in environments with random taste shocks. Roughly speaking, the only data that rejects time-consistent expected utility maximization is when a time-0 choice is revealed to be strictly dominated at time 1 with probability 1. This result applies to rich choice sets; to cases where the analyst observes the complete ranking of alternatives in every period and state of the world; to environments where it is natural to impose additional assumptions like concavity; and to cases where the analyst has access to supplementary cardinal information. However, we prove that there is a class of empirical designs that does produce robust point identification of the degree of time inconsistency: designs that estimate agents’ willingness to pay for different alternatives at both time 0 and time 1, and where the marginal utility of money can be assumed to not vary with agents’ time-1 preferences for the different alternatives.

Tuesday, August 10, 2021

AUG 10

9:00 AM - 9:30 AM

Safe Spaces: Shelters or Tribes?

Presented by: Jean Tirole (Toulouse School of Economics)

AUG 10

9:30 AM - 10:00 AM

A Model of Justification

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Presented by: Sarah Ridout (Harvard University)

I model decision-making constrained by morality, rationality, or other virtues. In addition to a primary preference over outcomes, the decision maker (DM) is characterized by a set of preferences that he considers justifiable. In each choice setting, he maximizes his primary preference over the subset of alternatives that maximize at least one of the justifiable preferences. The justification model unites a broad class of empirical work on distributional preferences, charitable donations, prejudice/discrimination, and corruption/bribery. I provide full behavioral characterizations of several variants of the justification model as well as practical tools for identifying primary preferences and justifications from choice behavior. I show that identification is partial in general, but full identification can be achieved by including lotteries in the domain and allowing for heterogeneity in both primary preferences and justifications. Since the heterogeneous model uses between-subject data, it is robust to consistency motives that may arise in within-subject experiments. I extend the heterogeneous model to information choice and show that it accounts for observed patterns of information demand and avoidance on ethical domains.

AUG 10

10:00 AM - 10:15 AM

Break

AUG 10

10:15 AM - 10:45 AM

How Flexible is that Functional Form? Measuring the Restrictiveness of Theories

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Presented by: Annie Liang (Northwestern University)

Co-author(s): Drew Fudenberg (MIT) and Wayne Gao (University of Pennsylvania)

We propose a new way to quantify the restrictiveness of an economic model, based on how well the model fits simulated, hypothetical data sets. The data sets are drawn at random from a distribution that satisfies some application-dependent content restrictions (such as that people prefer more money to less). Models that can fit almost all hypothetical data well are not restrictive. To illustrate our approach, we evaluate the restrictiveness of popular behavioral models in two experimental settings—certainty equivalents and initial play— and explain how restrictiveness reveals new insights about each of the models.

AUG 10

10:45 AM - 11:15 AM

Choice and Complexity

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Presented by: Jörg L. Spenkuch (Northwestern University)

Co-author(s): Yuval Salant (Northwestern University)

We study two dimensions of complexity that may affect individual decision-making. The first one is object complexity, which corresponds to the difficulty of evaluating any given object in the choice set. The second dimension is composition complexity, which refers to the difficulty of finding the best among similar alternatives. We develop a satisficing-with-evaluation-errors model that incorporates both dimensions and delivers sharp empirical predictions about their effect on choice behavior. We test these predictions in a novel data set with information on hundreds of millions of decisions in chess endgames. Chess endgames admit an objective measure of choice quality and, most importantly, have ample variation in object and composition complexity. Consistent with the theory, we document that even highly experienced decision makers are significantly more likely to make suboptimal choices as complexity increases along either dimension. Our analysis, therefore, helps to shed some of the first light on the role of complexity in decision-making outside of the laboratory.

AUG 10

11:15 AM - 11:30 AM

Break

AUG 10

11:30 AM - 12:00 PM

Incentive Complexity, Bounded Rationality, and Effort Provision

Presented by: David Huffman (University of Pittsburgh)

Co-author(s): Johannes Abeler (University of Oxford) and Collin Raymond (Purdue University)

This paper shows that dynamic incentives embedded in an organization’s workplace incentive scheme can be a shrouded attribute, due to contract complexity and worker bounded rationality. This is true in field experiments within the firm, and in complementary online experiments with real eort tasks. Structural estimates indicate that rational agents who fully understand the incentive scheme would behave sigificantly dierent from what we observe. A response to dynamic incentives does emerge when we reduce complexity or look at workers with higher cognitive ability. The results illustrate the potential value of complexity to organizations, they demonstrate that complex incentive contracts may allow firms to be achieve better than second-best, they identify specific features of contracts that can influence the eectiveness of incentives through the channel of complexity, and they imply heterogeneous eects of incentives depending on worker cognitive ability.

AUG 10

12:00 PM - 12:30 PM

The Negative Consequences of Loss-Framed Performance Incentives

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Presented by: Alex Rees-Jones (The Wharton School, University of Pennsylvania)

Co-author(s): Lamar Pierce (Olin Business School, Washington University in St Louis) and Charlotte Blank (Maritz)

Behavioral economists have proposed that incentive contracts result in higher productivity when bonuses are "loss framed" prepaid then clawed back if targets are unmet. We test this claim in a large-scale field experiment. Holding financial incentives fixed, we randomized the pre- or postpayment of sales bonuses at 294 car dealerships. Prepayment was estimated to reduce sales by 5%, generating a revenue loss of $45 million over 4 months. We document, both empirically and theoretically, that negative effects of loss framing can arise due to an increase in incentives for "gaming" behaviors. Based on these claims, we reassess the common wisdom regarding the desirability of loss framing.