Tuesday, August 17, 2021

Stanford SITE seminar: Dynamic Games, Contracts, and Markets, Aug 18-20

 

Date
 - 
Location
Zoom
ORGANIZED BY
  • Simon Board, University of California, Los Angeles
  • Gonzalo Cisternas, Massachusetts Institute of Technology
  • Mira Frick, Yale University
  • George Georgiadis, Northwestern University
  • Andrzej Skrzypacz, Stanford GSB
  • Takuo Sugaya, Stanford GSB

The idea of this session is to bring together microeconomic theorists working on dynamic games and contracts with more applied theorists working in macro, finance, organizational economics, and other fields. First, this is a venue to discuss the latest questions and techniques facing researchers working in dynamic games and contracts. Second, we wish to foster interdisciplinary discussion between scholars working on parallel topics in different disciplines, in particular, helping raise awareness among theorists of the open questions in other fields.

This is a continuation of successful SITE annual sessions 2013-2020. In previous years, we attracted people from economics, finance, operations research, political economy, and other related fields, ranging from Ph.D. students to senior professors. We hope to have a similar number of attendees this year as in the past. Specific topics likely to be covered include repeated and stochastic games, dynamic optimal contracts, dynamic market pricing, reputation, search, and learning and experimentation.

In This Session

Wednesday, August 18, 2021

AUG 18
9:00 AM - 9:45 AM

Wealth Dynamics in Communities

Presented by: Daniel Barron (Northwestern University)
Co-author(s): Yingni Guo (Northwestern University) and Bryony Reich (Northwestern University)

This paper develops a model to explore how favor exchange in communities influences wealth dynamics. We identify a key obstacle to wealth accumulation: wealth crowds out favor exchange. Therefore, low-wealth households are forced to choose between growing their wealth and accessing favor exchange within their communities. The outcome is that some communities are left behind, with wealth disparities that persist and sometimes even grow worse. Using numerical simulations, we show that place-based policies encourage both favor exchange and wealth accumulation and so have the potential to especially benet such communities.

AUG 18
9:45 AM - 10:00 AM

Break

AUG 18
10:00 AM - 10:45 AM

Optimal Dynamic Allocation: Simplicity through Information Design

Presented by: Faidra Monachou (Stanford University)
Co-author(s): Itai Ashlagi (Stanford University) and Afshin Nikzad (University of Southern California)

We study dynamic nonmonetary markets where objects are allocated to unit-demand agents with private types. An agent’s value for an object is supermodular in her type and the quality of the object, and her payoff is quasilinear in her waiting cost. We analyze direct-revelation mechanisms that elicit agents’ types and assign them to objects over time. We identify the welfare-maximizing mechanism and show that it can be implemented by a first-come first-served wait-list with deferrals when the
marketmaker can design the information disclosed to agents about the objects. The optimal disclosure policy pools adjacent object types.

AUG 18
10:45 AM - 11:00 AM

Break

AUG 18
11:00 AM - 11:45 AM

Probabilistic Assortative Matching under Nash Bargaining

Presented by: Nicolas Bonneton (University of Mannheim)
Co-author(s): Christopher Sandmann (London School of Economics)

This paper re-visits the canonical random search and matching model with Nash bargaining. By introducing pair-specific production shocks, our framework generates meeting-contingent match outcomes that are random. We provide a robust characterization of probabilistic matching patterns for any non-stationary environment, generalizing results by Shimer and Smith (2000). We nd that, although their prediction of single-peaked preferences over meetings is robust, search frictions upset positive assortative matching across well-assorted pairs. As a second contribution, we show that the non-stationary random search matching model is a mean eld game, and admits a representation as a system of forward-backward stochastic differential equations. This representation affords a novel existence and uniqueness result, casting doubt on the robustness of multiple self-fulfilling equilibrium paths frequently reported in the literature.

Thursday, August 19, 2021

AUG 19
9:00 AM - 9:45 AM

Price Experimentation in Confidential Negotiations

Presented by: Jangwoo Lee (McCombs School of Business, University of Texas at Austin)

I develop a model in which a long-lived seller concurrently negotiates with multiple long-lived buyers over two periods. Within this framework, I consider two protocols: a public negotiation process and a confidential negotiation process. In the confidential negotiation process, buyers competitively engage in “price experimentation”: they sacrifice initial profits so that they can enjoy informational advantages over competitors later. Due to this channel, the seller benefits from (1) maintaining confidentiality over past offers and (2) reducing the number of buyers in the confidential negotiation process, even without any entry cost.

AUG 19
9:45 AM - 10:00 AM

Break

AUG 19
10:00 AM - 11:45 AM

Large-Sample Rankings of Information Structures in Games

Presented by: Mira Frick (Yale University)
Co-author(s): Ryota Iijima (Yale University) and Yuhta Ishii (Pennsylvania State University)

 

 

AUG 19
10:45 AM - 11:00 AM

Break

AUG 19
11:00 AM - 11:45 AM

The Cost of Optimally Acquired Information

Presented by: Alexander W. Bloedel (Stanford University)
Co-author(s): Weijie Zhong, (Stanford Graduate School of Business)

This paper develops a theory for the expected cost of optimally acquired information when information can be acquired sequentially and there is no explicit cost of delay. We study the “reduced-form” Indirect Cost functions for information generated by sequential minimization of a “primitive” Direct Cost function. The class of Indirect Costs is characterized by a recursive condition called Sequential Learning-Proofness. This condition is inconsistent with Prior Invariance: Indirect Costs must depend on the decision-maker’s prior beliefs. 

We show that Sequential Learning-Proofness provides partial optimality foundations for the Uniformly Posterior Separable (UPS) cost functions used in the rational inattention literature: a cost function is UPS if and only if it is an Indirect Cost that (i) satisfies a mild regularity condition or, equivalently, (ii) is generated (only) by Direct Costs for which the op timal sequential strategy involves observing only Gaussian diffusion signals. We characterize the unique UPS cost function that is generated by a Prior-Invariant Direct Cost; it exists only when there are exactly two states. 

We also propose two specific UPS cost functions based on additional optimality principles. We introduce and characterize Total Information as the unique Indirect Cost that is Process Invariant when information can be decomposed both sequentially and “simultaneously”: it is uniquely invariant to the “merging” and “splitting” of experiments. Under regularity conditions, Mutual Information is the unique Indirect Cost that is Compression-Invariant when as pects of the state space can be “freely ignored”: it is uniquely invariant to the “merging” and “splitting” of states. We argue that Total Information and Mutual Information represent the normatively ideal costs of, respectively, “producing” and “processing” information. 

 

Friday, August 20, 2021

AUG 20
9:00 AM - 9:45 AM

Optimal Feedback in Contests

Presented by: George Georgiadis (Northwestern University)
Co-author(s): Jeffrey Ely (Northwestern University), Sina Khorasani (UC San Diego), and Luis Rayo (Northwestern University)

We derive optimal contests for environments where output takes the form of breakthroughs and the principal has an informational advantage over the contestants. Whether or not the principal is able to provide real-time feedback to contestants, the optimal prize allocation is egalitarian: all agents who have succeeded in a pre-specified time interval share the prize equally. When providing feedback is feasible, the optimal contest takes a stark cyclical form: contestants are fully apprised of their own success, and at the end of each fixed-length cycle, they are informed about peer success as well.

AUG 20
9:45 AM - 10:00 AM

Break

AUG 20
10:00 AM - 10:45 AM

Dynamic Amnesty Programs

Presented by: Sam Kapon (New York University)

A regulator faces a stream of agents each engaged in crime with stochastic returns. The regulator designs an amnesty program, committing to a time path of penalty reductions for criminals who self-report before they are detected. In an optimal time path, the intertemporal variation in the returns from crime can generate intertemporal variation in the generosity of amnesty. I construct an optimal time path and show that it exhibits amnesty cycles. Amnesty becomes increasingly generous over time until it hits a bound, at which point the cycle resets. Agents engaged in high return crime self-report at the end of each cycle, while agents engaged in low return crime self-report always.

AUG 20
10:45 AM - 11:00 AM

Break

AUG 20
11:00 AM - 11:45 AM

Screening for Breakthroughs

Presented by: Ludvig Sinander (Northwestern University)
Co-author(s): Gregorio Curello (University of Bonn)

We identify a new and pervasive dynamic agency problem: that of incentivising the prompt disclosure of productive information. To study it, we introduce a model in which a technological breakthrough occurs at an uncertain time and is privately observed by an agent, and a principal must incentivise disclosure via her control of the agent’s utility. We uncover a striking deadline structure of optimal mechanisms: they have a simple deadline form in an important special case, and a graduated deadline structure in general. We apply our results to the design of unemployment insurance schemes.

 

Monday, August 16, 2021

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)."

Sunday, August 15, 2021

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."



Saturday, August 14, 2021

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 Ãœnver, 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?

...

"ResultsNotwithstanding 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. 

Friday, August 13, 2021

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.


Thursday, August 12, 2021

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.

Wednesday, August 11, 2021

Stanford SITE seminar: Experimental Economics, August 12-13

 

Date
 - 
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

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

Tuesday, August 10, 2021

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.

...


Monday, August 9, 2021

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.