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on Economic Design |
| By: | Olivier De Groote; Anais Fabre; Margaux Luflade; Arnaud Maurel |
| Abstract: | The optimal functioning of centralized allocation systems is undermined by the presence of institutions operating off-platform - a feature common to virtually all real-world implementations. These off-platform options generate justified envy, as students may reject their centralized assignment in favor of an outside offer, leaving vacant seats in programs that others would have preferred to their current match. We examine whether sequential assignment procedures can mitigate this inefficiency: they allow students to delay their enrollment decision to potentially receive a better offer later, at the cost of waiting before knowing their final admission outcome. To quantify this trade-off, we estimate a dynamic model of application and acceptance decisions using rich administrative data from the French college admission system, which include rank-ordered lists and waiting decisions. We find that waiting costs are large. Yet, by improving students' assignment outcomes relative to a standard single-round system, the sequential mechanism decreases the share of students who leave the higher education system without a degree by 5.4% and leads to large welfare gains. |
| Keywords: | Centralized Assignment, Higher Education; Off-Platform Programs |
| JEL: | C61 I0 I23 I3 |
| Date: | 2025–08 |
| URL: | https://d.repec.org/n?u=RePEc:crm:wpaper:2555 |
| By: | Christopher Campos; Jesse Bruhn; Eric Chyn; Antonia Vazquez |
| Abstract: | Public school choice has evolved rapidly in the past two decades, as districts roll out new magnet, dual-language, and themed programs to broaden educational opportunity. We use newly collected national data to document that opt-in (voluntary) systems: (i) are the modal design; (ii) are harder to navigate; and (iii) have participation that is concentrated among more advantaged students. These facts suggest a striking inconsistency: districts have largely adopted centralized assignment algorithms to broaden access, but most rely on optional participation that fragments public education. We study the implications of this design choice in the Los Angeles Unified School District, the largest opt-in system in the country, combining nearly two decades of administrative data, randomized lotteries, and quasi-experimental expansions in access. Participation is highly selective, consistent with national evidence, and lottery estimates suggest that the students with the lowest demand for choice schools are the ones who gain the most from attending. Opt-in participation therefore embeds a selection mechanism that screens out high-return students and leaves many effective programs with unused capacity. To evaluate system-level implications, we estimate a structural model linking applications, enrollment, and achievement. Choice schools are vertically differentiated and generate meaningful gains, but the opt-in participation rule -through high application costs and negative selection on gains- prevents these benefits from reaching the students who need them most. Counterfactual simulations make the design stakes clear: information and travel-cost reductions have limited effects, whereas reforms that change the participation architecture eliminate core inefficiencies and deliver the largest district-wide achievement gains. These results underscore that system design -not school effectiveness alone- shapes who benefits from public school choice and to what extent. |
| Keywords: | school choice, market design, school effectiveness |
| JEL: | I20 I21 J01 |
| Date: | 2026–01 |
| URL: | https://d.repec.org/n?u=RePEc:crm:wpaper:26005 |
| By: | Canta, Chiara; Madio, Leonardo; Mantovani, Andrea; Reggiani, Carlo |
| Abstract: | Online platforms connecting physicians and patients are increasingly com-mon and often operate in heavily regulated contexts. We consider a platform that provides cost-reducing services for physicians and quality-enhancing ser-vices for patients. The platform also improves the matching between patients and physicians, thereby increasing competition among the latter. When prices are unregulated, physicians charge different prices online and offline, yet not all join the platform, which is suboptimal in terms of social welfare. The platform may also under- or over-invest in the quality level offered to patients, making their participation suboptimal as well. We then analyze price regulation. Un-der a single regulated price for medical visits, regardless of the booking channel, all physicians join the platform. However, the first-best allocation cannot be implemented: patient participation remains inefficiently low because patients do not internalize the platform’s cost-reducing effect. In contrast, allowing two regulated prices, one for offline visits and one for platform bookings, re-stores the first best. Overall, our findings suggest that an optimal pricing or reimbursement mechanism should differentiate across booking channels. |
| Keywords: | Healthcare online platforms; Price regulation; Patient-physician matching. |
| JEL: | I11 I18 L51 H75 |
| Date: | 2026–04 |
| URL: | https://d.repec.org/n?u=RePEc:tse:wpaper:131693 |
| By: | Galdino, Manoel (Universidade de São Paulo) |
| Abstract: | When and why would a hegemon prefer consensus to majority rule in an international organization? I argue that consensus can be a technology of hegemonic power rather than a constraint upon it. In a formal model, a hegemon privately observes the value of cooperation and uses Bayesian persuasion to influence weaker states' entry decisions. Under majority rule, weak states can bypass the hegemon, eliminating any screening problem. Under unanimity, weak states must include the hegemon in every bargaining coalition without knowing its type, creating a screening cutoff at which their behavior changes discretely. This generates an upward jump in the hegemon's value function---a non-convexity that Bayesian persuasion exploits. The institutional comparison has a single-crossing property: there is a unique prior threshold, in closed form, above which the hegemon prefers unanimity and below which majority can dominate by making entry easier. The mechanism reframes institutional design as a trade-off between informational leverage under unanimity and easier participation under majority, providing a distributive explanation for consensus rules in organizations like the GATT/WTO. |
| Date: | 2026–04–23 |
| URL: | https://d.repec.org/n?u=RePEc:osf:socarx:ca8vj_v1 |
| By: | Gonzalez Morin, Javier; Martimort, David |
| Abstract: | We consider the following screening model of procurement. An agent (the seller) has private information on his cost parameter. A principal (the buyer) learns an ex post signal on this parameter. The signal is private information to the principal and proper incentives to reveal this signal must be designed. In related contexts, money burning, i.e., the ex post destruction of some of the gains from trade, has shown to be useful to provide such incentives. We demonstrate that money burning allows the principal to implement the first-best output with zero information rent for the agent; although it is never optimal to do so since output distortions are less costly. More generally, money burning is rarely optimal, and only used as a tool of last resort if output distortions are no longer feasible. In particular, when output must be chosen before the non-verifiable signal realizes, money burning becomes more attractive. |
| Keywords: | Optimal contracting; asymmetric information; ex post signal; money burning |
| JEL: | D82 |
| Date: | 2026–04–22 |
| URL: | https://d.repec.org/n?u=RePEc:tse:wpaper:131687 |
| By: | Pamela Giustinelli; Edwin Leuven |
| Abstract: | We study belief accuracy in a centralized higher-education admissions system using Norwegian data that combine a large pre-admission expectations survey with administrative records on offers, enrollment, and completion. Program-specific cutoffs provide a fuzzy regression discontinuity design that identifies objective counterfactual outcomes at the admission margin and allows direct comparison with subjective, state-contingent beliefs (first-choice access versus the relevant second-choice offer state). We find that enrollment forecast errors are driven mainly by mistaken beliefs about offer probabilities, while beliefs about enrollment conditional on an offer are comparatively accurate. For completion, the dominant error is persistence optimism: applicants substantially overestimate completion conditional on enrollment under both access states. Applicants also overstate first-minus-second returns for both enrollment and completion. These errors are economically meaningful for choices: in a partial-equilibrium counterfactual exercise, correcting beliefs implies large declines in the predicted probability of keeping the currently ranked first choice on top. |
| Keywords: | Subjective probabilities, subjective ex ante returns, objective ex post returns, returns to enrollment, higher education |
| JEL: | C21 C83 D84 I26 |
| Date: | 2026–03 |
| URL: | https://d.repec.org/n?u=RePEc:crm:wpaper:26066 |
| By: | Matthias Fahn; Jin Li; Chang Sun |
| Abstract: | We study how AI affects compensation and job design when performance depends on workers' non-contractible effort. In a principal–agent model with limited liability, AI reduces effort costs but disproportionately lowers the cost of achieving satisfactory performance. This raises the incentive cost of sustaining high effort and can induce firms to replace high-wage, high-effort good jobs with low-wage, low-effort bad jobs, even when good jobs create more total surplus. As a result, AI can lower wages, reduce worker welfare, and even depress profits. If workers can adopt AI unilaterally, adoption occurs even when the resulting equilibrium harms both parties; when adoption requires worker cooperation, resistance is strongest where AI erodes rents embodied in good jobs. In a search-and-matching extension, endogenous outside options amplify these forces, reinforcing a bad-job economy and potentially reducing employment. |
| Keywords: | artificial intelligence, agency costs, job design, labor contracts, limited liability, incentives, search and matching |
| JEL: | D86 J41 O33 L23 |
| Date: | 2026 |
| URL: | https://d.repec.org/n?u=RePEc:ces:ceswps:_12612 |
| By: | Shuo Zhang; Peter Kuhn |
| Abstract: | We use an algorithm audit of China's four largest job boards to measure the causal effect of a job seeker's gender on the jobs that are recommended to them, and to identify the algorithmic processes that generate those recommendations. Focusing on identical male and female worker profiles seeking jobs in the same industry-occupation cell, we find precisely estimated but modest amounts of gender bias: Jobs recommended to women pay 0.2 percent less, request 0.9 percent less experience, come from smaller firms, and contain .07 standard deviations more stereotypically female content such as requests for patience, carefulness, and beauty. The dominant driver of these gender gaps is content-based matching between posted job ads and the declared gender in new workers' resumes. 'Action-based' mechanisms -based on a worker's own actions or recruiters' reactions to their resume- contribute relatively little to the gaps we measure. |
| Keywords: | Recommender System, Algorithm, Gender, Job Platform |
| JEL: | C93 J71 J16 O33 M50 |
| Date: | 2025–11 |
| URL: | https://d.repec.org/n?u=RePEc:crm:wpaper:25108 |
| By: | Hessel Oosterbeek; Tina Rozsos; Bas van der Klaauw |
| Abstract: | Close to 20% of secondary school students in Amsterdam - and elsewhere - transfer between secondary schools at some point, even when initially placed in their most-preferred school. School switching is costly for the students involved and disrupts the learning environment of their former and new classmates. Using data from the Amsterdam secondary-school match linked to administrative registers, we show that switching can be predicted by hard-to-rationalize initial school choices. Over 60% of switchers can be correctly identified at the admission stage. Simulations indicate that encouraging predicted switchers to adjust their preference ranking of schools could reduce the switching rate by almost 15%. |
| Keywords: | secondary education, school choice, school switching, admission lottery |
| JEL: | I21 C35 C53 |
| Date: | 2025–12 |
| URL: | https://d.repec.org/n?u=RePEc:crm:wpaper:25159 |
| By: | Martina Bossard, Marc Möller, Catherine Roux |
| Abstract: | We use a stylized model of a dynamic innovation tournament to show that the effectiveness of monetary incentives depends on whether contestants receive cardinal, ordinal, or no information about their rival’s performance. The model’s main implication is that performance information acts as a substitute for prize money in creating incentives to invest in new ideas: The investment-maximizing information policy switches from no to ordinal to cardinal information as the tournament’s prize is reduced. A laboratory experiment provides support for our theory but also unveils an unpredicted pattern of behavior capable of overturning the model’s conclusions concerning optimal policy. |
| Keywords: | Innovation Tournaments; Performance Information; Rank Information; R&D Investment. |
| JEL: | O31 C72 D83 |
| Date: | 2026–03 |
| URL: | https://d.repec.org/n?u=RePEc:ube:dpvwib:dp2602 |
| By: | Jeon, Doh-Shin; Drugov, Mikhail |
| Abstract: | This paper studies the incentives of a subscription-funded platform that offers both proprietary and third-party content to bias its recommendations about which con tent users should consume. Consistent with Netflix’s practice, we consider fixed-fee bargaining between the platform and a content provider, which eliminates any static incentive to bias recommendations. However, our dynamic model identifies two dis tinct incentives to bias recommendations: improving the platform’s future bargain ing position and increasing users’ expected surplus. The former favors first-party content, while the latter favors the ex ante superior content. As a result, biased recommendations may lead to either self-preferencing or third-party preferencing. |
| JEL: | D83 L42 |
| Date: | 2026–04–29 |
| URL: | https://d.repec.org/n?u=RePEc:tse:wpaper:131694 |