nep-des New Economics Papers
on Economic Design
Issue of 2025–03–10
eight papers chosen by
Guillaume Haeringer, Baruch College


  1. Multidimensional Monotonicity and Economic Applications By Frank Yang; Kai Hao Yang
  2. Robust Pricing for Cloud Computing By Dirk Bergemann; Rahul Deb
  3. Optimal Pricing of Cloud Services: Committed Spend under Demand Uncertainty By Dirk Bergemann; Michael C. Wang
  4. Buying from the Fringe (too) By Lluis Bru; Daniel Cardona; Jozsef Sakovics
  5. Optimal technology design By Garrett, Daniel; Georgiadis, George; Smolin, Alex; Szentes, Balázs
  6. The Benefits from Bundling Demand in K-12 Broadband Procurement By Gaurab Aryal; Charles Murry; Pallavi Pal; Arnab Palit
  7. Modeling the Modeler: A Normative Theory of Experimental Design By Evan Piermon; Fernando Payró Chew
  8. The Economics of Large Language Models: Token Allocation, Fine Tuning, and Optimal Pricing By Dirk Bergemann; Alessandro Bonatti; Alex Smolin

  1. By: Frank Yang (University of Chicago); Kai Hao Yang (Yale University)
    Abstract: We characterize the extreme points of multidimensional monotone functions from [0, 1]^n to [0, 1], as well as the extreme points of the set of one-dimensional marginals of these functions. These characterizations lead to new results in various mechanism design and information design problems, including public good provision with interdependent values; interim efficient bilateral trade mechanisms; asymmetric reduced form auctions; and optimal private private information structure. As another application, we also present a mechanism anti-equivalence theorem for two-agent, two-alternative social choice problems: A mechanism is payoff-equivalent to a deterministic DIC mechanism if and only if they are ex-post equivalent.
    Date: 2025–02–26
    URL: https://d.repec.org/n?u=RePEc:cwl:cwldpp:2428
  2. By: Dirk Bergemann (Yale University); Rahul Deb (Boston College)
    Abstract: We study the robust sequential screening problem of a monopolist seller of multiple cloud computing services facing a buyer who has private information about his demand distribution for these services. At the time of contracting, the buyer knows the distribution of his demand of various services and the seller simply knows the mean of the buyerÕs total demand. We show that a simple Òcommitted spend mechanismÓ is robustly optimal: it provides the seller with the highest profit guarantee against all demand distributions that have the known total mean demand. This mechanism requires the buyer to commit to a minimum total usage and a corresponding base payment; the buyer can choose the individual quantities of each service and is free to consume additional units (over the committed total usage) at a fixed marginal price. This result provides theoretical support for prevalent cloud computing pricing practices while highlighting the robustness of simple pricing schemes in environments with complex uncertainty.
    Date: 2025–02–10
    URL: https://d.repec.org/n?u=RePEc:cwl:cwldpp:2423
  3. By: Dirk Bergemann (Yale University); Michael C. Wang (Yale University)
    Abstract: We consider a seller who offers services to a buyer with multi unit demand. Prior to the realization of demand, the buyer receives a noisy signal of their future demand, and the seller can design contracts based on the reported value of this signal. Thus, the buyer can contract with the service provider for an unknown level of future consumption, such as in the market for cloud computing resources or software services. We characterize the optimal dynamic contract, extending the classic sequential screening framework to a nonlinear and multi-unit setting. The optimal mechanism gives discounts to buyers who report higher signals, but in exchange they must provide larger fixed payments. We then describe how the optimal mechanism can be implemented by two common forms of contracts observed in practice, the two-part tariff and the committed spend contract. Finally, we use extensions of our base model to shed light on policy-focused questions, such as analyzing how the optimal contract changes when the buyer faces commitment costs, or when there are liquid spot markets.
    Date: 2025–02–11
    URL: https://d.repec.org/n?u=RePEc:cwl:cwldpp:2424
  4. By: Lluis Bru (Universitat de les Illes Balears); Daniel Cardona (Universitat de les Illes Balears); Jozsef Sakovics (Universitat de les Illes Balears and School of Economics, University of Edinburgh)
    Abstract: We analyze how to divide the requirements of a (public) firm into lots, when potential suppliers suffer from heterogeneous diseconomies of scale. The optimal design leads to all firms, included the disadvantaged competitors, the fringe, being active, despite the concomitant cost of increasing supplier profit. Setting large lots that only large firms can produce competitively is necessary; but also setting small lots that the fringe firms can competitively bid for, reduces procurement cost. If, in addition, some medium-sized lots are set aside for the fringe -- as allowed by the US regulations, but not by the EU ones -- procurement cost is further reduced.
    Keywords: Procurement, sequential auctions, block sourcing, regulation, affirmative action
    JEL: L13 L51 D47 K23
    Date: 2023–07
    URL: https://d.repec.org/n?u=RePEc:edn:esedps:310
  5. By: Garrett, Daniel; Georgiadis, George; Smolin, Alex; Szentes, Balázs
    Abstract: This paper considers a moral hazard model with agent limited liability. Prior to interacting with the principal, the agent designs the production technology, which is a specification of his cost of generating each output distribution. After observing the production technology, the principal offers a payment scheme and then the agent chooses a distribution over outputs. We show that there is an optimal design involving only binary distributions (i.e., the cost of any other distribution is prohibitively high), and we characterize the equilibrium technology defined on the binary distributions. Notably, the equilibrium payoff of both players is 1/e.
    Keywords: moral hazard; limited liability; contract theory
    JEL: D86 D82
    Date: 2023–04–01
    URL: https://d.repec.org/n?u=RePEc:ehl:lserod:118115
  6. By: Gaurab Aryal; Charles Murry; Pallavi Pal; Arnab Palit
    Abstract: We study a new market design for K-12 school broadband procurement that switched from school-specific bidding to a system that bundled schools into groups. Using an event study approach, we estimate the program reduced internet prices by 37% per Mbps per month while increasing bandwidth by 500%. These benefits occurred by mitigating exposure risk in broadband procurement – the risk that providers win too few contracts to cover fixed infrastructure costs. Using a bounds approach, we show robustness of our estimates and document that participants saved at least as much as their federal subsidies and experienced substantial welfare gains.
    JEL: D44 H42 L86 L96
    Date: 2025–02
    URL: https://d.repec.org/n?u=RePEc:nbr:nberwo:33498
  7. By: Evan Piermon; Fernando Payró Chew
    Abstract: We consider an analyst whose goal is to identify a subject’s utility function through revealed preference analysis. We argue the analyst’s preference about which experiments to run should adhere to three normative principles: The first, Structural Invariance, requires that the value of a choice experiment only depends on what the experiment may potentially reveal. The second, Identification Separability, demands that the value of identification is independent of what would have been counterfactually identified had the subject had a different utility. Finally, Information Monotonicity asks that more in- formative experiments are preferred. We provide a representation theorem, showing that these three principles characterize Expected Identification Value maximization, a functional form that unifies several theories of experimental design. We also study several special cases and discuss potential applications.
    Keywords: Revealed Preferences, experimental design, choice experiments
    JEL: D81
    Date: 2024–12
    URL: https://d.repec.org/n?u=RePEc:bge:wpaper:1471
  8. By: Dirk Bergemann (Yale University); Alessandro Bonatti (Massachusetts Institute of Technology); Alex Smolin (Toulouse School of Economics)
    Abstract: We develop an economic framework to analyze the optimal pricing and product design of Large Language Models (LLM). Our framework captures several key features of LLMs: variable operational costs of processing input and output tokens; the ability to customize models through fine-tuning; and high-dimensional user heterogeneity in terms of task requirements and error sensitivity. In our model, a monopolistic seller offers multiple versions of LLMs through a menu of products. The optimal pricing structure depends on whether token allocation across tasks is contractible and whether users face scale constraints. Users with similar aggregate value-scale characteristics choose similar levels of fine-tuning and token consumption. The optimal mechanism can be implemented through menus of two-part tariffs, with higher markups for more intensive users. Our results rationalize observed industry practices such as tiered pricing based on model customization and usage levels.
    Date: 2025–02–11
    URL: https://d.repec.org/n?u=RePEc:cwl:cwldpp:2425

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