Research

Publications

Working Papers

  • Kei Ikegami, Procuring Hunting Effort: Structural Estimation and Optimal Contract Design
    (New draft: March 17, 2026)

    This paper analyzes the procurement of wildlife damage control under informational frictions and model uncertainty, focusing on deer management in Hokkaido, Japan. I develop a structural state-space model to estimate hunter responses to two prevalent incentive schemes: per-diem dispatch payments (input-based) and per-animal bounty payments (output-based). Using administrative records from 2022–2024, the empirical estimation reveals that while both schemes increase harvests, they differ in their impact on damage reduction: bounty-based incentives exhibit a capture-damage gap where increased harvests are positively correlated with realized damages. I then design optimal and robust contracts by accounting for model ambiguity regarding hunters’ behavioral margins and ecological linkages. The results show that while a standard optimal contract favors cost-effective per-diem payments, a max-min robust contract shifts toward bounty-based incentives. This shift occurs because bounties activate multiple behavioral channels, serving as a hedge that ensures stable performance across a range of model specifications. These findings provide an economic rationale for the coexistence of bounty schemes in practice as a tool for ensuring robustness against uncertainty.

  • Kei Ikegami, Exposure Design for Two-Sided Platforms
    (New draft: January 8, 2026)

    Online platforms choose exposure rules—who is shown to whom and how often—to speed up matches and raise flow surplus. Yet aggressively matching today’s best pairs can cannibalize future opportunities by thinning the effective option set for those who remain. I develop a two-sided sequential-search model with platform-controlled meeting propensities and define user value as the aggregate continuation value of search on the platform, a natural objective for platforms that seek to grow and retain users. I show that maximizing flow match surplus generally does not maximize user value, and I propose a tractable algorithm to compute user-value–optimal exposure via entropic regularization, annealing, and Bregman–Dykstra projections. Applying the framework to a doctor–spot-job platform, I estimate preferences under two exposure regimes and quantify the gains from redesigning exposure.

    • SSCW 2026, IIOC 2026, ERATO weekly meeting

  • Kei Ikegami, Bargaining over Leasing Contracts
    (New draft coming soon)

    This paper investigates how kinked revenue-sharing contracts are negotiated and how they embed bargaining power. Using proprietary panel data on tenant contracts and sales in shopping malls, I estimate a structural model in which a risk-averse tenant and mall renegotiate contracts based on realized sales. The results show that the mall-to-tenant power ratio shapes contract terms through two channels: (i) risk posture—powerful malls can insist on low-variance, high-fixed-rent contracts; and (ii) sales expectations—pessimistic forecasts cap fixed rent and shift weight to commissions. Because these forces offset, contract form alone seldom signals power imbalance. Counterfactual simulations imposing fairer bargaining weights indicate that, after risk adjustment, total rent can triple even when the mall is relatively weak.

    • ESWC 2025
    • IIOC 2025
    • APIOC 2024
    • UTMD Rising Star in Market Design
    • NYU seminar

  • Kei Ikegami, Atsushi Iwasaki, Akira Matsushita, and Kyohei Okumura,
    Evaluating the Efficiency of Regulation in Matching Markets with Distributional Disparities
    (New draft: July 7, 2025)
    Accepted for EC 2025 (Exemplary Paper Award, Empirics Track)

    Cap-based regulations are widely used to address distributional disparities in matching markets, but their efficiency relative to alternative instruments such as subsidies remains poorly understood. This paper develops a framework for evaluating policy interventions by incorporating regional constraints into a transferable utility matching model. We show that a policymaker with aggregate-level match data can implement a taxation policy that maximizes social welfare and outperforms any cap-based policy. Using newly collected data from the Japan Residency Matching Program, we estimate participant preferences and simulate counterfactual match outcomes under both cap-based and subsidy-based policies. The results reveal that the status quo cap-based regulation generates substantial efficiency losses, whereas small, targeted subsidies can achieve similar distributional goals with significantly higher social welfare.

    • SITE 2025
    • EC 2025
    • IIOC 2025
    • APIOC 2024
    • NYU seminar
    • JEA annual meeting 2024

  • Kei Ikegami, Ken Onishi, and Naoki Wakamori,
    Joint Venture Formation in Procurement Auctions
    (New draft: October 23, 2024)

    We propose a model for joint venture formation in the context of procurement auctions. This model enables us to identify the formation mechanism, which is necessary for simulating counterfactual auction settings. We estimate the model using newly collected Japanese procurement auction data. Our estimates reveal the presence of cost synergies: joint ventures are more likely to be cost-effective compared to standard bidders. Despite this pro-competitive effect, our simulation indicates that excessive encouragement of joint ventures hinders cost-effective procurement by reducing competition. This anti-competitive effect arises from the diminished incentive to enter the auction due to the possibility to compete with joint ventures.

    • AEA 2024
    • Otaru University of Commerce
    • Yokohama National University
    • NYU seminar
    • APIOC 2022

Work in Progress

  • Kei Ikegami and Kan Kuno, Wage Stagnation in Daycare Industry: A Two-Sided Market Perspective