Fikri Pitsuwan


Loading...

Last Name

Pitsuwan

First Name

Fikri

Organisational unit

Search Results

Publications 1 - 6 of 6
  • Artificial Bugs for Bug Bounty
    Item type: Working Paper
    Gersbach, Hans; Pitsuwan, Fikri; Blieske, Pio (2024)
    CEPR Discussion Papers
    Bug bounty programs, where external agents are invited to search and report vulnerabilities (bugs) in exchange for rewards (bounty), have become a major tool for companies to improve their systems. We suggest augmenting such programs by inserting artificial bugs to increase the incentives to search for real (organic) bugs. Using a model of crowdsearch, we identify the efficiency gains by artificial bugs, and we show that for this, it is sufficient to insert only one artificial bug. Artificial bugs are particularly beneficial, for instance, if the designer places high valuations on finding organic bugs or if the budget for bounty is not sufficiently high. We discuss how to implement artificial bugs and outline their further benefits.
  • Basu, Kaushik; Pitsuwan, Fikri; Zhang, Pengfei (2023)
    Journal of Economic Behavior & Organization
    A known policy dilemma occurs between the need to curb extra-large profits by some industries, like pharmaceuticals, and the need to ensure the incentive to produce is not damaged. This paper shows that a profit cap, imposed via taxation on a group of firms, can simultaneously eliminate inefficiency and excess profit by intensifying competition among oligopolistic firms. The result has a direct bearing on policy debates on COVID-19 vaccine sharing and the use of vaccine donation as a “humanitarian obligation,” and, more generally, on the regulatory institutions needed for industries that rely on R&D.
  • Pitsuwan, Fikri (2022)
    GPI Working Paper
    I study an intergenerational game in which each generation experiments on a risky technology that provides private benefits, but may also cause a temporary catastrophe. I find a folk-theorem-type result on which there is a continuum of equilibria. Compared to the socially optimal level, some equilibria exhibit too much, while others too little, experimentation. The reason is that the payoff externality causes preemptive experimentation, while the informational externality leads to more caution. Remarkably, for a particular temporal discount rate, there exists an optimal equilibrium in which the behavior of two-period-lived agents align with that of an infinitely-lived social planner. In a model with a political process, unequal political power, biased towards the young, supports an optimal equilibrium most often. Extensions include finite horizon, irreversible catastrophes, and risk-aversion.
  • Gersbach, Hans; Mamageishvili, Akaki; Pitsuwan, Fikri (2023)
    Lecture Notes in Computer Science ~ Algorithmic Game Theory
  • Gersbach, Hans; Pitsuwan, Fikri; Valvassori Bolgè, Giovanni (2024)
    CESifo Working Papers
    We examine democratic public-good provision with heterogeneous legislators. Decisions are taken by majority rule and an agenda-setter proposes a level of the public good, taxes, and subsidies. Members are heterogeneous with respect to their benefits from the public good. We find that, depending on the status quo public-good level, the agenda-setter will form a coalition with the agents who most desire, or least desire, the public good, and we may observe ‘strange bedfellow’ coalitions. Moreover, public-good provision is a non-monotonic function of the status quo public-good level. In the dynamic setting, public-good provision fluctuates endogenously, even if the agenda-setter stays the same over time. Moreover, the more polarized the legislature is, the higher is the volatility of public-good provision and the longer it may take for a society to recover from negative shocks to public-good provision. We illustrate these findings for a two-party system with polarized parties.
  • Crowdsearch
    Item type: Working Paper
    Gersbach, Hans; Mamageishvili, Akaki; Pitsuwan, Fikri (2023)
    CEPR Discussion Papers
    A common phenomenon is crowdsearch, i.e. when a group of agents is invited to search for a valuable physical or virtual object, e.g. creating and patenting on an invention, solving an open scientific problem, searching for a vulnerability in softwares, or mining for a nonce in proof-of-work blockchains. We study a binary model of crowdsearch in which agents have different abilities to find the object. We characterize the types of equilibria and identify which type of crowd guarantees that the object is found. Sometimes even an unlimited crowd is not sufficient. It can happen that inviting more agents lowers the probability of finding the object, which may also happen when non-strategic agents are added. We characterize the optimal prize and show that having one prize (winner-takes-all) maximizes the probability of finding the object but this is not necessarily optimal for the crowdsearch designer.
Publications 1 - 6 of 6