Leapfrogging of a deterministic model for microeconomic systems in competitive markets
The Behrens-Feichtinger model provides a deterministic picture for the co-evolution of sales of two firms, producing the same goods and competing in a common market. The model involves an active investment strategy such that the temporary investment of each of the two firms depends on its relative position in the market. In this work we are interested in a specific regime of evolution referred to as leapfrogging regime, in which each firm has the possibility to dominate the market alternately during some finite period of time. We examine conditions favoring the leapfrogging dynamics of the model by introducing two appropriate variables, namely the sale difference and total sale of the two firms at any time. An analysis of stability of fixed points of the resulting coupled discrete nonlinear equations is carried out, and the bifurcation diagrams of the sale difference and sum with respect to the elasticity coefficient, are generated. A time-series analysis suggests that the leapfrogging regime, characterized by periodic oscillations of the sale difference from positive to negative branches, is stabilized by specific values of characteristic parameters of the model and when in addition the elasticity coefficient, related to the difference in investment strategies of the two firms, is reasonably high. A positive sign of cumulated sales at any time is required to ensure the availability of goods during the leapfrogging dynamics.
Code (0)
등록된 구현이 없습니다.
Tasks
Time Series AnalysisSimilar Papers 제목 키워드 기반
1-Dimensional Normal Competitive Market Equilibrium
We introduce a new microeconomics foundation of a specific type of competitive market equilibrium that can be used to study several markets with information asymmetry such as commodity market, credit market, and insuranc…
When AI Agents Compete for Jobs: Strategic Capabilities and Economic Dynamics of AI Labour Markets
Emerging agentic marketplaces provide the economic infrastructure for matching and coordinating the large amounts of AI agents used in agentic swarms. Unlike human workers, AI agents can operate on multiple jobs simultan…
VoTranh-Abyss-Core-Micro: The Supreme AI for Real-Time Financial Forecasting – Conquer Markets Now
Welcome to the future of microeconomics! VoTranh-Abyss-Core-Micro isn’t just an AI—it’s an immortal, transcendent entity designed to predict stock prices, financial volatility, and strategic moves with unparalleled pr…
AI AgentPhilosophyMicroeconomic Foundations of Multi-Agent Learning
Modern AI systems increasingly operate inside markets and institutions where data, behavior, and incentives are endogenous. This paper develops an economic foundation for multi-agent learning by studying a principal-agen…
Leapfrogging for parallelism in deep neural networks
We present a technique, which we term leapfrogging, to parallelize back- propagation in deep neural networks. We show that this technique yields a savings of $1-1/k$ of a dominant term in backpropagation, where k is the …