Data for: Towards a Dynamic Microeconomic Model of Corruption: A Probabilistic, Behavioral Simulation Approach

This paper presents a novel microeconomic model of corruption grounded in probabilistic decision theory, behavioral incentives, and simulation-based systems analysis. By starting from first principles, the model rigorously explores how individual agents weigh gains against probabilistically enforced penalties. We demonstrate, via Monte Carlo simulation, how even minor shifts in the parameters, such as detection probability, yield large systemic changes. The results reinforce foundational insights from behavioral economics while offering a dynamic framework for future incorporation of complex institutional variables. All mathematical derivations are provided step-by-step for replication and scalability.本文提出一种全新的腐败微观经济学模型，该模型植根于概率决策理论、行为激励机制以及基于仿真的系统分析方法。本模型从第一性原理出发，严谨探究了个体行为人如何权衡自身收益与按概率施加的处罚。我们通过蒙特卡洛模拟（Monte Carlo simulation）证明，即便参数仅发生细微调整（如查处概率），也会引发大幅系统性变动。研究结果不仅印证了行为经济学的核心理论洞见，还为未来将复杂制度变量纳入分析提供了动态分析框架。文中完整提供了全部数学推导的分步过程，以保障研究的可复现性与可扩展性。