An agent-based model of school choice with information asymmetries

Going from a neighbourhood-based to a choice-based system of school selection can have positive effects on enrolment in higher achievement schools, increasing average student achievement. We develop an Agent-Based model (ABM) that simulates students’ decisions on a heterogeneous agents’ framework with information asymmetries between income levels, allowing to simulate school choice policies and determine their impact on school enrolment and average student achievement. We use data from Santiago schools to initialise the model and study the impact of a discrete information signal of school achievement, as a policy implemented in 2010 in Chile called <i>traffic lights.</i>

从基于学区划分的学校招生体系转向基于自主择校的招生体系，可有效提升优质学校的入学率，进而提高学生的平均学业表现。我们构建了基于智能体的模型（Agent-Based Model，ABM），该模型在不同收入水平群体间存在信息不对称的异质智能体框架下模拟学生的决策行为，可用于模拟择校政策并评估其对学校入学情况与学生平均学业表现的影响。我们采用智利圣地亚哥的学校相关数据对该模型进行初始化，并针对智利2010年推行的一项名为“交通灯（traffic lights）”的政策展开研究——该政策的核心是向公众发布学校学业表现的离散信息信号。