玻利维亚犯罪与暴力减少政策组合的路径依赖型基于主体的微观模拟：调查校准、自适应仿真器集成、全局敏感性分析、缓和马尔可夫链蒙特卡洛与多目标政策分析
A Path-Dependent Agent-Based Microsimulation of Crime and Violence Reduction Policy Portfolios in Bolivia: Survey Calibration, Adaptive Emulator Ensembles, Global Sensitivity, Tempered MCMC, and Multi-Objective Policy Analysis
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中文总结 AI 辅助
本研究构建了基于调查校准的路径依赖型主体微观模拟，评估玻利维亚多种犯罪与暴力减少政策组合，通过仿真器集成和敏感性分析处理不确定性，结果作为结构性政策情景而非因果预测。
中文摘要 AI 辅助
本研究开发了一种基于调查校准的、路径依赖的基于主体的微观模拟，用于评估玻利维亚的犯罪与暴力减少政策。利用2025年住户调查和2025年第四季度连续就业调查，结合官方扩展权重和跨调查供体匹配，构建了一个合成人口。该模型结合了异质性主体、基于地点的风险、犯罪适应性、机构能力、社区组织和多种政策渠道。不确定性通过自适应高斯过程和树集成仿真器、全局敏感性分析、缓和集成马尔可夫链蒙特卡洛以及预测性元校准进行传播。模拟的政策组合包括重点警务、社区控制、Guardabosques型激励、社会预防、环境干预、司法改革、调查、康复和金融网络破坏。结果被解释为结构性政策情景而非因果预测，并明确关注位移效应、分配效应、实施能力和多目标权衡。
英文摘要
This study develops a survey-calibrated, path-dependent agent-based microsimulation for evaluating crime and violence reduction policies in Bolivia. A synthetic population is constructed from the 2025 Household Survey and the fourth-quarter 2025 Continuous Employment Survey using official expansion weights and cross-survey donor matching. The model combines heterogeneous agents, place-based risk, criminal adaptation, institutional capacity, community organization, and multiple policy channels. Uncertainty is propagated through adaptive Gaussian-process and tree-ensemble emulators, global sensitivity analysis, tempered ensemble MCMC, and predictive meta-calibration. Simulated portfolios include focused policing, community control, Guardabosques-type incentives, social prevention, environmental interventions, justice reforms, investigation, rehabilitation, and financial-network disruption. Results are interpreted as structural policy scenarios rather than causal forecasts, with explicit attention to displacement, distributional effects, implementation capacity, and multi-objective trade-offs.
