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
Abstract
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.
Related
- TypedBench: A Benchmark for Calibration, Framing Sensitivity, and Cost in System One Decision Models
- Data-driven calibration of a two-dimensional traffic flow model: Dimension reduction and optimization strategies
- Derivative-Informed Dimension Reduction of Stochastic Differential Equations: A Path-Space Sensitivity Approach
- Helstrom geometry with time-dependent spectral calibration
- Calibration scoring under dependent seed variables in Cooke's Classical Model: a Mehler-Hermite design-effect correction
BibTeX
@misc{fernandezsalguero2026pathdependent,
title = {{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}},
author = {Ricardo Alonzo Fernández-Salguero},
howpublished = {arXiv},
year = {2026},
month = oct,
doi = {10.48550/arxiv.2610.03895},
eprint = {2610.03895},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2610.03895},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - 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
AU - Ricardo Alonzo Fernández-Salguero
PY - 2026
DA - 2026/10/02
PB - arXiv
DO - 10.48550/arxiv.2610.03895
UR - https://arxiv.org/abs/2610.03895
AB - 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.
ER -