Agent-Based Modeling of Internal Migration

基于代理的内部迁移建模

• 批准号: 8820409
• 负责人: LINGXIN HAO
• 金额: $ 24.01万
• 依托单位: JOHNS HOPKINS UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-26 至 2016-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8820409
• 关键词: Accounting; Age; Algorithms; Area; Benchmarking; Capital; Censuses; China; Chinese People; Complex; Computer Simulation; Contrast Media; Country; Data; Databases; Decision Making; Destinations; Development; Disadvantaged; Economic Conditions; Economics; Education; Employment; Environment; Etiology; Face; Family member; Feedback; Gender; Health; Health Care Costs; Home environment; Household; Immigration; Individual; Industry; Inequality; Internal Migrations; International; Intervention; Investments; Labor Forces; Literature; Marketing; Methods; Mexico; Modeling; Network-based; Nomads; Occupations; Outcome; Pattern; Personal Satisfaction; Policies; Population; Population Distributions; Population Growth; Population Research; Probability; Process; Production; Property; Province; Public Health; Publishing; Recording of previous events; Research; Rights; Rural; Rural Developments; Rural Spatial Distributions; Simulate; Stress; Surveys; System; Techniques; Testing; Theoretical model; United States; Urbanization; Validation; Wages; base; cluster computing; experience; improved; innovation; insight; migration; outcome forecast; preference; pressure; public health relevance; research study; rural-urban migration; social; statistics; theories

DESCRIPTION (provided by applicant): Agent-based Modeling of Rural-urban Migration in China We propose to develop a large-scale agent-based model of rural-to-urban migration in China. Large-scale migrations, both within countries and across countries, are transforming the world's population. Agent-based modeling (ABM) is a promising and underutilized means for understanding the implications of these complex migrations for population distribution and growth because it can include feedback loops, allow actor-place interactions, and reveal unexpected, emergent properties of the complex system of migration. Recent developments in ABM, notably algorithms for the efficient use of powerful computing clusters to estimate models with billions of actors (Parker and Epstein 2011), make this technique especially promising for modeling large, complex spatial processes. Thus, we would argue that the development of ABM to study large-scale migrations is an innovation that is of high scientific priority for population research. China is an excellent choice for the development of the first such model because it has, since the mid-1980s, undergone the largest single migration in the world's history, transferring some 230 million rural people by 2011, accounting for 17.4% of China's total population (Chinese National Bureau of Statistics 2012). About half of China's rural migration is from the rural inner provinces to the urbanized coast. Rural migrants are drawn to coastal areas primarily because of the high employment prospects in export-oriented industries and migrant networks (Hao et al. 2013). This monumental population shift has global economic, demographic, health, and political ramifications. While its importance is well documented, little has been done to identify and test the basic underlying causal mechanisms. The scale and duration of China's mass migration present a unique opportunity to gain valuable insights into this important historical phenomenon. The project will (1) explore, develop, and validate the conceptual model by reformulating and improving existing theories to apply to China's rural-urban migration; (2) develop a large-scale agent-based model of rural-urban migration in China, using empirically calibrated initial conditions, ex ante structural parameters, and "open" parameters to be experimented ex post, and validate the simulated stylized patterns against the reality; (3) test the explanatory power of each of the component theories integrated in our base-case model; (4) explore the dynamic outcomes of the base-case model under varying policies, economic conditions, individual preferences, and initial population conditions, and (5) find general principles of mass migration and to produce and publish our methods and results so that ABM can be applied to other large, complex migration flows.

描述（由申请人提供）：中国城乡人口流动的基于主体的模型 我们建议开发一个基于主体的中国城乡人口流动模型。国家内部和国家之间的大规模移民正在改变世界人口。基于主体的建模 (ABM) 是一种很有前途但未得到充分利用的方法，可用于理解这些复杂的迁移对人口分布和增长的影响，因为它可以包含反馈循环，允许参与者与地点之间的交互，并揭示复杂迁移系统的意外的突发特性。 ABM 的最新发展，特别是有效使用强大的计算集群来估计具有数十亿参与者的模型的算法（Parker 和 Epstein 2011），使得该技术特别有希望用于建模大型、复杂的空间过程。因此，我们认为，开发 ABM 来研究大规模迁徙是一项创新，对于人口来说具有高度的科学优先权。 研究。中国是第一个发展此类模式的绝佳选择，因为自 20 世纪 80 年代中期以来，中国经历了世界历史上最大规模的一次人口迁移，到 2011 年转移了约 2.3 亿农村人口，占中国总人口的 17.4%（中国国家统计局，2012）。中国大约一半的农村人口迁移是从农村内陆省份流向城市化的沿海地区。农村移民被吸引到沿海地区主要是因为出口导向型产业和移民网络的良好就业前景（Hao 等，2013）。这一巨大的人口变化对全球经济、人口、健康和政治产生了影响。尽管其重要性已有充分记录，但在识别和测试基本因果机制方面却做得很少。中国大规模人口迁移的规模和持续时间为深入了解这一重要历史现象提供了独特的机会。该项目将（1）通过重新阐述和完善现有理论来探索、开发和验证概念模型，以应用于中国的城乡人口流动； （2）开发一个基于主体的中国城乡迁移大规模模型，利用经验校准的初始条件、事前结构参数和事后实验的“开放”参数，并根据现实验证模拟的程式化模式； (3) 测试我们的基本案例模型中集成的每个组件理论的解释力； (4) 探索基本案例模型在不同政策、经济条件、个人偏好和初始人口条件下的动态结果，(5) 找到大规模移民的一般原则，并产生和发布我们的方法和结果，以便 ABM 可以应用于其他大型、复杂的移民流动。