京津冀地区人口规模调控政策参数化路径与系统模拟

政策调控是实现区域社会经济均衡发展的主要手段,采用系统分析方法评估和预测政策实施效果是进行决策的重要依据。然而,当前政策制定存在目标指向性不具体、调控力度不明确、协同作用机制不清晰等问题,既阻碍了政策的有效落实,更无法开展政策实施效果分析和决策优化。其根本症结在于缺少能够量化具体的政策目标并精确指导区域管理对策的政策参数。本文提出了面向系统动力学(System Dynamic, SD)模拟的区域调控政策参数化路径。通过细化政策指标、量化政策参数和区间化调控范围等方法,将政策调控转变为系统变量形式,代入到政策交互作用的系统动力学模型中,实现对政策调控效果的模拟。本文以区域人口规模调控政策为切入点,选择京津冀地区为案例区进行实证研究。结果显示,面向系统动力学模拟的政策参数化方案很好地重现了区域人口规模政策调控过程,能有效提高调控政策实施的精确性和可操作度,并为区域调控政策的配置和优化提供理论和方法的支撑。

Parameterization and system dynamics modeling of regional population regulation policies in the Beijing-Tianjin-Hebei region

As a most influential measure to achieve regional sustainable development and transformation strategies, coordinated regulation and control policies are drawing increasing attentions from scientists and policymakers. It is important to understand the mechanisms of policy performance and systematically estimate the effects before making regional development decisions. However, a number of problems have arisen during the formulation and implementation of current policies, such as lack of specific targeted policy orientation, unclear policy maneuverability, uncertain policy interaction mechanisms, and vague policy impacts, which all hindered the effective implementation of policy objectives. The crux of the problem lies in the lack of policy parameters that can bridge the gap between directive policy objectives and specific management practices, and between specific policy measures and system responses. Thus, this study proposes a framework of policy parameterization, which includes four steps: refining policy indicators, quantifying policy parameters, identifying regulatory regions, and modeling. Taking the regional population regulation and control of the Beijing-Tianjin-Hebei region as an example, this study implemented the policy parameterization framework in the system dynamic (SD) model of population regulation and control of the study area. The results show that: (1) The policy parameterization method has well represented the policy functional process by integrating with the SD model. (2) The trend of population regulation changes in the case study area indicates that population migration control policy had limited effect on the population dynamics. Only by improving the regional population carrying capacity, system sustainability can be achieved. (3) The parameterization method is able to specify policy implementation practices by providing specific indicators and their regulation intervals, and further providing a basis for scenario analysis and strategy optimization. Thus it can be a useful tool for directing regional regulatory policy making.