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Anticipating employment location patterns in economic regions: modeling complex dynamics
Applied Network Science ( IF 1.3 ) Pub Date : 2019-11-13 , DOI: 10.1007/s41109-019-0208-2
Sanda Kaufman , Miron Kaufman , Mark Salling

Complex social-ecological systems—such as cities and regions—change in time whether or not we intervene through plans and policies. This is due in part to the numerous individual and organizational actors who make self-interested, unilateral decisions. Public decision makers are expected to act in the public interest and are accountable to constituents. They need the ability to explore alternatives, select ones that are likely to benefit the public, and avoid or mitigate negative outcomes. Predicting processes and outcomes in the context of complex systems is risky, however, and mistakes can be costly. Switching from prediction of specific future states to anticipation of possible ranges of futures may help contend with the uncertainties inherent in these systems. We propose here a dynamic network model for generating ranges of possible futures for employment location in an economic region. The model can be used to anticipate employment location effects of various policies. First, using historical (2002–2015) number and location of jobs in two rather different metropolitan areas, we calibrate the model for each and validate it against actual data. Having found that the model performs well, we show how policy makers can use it to ask what-if questions regarding proposed policies to either attract businesses to specific locations or discourage them from locating in parts of the region.

中文翻译:

预测经济区域的就业区位模式:对复杂的动力学建模

无论我们是否通过计划和政策进行干预,复杂的社会生态系统(例如城市和地区)都会随时间变化。这部分是由于众多个人和组织参与者做出了自私的,单方面的决定。公众决策者应为公众利益行事,并对选民负责。他们需要有能力探索替代方案,选择可能使公众受益的替代方案,并避免或减轻负面结果。但是,在复杂系统的情况下预测过程和结果是有风险的,并且错误可能会造成很高的代价。从对特定未来状态的预测转换为对未来可能范围的预期可能有助于应对这些系统固有的不确定性。我们在这里提出一种动态网络模型,用于生成经济区域中就业地点的可能期货范围。该模型可用于预测各种政策对就业地点的影响。首先,我们使用历史记录(2002-2015)在两个截然不同的大都市地区的工作数量和位置,针对每个模型对模型进行校准,并根据实际数据进行验证。发现该模型运行良好后,我们将展示决策者如何使用它来询问有关拟议政策的假设问题,以吸引企业到特定地点或阻止他们在该地区的某些地区工作。使用历史数据(2002-2015年)在两个截然不同的大都市地区工作岗位的数量和位置,我们对每个模型进行校准,并根据实际数据进行验证。发现该模型运行良好后,我们将展示决策者如何使用它来询问有关拟议政策的假设问题,以吸引企业到特定地点或阻止他们在该地区的某些地区工作。使用历史数据(2002-2015年)在两个截然不同的大都市地区工作岗位的数量和位置,我们对每个模型进行校准,并根据实际数据进行验证。发现该模型运行良好后,我们将展示决策者如何使用它来询问有关拟议政策的假设问题,以吸引企业到特定地点或阻止他们在该地区的某些地区工作。
更新日期:2019-11-13
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