Modelling a tradable transport permit scheme using system dynamics
Modelling a tradable transport permit scheme using system dynamics
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DOI：
10.3389/ffutr.2023.994349
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发表时间：
2023-01
期刊：
影响因子：
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通讯作者：
G. Harrison;S. Shepherd
中科院分区：
文献类型：
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作者：
G. Harrison;S. Shepherd
简介：在本文中，我们考虑可交易运输许可证计划（TTPS）的系统动力学（SD）建模。 TTPS 复杂且不确定，尚未在世界任何地方的实验性试验之外得到实施，但一段时间以来，它被认为是减少汽车出行及其相关外部性的有效和公平的政策反应。方法：尽管有大量计量经济学模型探索 TTPS 的潜力，但（据我们所知）还没有发布使用 SD 方法的模型。 SD 是一种适合我们加深对 TTPS 效率和公平性理解的方法，因为它可以捕获反馈并跟踪一段时间内 TTPS 的影响。因此，我们借鉴现有文献，开发了 TTPS 的 SD 模型。这是一个微观层面的模型，在几个月内每天都考虑人口内的异质性。我们对价格敏感性、初始许可证价格、每日偏好和许可证分配进行敏感性测试，并开发这些属性的组合场景。结果：我们的建模结果表明 TTPS 对整个群体的异质性敏感，这将影响最终的均衡价格。贸易鼓励财富在人群中的重新分配，但也可能意味着某些旅行需求得不到满足，这可能需要根据需要进行一些分配或受保护许可证的某一部分。将非汽车用户纳入分配进一步鼓励交易行为，并允许对汽车使用的外部性进行补偿。讨论：通过对输出的分析，我们能够为成功的 TTPS 所需的治理框架带来新的见解。特别是，我们已经展示了在考虑全民公平问题时，在 TTPS 设计中分配考虑的重要性。尽管没有现有方案的数据可供我们校准模型，但我们将趋势与现场 TTPS 实验的数据进行了比较。
Introduction: In this paper we consider system dynamics (SD) modelling of tradable transport permit schemes (TTPS). TTPS are complex and uncertain, having not yet been implemented beyond experimental trials anywhere in the world, yet have for some time been suggested as an efficient and equitable policy response to reducing car-based travel and its associated externalities. Method: Although there is a large number of econometric models that explore the potential of TTPS, there have been none published (to our knowledge) that have used the SD approach. SD is an appropriate method for developing our understanding of TTPS efficiency and equity as it captures feedbacks and tracks the influence of the TTPS over a period of time. Thus, we have developed an SD model of TTPS, drawing from the literature that already exists. It is a micro-level model that considers heterogeneity within a population on a daily basis over a matter of months. We carry out sensitivity testing of price sensitivity, initial permit price, daily preference and permit allocation and develop combined scenarios of these attributes. Results: Our modelling results suggest a sensitivity of TTPS to heterogeneity across the population, which will influence the final equilibrium price. Trading encourages a redistribution of wealth across the population but may also mean that some travel needs are not met, which may require some allocation according to need or a certain portion of protected permits. The inclusion of non-car users within the allocation further encourages trading behaviours and allows for compensation for externalities of car use. Discussion: Through an analysis of outputs we are able to bring new insights into the governance frameworks required for a successful TTPS. In particular we have shown the importance of allocation considerations in the design of a TTPS when issues of fairness across the population are considered. Although there is no data of existing schemes available for us to calibrate our models, we compare the trends with data from an in-the-field TTPS experiment.