摘要翻译：
了解市场参与者的渠道选择对政策制定者来说很重要，因为这会产生关于哪些渠道在传递信息方面有效的信息。这些渠道选择是社会互动递归过程的结果，并决定了可观察的交易网络。它们的特点是由于对等体相互作用而产生反馈机制，因此需要理解为复杂适应系统(CAS)。在建立CAS模型时，由于内生性无处不在，传统的方法如回归分析面临着严重的缺陷。作为另一种选择，基于过程的分析允许研究人员捕捉这些内生过程和多个反馈循环。本文将基于Agent的建模方法(ABM)应用于印度尼西亚橡胶贸易的实证实例。反馈机制是通过一种创新的社会矩阵方法来建模的，它允许在特定时期做出的决策反馈到后续时期的决策过程中，并允许Agent根据其个体特征系统地为决策参数分配不同的权重。在对观测网络的验证中，通过一种进化校准方法来处理发现的估计中的不确定性，以及模型确定下的不确定性：遗传算法找到使模拟网络和观测网络之间的相似性最大化的参数组合。结果表明，销售商的渠道选择决策主要受物理距离和债务义务以及同伴互动的驱动。在社会矩阵中，最有影响力的个人是住在其他商人附近、活跃在社会群体中、属于所在村庄大多数族裔的卖家。
---
英文标题：
《Modelling Social Evolutionary Processes and Peer Effects in Agricultural
  Trade Networks: the Rubber Value Chain in Indonesia》
---
作者：
Thomas Kopp, Jan Salecker
---
最新提交年份：
2018
---
分类信息：

一级分类：Economics        经济学
二级分类：General Economics        一般经济学
分类描述：General methodological, applied, and empirical contributions to economics.
对经济学的一般方法、应用和经验贡献。
--
一级分类：Quantitative Finance        数量金融学
二级分类：Economics        经济学
分类描述：q-fin.EC is an alias for econ.GN. Economics, including micro and macro economics, international economics, theory of the firm, labor economics, and other economic topics outside finance
q-fin.ec是econ.gn的别名。经济学，包括微观和宏观经济学、国际经济学、企业理论、劳动经济学和其他金融以外的经济专题
--

---
英文摘要：
  Understanding market participants' channel choices is important to policy makers because it yields information on which channels are effective in transmitting information. These channel choices are the result of a recursive process of social interactions and determine the observable trading networks. They are characterized by feedback mechanisms due to peer interaction and therefore need to be understood as complex adaptive systems (CAS). When modelling CAS, conventional approaches like regression analyses face severe drawbacks since endogeneity is omnipresent. As an alternative, process-based analyses allow researchers to capture these endogenous processes and multiple feedback loops. This paper applies an agent-based modelling approach (ABM) to the empirical example of the Indonesian rubber trade. The feedback mechanisms are modelled via an innovative approach of a social matrix, which allows decisions made in a specific period to feed back into the decision processes in subsequent periods, and allows agents to systematically assign different weights to the decision parameters based on their individual characteristics. In the validation against the observed network, uncertainty in the found estimates, as well as under determination of the model, are dealt with via an approach of evolutionary calibration: a genetic algorithm finds the combination of parameters that maximizes the similarity between the simulated and the observed network. Results indicate that the sellers' channel choice decisions are mostly driven by physical distance and debt obligations, as well as peer-interaction. Within the social matrix, the most influential individuals are sellers that live close by to other traders, are active in social groups and belong to the ethnic majority in their village.
---
PDF链接：
https://arxiv.org/pdf/1811.11476