Evolution of Trading Structures

Evolution of Trading Structures
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交易结构的演变

DOI:
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发表时间:
1996
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通讯作者:
Yannis M. Ioannides
Yannis M. Ioannides
中科院分区:
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文献类型:
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作者:
Yannis M. Ioannides

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本文回顾了交易结构的演变,通过研究两个相关的链在文献中的经济学与互动代理,一个,工程,假设一个特定的拓扑结构之间的互动代理,和两个,工程,让随机机制确定该拓扑结构。论文回顾了各向同性环境下的交互式离散选择模型,并提出了在某些程式化的各向异性环境下的扩展,这对经济学家来说特别有趣。特别是,互动的循环模式突出了货币和信贷的作用;树型设置描述了瓦尔拉斯互动。本文提出的随机拓扑互动的方法,它作为就业的规模分析的交易集团,从而利用全方位的可能的拓扑性质的交易结构。本文提出了一个整合这些方法,旨在利用其自然互补性。在最简单的可能版本中,我们的合成涉及个人的决定和期望,随机性和自然组合,以确定初始的“原始”互动拓扑。相互作用的动态性从此推动着经济的发展,贸易结构的演变关键取决于相互作用模型均衡结构的多重性和稳定性。该文件涉及一些额外的主题,包括匹配模型,空间方面的贸易结构的演变和统计推断的问题。
This paper reviews the evolution of trading structures by examining two pertinent strands in the literature on economics with interacting agents, one, works that presume a specified topology of interactions among agents, and two, works that let random mechanisms determine that topology. The papr reviews interactive discrete choice models in isotropic settings and proposes extensions within certain stylized anisotopic settings which are particularly interesting for economists. In particular, circular patterns of interaction highlight the role of money and credit; tree-type settings depict Walrasian interactions. The paper suggests that the random topology of interaction approach, which as employed analyses of sizes of trading gorups and thus exploit the full range of possible topological properties of trading structures. The paper proposes an integration of those approaches which is intended to exploit their natural complementaries. In the simplest possible version, our sythesis involves individual decisions and expectations, randomness, and nature combinng to fix an initial "primordial" topology of interaction. The dynamics of interaction move the economy from then on. The evolution of trading structures depends criticlaly upon multiplicity and stability properties of equilibrium configurations of the interaction model. The paper addresses a number of additional topics, including matching models, spatial aspects of the evolution of trading structures and issues of statistical inference.