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Markets as communication systems

Simulating and assessing the performance of market networks

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Abstract

As the information relative to endowments, costs and preferences is dispersed among many agents, the quality of resource allocation depends on the ability of markets to communicate information inside the economic system. Because information is transferred through negotiation and transaction behaviors, the network of trading relations defines the channels through which it flows. In the present study, we use new computational tools to analyze the performance of two wholesale trade institutions widely used around the world: network trading and marketplace trading. Whilst network trading and marketplace trading disseminate far fewer bits of information than a perfectly transparent benchmark market, they often manage to generate an allocation of resources that is almost as good. In many cases, network trading proves more effective than marketplace trading (contrary to a common preconception). This surprising performance of network trading is linked to a form of indirect arbitrage induced by connections between networks. Implications for market design and public policy making are presented, along with prospects for further research.

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Notes

  1. In the economic literature, networks are sometimes presented as coordination mechanisms alternative to markets and hierarchies. Another approach (more fruitful in our view) considers that the network topologies is an attribute of all institutions (markets, hierarchies and others). The network gives the set of all possible interactions between the agents involved in an institution. This approach has led to two strands of literature. The first analyzes the performance of network topologies without specifying the institution shaped by the network (e.g. Jackson 2003). The second deals with the performance of network topologies for specific institutions such as the firm (e.g. Aoki 1986) or the market (e.g. Smith 1982; Ioannides 1997). The present article belongs to the last category.

  2. According to Jack Birner, it was also the point of view of Hayek who first brought to the fore that markets are communication systems: “[W]hat Hayek presents is a network theory of markets in which connectivity, frequency and strength of interactions, the establishing of new relations and the transmission of new information are central features” (Birner 1999, p. 40).

  3. Except when the network plays the role of both a transaction network and an information network on unreliable agents (Bloch et al. 2008). In this case, a U-shaped curve was found: stability is linked to low and high degrees of connection, whereas networks of intermediate density are unstable.

  4. Aid agencies have funded the construction of numerous wholesale markets in African countries.

  5. All the more so as the modelling involves various simplifications that underestimate the performance of network trading and that overestimate the performance of marketplace trading. Indeed, in order to keep the model simple, transaction costs have not been integrated into the model. These costs of search (communication, travel), negotiation, and enforcement are usually lower in the case of network trading because of the repetition of transactions between the same wholesalers. Moreover, real network trading institutions sometimes involve some mechanisms of flexibility (see Section 2.2) that have not been included in the analysis. Last but not least, we assumed a perfect transparency at the level of marketplaces (see Section 2.4), what is not always the case in the real world (see Section 2.2).

  6. Another empirical confirmation of the link between HZ and network trading can be found in the way the international trade of agricultural commodities is organized. This trade put in relation many production zones affected by natural hazards (climatic shocks, pests and diseases). Inside the zones, these hazards are correlated (they affect many farmers at the same time). On the contrary, at the international level, as the production zones are far from each other, the shocks affecting them are not correlated. In such a situation, our model predicts that network trading is better. As a matter of fact, the international trade of the main agricultural commodities such as coffee or cocoa is based on network trading: importers buy always to the same exporters, arbitrating between different countries but very few between different exporters of the same country. (the existing exchanges such as NYBOT or LIFFE are only used to hedge price risk, not to trade.)

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Acknowledgements

We thank Alan Kirman for valuable comments on an earlier draft and the two referees of the review for very interesting comments and suggestions.

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  1. UMR MOISA, CIRAD, 73 rue Jean-François Breton, TA C-99/15, 34398, Montpellier Cedex 5, France

    Franck Galtier

  2. UPR GREEN, CIRAD, Campus international de Baillarguet, TA C-47/F, 34398, Montpellier Cedex 5, France

    François Bousquet & Martine Antona

  3. UPR GREEN, CIRAD & UnB Faculdade de tecnologia, UnB Faculdade de tecnologia, Departamento de engenharia mecanica, Campus Universitario Darcy Ribeiro Asa Norte, Brasilia, DF, Brazil

    Pierre Bommel

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Correspondence to Franck Galtier.

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Galtier, F., Bousquet, F., Antona, M. et al. Markets as communication systems. J Evol Econ 22, 161–201 (2012). https://doi.org/10.1007/s00191-011-0225-5

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