Annick Vignes

Fashion, novelty and optimality: an application from Physics

We apply a physical-based model to describe the clothes fashion market. Every time a new outlet appears on the market, it can invade the market under certain specific conditions. Hence, the “old” outlet can be completely dominated and disappears. Each creator competes for a finite population of agents. Fashion phenomena are shown to result from a collective phenomenon produced by local individual imitation effects. We assume that, in each step of the imitation process, agents only interact with a subset rather than with the whole set of agents. People are actually more likely to influence (and be influenced by) their close “neighbors”. Accordingly, we discuss which strategy is best fitted for new producers when people are either simply organized into anonymous reference groups or when they are organized in social groups hierarchically ordered. While counterfeits are shown to reinforce the first strategy, creating social leaders can permit to avoid them.

Syndication Strategies in Venture Capital Networks

Empirical evidence shows that venture capitalists syndicate to finance start-ups. This paper focuses on the role of the social network generated by these syndication operations. We consider the links developed between venture capitalists, through co-investment rounds, and we study their relationships both through network and econometric analyses. We first demonstrate that the syndication network is not random. Secondly, we show that the different assortativities (degree, spatial, industrial) are positive, suggesting that venture capitalists tend to co-invest with their peers. Thirdly, we measure the influence of different proximities (spatial, national and industrial) on the collaborations between the different players. National and industrial proximity have a strong impact on the determination of links. Finally, we provide evidence that past partners are preferred for future syndication, even if new links do appear regularly.

Residential Income Segregation: A Behavioral Model of the Housing Market

We represent the functioning of the housing market and study the relation between income segregation, income inequality and house prices by introducing a spatial Agent-Based Model (ABM). Differently from traditional models in urban economics, we explicitly specify the behavior of buyers and sellers and the price formation mechanism. Buyers who differ by income select among heterogeneous neighborhoods using a probabilistic model of residential choice; sellers employ an aspiration level heuristic to set their reservation offer price; prices are determined through a continuous double auction. We first provide an approximate analytical solution of the ABM, shedding light on the structure of the model and on the effect of the parameters. We then simulate the ABM and find that: (i) a more unequal income distribution lowers the prices globally, but implies stronger segregation; (ii) a spike of the demand in one part of the city increases the prices all over the city; (iii) subsidies are more efficient than taxes in fostering social mixing.