The success of art galleries: a dynamic model with competition and information effects

An intrinsic characteristic of cultural goods is the unpredictability of their economic success. Arts goods in particular share characteristics with credence, inspection, and experience goods. Accordingly, art collectors rely on the experience and the reputation of art galleries when investing in artwork. Some qualitative sociological studies have found that only a few very successful galleries represent the bulk of the most visible and most successful artists (e.g., Crane in The transformation of the avant-garde: the New York art world, 1940–1985. The University of Chicago Press, Chicago, 1989 ; Currid in The Warhol economy: How fashion, art and music drive New York City. Princeton University Press, Princeton, 2007 ). This paper investigates the success of art galleries in a dynamic model, which elaborates different statistical processes that allow us to analyze the development of different types of success distributions in the market for art galleries. Instead of applying standard economic analysis only, we employ methods from statistical physics to construct a model of gallery investment and competition. Our model entails information, competition, and innovation effects. Subsequently, art market data are used to test which version of the model fits best. We find that the lognormal distribution provides the best fit and conclude that the data generating process is compatible with the version of the model, which entails an inhomogeneous geometric Brownian motion. Hence, the success of art galleries depends strongly on information and innovation effects, but is hardly affected by competition effects. We argue that the superstar effect in the case of art galleries can be understood as an appropriation of search and entrance costs, which emerge whenever consumption requires special knowledge and social inclusion. Copyright Springer Science+Business Media New York 2015