In economics, market concentration is a function of the number of firms and their respective shares of the total production (alternatively, total capacity or total reserves) in a market. Alternative terms are Industry concentration and Seller concentration.
Note, , which is the exponential index.
When antitrust agencies are evaluating a potential violation of competition laws, they will typically make a determination of the relevant market and attempt to measure market concentration within the relevant market.
As an economic tool market concentration is useful because it reflects the degree of competition in the market. Tirole (1988, p. 247) notes that:
There are game theoretic models of market interaction (e.g. among oligopolists) that predict that an increase in market concentration will result in higher prices and lower consumer welfare even when collusion in the sense of cartelization (i.e. explicit collusion) is absent. Examples are Cournot oligopoly, and Bertrand oligopoly for differentiated products.
Empirical studies that are designed to test the relationship between market concentration and prices are collectively known as price-concentration studies; see Weiss (1989).
Typically, any study that claims to test the relationship between price and the level of market concentration is also (jointly, that is, simultaneously) testing whether the market definition (according to which market concentration is being calculated) is relevant; that is, whether the boundaries of each market is not being determined either too narrowly or too broadly so as to make the defined "market" meaningless from the point of the competitive interactions of the firms that it includes (or is made of).
In economics, market concentration is a criterion that can be used to rank order various distributions of firms' shares of the total production (alternatively, total capacity or total reserves) in a market.
Section 1 of the Department of Justice and the Federal Trade Commission's Horizontal Merger Guidelines is entitled "Market Definition, Measurement and Concentration." Herfindahl index is the measure of concentration that these Guidelines state that will be used.
A simple measure of market concentration is 1/N where N is the number of firms in the market. This measure of concentration ignores the dispersion among the firms' shares. It is decreasing in the number of firms and nonincreasing in the degree of symmetry between them. This measure is practically useful only if a sample of firms' market shares is believed to be random, rather than determined by the firms' inherent characteristics.
Any criterion that can be used to compare or rank distributions (e.g. probability distribution, frequency distribution or size distribution) can be used as a market concentration criterion. Examples are stochastic dominance and Gini coefficient.
Curry and George (1981) enlist the following "alternative" measures of concentration:
(b) The Rosenbluth (1961) index (also Hall and Tideman, 1967):
(c) Comprehensive concentration index (Horvath 1970):
(d) The Pareto slope (Ijiri and Simon, 1971). If the Pareto distribution is plotted on double logarithmic scales, [then] the distribution function is linear, and its slope can be calculated if it is fitted to an observed size-distribution.
(e) The Linda index (1976)
(f) The U Index (Davies, 1980):
The "number of effective competitors" is the inverse of the Herfindahl index.
Terrence Kavyu Muthoka defines distribution just as functionals in the Swartz space which is the space of functions with compact support and with all derivatives existing.The Media:Dirac Distribution or the Dirac function is a good example .