Choosing between Concentration Indices: The Iso-Concentration Curve
Choosing between Concentration Indices: The Iso-Concentration Curve
复制标题
在浓度指数之间进行选择：等浓度曲线
DOI：
--
复制
发表时间：
1979
期刊：
影响因子：
--
通讯作者：
S. Davies
中科院分区：
文献类型：
--
作者：
S. Davies
在任何一个行业中，通常都可以确定集中的两个组成部分：n，该行业的企业数量; I，这些企业在市场份额上的不平等。例如，在传统的结构-行为-业绩模型中，将产业盈利能力与串通的可能性联系起来，通常认为，串通（和其他一些非竞争性制度，如价格领先）应该更容易实现和维持，因为产业中的公司越少，对于一定数量的公司，领先公司的份额就越大。在关于最适当的集中度经验指数的文献中，大部分争论都集中在这两个组成部分应具有的相对权重上。因此，菲利普斯（Phillips，1976，p.242）和其他许多人沿着批评了集中率（CR），因为它忽略了领先企业集团内部的规模不平等（这本身就是任意定义的），而只强调领先企业集团和所有其他企业之间的不平等。同样，他声称CR和公司数量（n）之间的关系是可变的和模糊的。从洛伦兹曲线（L）导出的各种指数克服了其中的一些问题;基于整个累积浓度曲线，它们相当明确地反映了I。然而，这是以忽略企业数量为代价的--一个由100家同等规模的企业组成的行业，其L值（如表1所定义）与5家同等规模的企业中的一家相同。最初，人们认为赫芬达尔指数（H）和其他类似的指数克服了这些问题，因为它们反映了I和n。然而，随后，哈特提出，H对n太敏感，因此，CR可能是更好的。2另一方面，菲利普斯质疑附加在I上的权重是否合适（1976年，第100页）。242-243）。近年来，由信息论衍生出来的各种熵统计方法越来越受到人们的欢迎。虽然大多数经济学家对这些问题的关注较少，但哈特（1975，第427页）指出，一阶熵（E）可能会因为明显依赖于n而受到影响。当然，在文献中还提出了许多其他的指数，尽管它们大多可以被看作是四种基本类型中的一种或另一种的变体
It is usual to identify two constituent parts to concentration in any industry: n, the number of firms in that industry and I, the inequalities in the market shares of those firms. For instance, in the conventional structure-conduct-performance models relating industry profitability to the potential for collusion, it is usually argued that collusion (and a number of other non-competitive regimes, e.g. price leadership) should be easier to achieve and sustain, the fewer firms there are in the industry and, for a given number of firms, the more disproportionately large is the share of the leading firms. In the literature concerning the most appropriate empirical index of concentration, much of the argument has centred on the relative weights that should be attached to these two constituents. Thus Phillips (1976, p. 242), along with many others, has criticized the concentration ratio (CR) because it ignores size inequalities within the leading group of firms (which itself is arbitrarily defined) and emphasizes only the inequalities between the leading group and all other firms. Similarly, he claims the relationship between CR and firm numbers (n) is variable and ambiguous. The various indices derived from the Lorenz Curve (L) overcome some of these problems; being based on the entire cumulative concentration curve, they reflect I fairly unambiguously. This is achieved, however, only at the cost of virtually ignoring firm numbers-an industry of 100 equally sized firms will record the same value for L (as defined in Table 1) as one of five equally sized firms. Initially it was supposed that the Herfindahl index (H) and other similar indices1 overcame these problems in that they reflected both I and n. Subsequently, however, Hart has suggested that H is too sensitive to n and that, therefore, CR may be preferable.2 Phillips, on the other hand, has questioned whether the weighting attached to I is appropriate (1976, pp. 242-243). In recent years, the various entropy statistics, arising out of information theory, have become increasingly popular. While these have been subject to less critical attention by most economists, Hart (1975, p. 427) notes that the firstorder entropy (E) may suffer from its clear dependence on n. There are, of course, many other indices suggested in the literature, although mostly they may be seen as variations on one or other of the four basic types