Question: The Herfindahl Index coefficient and Gini coefficient are tools used in the analysis of industry concentration. Giving examples, assess their respective contribution to our understanding of industry structure.

A numerical approach to understanding economic structures has been the basis for the development of the Herfindahl-Hirschman Index and Gini coefficient. The concentration and industry structure are easily conceivable from a combination of these two indexes. The Herfindahl-Hirschman Index measures the size of the top 50 firms in the industry relative to the market. This comparison is in the form of a sum of the squares of their market shares. The primary basis behind the index is to understand the existing market structure based on the relative market shares of the top 50 (or all, if less than 50) firms. The coefficient will tend to be very high in case there is an oligopolistic market structure in which a small proportion of the firms will be holding large market shares.

However, if the market is such that the top 50 firms have small and roughly equal market shares, the coefficient will be very low. The difference between the two market structures is easily understandable by looking at the value of the coefficient. An oligopolistic market will generally have an H-H index of above 1800. This would mean that the market is concentrated and the top 50 firms have a significant majority share of the market. An industry with an H-H index of between 1,000 and 1,800 is assumed to be moderately concentrated i.e. there is a fair degree of distribution of market share with a few firms standing out slightly above the others. A market with just one firm serving the entire market (monopoly) will have an index value of 10,000. The minimum index value is of course close to zero assuming a perfect competitive market. The differences in these index values explain a lot about the industry and are often used to estimate the division of wealth between firms.

The Herfindahl-Hirschman Index of the automobile industry in the U.S. is in between 1,800 and 10,000. This is because of the fact that the industry has a lot of large players with significant market shares. However, the use of the Gini coefficient is more pertinent in measuring the distribution of wealth between firms in an industry.

The division of the US automobile industry is also supported by the Gini coefficient. Intuitively, the Gini coefficient is a measure of the relative dispersion of wealth in an industry. It measures the level of inequality of distribution of wealth in an industry. A Gini coefficient of 0 signifies perfect equality of wealth meaning that all firms in the industry have equal wealth. However, a perfect inequality of wealth is denoted by a Gini coefficient of 1. While theoretically it is impossible to have industries with Gini’s of 0 and 1, the extent to which they are close to either of these benchmarks denotes the concentration of the industry.

The US automobile sector has a Gini well above 0.5 denoting that the industry is concentrated and there is significant inequality of wealth amassed by the automobile firms. The combinatory use of the two indexes gives a clearer picture of the degree to which different firms have a share of the market and the extent of income equality (or inequality) relative to a perfect equality of wealth distribution.

Question: In the market for air travel, why might a high degree of price discrimination lead to an improvement in both allocative and technical efficiency, and yet a reduction in consumer surplus?

A high degree of price discrimination in the a