which of the following is a measure of the degree of industry concentration

To measure industry concentration, you can look at the number of firms in an industry. This measure is called the Herfindahl-Hirschman index. However, there are other ways of estimating the level of concentration. You can also look at the Standard location quotient.


An occupation is a set of activities performed by an employee in a specific industry. Many employees perform similar tasks within the same industry. Some occupations are highly concentrated within just a few industries, while others are distributed throughout many industries. The Standard Occupational Classification (SOC) system is used to calculate the concentration of occupations in an industry.

An occupation’s concentration in an industry influences employment outcomes, although the relationship is only weak. This relationship is largely due to changes in the employment patterns of workers in a particular industry. In addition, the extent of occupational concentration in a given industry is often overestimated due to bias arising from unobserved worker characteristics.

Occupational concentration is also influenced by the educational level of workers. In addition, the employment outcomes of workers with different levels of education may differ. This is illustrated in the next subsection. Although occupational concentration may affect employment outcomes in the United States, it also influences the segregation of workers in a given industry.

The degree of industry concentration can also be influenced by barriers to entry. These barriers prevent new firms from competing with the established firms. These barriers can be imposed by government-granted privileges, such as patents and exclusive franchises. The existing firms may also have a competitive advantage, due to their lower costs and brand loyalty.

Computer occupations are widespread and reflect the importance of information technology. However, there are also a number of computer occupations that have low industry concentrations. These include computer systems analysts, web developers, and computer network architects. These occupations are spread widely across industries, but their industry concentration is low.

Occupation-based variables are also subject to measurement error. For example, errors in the occupation coding may cause overestimation of the frequency of occupation changes. Further, the miscoding of occupations can lead to errors that affect the employment shares. Moreover, occupation mismeasurement is not systematic. Consequently, a large number of occupations may be misclassified, increasing the standard errors of occupation-based variables.

The degree of industry concentration in a given industry can be high for some occupations. The health care and social assistance industry, for example, employed 87 percent of registered nurses. This represents one out of every eight jobs in the industry. Another example is retail salespeople and cashiers. Retail salespeople made up 45 percent of all retail sector employment, but fewer than 20 percent of them worked outside of it.

Herfindahl-Hirschman index

The Herfindahl-Hirschmann index is an index that measures the concentration of a particular industry. It is most often calculated as a ratio and indicates whether a sector has a high degree of concentration. When the concentration ratio increases, there is a high probability that a market will become dominated by a few players. High concentration is a concern for regulators, and mergers that increase the index by 200 points are likely to be viewed as antitrust violations.

The degree of industry concentration varies among industries, depending on their size and geographic area. For instance, the footwear industry in the U.S. is not very concentrated, while the house slipper industry has a high level of concentration. In addition, the semiconductor manufacturing industry is relatively concentrated.

Although the Herfindahl index is an accurate indicator of concentration, the Herfindahl index is not a perfect tool. While it does require only a small amount of data, it fails to account for the complexities of markets. Companies with a high index value are more likely to have a high degree of market power, but that doesn’t necessarily mean that the industry is more or less competitive.

The Herfindahl-Hirschmann index measures the degree of industry concentration by taking into account the proportion of market share held by each firm. For instance, if there are five firms in a market, the Herfindahl-Hirsch-Hirschman index would be 3000, while if a market is monopolistic, the index would be as high as 10,000.

The CR4 index also does not account for differences in market structure. Four firms with a 20% market share each have the same CR4 value. In contrast, firms with 4% market shares have the same CR4 value as firms with 1% or 5% market share. As a result, the level of competition between four equal-sized firms is different.

A merger could violate antitrust laws if the merger would increase an industry’s HHI by 200 points. To avoid such a violation, the deal maker must show that the merger does not result in a monopolistic situation. An example of an industry with a high HHI would be a merger between eight firms with varying market shares.

One company may have a 90% market share in a particular product segment. This is a problem if companies are targeting different geographies. For example, two firms in the food industry may have a 50% market share, but each would target different products.

Standard location quotient

The Standard Location Quotient (LQ) measures the degree to which an industry’s jobs are concentrated within a metropolitan area. In the Twin Cities region, this measure reveals which industries are the most prevalent and in which regions there is a greater concentration. This measure uses employment data from the private sector for the year 2015 to determine the percentage of each industry’s employment in the metro area.

Using the location quotient (LQ), we can compare the concentration of industry in a given region to that of the entire nation. The LQ is computed using a number of variables, including the regional or national size of the industry. For example, if a mining region has a quotient of 1.0, the concentration of mining is 1.8.

The location quotient is used to measure the degree to which one industry dominates a region. This ratio is calculated by comparing the share of industry establishments in a metropolitan area to the total number of industry establishments in a region. A higher value indicates a higher level of industry specialization, while a lower number indicates deficiency. The location quotient is useful for understanding the economic strengths and weaknesses of a region.

A region’s LQ can identify export industries, such as manufacturing, that are based in the area. If the LQ is high enough, these industries can provide a competitive advantage to the area’s economy. Additionally, the LQ can indicate economic development opportunities based on a region’s existing skilled labor pool, facilities, and transportation hubs. Furthermore, if the LQ is significantly lower than 1.0, there may be opportunity for expanding related industries within a region.

The LSDs of different industries vary greatly. Those industries with a high variance have a high geographic concentration, while industries with low variance have low geographic concentration. Similarly, industries with low variances are more evenly spread across the country. This data allows us to calculate a standard location quotient for an industry and calculate its relative geographic concentration.

A region with a high LQ has high employment concentration in many industries. The number of registered nurses, for instance, is 10 percent of the total number of jobs in the region. The LQ for registered nurses in a region is 1.11. These industries tend to be export-oriented, and therefore bring money into the region. In contrast, retail and services are usually local-based.

Utah has a high location quotient for mining industries, which has an extreme value of 10. The other industries in Utah have more normal LQ values. This means that the degree of industry concentration is greater in these regions than elsewhere in the state. However, the mining sector is the most concentrated in the state, and it is located in the northwest, north, and eastern regions.

The LQ measures the degree of industry concentration by comparing the number of jobs in a region to the number of jobs in the country. An LQ of one indicates that an industry is more concentrated in the region than it is in the nation, and a LQ of two or higher indicates that an industry is export-oriented.

Chelsea Glover