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Industry clusters Background Controversy Cluster drivers Identifying clusters Clusters and economic performance Clusters and policy

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Industry clusters Source: Making Sense of Clusters by Joseph

Cortright, Impresa, Inc., for the Brookings Institution.

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Identifying clusters

How to identify an industry cluster?

Two approaches: top-down an bottom-up

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Identifying clustersTop-down approachDeductive – relies on secondary data Location quotients Input-output relationships Patent data and industry-specific data

(directories)

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Identifying clustersTop-down approach Location quotients

Advantage: easily calculated Disadvantage: no information regarding inter-industry

links

A location quotient greater than one indicates that an industry has a strong presence in a state or area relative to the U.S. economy.

The following slide shows LQs for manufacturing in Tennessee.

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Manufacturing industry LQ311Food manufacturing 1.34312Beverage and tobacco product manufacturing 1.52313Textile mills 1.79314Textile product mills 1.18315Apparel manufacturing 1.48316Leather and allied product manufacturing 0.49321Wood product manufacturing 1.53322Paper manufacturing 2.85323Printing and related support activities 1.17324Petroleum and coal products manufacturing 0.48325Chemical manufacturing 1.47326Plastics and rubber products manufacturing 1.67327Nonmetallic mineral product manufacturing 1.61331Primary metal manufacturing 1.41332Fabricated metal product manufacturing 1.43333Machinery manufacturing 1.04334Computer and electronic product manufacturing 0.17335Electrical equipment and appliance mfg. 2.41336Transportation equipment manufacturing 1.81337Furniture and related product manufacturing 1.21339Miscellaneous manufacturing 1.58

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Identifying clustersQuite a few manufacturing sectors are important in Tennessee, as indicated by the large LQS, but how are they linked? Are they clusters?

LQs are a start, but don’t provide enough information.

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Identifying clusters Input-output relationships

Advantage: show inter-industry relationships Disadvantage: difficult to estimate for sub-national areas

The point of an input-output table is to show inter-industry purchasing and sales relationships. This would seem essential for the purpose of identifying clusters.

A direct requirements table shows the distribution of input purchases for a given column industry. The following slide shows the direct requirements for the electrical equipment industry in Tennessee.

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Identifying clustersWe know that the direct requirements table shows the distribution of input purchases for a given industry.

Let’s start with the Tennessee industry with the largest LQ in the slide above, electrical equipment and appliance manufacturing, with an LQ of 2.41. This means that electrical equipment manufacturing has more than twice the share of employment in Tennessee as it does in the U.S. economy.

The following slide shows some of the direct requirement coefficients for the electrical equipment industry in Tennessee.

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CLUSTER ANALYSISElectrical equipment, appliances, and components

NAICS Input Industry

Direct Requirem

ent Coefficient LQ

331 Primary metals 0.177 1.41332 Fabricated metal products 0.070 1.43

335Electrical equipment, appliances, and components 0.068 2.41

334 Computer and electronic products 0.029 0.17325 Chemical products 0.025 1.47333 Machinery 0.020 1.04326 Plastics and rubber products 0.014 1.67327 Nonmetallic mineral products 0.012 1.61322 Paper products 0.009 2.85324 Petroleum and coal products 0.009 0.48

Share of all input purchases 0.433

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Identifying clustersTen industries supply 43% of the inputs for electrical machinery manufacturing.

Many of these supplying industries in Tennessee have LQs greater than one, indicating a strong presence in the state.

One could easily conclude that electrical equipment manufacturing is indeed a cluster that includes primary metals, fabricated metal products, chemical products, machinery, paper, and other industries.

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Identifying clustersOne industry, computer and electronic products, has a low LQ in Tennessee. Thus, Tennessee companies in electrical machinery manufacturing probably purchase these inputs from other states and countries.

The low LQ for computer products suggests an opportunity for Tennessee: recruit or expand this industry, since an internal market is already identified.

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Identifying clustersOne could repeat this process for other industries in Tennessee, resulting in a set of industry clusters.

In addition to input relationships, one could use an input-output table to determine sales linkages to other industries in the state.

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Identifying clustersFeser and Bergman use both input linkages and sales linkages to identify 23 industry clusters for the U.S. economy.

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Identifying clustersOther top-down methods include patent linkages and industry directories.

Researchers have combed through patent applications to find linkages, as each application provides details about specific precursors to the new idea.

Industry directories frequently provide purchasing and selling details for individual firms, allowing a research to piece together potential industry clusters.

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Identifying clustersBottom-up methods

Bottom-up approaches to identify clusters are much less data-driven in favor of a qualitative approach.

One approach involves extensive interviews with firm managers in order to document linkages with other firms in the area.

Additionally, case studies can be used to piece together industry clusters.

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Identifying clustersIn summary, there is not one best method of identifying an industry cluster.

The best studies consist of a blend of top-down and qualitative approaches.

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Clusters and economic performanceWhich types of clusters drive local economic growth?Do clusters promote growth and higher incomes?

It is generally accepted that clusters consisting of traded industries drive local economic growth. A traded industry is one that exports a good or service from the region. Thus, a traded industry relies on external demand for the good or service.

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Clusters and economic performanceBy contrast, a non-traded industry supplies goods and services mostly for the local market. These industries include health care services, retailing, personal services (hair, dry-cleaning), restaurants, and others.

Non-traded industries rely on growth generated by the traded industries.

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Clusters and economic performanceMichael Porter has examined traded v non-traded industries.

He found that non-traded industries have about 2/3 of the jobs locally, but pay much less than the traded industries.

Specialized traded industries are the core of local economic prosperity. So, local economic development efforts should focus on these industries.

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Clusters and economic performanceWe know that economics has long argued for specialization as the means of promoting productivity and higher incomes.

However, for a region or a state, over-reliance on a handful of specialized industries can expose the economy to substantial risk in case demand for the industry’s output declines.

This is clearly the case now in North Dakota, Texas, and Oklahoma, states that are reeling from the plunge in oil prices.

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Clusters and economic performanceResearch shows that larger states and metro areas tend to become more diverse industrially simply because they are larger. The larger size makes it possible to support more clusters and diversify.

This means that small cities and states will necessarily be less diversified industrially compared with larger states.

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Clusters and economic performanceIdeally, a state or region will work to increase the diversity of industry clusters so as to not rely too much on one or two industries.

However, diversification may be difficult to implement. Will a local government turn down economic incentives for a willing industry because the firm would not add to diversity for the local economy?

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Clusters and policyWhat lessons have been learned for policymakers from the cluster concept?

First, the cluster concept is useful for understanding local economies and developing growth strategies. Knowledge is power.

Second, there is general agreement that policymakers cannot create a cluster where one does not already exist. Instead, policy should focus on strengthening existing clusters.

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Clusters and policyThird, the best policy will establish the right conditions for the emergence of new clusters, then be ready to assist the clusters that pop up. Assistance could come in the form of education and training, a favorable business environment, an entrepreneurial culture, and capital availability.

Fourth, path dependence tells us that new clusters emerge from the extension of new knowledge and expertise.