February 27, 2024

This article draws from Shaffer, R.E., S.C. Deller and D.W. Marcouiller. 2004. Community Economics: Linking Theory and Practice. Oxford: Blackwell Professional Publishing.

By Steven Deller, University of Wisconsin

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As we have seen, numerous tools can be used upon which to base a Targeted Regional Economic Analysis (TRED) effort. These range from simple location quotient analysis as suggested by Michael Porter to complex statistical modeling as offered by John Leatherman. One important tool that has been used to decompose economic change over time into local and external factors is shift-share analysis. While shift-share can be used to measure any type of change, we will examine it for employment change only.

Essentially, shift-share breaks employment change into three components. The first component describes how the local economy would grow if it performed in exactly the same way as the national economy (national growth component: NG). This assumes that local conditions and structure are the same as the national economy. The second component describes the local economy as made up of different sectors from the national economy (industrial mix component: IM). This component tracks whether the local mix of sectors or industries is growing at a different rate than the same sectors in the national economy. In other words, this measures whether more employment is concentrated in faster or slower growth components locally than it is nationally. The third component is referred to as the local or competitive share. The local share is the employment change that is due to favorable local conditions and actions that support particular sectors. This latter component can point to potential industrial clusters and industries that may be targeted for additional analysis and development efforts.

The first step in shift-share analysis is to calculate the national growth component (NG). Sometimes, this is referred to as the National Share (NS). It measures the potential change in local employment assuming the local economy is similar to and growing at the same rate as the national economy. Multiplying the base year employment in each sector by the national average employment growth rate, and then summing over all the sectors, yields the national growth component. The results show how many new jobs were created locally due to national economic trends (i.e., simply because the national economy is growing in general), again assuming that the local and national economies are identical. Mathematically, the national share is calculated according to equation 1:

NS_i = e^t-1_i (E^t/E^t-1)

where e is community employment, i is the sector under examination, E is national employment and t is the time period.

The second step in shift-share analysis is to compute the industrial mix component (IM). The industrial mix component is determined by multiplying the local employment in each economic sector by the difference in the national growth rate for that sector and the growth rate for the whole economy (i.e., all sectors). A positive industrial mix indicates that most of the local employment is in sectors that are growing faster than national total employment. A negative industrial mix indicates just the opposite. Using the same notation, the industrial mix is calculated according to equation 2:

IM_i = e^t-1_i ((E^t_i/E^t-1_i) – (E^t/E^t-1))

The competitive share component (CS) measures the ability of the local economy to capture an increasing (decreasing) share of a particular sector’s growth. Sometimes, this is also referred to as the regional share. It is computed by multiplying the local employment in each economic sector by the difference in the growth rate of that sector nationally and locally. After doing this for all sectors, the results are summed to give the community competitive share. A positive competitive share indicates the community gained additional jobs over those due to national growth and its industrial structure. This gain suggests the community is more competitive (efficient) in securing additional employment than the rest of the nation, that is, it is drawing jobs away from the national economy or other regions. It is important to examine the competitive share for both the community and particular sectors. Each yields different information. Again, using the same notation, the competitive (or regional) share is calculated using equation 3:

CSi = e^t-1_i ((e^t_i /e^t-1_i ) – (E^t_i /E^t-1_i ))

At a minimum, a positive competitive share (CS) allows local leaders to target their efforts on industrial sectors in which the region is demonstrated to have a competitive advantage.

One problem with shift-share analysis is that it is a tautology: the change that occurs is broken into three separate components that equal the change that occurs.

Shift-share analysis does not give the practitioner any insight into what conditions and actions can cause the local share to take on any particular value. Thus, the tool, while useful in sorting through change, offers no theoretical insight as to why or how the change occurred. Again, this is a descriptive tool that can help the community practitioner draw inductive conclusions about past changes. It cannot or should not be used to make inferences about future changes. Like the location quotient analysis described elsewhere, shift-share analysis provides a simple method to point the targeting effort in specific directions.

Further details are provided in the accompanying edited volume (Targeting Regional Economic Development)

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